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+Metadata-Version: 2.1
+Name: pandas
+Version: 3.0.5
+Summary: Powerful data structures for data analysis, time series, and statistics
+Author-Email: The Pandas Development Team <pandas-dev@python.org>
+License: BSD 3-Clause License
+         
+         Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
+         All rights reserved.
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+         Copyright (c) 2010-2019 Keith Goodman
+         Copyright (c) 2019 Bottleneck Developers
+         All rights reserved.
+         
+         Redistribution and use in source and binary forms, with or without
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+         
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+         ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+         POSSIBILITY OF SUCH DAMAGE.Copyright 2017- Paul Ganssle <paul@ganssle.io>
+         Copyright 2017- dateutil contributors (see AUTHORS file)
+         
+            Licensed under the Apache License, Version 2.0 (the "License");
+            you may not use this file except in compliance with the License.
+            You may obtain a copy of the License at
+         
+                http://www.apache.org/licenses/LICENSE-2.0
+         
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+         
+         The above license applies to all contributions after 2017-12-01, as well as
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+         --------------------------------------------------------------------------------
+         dateutil - Extensions to the standard Python datetime module.
+         
+         Copyright (c) 2003-2011 - Gustavo Niemeyer <gustavo@niemeyer.net>
+         Copyright (c) 2012-2014 - Tomi Pieviläinen <tomi.pievilainen@iki.fi>
+         Copyright (c) 2014-2016 - Yaron de Leeuw <me@jarondl.net>
+         Copyright (c) 2015-     - Paul Ganssle <paul@ganssle.io>
+         Copyright (c) 2015-     - dateutil contributors (see AUTHORS file)
+         
+         All rights reserved.
+         
+         Redistribution and use in source and binary forms, with or without
+         modification, are permitted provided that the following conditions are met:
+         
+             * Redistributions of source code must retain the above copyright notice,
+               this list of conditions and the following disclaimer.
+             * Redistributions in binary form must reproduce the above copyright notice,
+               this list of conditions and the following disclaimer in the documentation
+               and/or other materials provided with the distribution.
+             * Neither the name of the copyright holder nor the names of its
+               contributors may be used to endorse or promote products derived from
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+         
+         The above BSD License Applies to all code, even that also covered by Apache 2.0.# MIT License
+         
+         Copyright (c) 2019 Hadley Wickham; RStudio; and Evan Miller
+         
+         Permission is hereby granted, free of charge, to any person obtaining a copy
+         of this software and associated documentation files (the "Software"), to deal
+         in the Software without restriction, including without limitation the rights
+         to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+         copies of the Software, and to permit persons to whom the Software is
+         furnished to do so, subject to the following conditions:
+         
+         The above copyright notice and this permission notice shall be included in all
+         copies or substantial portions of the Software.
+         
+         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+         IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+         FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+         AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+         LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+         OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+         SOFTWARE.
+         Based on http://opensource.org/licenses/MIT
+         
+         This is a template. Complete and ship as file LICENSE the following 2
+         lines (only)
+         
+         YEAR:
+         COPYRIGHT HOLDER:
+         
+         and specify as
+         
+         License: MIT + file LICENSE
+         
+         Copyright (c) <YEAR>, <COPYRIGHT HOLDER>
+         
+         Permission is hereby granted, free of charge, to any person obtaining
+         a copy of this software and associated documentation files (the
+         "Software"), to deal in the Software without restriction, including
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+         distribute, sublicense, and/or sell copies of the Software, and to
+         permit persons to whom the Software is furnished to do so, subject to
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+         included in all copies or substantial portions of the Software.
+         
+         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+         EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+         MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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+         LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+         OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+         WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+         The MIT License
+         
+         Copyright (c) 2008-     Attractive Chaos <attractor@live.co.uk>
+         
+         Permission is hereby granted, free of charge, to any person obtaining
+         a copy of this software and associated documentation files (the
+         "Software"), to deal in the Software without restriction, including
+         without limitation the rights to use, copy, modify, merge, publish,
+         distribute, sublicense, and/or sell copies of the Software, and to
+         permit persons to whom the Software is furnished to do so, subject to
+         the following conditions:
+         
+         The above copyright notice and this permission notice shall be
+         included in all copies or substantial portions of the Software.
+         
+         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+         EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+         MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+         NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
+         BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
+         ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+         CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+         SOFTWARE.musl as a whole is licensed under the following standard MIT license:
+         
+         ----------------------------------------------------------------------
+         Copyright © 2005-2020 Rich Felker, et al.
+         
+         Permission is hereby granted, free of charge, to any person obtaining
+         a copy of this software and associated documentation files (the
+         "Software"), to deal in the Software without restriction, including
+         without limitation the rights to use, copy, modify, merge, publish,
+         distribute, sublicense, and/or sell copies of the Software, and to
+         permit persons to whom the Software is furnished to do so, subject to
+         the following conditions:
+         
+         The above copyright notice and this permission notice shall be
+         included in all copies or substantial portions of the Software.
+         
+         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+         EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+         MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+         IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+         CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+         TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+         SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+         ----------------------------------------------------------------------
+         
+         Authors/contributors include:
+         
+         A. Wilcox
+         Ada Worcester
+         Alex Dowad
+         Alex Suykov
+         Alexander Monakov
+         Andre McCurdy
+         Andrew Kelley
+         Anthony G. Basile
+         Aric Belsito
+         Arvid Picciani
+         Bartosz Brachaczek
+         Benjamin Peterson
+         Bobby Bingham
+         Boris Brezillon
+         Brent Cook
+         Chris Spiegel
+         Clément Vasseur
+         Daniel Micay
+         Daniel Sabogal
+         Daurnimator
+         David Carlier
+         David Edelsohn
+         Denys Vlasenko
+         Dmitry Ivanov
+         Dmitry V. Levin
+         Drew DeVault
+         Emil Renner Berthing
+         Fangrui Song
+         Felix Fietkau
+         Felix Janda
+         Gianluca Anzolin
+         Hauke Mehrtens
+         He X
+         Hiltjo Posthuma
+         Isaac Dunham
+         Jaydeep Patil
+         Jens Gustedt
+         Jeremy Huntwork
+         Jo-Philipp Wich
+         Joakim Sindholt
+         John Spencer
+         Julien Ramseier
+         Justin Cormack
+         Kaarle Ritvanen
+         Khem Raj
+         Kylie McClain
+         Leah Neukirchen
+         Luca Barbato
+         Luka Perkov
+         M Farkas-Dyck (Strake)
+         Mahesh Bodapati
+         Markus Wichmann
+         Masanori Ogino
+         Michael Clark
+         Michael Forney
+         Mikhail Kremnyov
+         Natanael Copa
+         Nicholas J. Kain
+         orc
+         Pascal Cuoq
+         Patrick Oppenlander
+         Petr Hosek
+         Petr Skocik
+         Pierre Carrier
+         Reini Urban
+         Rich Felker
+         Richard Pennington
+         Ryan Fairfax
+         Samuel Holland
+         Segev Finer
+         Shiz
+         sin
+         Solar Designer
+         Stefan Kristiansson
+         Stefan O'Rear
+         Szabolcs Nagy
+         Timo Teräs
+         Trutz Behn
+         Valentin Ochs
+         Will Dietz
+         William Haddon
+         William Pitcock
+         
+         Portions of this software are derived from third-party works licensed
+         under terms compatible with the above MIT license:
+         
+         The TRE regular expression implementation (src/regex/reg* and
+         src/regex/tre*) is Copyright © 2001-2008 Ville Laurikari and licensed
+         under a 2-clause BSD license (license text in the source files). The
+         included version has been heavily modified by Rich Felker in 2012, in
+         the interests of size, simplicity, and namespace cleanliness.
+         
+         Much of the math library code (src/math/* and src/complex/*) is
+         Copyright © 1993,2004 Sun Microsystems or
+         Copyright © 2003-2011 David Schultz or
+         Copyright © 2003-2009 Steven G. Kargl or
+         Copyright © 2003-2009 Bruce D. Evans or
+         Copyright © 2008 Stephen L. Moshier or
+         Copyright © 2017-2018 Arm Limited
+         and labelled as such in comments in the individual source files. All
+         have been licensed under extremely permissive terms.
+         
+         The ARM memcpy code (src/string/arm/memcpy.S) is Copyright © 2008
+         The Android Open Source Project and is licensed under a two-clause BSD
+         license. It was taken from Bionic libc, used on Android.
+         
+         The AArch64 memcpy and memset code (src/string/aarch64/*) are
+         Copyright © 1999-2019, Arm Limited.
+         
+         The implementation of DES for crypt (src/crypt/crypt_des.c) is
+         Copyright © 1994 David Burren. It is licensed under a BSD license.
+         
+         The implementation of blowfish crypt (src/crypt/crypt_blowfish.c) was
+         originally written by Solar Designer and placed into the public
+         domain. The code also comes with a fallback permissive license for use
+         in jurisdictions that may not recognize the public domain.
+         
+         The smoothsort implementation (src/stdlib/qsort.c) is Copyright © 2011
+         Valentin Ochs and is licensed under an MIT-style license.
+         
+         The x86_64 port was written by Nicholas J. Kain and is licensed under
+         the standard MIT terms.
+         
+         The mips and microblaze ports were originally written by Richard
+         Pennington for use in the ellcc project. The original code was adapted
+         by Rich Felker for build system and code conventions during upstream
+         integration. It is licensed under the standard MIT terms.
+         
+         The mips64 port was contributed by Imagination Technologies and is
+         licensed under the standard MIT terms.
+         
+         The powerpc port was also originally written by Richard Pennington,
+         and later supplemented and integrated by John Spencer. It is licensed
+         under the standard MIT terms.
+         
+         All other files which have no copyright comments are original works
+         produced specifically for use as part of this library, written either
+         by Rich Felker, the main author of the library, or by one or more
+         contibutors listed above. Details on authorship of individual files
+         can be found in the git version control history of the project. The
+         omission of copyright and license comments in each file is in the
+         interest of source tree size.
+         
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+         
+         Bobby Bingham
+         John Spencer
+         Nicholas J. Kain
+         Rich Felker
+         Richard Pennington
+         Stefan Kristiansson
+         Szabolcs Nagy
+         
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+         
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+         the files covered by the above exception were sufficiently trivial not
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+         negated the permissions granted in the license. In the spirit of
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+         THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+         ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+         WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+         DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+         FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+         DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+         SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+         CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+         OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+         OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.A. HISTORY OF THE SOFTWARE
+         ==========================
+         
+         Python was created in the early 1990s by Guido van Rossum at Stichting
+         Mathematisch Centrum (CWI, see https://www.cwi.nl) in the Netherlands
+         as a successor of a language called ABC.  Guido remains Python's
+         principal author, although it includes many contributions from others.
+         
+         In 1995, Guido continued his work on Python at the Corporation for
+         National Research Initiatives (CNRI, see https://www.cnri.reston.va.us)
+         in Reston, Virginia where he released several versions of the
+         software.
+         
+         In May 2000, Guido and the Python core development team moved to
+         BeOpen.com to form the BeOpen PythonLabs team.  In October of the same
+         year, the PythonLabs team moved to Digital Creations, which became
+         Zope Corporation.  In 2001, the Python Software Foundation (PSF, see
+         https://www.python.org/psf/) was formed, a non-profit organization
+         created specifically to own Python-related Intellectual Property.
+         Zope Corporation was a sponsoring member of the PSF.
+         
+         All Python releases are Open Source (see https://opensource.org for
+         the Open Source Definition).  Historically, most, but not all, Python
+         releases have also been GPL-compatible; the table below summarizes
+         the various releases.
+         
+             Release         Derived     Year        Owner       GPL-
+                             from                                compatible? (1)
+         
+             0.9.0 thru 1.2              1991-1995   CWI         yes
+             1.3 thru 1.5.2  1.2         1995-1999   CNRI        yes
+             1.6             1.5.2       2000        CNRI        no
+             2.0             1.6         2000        BeOpen.com  no
+             1.6.1           1.6         2001        CNRI        yes (2)
+             2.1             2.0+1.6.1   2001        PSF         no
+             2.0.1           2.0+1.6.1   2001        PSF         yes
+             2.1.1           2.1+2.0.1   2001        PSF         yes
+             2.1.2           2.1.1       2002        PSF         yes
+             2.1.3           2.1.2       2002        PSF         yes
+             2.2 and above   2.1.1       2001-now    PSF         yes
+         
+         Footnotes:
+         
+         (1) GPL-compatible doesn't mean that we're distributing Python under
+             the GPL.  All Python licenses, unlike the GPL, let you distribute
+             a modified version without making your changes open source.  The
+             GPL-compatible licenses make it possible to combine Python with
+             other software that is released under the GPL; the others don't.
+         
+         (2) According to Richard Stallman, 1.6.1 is not GPL-compatible,
+             because its license has a choice of law clause.  According to
+             CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1
+             is "not incompatible" with the GPL.
+         
+         Thanks to the many outside volunteers who have worked under Guido's
+         direction to make these releases possible.
+         
+         
+         B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON
+         ===============================================================
+         
+         Python software and documentation are licensed under the
+         Python Software Foundation License Version 2.
+         
+         Starting with Python 3.8.6, examples, recipes, and other code in
+         the documentation are dual licensed under the PSF License Version 2
+         and the Zero-Clause BSD license.
+         
+         Some software incorporated into Python is under different licenses.
+         The licenses are listed with code falling under that license.
+         
+         
+         PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
+         --------------------------------------------
+         
+         1. This LICENSE AGREEMENT is between the Python Software Foundation
+         ("PSF"), and the Individual or Organization ("Licensee") accessing and
+         otherwise using this software ("Python") in source or binary form and
+         its associated documentation.
+         
+         2. Subject to the terms and conditions of this License Agreement, PSF hereby
+         grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,
+         analyze, test, perform and/or display publicly, prepare derivative works,
+         distribute, and otherwise use Python alone or in any derivative version,
+         provided, however, that PSF's License Agreement and PSF's notice of copyright,
+         i.e., "Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
+         2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 Python Software Foundation;
+         All Rights Reserved" are retained in Python alone or in any derivative version
+         prepared by Licensee.
+         
+         3. In the event Licensee prepares a derivative work that is based on
+         or incorporates Python or any part thereof, and wants to make
+         the derivative work available to others as provided herein, then
+         Licensee hereby agrees to include in any such work a brief summary of
+         the changes made to Python.
+         
+         4. PSF is making Python available to Licensee on an "AS IS"
+         basis.  PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
+         IMPLIED.  BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND
+         DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
+         FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT
+         INFRINGE ANY THIRD PARTY RIGHTS.
+         
+         5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
+         FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
+         A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON,
+         OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
+         
+         6. This License Agreement will automatically terminate upon a material
+         breach of its terms and conditions.
+         
+         7. Nothing in this License Agreement shall be deemed to create any
+         relationship of agency, partnership, or joint venture between PSF and
+         Licensee.  This License Agreement does not grant permission to use PSF
+         trademarks or trade name in a trademark sense to endorse or promote
+         products or services of Licensee, or any third party.
+         
+         8. By copying, installing or otherwise using Python, Licensee
+         agrees to be bound by the terms and conditions of this License
+         Agreement.
+         
+         
+         BEOPEN.COM LICENSE AGREEMENT FOR PYTHON 2.0
+         -------------------------------------------
+         
+         BEOPEN PYTHON OPEN SOURCE LICENSE AGREEMENT VERSION 1
+         
+         1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an
+         office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the
+         Individual or Organization ("Licensee") accessing and otherwise using
+         this software in source or binary form and its associated
+         documentation ("the Software").
+         
+         2. Subject to the terms and conditions of this BeOpen Python License
+         Agreement, BeOpen hereby grants Licensee a non-exclusive,
+         royalty-free, world-wide license to reproduce, analyze, test, perform
+         and/or display publicly, prepare derivative works, distribute, and
+         otherwise use the Software alone or in any derivative version,
+         provided, however, that the BeOpen Python License is retained in the
+         Software, alone or in any derivative version prepared by Licensee.
+         
+         3. BeOpen is making the Software available to Licensee on an "AS IS"
+         basis.  BEOPEN MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
+         IMPLIED.  BY WAY OF EXAMPLE, BUT NOT LIMITATION, BEOPEN MAKES NO AND
+         DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
+         FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF THE SOFTWARE WILL NOT
+         INFRINGE ANY THIRD PARTY RIGHTS.
+         
+         4. BEOPEN SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF THE
+         SOFTWARE FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS
+         AS A RESULT OF USING, MODIFYING OR DISTRIBUTING THE SOFTWARE, OR ANY
+         DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
+         
+         5. This License Agreement will automatically terminate upon a material
+         breach of its terms and conditions.
+         
+         6. This License Agreement shall be governed by and interpreted in all
+         respects by the law of the State of California, excluding conflict of
+         law provisions.  Nothing in this License Agreement shall be deemed to
+         create any relationship of agency, partnership, or joint venture
+         between BeOpen and Licensee.  This License Agreement does not grant
+         permission to use BeOpen trademarks or trade names in a trademark
+         sense to endorse or promote products or services of Licensee, or any
+         third party.  As an exception, the "BeOpen Python" logos available at
+         http://www.pythonlabs.com/logos.html may be used according to the
+         permissions granted on that web page.
+         
+         7. By copying, installing or otherwise using the software, Licensee
+         agrees to be bound by the terms and conditions of this License
+         Agreement.
+         
+         
+         CNRI LICENSE AGREEMENT FOR PYTHON 1.6.1
+         ---------------------------------------
+         
+         1. This LICENSE AGREEMENT is between the Corporation for National
+         Research Initiatives, having an office at 1895 Preston White Drive,
+         Reston, VA 20191 ("CNRI"), and the Individual or Organization
+         ("Licensee") accessing and otherwise using Python 1.6.1 software in
+         source or binary form and its associated documentation.
+         
+         2. Subject to the terms and conditions of this License Agreement, CNRI
+         hereby grants Licensee a nonexclusive, royalty-free, world-wide
+         license to reproduce, analyze, test, perform and/or display publicly,
+         prepare derivative works, distribute, and otherwise use Python 1.6.1
+         alone or in any derivative version, provided, however, that CNRI's
+         License Agreement and CNRI's notice of copyright, i.e., "Copyright (c)
+         1995-2001 Corporation for National Research Initiatives; All Rights
+         Reserved" are retained in Python 1.6.1 alone or in any derivative
+         version prepared by Licensee.  Alternately, in lieu of CNRI's License
+         Agreement, Licensee may substitute the following text (omitting the
+         quotes): "Python 1.6.1 is made available subject to the terms and
+         conditions in CNRI's License Agreement.  This Agreement together with
+         Python 1.6.1 may be located on the internet using the following
+         unique, persistent identifier (known as a handle): 1895.22/1013.  This
+         Agreement may also be obtained from a proxy server on the internet
+         using the following URL: http://hdl.handle.net/1895.22/1013".
+         
+         3. In the event Licensee prepares a derivative work that is based on
+         or incorporates Python 1.6.1 or any part thereof, and wants to make
+         the derivative work available to others as provided herein, then
+         Licensee hereby agrees to include in any such work a brief summary of
+         the changes made to Python 1.6.1.
+         
+         4. CNRI is making Python 1.6.1 available to Licensee on an "AS IS"
+         basis.  CNRI MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
+         IMPLIED.  BY WAY OF EXAMPLE, BUT NOT LIMITATION, CNRI MAKES NO AND
+         DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
+         FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON 1.6.1 WILL NOT
+         INFRINGE ANY THIRD PARTY RIGHTS.
+         
+         5. CNRI SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
+         1.6.1 FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
+         A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON 1.6.1,
+         OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
+         
+         6. This License Agreement will automatically terminate upon a material
+         breach of its terms and conditions.
+         
+         7. This License Agreement shall be governed by the federal
+         intellectual property law of the United States, including without
+         limitation the federal copyright law, and, to the extent such
+         U.S. federal law does not apply, by the law of the Commonwealth of
+         Virginia, excluding Virginia's conflict of law provisions.
+         Notwithstanding the foregoing, with regard to derivative works based
+         on Python 1.6.1 that incorporate non-separable material that was
+         previously distributed under the GNU General Public License (GPL), the
+         law of the Commonwealth of Virginia shall govern this License
+         Agreement only as to issues arising under or with respect to
+         Paragraphs 4, 5, and 7 of this License Agreement.  Nothing in this
+         License Agreement shall be deemed to create any relationship of
+         agency, partnership, or joint venture between CNRI and Licensee.  This
+         License Agreement does not grant permission to use CNRI trademarks or
+         trade name in a trademark sense to endorse or promote products or
+         services of Licensee, or any third party.
+         
+         8. By clicking on the "ACCEPT" button where indicated, or by copying,
+         installing or otherwise using Python 1.6.1, Licensee agrees to be
+         bound by the terms and conditions of this License Agreement.
+         
+                 ACCEPT
+         
+         
+         CWI LICENSE AGREEMENT FOR PYTHON 0.9.0 THROUGH 1.2
+         --------------------------------------------------
+         
+         Copyright (c) 1991 - 1995, Stichting Mathematisch Centrum Amsterdam,
+         The Netherlands.  All rights reserved.
+         
+         Permission to use, copy, modify, and distribute this software and its
+         documentation for any purpose and without fee is hereby granted,
+         provided that the above copyright notice appear in all copies and that
+         both that copyright notice and this permission notice appear in
+         supporting documentation, and that the name of Stichting Mathematisch
+         Centrum or CWI not be used in advertising or publicity pertaining to
+         distribution of the software without specific, written prior
+         permission.
+         
+         STICHTING MATHEMATISCH CENTRUM DISCLAIMS ALL WARRANTIES WITH REGARD TO
+         THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
+         FITNESS, IN NO EVENT SHALL STICHTING MATHEMATISCH CENTRUM BE LIABLE
+         FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
+         WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
+         ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
+         OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
+         
+         ZERO-CLAUSE BSD LICENSE FOR CODE IN THE PYTHON DOCUMENTATION
+         ----------------------------------------------------------------------
+         
+         Permission to use, copy, modify, and/or distribute this software for any
+         purpose with or without fee is hereby granted.
+         
+         THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
+         REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
+         AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
+         INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
+         LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
+         OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
+         PERFORMANCE OF THIS SOFTWARE.
+         Copyright (c) 2014, Al Sweigart
+         All rights reserved.
+         
+         Redistribution and use in source and binary forms, with or without
+         modification, are permitted provided that the following conditions are met:
+         
+         * Redistributions of source code must retain the above copyright notice, this
+           list of conditions and the following disclaimer.
+         
+         * Redistributions in binary form must reproduce the above copyright notice,
+           this list of conditions and the following disclaimer in the documentation
+           and/or other materials provided with the distribution.
+         
+         * Neither the name of the {organization} nor the names of its
+           contributors may be used to endorse or promote products derived from
+           this software without specific prior written permission.
+         
+         THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+         AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+         IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+         DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+         FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+         DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+         SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+         CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+         OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+         OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.Copyright (c) 2017 Anthony Sottile
+         
+         Permission is hereby granted, free of charge, to any person obtaining a copy
+         of this software and associated documentation files (the "Software"), to deal
+         in the Software without restriction, including without limitation the rights
+         to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+         copies of the Software, and to permit persons to whom the Software is
+         furnished to do so, subject to the following conditions:
+         
+         The above copyright notice and this permission notice shall be included in
+         all copies or substantial portions of the Software.
+         
+         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+         IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+         FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+         AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+         LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+         OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+         THE SOFTWARE.Copyright (c) 2015-2019 Jared Hobbs
+         
+         Permission is hereby granted, free of charge, to any person obtaining a copy of
+         this software and associated documentation files (the "Software"), to deal in
+         the Software without restriction, including without limitation the rights to
+         use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+         of the Software, and to permit persons to whom the Software is furnished to do
+         so, subject to the following conditions:
+         
+         The above copyright notice and this permission notice shall be included in all
+         copies or substantial portions of the Software.
+         
+         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+         IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+         FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+         AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+         LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+         OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+         SOFTWARE.Developed by ESN, an Electronic Arts Inc. studio.
+         Copyright (c) 2014, Electronic Arts Inc.
+         All rights reserved.
+         
+         Redistribution and use in source and binary forms, with or without
+         modification, are permitted provided that the following conditions are met:
+         * Redistributions of source code must retain the above copyright
+         notice, this list of conditions and the following disclaimer.
+         * Redistributions in binary form must reproduce the above copyright
+         notice, this list of conditions and the following disclaimer in the
+         documentation and/or other materials provided with the distribution.
+         * Neither the name of ESN, Electronic Arts Inc. nor the
+         names of its contributors may be used to endorse or promote products
+         derived from this software without specific prior written permission.
+         
+         THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+         ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+         WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+         DISCLAIMED. IN NO EVENT SHALL ELECTRONIC ARTS INC. BE LIABLE
+         FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+         (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+         LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+         ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+         (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+         SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+         
+         ----
+         
+         Portions of code from MODP_ASCII - Ascii transformations (upper/lower, etc)
+         https://github.com/client9/stringencoders
+         
+           Copyright 2005, 2006, 2007
+           Nick Galbreath -- nickg [at] modp [dot] com
+           All rights reserved.
+         
+           Redistribution and use in source and binary forms, with or without
+           modification, are permitted provided that the following conditions are
+           met:
+         
+             Redistributions of source code must retain the above copyright
+             notice, this list of conditions and the following disclaimer.
+         
+             Redistributions in binary form must reproduce the above copyright
+             notice, this list of conditions and the following disclaimer in the
+             documentation and/or other materials provided with the distribution.
+         
+             Neither the name of the modp.com nor the names of its
+             contributors may be used to endorse or promote products derived from
+             this software without specific prior written permission.
+         
+           THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+           "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+           LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+           A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+           OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+           SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+           LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+           DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+           THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+           (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+           OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+         
+           This is the standard "new" BSD license:
+           http://www.opensource.org/licenses/bsd-license.php
+         
+         https://github.com/client9/stringencoders/blob/cfd5c1507325ae497ea9bacdacba12c0ffd79d30/COPYING
+         
+         ----
+         
+         Numeric decoder derived from from TCL library
+         https://opensource.apple.com/source/tcl/tcl-14/tcl/license.terms
+          * Copyright (c) 1988-1993 The Regents of the University of California.
+          * Copyright (c) 1994 Sun Microsystems, Inc.
+         
+           This software is copyrighted by the Regents of the University of
+           California, Sun Microsystems, Inc., Scriptics Corporation, ActiveState
+           Corporation and other parties.  The following terms apply to all files
+           associated with the software unless explicitly disclaimed in
+           individual files.
+         
+           The authors hereby grant permission to use, copy, modify, distribute,
+           and license this software and its documentation for any purpose, provided
+           that existing copyright notices are retained in all copies and that this
+           notice is included verbatim in any distributions. No written agreement,
+           license, or royalty fee is required for any of the authorized uses.
+           Modifications to this software may be copyrighted by their authors
+           and need not follow the licensing terms described here, provided that
+           the new terms are clearly indicated on the first page of each file where
+           they apply.
+         
+           IN NO EVENT SHALL THE AUTHORS OR DISTRIBUTORS BE LIABLE TO ANY PARTY
+           FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES
+           ARISING OUT OF THE USE OF THIS SOFTWARE, ITS DOCUMENTATION, OR ANY
+           DERIVATIVES THEREOF, EVEN IF THE AUTHORS HAVE BEEN ADVISED OF THE
+           POSSIBILITY OF SUCH DAMAGE.
+         
+           THE AUTHORS AND DISTRIBUTORS SPECIFICALLY DISCLAIM ANY WARRANTIES,
+           INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY,
+           FITNESS FOR A PARTICULAR PURPOSE, AND NON-INFRINGEMENT.  THIS SOFTWARE
+           IS PROVIDED ON AN "AS IS" BASIS, AND THE AUTHORS AND DISTRIBUTORS HAVE
+           NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR
+           MODIFICATIONS.
+         
+           GOVERNMENT USE: If you are acquiring this software on behalf of the
+           U.S. government, the Government shall have only "Restricted Rights"
+           in the software and related documentation as defined in the Federal
+           Acquisition Regulations (FARs) in Clause 52.227.19 (c) (2).  If you
+           are acquiring the software on behalf of the Department of Defense, the
+           software shall be classified as "Commercial Computer Software" and the
+           Government shall have only "Restricted Rights" as defined in Clause
+           252.227-7013 (c) (1) of DFARs.  Notwithstanding the foregoing, the
+           authors grant the U.S. Government and others acting in its behalf
+           permission to use and distribute the software in accordance with the
+           terms specified in this license.
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Console
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Cython
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Classifier: Topic :: Scientific/Engineering
+Project-URL: homepage, https://pandas.pydata.org
+Project-URL: documentation, https://pandas.pydata.org/docs/
+Project-URL: repository, https://github.com/pandas-dev/pandas
+Requires-Python: >=3.11
+Requires-Dist: numpy>=1.26.0; python_version < "3.14"
+Requires-Dist: numpy>=2.3.3; python_version >= "3.14"
+Requires-Dist: python-dateutil>=2.8.2
+Requires-Dist: tzdata; sys_platform == "win32"
+Requires-Dist: tzdata; sys_platform == "emscripten"
+Provides-Extra: test
+Requires-Dist: hypothesis>=6.116.0; extra == "test"
+Requires-Dist: pytest<9.1,>=8.3.4; extra == "test"
+Requires-Dist: pytest-xdist>=3.6.1; extra == "test"
+Provides-Extra: pyarrow
+Requires-Dist: pyarrow>=13.0.0; extra == "pyarrow"
+Provides-Extra: performance
+Requires-Dist: bottleneck>=1.4.2; extra == "performance"
+Requires-Dist: numba>=0.60.0; extra == "performance"
+Requires-Dist: numexpr>=2.10.2; extra == "performance"
+Provides-Extra: computation
+Requires-Dist: scipy>=1.14.1; extra == "computation"
+Requires-Dist: xarray>=2024.10.0; extra == "computation"
+Provides-Extra: fss
+Requires-Dist: fsspec>=2024.10.0; extra == "fss"
+Provides-Extra: aws
+Requires-Dist: s3fs>=2024.10.0; extra == "aws"
+Provides-Extra: gcp
+Requires-Dist: gcsfs>=2024.10.0; extra == "gcp"
+Provides-Extra: excel
+Requires-Dist: odfpy>=1.4.1; extra == "excel"
+Requires-Dist: openpyxl>=3.1.5; extra == "excel"
+Requires-Dist: python-calamine>=0.3.0; extra == "excel"
+Requires-Dist: pyxlsb>=1.0.10; extra == "excel"
+Requires-Dist: xlrd>=2.0.1; extra == "excel"
+Requires-Dist: xlsxwriter>=3.2.0; extra == "excel"
+Provides-Extra: parquet
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+Provides-Extra: feather
+Requires-Dist: pyarrow>=13.0.0; extra == "feather"
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+Requires-Dist: tables>=3.10.1; extra == "hdf5"
+Provides-Extra: spss
+Requires-Dist: pyreadstat>=1.2.8; extra == "spss"
+Provides-Extra: postgresql
+Requires-Dist: SQLAlchemy>=2.0.36; extra == "postgresql"
+Requires-Dist: psycopg2>=2.9.10; extra == "postgresql"
+Requires-Dist: adbc-driver-postgresql>=1.2.0; extra == "postgresql"
+Provides-Extra: mysql
+Requires-Dist: SQLAlchemy>=2.0.36; extra == "mysql"
+Requires-Dist: pymysql>=1.1.1; extra == "mysql"
+Provides-Extra: sql-other
+Requires-Dist: SQLAlchemy>=2.0.36; extra == "sql-other"
+Requires-Dist: adbc-driver-postgresql>=1.2.0; extra == "sql-other"
+Requires-Dist: adbc-driver-sqlite>=1.2.0; extra == "sql-other"
+Provides-Extra: html
+Requires-Dist: beautifulsoup4>=4.12.3; extra == "html"
+Requires-Dist: html5lib>=1.1; extra == "html"
+Requires-Dist: lxml>=5.3.0; extra == "html"
+Provides-Extra: xml
+Requires-Dist: lxml>=5.3.0; extra == "xml"
+Provides-Extra: plot
+Requires-Dist: matplotlib>=3.9.3; extra == "plot"
+Provides-Extra: output-formatting
+Requires-Dist: jinja2>=3.1.5; extra == "output-formatting"
+Requires-Dist: tabulate>=0.9.0; extra == "output-formatting"
+Provides-Extra: clipboard
+Requires-Dist: PyQt5>=5.15.9; extra == "clipboard"
+Requires-Dist: qtpy>=2.4.2; extra == "clipboard"
+Provides-Extra: compression
+Requires-Dist: zstandard>=0.23.0; extra == "compression"
+Provides-Extra: timezone
+Requires-Dist: pytz>=2020.1; extra == "timezone"
+Provides-Extra: all
+Requires-Dist: adbc-driver-postgresql>=1.2.0; extra == "all"
+Requires-Dist: adbc-driver-sqlite>=1.2.0; extra == "all"
+Requires-Dist: beautifulsoup4>=4.12.3; extra == "all"
+Requires-Dist: bottleneck>=1.4.2; extra == "all"
+Requires-Dist: fastparquet>=2024.11.0; extra == "all"
+Requires-Dist: fsspec>=2024.10.0; extra == "all"
+Requires-Dist: gcsfs>=2024.10.0; extra == "all"
+Requires-Dist: html5lib>=1.1; extra == "all"
+Requires-Dist: hypothesis>=6.116.0; extra == "all"
+Requires-Dist: jinja2>=3.1.5; extra == "all"
+Requires-Dist: lxml>=5.3.0; extra == "all"
+Requires-Dist: matplotlib>=3.9.3; extra == "all"
+Requires-Dist: numba>=0.60.0; extra == "all"
+Requires-Dist: numexpr>=2.10.2; extra == "all"
+Requires-Dist: odfpy>=1.4.1; extra == "all"
+Requires-Dist: openpyxl>=3.1.5; extra == "all"
+Requires-Dist: psycopg2>=2.9.10; extra == "all"
+Requires-Dist: pyarrow>=13.0.0; extra == "all"
+Requires-Dist: pyiceberg>=0.8.1; extra == "all"
+Requires-Dist: pymysql>=1.1.1; extra == "all"
+Requires-Dist: PyQt5>=5.15.9; extra == "all"
+Requires-Dist: pyreadstat>=1.2.8; extra == "all"
+Requires-Dist: pytest>=8.3.4; extra == "all"
+Requires-Dist: pytest-xdist>=3.6.1; extra == "all"
+Requires-Dist: python-calamine>=0.3.0; extra == "all"
+Requires-Dist: pytz>=2020.1; extra == "all"
+Requires-Dist: pyxlsb>=1.0.10; extra == "all"
+Requires-Dist: qtpy>=2.4.2; extra == "all"
+Requires-Dist: scipy>=1.14.1; extra == "all"
+Requires-Dist: s3fs>=2024.10.0; extra == "all"
+Requires-Dist: SQLAlchemy>=2.0.36; extra == "all"
+Requires-Dist: tables>=3.10.1; extra == "all"
+Requires-Dist: tabulate>=0.9.0; extra == "all"
+Requires-Dist: xarray>=2024.10.0; extra == "all"
+Requires-Dist: xlrd>=2.0.1; extra == "all"
+Requires-Dist: xlsxwriter>=3.2.0; extra == "all"
+Requires-Dist: zstandard>=0.23.0; extra == "all"
+Description-Content-Type: text/markdown
+
+<picture align="center">
+  <source media="(prefers-color-scheme: dark)" srcset="https://pandas.pydata.org/static/img/pandas_white.svg">
+  <img alt="Pandas Logo" src="https://pandas.pydata.org/static/img/pandas.svg">
+</picture>
+
+-----------------
+
+# pandas: A Powerful Python Data Analysis Toolkit
+
+| | |
+| --- | --- |
+| Testing | [![CI - Test](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml/badge.svg)](https://github.com/pandas-dev/pandas/actions/workflows/unit-tests.yml) [![Coverage](https://codecov.io/github/pandas-dev/pandas/coverage.svg?branch=main)](https://codecov.io/gh/pandas-dev/pandas) |
+| Package | [![PyPI Latest Release](https://img.shields.io/pypi/v/pandas.svg)](https://pypi.org/project/pandas/) [![PyPI Downloads](https://img.shields.io/pypi/dm/pandas.svg?label=PyPI%20downloads)](https://pypi.org/project/pandas/) [![Conda Latest Release](https://anaconda.org/conda-forge/pandas/badges/version.svg)](https://anaconda.org/conda-forge/pandas) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/pandas.svg?label=Conda%20downloads)](https://anaconda.org/conda-forge/pandas) |
+| Meta | [![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3509134.svg)](https://doi.org/10.5281/zenodo.3509134) [![License - BSD 3-Clause](https://img.shields.io/pypi/l/pandas.svg)](https://github.com/pandas-dev/pandas/blob/main/LICENSE) [![Slack](https://img.shields.io/badge/join_Slack-information-brightgreen.svg?logo=slack)](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) [![LFX Health Score](https://insights.linuxfoundation.org/api/badge/health-score?project=pandas-dev-pandas)](https://insights.linuxfoundation.org/project/pandas-dev-pandas) |
+
+
+## What is it?
+
+**pandas** is a Python package that provides fast, flexible, and expressive data
+structures designed to make working with "relational" or "labeled" data both
+easy and intuitive. It aims to be the fundamental high-level building block for
+doing practical, **real-world** data analysis in Python. Additionally, it has
+the broader goal of becoming **the most powerful and flexible open-source data
+analysis/manipulation tool available in any language**. It is already well on
+its way towards this goal.
+
+## Table of Contents
+
+- [Main Features](#main-features)
+- [Where to get it](#where-to-get-it)
+- [Dependencies](#dependencies)
+- [Installation from sources](#installation-from-sources)
+- [License](#license)
+- [Documentation](#documentation)
+- [Background](#background)
+- [Getting Help](#getting-help)
+- [Discussion and Development](#discussion-and-development)
+- [Contributing to pandas](#contributing-to-pandas)
+
+## Main Features
+Here are just a few of the things that pandas does well:
+
+  - Easy handling of [**missing data**][missing-data] (represented as
+    `NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data
+  - Size mutability: columns can be [**inserted and
+    deleted**][insertion-deletion] from DataFrame and higher dimensional
+    objects
+  - Automatic and explicit [**data alignment**][alignment]: objects can
+    be explicitly aligned to a set of labels, or the user can simply
+    ignore the labels and let `Series`, `DataFrame`, etc. automatically
+    align the data for you in computations
+  - Powerful, flexible [**group by**][groupby] functionality to perform
+    split-apply-combine operations on data sets, for both aggregating
+    and transforming data
+  - Make it [**easy to convert**][conversion] ragged,
+    differently-indexed data in other Python and NumPy data structures
+    into DataFrame objects
+  - Intelligent label-based [**slicing**][slicing], [**fancy
+    indexing**][fancy-indexing], and [**subsetting**][subsetting] of
+    large data sets
+  - Intuitive [**merging**][merging] and [**joining**][joining] data
+    sets
+  - Flexible [**reshaping**][reshape] and [**pivoting**][pivot-table] of
+    data sets
+  - [**Hierarchical**][mi] labeling of axes (possible to have multiple
+    labels per tick)
+  - Robust I/O tools for loading data from [**flat files**][flat-files]
+    (CSV and delimited), [**Excel files**][excel], [**databases**][db],
+    and saving/loading data from the ultrafast [**HDF5 format**][hdfstore]
+  - [**Time series**][timeseries]-specific functionality: date range
+    generation and frequency conversion, moving window statistics,
+    date shifting and lagging
+
+
+   [missing-data]: https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html
+   [insertion-deletion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#column-selection-addition-deletion
+   [alignment]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html?highlight=alignment#intro-to-data-structures
+   [groupby]: https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#group-by-split-apply-combine
+   [conversion]: https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#dataframe
+   [slicing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#slicing-ranges
+   [fancy-indexing]: https://pandas.pydata.org/pandas-docs/stable/user_guide/advanced.html#advanced
+   [subsetting]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#boolean-indexing
+   [merging]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#database-style-dataframe-or-named-series-joining-merging
+   [joining]: https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-on-index
+   [reshape]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
+   [pivot-table]: https://pandas.pydata.org/pandas-docs/stable/user_guide/reshaping.html
+   [mi]: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#hierarchical-indexing-multiindex
+   [flat-files]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#csv-text-files
+   [excel]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#excel-files
+   [db]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#sql-queries
+   [hdfstore]: https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#hdf5-pytables
+   [timeseries]: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#time-series-date-functionality
+
+## Where to get it
+The source code is currently hosted on GitHub at:
+https://github.com/pandas-dev/pandas
+
+Binary installers for the latest released version are available at the [Python
+Package Index (PyPI)](https://pypi.org/project/pandas) and on [Conda](https://anaconda.org/conda-forge/pandas).
+
+```sh
+# conda
+conda install -c conda-forge pandas
+```
+
+```sh
+# or PyPI
+pip install pandas
+```
+
+The list of changes to pandas between each release can be found
+[here](https://pandas.pydata.org/pandas-docs/stable/whatsnew/index.html). For full
+details, see the commit logs at https://github.com/pandas-dev/pandas.
+
+## Dependencies
+- [NumPy - Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arrays](https://www.numpy.org)
+- [python-dateutil - Provides powerful extensions to the standard datetime module](https://dateutil.readthedocs.io/en/stable/index.html)
+- [tzdata - Provides an IANA time zone database](https://tzdata.readthedocs.io/en/latest/) (Only required on Windows/Emscripten)
+
+See the [full installation instructions](https://pandas.pydata.org/pandas-docs/stable/install.html#dependencies) for minimum supported versions of required, recommended and optional dependencies.
+
+## Installation from sources
+To install pandas from source you need [Cython](https://cython.org/) in addition to the normal
+dependencies above. Cython can be installed from PyPI:
+
+```sh
+pip install cython
+```
+
+In the `pandas` directory (same one where you found this file after
+cloning the git repo), execute:
+
+```sh
+pip install .
+```
+
+or for installing in [development mode](https://pip.pypa.io/en/latest/cli/pip_install/#install-editable):
+
+
+```sh
+python -m pip install -ve . --no-build-isolation --config-settings editable-verbose=true
+```
+
+See the full instructions for [installing from source](https://pandas.pydata.org/docs/dev/development/contributing_environment.html).
+
+## License
+[BSD 3](LICENSE)
+
+## Documentation
+The official documentation is hosted on [PyData.org](https://pandas.pydata.org/pandas-docs/stable/).
+
+## Background
+Work on ``pandas`` started at [AQR](https://www.aqr.com/) (a quantitative hedge fund) in 2008 and
+has been under active development since then.
+
+## Getting Help
+
+For usage questions, the best place to go to is [Stack Overflow](https://stackoverflow.com/questions/tagged/pandas).
+Further, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata).
+
+## Discussion and Development
+Most development discussions take place on GitHub in this repo, via the [GitHub issue tracker](https://github.com/pandas-dev/pandas/issues).
+
+Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions.
+
+There are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors.
+
+Additional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page.
+
+## Contributing to pandas
+
+[![Open Source Helpers](https://www.codetriage.com/pandas-dev/pandas/badges/users.svg)](https://www.codetriage.com/pandas-dev/pandas)
+
+All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
+
+A detailed overview on how to contribute can be found in the **[contributing guide](https://pandas.pydata.org/docs/dev/development/contributing.html)**.
+
+If you are simply looking to start working with the pandas codebase, navigate to the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?q=is%3Aissue%20state%3Aopen%20label%3ADocs%20sort%3Aupdated-desc) and [good first issue](https://github.com/pandas-dev/pandas/issues?q=is%3Aissue%20state%3Aopen%20label%3A%22good%20first%20issue%22%20sort%3Aupdated-desc) where you could start out.
+
+You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas).
+
+Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’... you can do something about it!
+
+Feel free to ask questions on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Slack](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack).
+
+As contributors and maintainers to this project, you are expected to abide by pandas' code of conduct. More information can be found at: [Contributor Code of Conduct](https://github.com/pandas-dev/.github/blob/master/CODE_OF_CONDUCT.md)
+
+<hr>
+
+[Go to Top](#table-of-contents)

.cache/pip/http-v2/4/5/2/4/1/45241d61b1606b84c3825a9119b750e7cd16e5fac504d31f79203a8e.body

@@ -0,0 +1,84 @@
+Metadata-Version: 2.4
+Name: click
+Version: 8.4.2
+Summary: Composable command line interface toolkit
+Maintainer-email: Pallets <contact@palletsprojects.com>
+Requires-Python: >=3.10
+Description-Content-Type: text/markdown
+License-Expression: BSD-3-Clause
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Typing :: Typed
+License-File: LICENSE.txt
+Requires-Dist: colorama; platform_system == 'Windows'
+Project-URL: Changes, https://click.palletsprojects.com/page/changes/
+Project-URL: Chat, https://discord.gg/pallets
+Project-URL: Documentation, https://click.palletsprojects.com/
+Project-URL: Donate, https://palletsprojects.com/donate
+Project-URL: Source, https://github.com/pallets/click/
+
+<div align="center"><img src="https://raw.githubusercontent.com/pallets/click/refs/heads/stable/docs/_static/click-name.svg" alt="" height="150"></div>
+
+# Click
+
+Click is a Python package for creating beautiful command line interfaces
+in a composable way with as little code as necessary. It's the "Command
+Line Interface Creation Kit". It's highly configurable but comes with
+sensible defaults out of the box.
+
+It aims to make the process of writing command line tools quick and fun
+while also preventing any frustration caused by the inability to
+implement an intended CLI API.
+
+Click in three points:
+
+-   Arbitrary nesting of commands
+-   Automatic help page generation
+-   Supports lazy loading of subcommands at runtime
+
+
+## A Simple Example
+
+```python
+import click
+
+@click.command()
+@click.option("--count", default=1, help="Number of greetings.")
+@click.option("--name", prompt="Your name", help="The person to greet.")
+def hello(count, name):
+    """Simple program that greets NAME for a total of COUNT times."""
+    for _ in range(count):
+        click.echo(f"Hello, {name}!")
+
+if __name__ == '__main__':
+    hello()
+```
+
+```
+$ python hello.py --count=3
+Your name: Click
+Hello, Click!
+Hello, Click!
+Hello, Click!
+```
+
+
+## Donate
+
+The Pallets organization develops and supports Click and other popular
+packages. In order to grow the community of contributors and users, and
+allow the maintainers to devote more time to the projects, [please
+donate today][].
+
+[please donate today]: https://palletsprojects.com/donate
+
+## Contributing
+
+See our [detailed contributing documentation][contrib] for many ways to
+contribute, including reporting issues, requesting features, asking or answering
+questions, and making PRs.
+
+[contrib]: https://palletsprojects.com/contributing/
+

.cache/pip/http-v2/6/4/6/7/b/6467bdd236eabb4648139f514441e5510842fbc90755e4738c64fcf3.body

@@ -0,0 +1,341 @@
+Metadata-Version: 2.4
+Name: colorlog
+Version: 6.12.0
+Summary: Add colours to the output of Python's logging module.
+Home-page: https://github.com/borntyping/python-colorlog
+Author: Sam Clements
+Author-email: sam@borntyping.co.uk
+License: MIT License
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Console
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.6
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Topic :: Terminals
+Classifier: Topic :: Utilities
+Requires-Python: >=3.6
+Description-Content-Type: text/markdown
+License-File: LICENSE
+Requires-Dist: colorama; sys_platform == "win32"
+Provides-Extra: development
+Requires-Dist: black; extra == "development"
+Requires-Dist: flake8; extra == "development"
+Requires-Dist: mypy; extra == "development"
+Requires-Dist: pytest; extra == "development"
+Requires-Dist: types-colorama; extra == "development"
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: description-content-type
+Dynamic: home-page
+Dynamic: license
+Dynamic: license-file
+Dynamic: provides-extra
+Dynamic: requires-python
+Dynamic: summary
+
+# Log formatting with colors!
+
+[![](https://img.shields.io/pypi/v/colorlog.svg)](https://pypi.org/project/colorlog/)
+[![](https://img.shields.io/pypi/l/colorlog.svg)](https://pypi.org/project/colorlog/)
+
+Add colours to the output of Python's `logging` module.
+
+- [Source on GitHub](https://github.com/borntyping/python-colorlog)
+- [Package on PyPI](https://pypi.org/pypi/colorlog/)
+
+## Status
+
+colorlog currently requires Python 3.6 or higher. Older versions (below 5.x.x)
+support Python 2.6 and above.
+
+- colorlog 6.x requires Python 3.6 or higher.
+- colorlog 5.x is an interim version that will warn Python 2 users to downgrade.
+- colorlog 4.x is the final version supporting Python 2.
+
+[colorama] is included as a dependency on Windows, where it is automatically
+initialised to support colored output.
+
+This library is over a decade old and supported a wide set of Python versions
+for most of its life, which has made it a difficult library to add new features
+to. colorlog 6 may break backwards compatibility so that newer features
+can be added more easily, but may still not accept all changes or feature
+requests. colorlog 4 might accept essential bugfixes but should not be
+considered actively maintained and will not accept any major changes or new
+features.
+
+## Installation
+
+Install from PyPI with:
+
+```bash
+pip install colorlog
+```
+
+Several Linux distributions provide official packages ([Debian], [Arch],
+[Fedora], [Gentoo], [OpenSuse] and [Ubuntu]), and others have user provided
+packages ([BSD ports], [Conda]).
+
+## Usage
+
+```python
+import colorlog
+
+handler = colorlog.StreamHandler()
+handler.setFormatter(colorlog.ColoredFormatter())
+
+logger = colorlog.getLogger('example')
+logger.addHandler(handler)
+```
+
+### Arguments
+
+`ColoredFormatter` extends [`logging.Formatter`][formatter] and accepts the
+following arguments:
+
+- `fmt` *(default=`None`)*: A format string used to output the message. If
+  `None`, a default format string is selected based on `style` (e.g.
+  `%(log_color)s%(levelname)s:%(name)s:%(message)s` for `%` style).
+- `datefmt`, `style`, `validate`, `defaults`: see
+  [`logging.Formatter`][formatter].
+- `reset` *(default=`True`)*: Implicitly adds a color reset code to the
+  message output, unless the output already ends with one.
+- `log_colors` *(default=`None`)*: A mapping of record level names to color
+  names. If `None`, `colorlog.default_log_colors` is used.
+- `secondary_log_colors` *(default=`None`)*: A mapping of names to `log_colors`
+  style mappings, defining additional colors that can be used in format strings.
+  If `None`, an empty mapping is used.
+- `stream` *(default=`None`)*: The stream being written to (e.g. `sys.stderr`).
+  Used to detect whether the output is a TTY. Colors are disabled automatically
+  on non-TTY streams unless `force_color` is set.
+- `no_color` *(default=`False`)*: Disable color output. Can also be set via the
+  `NO_COLOR` environment variable.
+- `force_color` *(default=`False`)*: Force color output even on non-TTY streams.
+  Takes precedence over `no_color`. Can also be set via the `FORCE_COLOR`
+  environment variable.
+
+### Color escape codes
+
+Color escape codes can be selected based on the log records level, by adding
+parameters to the format string:
+
+- `log_color`: Return the color associated with the records level.
+- `<name>_log_color`: Return another color based on the records level if the
+  formatter has secondary colors configured (see `secondary_log_colors` below).
+
+Multiple escape codes can be used at once by joining them with commas when
+configuring the color for a log level (but can't be used directly in the format
+string). For example, `black,bg_white` would use the escape codes for black
+text on a white background.
+
+The following escape codes are made available for use in the format string:
+
+- `{color}`, `fg_{color}`, `bg_{color}`: Foreground and background colors.
+- `bold`, `bold_{color}`, `fg_bold_{color}`, `bg_bold_{color}`: Bold/bright
+  colors.
+- `thin`, `thin_{color}`, `fg_thin_{color}`: Thin colors (terminal dependent).
+- `reset`: Clear all formatting (both foreground and background colors).
+
+The available color names are:
+
+- `black`
+- `red`
+- `green`
+- `yellow`
+- `blue`
+- `purple`
+- `cyan`
+- `white`
+
+You can also use "bright" colors. These aren't standard ANSI codes, and
+support for these varies wildly across different terminals.
+
+- `light_black`
+- `light_red`
+- `light_green`
+- `light_yellow`
+- `light_blue`
+- `light_purple`
+- `light_cyan`
+- `light_white`
+
+In addition to pre-defined color names, you can use integers from 0 to 255 for
+256-color support (e.g. `fg_196`, `bg_42`).
+
+## Examples
+
+![Example output](docs/example.png)
+
+The following snippet creates a `ColoredFormatter` for use in a logging setup,
+with a custom format string and log colors:
+
+```python
+from colorlog import ColoredFormatter
+
+formatter = ColoredFormatter(
+	"%(log_color)s%(levelname)-8s%(reset)s %(blue)s%(message)s",
+	log_colors={
+		"DEBUG": "cyan",
+		"INFO": "green",
+		"WARNING": "yellow",
+		"ERROR": "red",
+		"CRITICAL": "red,bg_white",
+	}
+)
+```
+
+*See `docs/example.py` for full example script.*
+
+### Using `secondary_log_colors`
+
+Secondary log colors are a way to have more than one color that is selected
+based on the log level. Each key in `secondary_log_colors` adds an attribute
+that can be used in format strings (`message` becomes `message_log_color`), and
+has a corresponding value that is identical in format to the `log_colors`
+argument.
+
+The following example highlights the level name using the default log colors,
+and highlights the message in red for `error` and `critical` level log messages.
+
+```python
+from colorlog import ColoredFormatter
+
+formatter = ColoredFormatter(
+	"%(log_color)s%(levelname)-8s%(reset)s %(message_log_color)s%(message)s",
+	secondary_log_colors={
+		'message': {
+			'ERROR': 'red',
+			'CRITICAL': 'red'
+		}
+	}
+)
+```
+
+### With [`dictConfig`][dictconfig]
+
+```python
+logging.config.dictConfig({
+	'formatters': {
+		'colored': {
+			'()': 'colorlog.ColoredFormatter',
+			'format': "%(log_color)s%(levelname)-8s%(reset)s %(blue)s%(message)s"
+		}
+	}
+})
+```
+
+A full example dictionary can be found in `tests/test_colorlog.py`.
+
+### With [`fileConfig`][fileconfig]
+
+```ini
+...
+
+[formatters]
+keys=color
+
+[formatter_color]
+class=colorlog.ColoredFormatter
+format=%(log_color)s%(levelname)-8s%(reset)s %(bg_blue)s[%(name)s]%(reset)s %(message)s from fileConfig
+datefmt=%m-%d %H:%M:%S
+```
+
+An instance of ColoredFormatter created with those arguments will then be used
+by any handlers that are configured to use the `color` formatter.
+
+A full example configuration can be found in `tests/test_config.ini`.
+
+### With custom log levels
+
+ColoredFormatter will work with custom log levels added with
+[`logging.addLevelName`][addlevelname]:
+
+```python
+import logging, colorlog
+TRACE = 5
+logging.addLevelName(TRACE, 'TRACE')
+formatter = colorlog.ColoredFormatter(log_colors={'TRACE': 'yellow'})
+handler = logging.StreamHandler()
+handler.setFormatter(formatter)
+logger = logging.getLogger('example')
+logger.addHandler(handler)
+logger.setLevel('TRACE')
+logger.log(TRACE, 'a message using a custom level')
+```
+
+## Tests
+
+Tests similar to the above examples are found in `tests/test_colorlog.py`.
+
+## Status
+
+colorlog is in maintenance mode. I try and ensure bugfixes are published,
+but compatibility a wide set of Python versions makes this a difficult
+codebase to add features to. Any changes that might break backwards
+compatibility for existing users will not be considered.
+
+## Alternatives
+
+There are some more modern libraries for improving Python logging you may
+find useful.
+
+- [structlog]
+- [jsonlog]
+
+## Projects using colorlog
+
+GitHub provides [a list of projects that depend on colorlog][dependents].
+
+Some early adopters included [Errbot], [Pythran], and [zenlog].
+
+## Licence
+
+Copyright (c) 2012-2025 Sam Clements <sam@borntyping.co.uk>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
+the Software, and to permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+[addlevelname]: https://docs.python.org/3/library/logging.html#logging.addLevelName
+[arch]: https://archlinux.org/packages/extra/any/python-colorlog/
+[bsd ports]: https://www.freshports.org/devel/py-colorlog/
+[colorama]: https://pypi.python.org/pypi/colorama
+[conda]: https://anaconda.org/conda-forge/colorlog
+[debian]: https://packages.debian.org/trixie/python3-colorlog
+[dependents]: https://github.com/borntyping/python-colorlog/network/dependents?package_id=UGFja2FnZS01MDk3NDcyMQ%3D%3D
+[dictconfig]: http://docs.python.org/3/library/logging.config.html#logging.config.dictConfig
+[errbot]: http://errbot.io/
+[fedora]: https://src.fedoraproject.org/rpms/python-colorlog
+[fileconfig]: http://docs.python.org/3/library/logging.config.html#logging.config.fileConfig
+[formatter]: http://docs.python.org/3/library/logging.html#logging.Formatter
+[gentoo]: https://packages.gentoo.org/packages/dev-python/colorlog
+[jsonlog]: https://github.com/borntyping/jsonlog
+[opensuse]: http://rpm.pbone.net/index.php3?stat=3&search=python-colorlog&srodzaj=3
+[pythran]: https://github.com/serge-sans-paille/pythran
+[structlog]: https://www.structlog.org/en/stable/
+[ubuntu]: https://launchpad.net/python-colorlog
+[zenlog]: https://github.com/ManufacturaInd/python-zenlog

.cache/pip/http-v2/9/b/c/f/c/9bcfc39a5bcc4f49a5aca18ef0b4567e959c4b71251fb90ea1371fe7.body

@@ -0,0 +1,1600 @@
+Metadata-Version: 2.4
+Name: tqdm
+Version: 4.70.0
+Summary: Fast, Extensible Progress Meter
+Maintainer-email: tqdm developers <devs@tqdm.ml>
+License: MPL-2.0 AND MIT
+Project-URL: homepage, https://tqdm.github.io
+Project-URL: repository, https://github.com/tqdm/tqdm
+Project-URL: changelog, https://tqdm.github.io/releases
+Project-URL: wiki, https://github.com/tqdm/tqdm/wiki
+Keywords: progressbar,progressmeter,progress,bar,meter,rate,eta,console,terminal,time
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Console
+Classifier: Environment :: MacOS X
+Classifier: Environment :: Other Environment
+Classifier: Environment :: Win32 (MS Windows)
+Classifier: Environment :: X11 Applications
+Classifier: Framework :: IPython
+Classifier: Framework :: Jupyter
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: End Users/Desktop
+Classifier: Intended Audience :: Other Audience
+Classifier: Intended Audience :: System Administrators
+Classifier: Operating System :: MacOS
+Classifier: Operating System :: MacOS :: MacOS X
+Classifier: Operating System :: Microsoft
+Classifier: Operating System :: Microsoft :: MS-DOS
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX
+Classifier: Operating System :: POSIX :: BSD
+Classifier: Operating System :: POSIX :: BSD :: FreeBSD
+Classifier: Operating System :: POSIX :: Linux
+Classifier: Operating System :: POSIX :: SunOS/Solaris
+Classifier: Operating System :: Unix
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: Implementation
+Classifier: Programming Language :: Python :: Implementation :: IronPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Programming Language :: Unix Shell
+Classifier: Topic :: Desktop Environment
+Classifier: Topic :: Education :: Computer Aided Instruction (CAI)
+Classifier: Topic :: Education :: Testing
+Classifier: Topic :: Office/Business
+Classifier: Topic :: Other/Nonlisted Topic
+Classifier: Topic :: Software Development :: Build Tools
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Topic :: Software Development :: Pre-processors
+Classifier: Topic :: Software Development :: User Interfaces
+Classifier: Topic :: System :: Installation/Setup
+Classifier: Topic :: System :: Logging
+Classifier: Topic :: System :: Monitoring
+Classifier: Topic :: System :: Shells
+Classifier: Topic :: Terminals
+Classifier: Topic :: Utilities
+Requires-Python: >=3.8
+Description-Content-Type: text/x-rst
+License-File: LICENCE
+Requires-Dist: colorama; platform_system == "Windows"
+Provides-Extra: discord
+Requires-Dist: requests; extra == "discord"
+Requires-Dist: envwrap; extra == "discord"
+Provides-Extra: slack
+Requires-Dist: slack-sdk; extra == "slack"
+Requires-Dist: envwrap; extra == "slack"
+Provides-Extra: telegram
+Requires-Dist: requests; extra == "telegram"
+Requires-Dist: envwrap; extra == "telegram"
+Provides-Extra: notebook
+Requires-Dist: ipywidgets>=6; extra == "notebook"
+Dynamic: license-file
+
+|Logo|
+
+tqdm
+====
+
+|Py-Versions| |Versions| |Conda-Forge-Status| |Docker| |Snapcraft|
+
+|Build-Status| |Coverage-Status| |Branch-Coverage-Status| |Codacy-Grade| |Libraries-Rank| |PyPI-Downloads|
+
+|LICENCE| |OpenHub-Status| |colab-demo| |binder-demo| |awesome-python|
+
+``tqdm`` derives from the Arabic word *taqaddum* (تقدّم) which can mean "progress,"
+and is an abbreviation for "I love you so much" in Spanish (*te quiero demasiado*).
+
+Instantly make your loops show a smart progress meter - just wrap any
+iterable with ``tqdm(iterable)``, and you're done!
+
+.. code:: python
+
+    from tqdm import tqdm
+    for i in tqdm(range(10000)):
+        ...
+
+``76%|████████████████████████        | 7568/10000 [00:33<00:10, 229.00it/s]``
+
+``trange(N)`` can also be used as a convenient shortcut for
+``tqdm(range(N))``.
+
+|Screenshot|
+    |Video| |Slides| |Merch|
+
+It can also be executed as a module with pipes:
+
+.. code:: sh
+
+    $ seq 9999999 | tqdm --bytes | wc -l
+    75.2MB [00:00, 217MB/s]
+    9999999
+
+    $ tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` \
+        > backup.tgz
+     32%|██████████▍                      | 8.89G/27.9G [00:42<01:31, 223MB/s]
+
+Overhead is low -- about 60ns per iteration (80ns with ``tqdm.gui``), and is
+unit tested against performance regression.
+By comparison, the well-established
+`ProgressBar <https://github.com/niltonvolpato/python-progressbar>`__ has
+an 800ns/iter overhead.
+
+In addition to its low overhead, ``tqdm`` uses smart algorithms to predict
+the remaining time and to skip unnecessary iteration displays, which allows
+for a negligible overhead in most cases.
+
+``tqdm`` works on any platform
+(Linux, Windows, Mac, FreeBSD, NetBSD, Solaris/SunOS),
+in any console or in a GUI, and is also friendly with IPython/Jupyter notebooks.
+
+``tqdm`` does not require any dependencies (not even ``curses``!), just
+Python and an environment supporting ``carriage return \r`` and
+``line feed \n`` control characters.
+
+**Featured Sponsors**
+
+======== ================================================
+|OpenAI|                  Your Logo Here
+======== ================================================
+OpenAI   `Sponsors <https://github.com/sponsors/tqdm>`__
+======== ================================================
+
+.. |OpenAI| image:: https://avatars.githubusercontent.com/u/14957082?s=96
+   :target: https://openai.com
+
+------------------------------------------
+
+.. contents:: Table of contents
+   :backlinks: top
+   :local:
+
+
+Installation
+------------
+
+Latest PyPI stable release
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+|Versions| |PyPI-Downloads| |Libraries-Dependents|
+
+.. code:: sh
+
+    pip install tqdm
+
+Latest development release on GitHub
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+|GitHub-Status| |GitHub-Stars| |GitHub-Commits| |GitHub-Forks| |GitHub-Updated|
+
+Pull and install pre-release ``devel`` branch:
+
+.. code:: sh
+
+    pip install "git+https://github.com/tqdm/tqdm.git@devel#egg=tqdm"
+
+Latest Conda release
+~~~~~~~~~~~~~~~~~~~~
+
+|Conda-Forge-Status|
+
+.. code:: sh
+
+    conda install -c conda-forge tqdm
+
+Latest Snapcraft release
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+|Snapcraft|
+
+There are 3 channels to choose from:
+
+.. code:: sh
+
+    snap install tqdm  # implies --stable, i.e. latest tagged release
+    snap install tqdm  --candidate  # master branch
+    snap install tqdm  --edge  # devel branch
+
+Note that ``snap`` binaries are purely for CLI use (not ``import``-able), and
+automatically set up ``bash`` tab-completion.
+
+Latest Docker release
+~~~~~~~~~~~~~~~~~~~~~
+
+|Docker|
+
+.. code:: sh
+
+    docker pull tqdm/tqdm
+    docker run -i --rm tqdm/tqdm --help
+
+Other
+~~~~~
+
+There are other (unofficial) places where ``tqdm`` may be downloaded, particularly for CLI use:
+
+|Repology|
+
+.. |Repology| image:: https://repology.org/badge/tiny-repos/python:tqdm.svg
+   :target: https://repology.org/project/python:tqdm/versions
+
+Changelog
+---------
+
+The list of all changes is available either on GitHub's Releases:
+|GitHub-Status|, on the
+`wiki <https://github.com/tqdm/tqdm/wiki/Releases>`__, or on the
+`website <https://tqdm.github.io/releases>`__.
+
+
+Usage
+-----
+
+``tqdm`` is very versatile and can be used in a number of ways.
+The three main ones are given below.
+
+Iterable-based
+~~~~~~~~~~~~~~
+
+Wrap ``tqdm()`` around any iterable:
+
+.. code:: python
+
+    from tqdm import tqdm
+    from time import sleep
+
+    text = ""
+    for char in tqdm(["a", "b", "c", "d"]):
+        sleep(0.25)
+        text = text + char
+
+``trange(i)`` is a special optimised instance of ``tqdm(range(i))``:
+
+.. code:: python
+
+    from tqdm import trange
+
+    for i in trange(100):
+        sleep(0.01)
+
+Instantiation outside of the loop allows for manual control over ``tqdm()``:
+
+.. code:: python
+
+    pbar = tqdm(["a", "b", "c", "d"])
+    for char in pbar:
+        sleep(0.25)
+        pbar.set_description("Processing %s" % char)
+
+Manual
+~~~~~~
+
+Manual control of ``tqdm()`` updates using a ``with`` statement:
+
+.. code:: python
+
+    with tqdm(total=100) as pbar:
+        for i in range(10):
+            sleep(0.1)
+            pbar.update(10)
+
+If the optional variable ``total`` (or an iterable with ``len()``) is
+provided, predictive stats are displayed.
+
+``with`` is also optional (you can just assign ``tqdm()`` to a variable,
+but in this case don't forget to ``del`` or ``close()`` at the end:
+
+.. code:: python
+
+    pbar = tqdm(total=100)
+    for i in range(10):
+        sleep(0.1)
+        pbar.update(10)
+    pbar.close()
+
+Module
+~~~~~~
+
+Perhaps the most wonderful use of ``tqdm`` is in a script or on the command
+line. Simply inserting ``tqdm`` (or ``python -m tqdm``) between pipes will pass
+through all ``stdin`` to ``stdout`` while printing progress to ``stderr``.
+
+The example below demonstrate counting the number of lines in all Python files
+in the current directory, with timing information included.
+
+.. code:: sh
+
+    $ time find . -name '*.py' -type f -exec cat \{} \; | wc -l
+    857365
+
+    real    0m3.458s
+    user    0m0.274s
+    sys     0m3.325s
+
+    $ time find . -name '*.py' -type f -exec cat \{} \; | tqdm | wc -l
+    857366it [00:03, 246471.31it/s]
+    857365
+
+    real    0m3.585s
+    user    0m0.862s
+    sys     0m3.358s
+
+Note that the usual arguments for ``tqdm`` can also be specified.
+
+.. code:: sh
+
+    $ find . -name '*.py' -type f -exec cat \{} \; |
+        tqdm --unit loc --unit_scale --total 857366 >> /dev/null
+    100%|█████████████████████████████████| 857K/857K [00:04<00:00, 246Kloc/s]
+
+Backing up a large directory?
+
+.. code:: sh
+
+    $ tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` \
+      > backup.tgz
+     44%|██████████████▊                   | 153M/352M [00:14<00:18, 11.0MB/s]
+
+This can be beautified further:
+
+.. code:: sh
+
+    $ BYTES=$(du -sb docs/ | cut -f1)
+    $ tar -cf - docs/ \
+      | tqdm --bytes --total "$BYTES" --desc Processing | gzip \
+      | tqdm --bytes --total "$BYTES" --desc Compressed --position 1 \
+      > ~/backup.tgz
+    Processing: 100%|██████████████████████| 352M/352M [00:14<00:00, 30.2MB/s]
+    Compressed:  42%|█████████▎            | 148M/352M [00:14<00:19, 10.9MB/s]
+
+Or done on a file level using 7-zip:
+
+.. code:: sh
+
+    $ 7z a -bd -r backup.7z docs/ | grep Compressing \
+      | tqdm --total $(find docs/ -type f | wc -l) --unit files \
+      | grep -v Compressing
+    100%|██████████████████████████▉| 15327/15327 [01:00<00:00, 712.96files/s]
+
+Pre-existing CLI programs already outputting basic progress information will
+benefit from ``tqdm``'s ``--update`` and ``--update_to`` flags:
+
+.. code:: sh
+
+    $ seq 3 0.1 5 | tqdm --total 5 --update_to --null
+    100%|████████████████████████████████████| 5.0/5 [00:00<00:00, 9673.21it/s]
+    $ seq 10 | tqdm --update --null  # 1 + 2 + ... + 10 = 55 iterations
+    55it [00:00, 90006.52it/s]
+
+FAQ and Known Issues
+--------------------
+
+|GitHub-Issues|
+
+The most common issues relate to excessive output on multiple lines, instead
+of a neat one-line progress bar.
+
+- Consoles in general: require support for carriage return (``CR``, ``\r``).
+
+  * Some cloud logging consoles which don't support ``\r`` properly
+    (`cloudwatch <https://github.com/tqdm/tqdm/issues/966>`__,
+    `K8s <https://github.com/tqdm/tqdm/issues/1319>`__) may benefit from
+    ``export TQDM_POSITION=-1``.
+
+- Nested progress bars:
+
+  * Consoles in general: require support for moving cursors up to the
+    previous line. For example,
+    `IDLE <https://github.com/tqdm/tqdm/issues/191#issuecomment-230168030>`__,
+    `ConEmu <https://github.com/tqdm/tqdm/issues/254>`__ and
+    `PyCharm <https://github.com/tqdm/tqdm/issues/203>`__ (also
+    `here <https://github.com/tqdm/tqdm/issues/208>`__,
+    `here <https://github.com/tqdm/tqdm/issues/307>`__, and
+    `here <https://github.com/tqdm/tqdm/issues/454#issuecomment-335416815>`__)
+    lack full support.
+  * Windows: additionally may require the Python module ``colorama``
+    to ensure nested bars stay within their respective lines.
+
+- Unicode:
+
+  * Environments which report that they support unicode will have solid smooth
+    progress bars. The fallback is an ``ascii``-only bar.
+  * Windows consoles often only partially support unicode and thus
+    `often require explicit ascii=True <https://github.com/tqdm/tqdm/issues/454#issuecomment-335416815>`__
+    (also `here <https://github.com/tqdm/tqdm/issues/499>`__). This is due to
+    either normal-width unicode characters being incorrectly displayed as
+    "wide", or some unicode characters not rendering.
+
+- Wrapping generators:
+
+  * Generator wrapper functions tend to hide the length of iterables.
+    ``tqdm`` does not.
+  * Replace ``tqdm(enumerate(...))`` with ``enumerate(tqdm(...))`` or
+    ``tqdm(enumerate(x), total=len(x), ...)``.
+    The same applies to ``numpy.ndenumerate``.
+  * Replace ``tqdm(zip(a, b))`` with ``zip(tqdm(a), b)`` or even
+    ``zip(tqdm(a), tqdm(b))``.
+  * The same applies to ``itertools``.
+  * Some useful convenience functions can be found under ``tqdm.contrib``.
+
+- `No intermediate output in docker-compose <https://github.com/tqdm/tqdm/issues/771>`__:
+  use ``docker-compose run`` instead of ``docker-compose up`` and ``tty: true``.
+
+- Overriding defaults via environment variables:
+  e.g. in CI/cloud jobs, ``export TQDM_MININTERVAL=5`` to avoid log spam.
+  This override logic is handled by the ``tqdm.utils.envwrap`` decorator
+  (useful independent of ``tqdm``).
+
+If you come across any other difficulties, browse and file |GitHub-Issues|.
+
+Documentation
+-------------
+
+|Py-Versions| |README-Hits| (Since 19 May 2016)
+
+.. code:: python
+
+    class tqdm():
+      """
+      Decorate an iterable object, returning an iterator which acts exactly
+      like the original iterable, but prints a dynamically updating
+      progress bar every time a value is requested.
+      """
+
+      @envwrap("tqdm")  # override defaults via env vars
+      def __init__(self, iterable=None, desc=None, total=None, leave=True,
+                   file=None, ncols=None, mininterval=0.1,
+                   maxinterval=10.0, miniters=None, ascii=None, disable=False,
+                   unit='it', unit_scale=False, dynamic_ncols=False,
+                   smoothing=0.3, bar_format=None, initial=0, position=None,
+                   postfix=None, unit_divisor=1000, write_bytes=False,
+                   lock_args=None, nrows=None, colour=None, delay=0):
+
+Parameters
+~~~~~~~~~~
+
+* iterable  : iterable, optional  
+    Iterable to decorate with a progress bar.
+    Leave blank to manually manage the updates.
+* desc  : str, optional  
+    Prefix for the progress bar.
+* total  : int or float, optional  
+    The number of expected iterations. If unspecified,
+    len(iterable) is used if possible. If float("inf") or as a last
+    resort, only basic progress statistics are displayed
+    (no ETA, no progress bar).
+    If ``gui`` is True and this parameter needs subsequent updating,
+    specify an initial arbitrary large positive number,
+    e.g. 9e9.
+* leave  : bool, optional  
+    If [default: True], keeps all traces of the progress bar
+    upon termination of iteration.
+    If ``None``, will leave only if ``position`` is ``0``.
+* file  : ``io.TextIOWrapper`` or ``io.StringIO``, optional  
+    Specifies where to output the progress messages
+    (default: sys.stderr). Uses ``file.write(str)`` and ``file.flush()``
+    methods.  For encoding, see ``write_bytes``.
+* ncols  : int, optional  
+    The width of the entire output message. If specified,
+    dynamically resizes the progress bar to stay within this bound.
+    If unspecified, attempts to use environment width. The
+    fallback is a meter width of 10 and no limit for the counter and
+    statistics. If 0, will not print any meter (only stats).
+* mininterval  : float, optional  
+    Minimum progress display update interval [default: 0.1] seconds.
+* maxinterval  : float, optional  
+    Maximum progress display update interval [default: 10] seconds.
+    Automatically adjusts ``miniters`` to correspond to ``mininterval``
+    after long display update lag. Only works if ``dynamic_miniters``
+    or monitor thread is enabled.
+* miniters  : int or float, optional  
+    Minimum progress display update interval, in iterations.
+    If 0 and ``dynamic_miniters``, will automatically adjust to equal
+    ``mininterval`` (more CPU efficient, good for tight loops).
+    If > 0, will skip display of specified number of iterations.
+    Tweak this and ``mininterval`` to get very efficient loops.
+    If your progress is erratic with both fast and slow iterations
+    (network, skipping items, etc) you should set miniters=1.
+* ascii  : bool or str, optional  
+    If unspecified or False, use unicode (smooth blocks) to fill
+    the meter. The fallback is to use ASCII characters " 123456789#".
+* disable  : bool, optional  
+    Whether to disable the entire progress bar wrapper
+    [default: False]. If set to None, disable on non-TTY.
+* unit  : str, optional  
+    String that will be used to define the unit of each iteration
+    [default: it].
+* unit_scale  : bool or int or float, optional  
+    If 1 or True, the number of iterations will be reduced/scaled
+    automatically and a metric prefix following the
+    International System of Units standard will be added
+    (kilo, mega, etc.) [default: False]. If any other non-zero
+    number, will scale ``total`` and ``n``.
+* dynamic_ncols  : bool, optional  
+    If set, constantly alters ``ncols`` and ``nrows`` to the
+    environment (allowing for window resizes) [default: False].
+* smoothing  : float, optional  
+    Exponential moving average smoothing factor for speed estimates
+    (ignored in GUI mode). Ranges from 0 (average speed) to 1
+    (current/instantaneous speed) [default: 0.3].
+* bar_format  : str, optional  
+    Specify a custom bar string formatting. May impact performance.
+    [default: '{l_bar}{bar}{r_bar}'], where
+    l_bar='{desc}: {percentage:3.0f}%|' and
+    r_bar='| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, '
+    '{rate_fmt}{postfix}]'
+    Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,
+    percentage, elapsed, elapsed_s, ncols, nrows, desc, unit,
+    rate, rate_fmt, rate_noinv, rate_noinv_fmt,
+    rate_inv, rate_inv_fmt, postfix, unit_divisor,
+    remaining, remaining_s, eta.
+    Note that a trailing ": " is automatically removed after {desc}
+    if the latter is empty.
+* initial  : int or float, optional  
+    The initial counter value. Useful when restarting a progress
+    bar [default: 0]. If using float, consider specifying ``{n:.3f}``
+    or similar in ``bar_format``, or specifying ``unit_scale``.
+* position  : int, optional  
+    Specify the line offset to print this bar (starting from 0)
+    Automatic if unspecified.
+    Useful to manage multiple bars at once (eg, from threads).
+* postfix  : dict or ``*``, optional  
+    Specify additional stats to display at the end of the bar.
+    Calls ``set_postfix(**postfix)`` if possible (dict).
+* unit_divisor  : float, optional  
+    [default: 1000], ignored unless ``unit_scale`` is True.
+* write_bytes  : bool, optional  
+    Whether to write bytes. If (default: False) will write unicode.
+* lock_args  : tuple, optional  
+    Passed to ``refresh`` for intermediate output
+    (initialisation, iterating, and updating).
+* nrows  : int, optional  
+    The screen height. If specified, hides nested bars outside this
+    bound. If unspecified, attempts to use environment height.
+    The fallback is 20.
+* colour  : str, optional  
+    Bar colour (e.g. 'green', '#00ff00').
+* delay  : float, optional  
+    Don't display until [default: 0] seconds have elapsed.
+
+Extra CLI Options
+~~~~~~~~~~~~~~~~~
+
+* delim  : chr, optional  
+    Delimiting character [default: '\n']. Use '\0' for null.
+    N.B.: on Windows systems, Python converts '\n' to '\r\n'.
+* buf_size  : int, optional  
+    String buffer size in bytes [default: 256]
+    used when ``delim`` is specified.
+* bytes  : bool, optional  
+    If true, will count bytes, ignore ``delim``, and default
+    ``unit_scale`` to True, ``unit_divisor`` to 1024, and ``unit`` to 'B'.
+* tee  : bool, optional  
+    If true, passes ``stdin`` to both ``stderr`` and ``stdout``.
+* update  : bool, optional  
+    If true, will treat input as newly elapsed iterations,
+    i.e. numbers to pass to ``update()``. Note that this is slow
+    (~2e5 it/s) since every input must be decoded as a number.
+* update_to  : bool, optional  
+    If true, will treat input as total elapsed iterations,
+    i.e. numbers to assign to ``self.n``. Note that this is slow
+    (~2e5 it/s) since every input must be decoded as a number.
+* null  : bool, optional  
+    If true, will discard input (no stdout).
+* manpath  : str, optional  
+    Directory in which to install tqdm man pages.
+* comppath  : str, optional  
+    Directory in which to place tqdm completion.
+* log  : str, optional  
+    CRITICAL|FATAL|ERROR|WARN(ING)|[default: 'INFO']|DEBUG|NOTSET.
+
+Returns
+~~~~~~~
+
+* out  : decorated iterator.  
+
+.. code:: python
+
+    class tqdm():
+      def update(self, n=1):
+          """
+          Manually update the progress bar, useful for streams
+          such as reading files.
+          E.g.:
+          >>> t = tqdm(total=filesize) # Initialise
+          >>> for current_buffer in stream:
+          ...    ...
+          ...    t.update(len(current_buffer))
+          >>> t.close()
+          The last line is highly recommended, but possibly not necessary if
+          `t.update()` will be called in such a way that `filesize` will be
+          exactly reached and printed.
+
+          Parameters
+          ----------
+          n  : int or float, optional
+              Increment to add to the internal counter of iterations
+              [default: 1]. If using float, consider specifying `{n:.3f}`
+              or similar in `bar_format`, or specifying `unit_scale`.
+
+          Returns
+          -------
+          out  : bool or None
+              True if a `display()` was triggered.
+          """
+
+      def close(self):
+          """Cleanup and (if leave=False) close the progress bar."""
+
+      def clear(self, nomove=False):
+          """Clear current bar display."""
+
+      def refresh(self):
+          """
+          Force refresh the display of this bar.
+
+          Parameters
+          ----------
+          nolock  : bool, optional
+              If `True`, does not lock.
+              If [default: `False`]: calls `acquire()` on internal lock.
+          lock_args  : tuple, optional
+              Passed to internal lock's `acquire()`.
+              If specified, will only `display()` if `acquire()` returns `True`.
+          """
+
+      def unpause(self):
+          """Restart tqdm timer from last print time."""
+
+      def reset(self, total=None):
+          """
+          Resets to 0 iterations for repeated use.
+
+          Consider combining with `leave=True`.
+
+          Parameters
+          ----------
+          total  : int or float, optional. Total to use for the new bar.
+          """
+
+      def set_description(self, desc=None, refresh=True):
+          """
+          Set/modify description of the progress bar.
+
+          Parameters
+          ----------
+          desc  : str, optional
+          refresh  : bool, optional
+              Forces refresh [default: True].
+          """
+
+      def set_postfix(self, ordered_dict=None, refresh=True, **tqdm_kwargs):
+          """
+          Set/modify postfix (additional stats)
+          with automatic formatting based on datatype.
+
+          Parameters
+          ----------
+          ordered_dict  : dict or OrderedDict, optional
+          refresh  : bool, optional
+              Forces refresh [default: True].
+          kwargs  : dict, optional
+          """
+
+      @classmethod
+      def write(cls, s, file=sys.stdout, end="\n"):
+          """Print a message via tqdm (without overlap with bars)."""
+
+      @property
+      def format_dict(self):
+          """Public API for read-only member access."""
+
+      def display(self, msg=None, pos=None):
+          """
+          Use `self.sp` to display `msg` in the specified `pos`.
+
+          Consider overloading this function when inheriting to use e.g.:
+          `self.some_frontend(**self.format_dict)` instead of `self.sp`.
+
+          Parameters
+          ----------
+          msg  : str, optional. What to display (default: `repr(self)`).
+          pos  : int, optional. Position to `moveto`
+            (default: `abs(self.pos)`).
+          """
+
+      @classmethod
+      @contextmanager
+      def wrapattr(cls, stream, method, total=None, bytes=True, **tqdm_kwargs):
+          """
+          stream  : file-like object.
+          method  : str, "read" or "write". The result of `read()` and
+              the first argument of `write()` should have a `len()`.
+
+          >>> with tqdm.wrapattr(file_obj, "read", total=file_obj.size) as fobj:
+          ...     while True:
+          ...         chunk = fobj.read(chunk_size)
+          ...         if not chunk:
+          ...             break
+          """
+
+      @classmethod
+      def pandas(cls, *targs, **tqdm_kwargs):
+          """Registers the current `tqdm` class with `pandas`."""
+
+    def trange(*args, **tqdm_kwargs):
+        """Shortcut for `tqdm(range(*args), **tqdm_kwargs)`."""
+
+Convenience Functions
+~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: python
+
+    def tqdm.contrib.tenumerate(iterable, start=0, total=None,
+                                tqdm_class=tqdm.auto.tqdm, **tqdm_kwargs):
+        """Equivalent of `numpy.ndenumerate` or builtin `enumerate`."""
+
+    def tqdm.contrib.tzip(iter1, *iter2plus, **tqdm_kwargs):
+        """Equivalent of builtin `zip`."""
+
+    def tqdm.contrib.tmap(function, *sequences, **tqdm_kwargs):
+        """Equivalent of builtin `map`."""
+
+Submodules
+~~~~~~~~~~
+
+.. code:: python
+
+    class tqdm.notebook.tqdm(tqdm.tqdm):
+        """IPython/Jupyter Notebook widget."""
+
+    class tqdm.auto.tqdm(tqdm.tqdm):
+        """Automatically chooses between `tqdm.notebook` and `tqdm.tqdm`."""
+
+    class tqdm.asyncio.tqdm(tqdm.tqdm):
+      """Asynchronous version."""
+      @classmethod
+      def as_completed(cls, fs, *, loop=None, timeout=None, total=None,
+                       **tqdm_kwargs):
+          """Wrapper for `asyncio.as_completed`."""
+
+    class tqdm.gui.tqdm(tqdm.tqdm):
+        """Matplotlib GUI version."""
+
+    class tqdm.tk.tqdm(tqdm.tqdm):
+        """Tkinter GUI version."""
+
+    class tqdm.rich.tqdm(tqdm.tqdm):
+        """`rich.progress` version."""
+
+    class tqdm.keras.TqdmCallback(keras.callbacks.Callback):
+        """Keras callback for epoch and batch progress."""
+
+    class tqdm.dask.TqdmCallback(dask.callbacks.Callback):
+        """Dask callback for task progress."""
+
+
+``contrib``
++++++++++++
+
+The ``tqdm.contrib`` package also contains experimental modules:
+
+- `tqdm.contrib.itertools <https://tqdm.github.io/docs/contrib.itertools/>`_: Thin wrappers around ``itertools``
+- `tqdm.contrib.concurrent <https://tqdm.github.io/docs/contrib.concurrent/>`_: Thin wrappers around ``concurrent.futures``
+- `tqdm.contrib.slack <https://tqdm.github.io/docs/contrib.slack/>`_: Posts to `Slack <https://slack.com>`__ bots
+- `tqdm.contrib.discord <https://tqdm.github.io/docs/contrib.discord/>`_: Posts to `Discord <https://discord.com>`__ bots
+- `tqdm.contrib.telegram <https://tqdm.github.io/docs/contrib.telegram/>`_: Posts to `Telegram <https://telegram.org>`__ bots
+- `tqdm.contrib.bells <https://tqdm.github.io/docs/shortcuts/>`_: Automagically enables all optional features
+
+  * ``auto``, ``pandas``, ``slack``, ``discord``, ``telegram``
+
+.. image:: https://tqdm.github.io/img/screenshot-discord.png
+   :alt: Screenshot of `tqdm.contrib.discord` in action
+
+Examples and Advanced Usage
+---------------------------
+
+- See the `examples <https://github.com/tqdm/tqdm/tree/master/examples>`__
+  folder;
+- import the module and run ``help()``;
+- consult the `wiki <https://github.com/tqdm/tqdm/wiki>`__;
+
+  * this has an
+    `excellent article <https://github.com/tqdm/tqdm/wiki/How-to-make-a-great-Progress-Bar>`__
+    on how to make a **great** progress bar;
+
+- check out the `slides from PyData London <https://tqdm.github.io/PyData2019/slides.html>`__, or
+- run the |binder-demo|.
+
+Description and additional stats
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Custom information can be displayed and updated dynamically on ``tqdm`` bars
+with the ``desc`` and ``postfix`` arguments:
+
+.. code:: python
+
+    from tqdm import tqdm, trange
+    from random import random, randint
+    from time import sleep
+
+    with trange(10) as t:
+        for i in t:
+            # Description will be displayed on the left
+            t.set_description('GEN %i' % i)
+            # Postfix will be displayed on the right,
+            # formatted automatically based on argument's datatype
+            t.set_postfix(loss=random(), gen=randint(1,999), str='h',
+                          lst=[1, 2])
+            sleep(0.1)
+
+    with tqdm(total=10, bar_format="{postfix[0]} {postfix[1][value]:>8.2g}",
+              postfix=["Batch", {"value": 0}]) as t:
+        for i in range(10):
+            sleep(0.1)
+            t.postfix[1]["value"] = i / 2
+            t.update()
+
+Points to remember when using ``{postfix[...]}`` in the ``bar_format`` string:
+
+- ``postfix`` also needs to be passed as an initial argument in a compatible
+  format, and
+- ``postfix`` will be auto-converted to a string if it is a ``dict``-like
+  object. To prevent this behaviour, insert an extra item into the dictionary
+  where the key is not a string.
+
+Additional ``bar_format`` parameters may also be defined by overriding
+``format_dict``, and the bar itself may be modified using ``ascii``:
+
+.. code:: python
+
+    from tqdm import tqdm
+    class TqdmExtraFormat(tqdm):
+        """Provides a `total_time` format parameter"""
+        @property
+        def format_dict(self):
+            d = super().format_dict
+            total_time = d["elapsed"] * (d["total"] or 0) / max(d["n"], 1)
+            d.update(total_time=self.format_interval(total_time) + " in total")
+            return d
+
+    for i in TqdmExtraFormat(
+          range(9), ascii=" .oO0",
+          bar_format="{total_time}: {percentage:.0f}%|{bar}{r_bar}"):
+        if i == 4:
+            break
+
+.. code::
+
+    00:00 in total: 44%|0000.     | 4/9 [00:00<00:00, 962.93it/s]
+
+Note that ``{bar}`` also supports a format specifier ``[width][type]``.
+
+- ``width``
+
+  * unspecified (default): automatic to fill ``ncols``
+  * ``int >= 0``: fixed width overriding ``ncols`` logic
+  * ``int < 0``: subtract from the automatic default
+
+- ``type``
+
+  * ``a``: ascii (``ascii=True`` override)
+  * ``u``: unicode (``ascii=False`` override)
+  * ``b``: blank (``ascii="  "`` override)
+
+This means a fixed bar with right-justified text may be created by using:
+``bar_format="{l_bar}{bar:10}|{bar:-10b}right-justified"``
+
+Nested progress bars
+~~~~~~~~~~~~~~~~~~~~
+
+``tqdm`` supports nested progress bars. Here's an example:
+
+.. code:: python
+
+    from tqdm.auto import trange
+    from time import sleep
+
+    for i in trange(4, desc='1st loop'):
+        for j in trange(5, desc='2nd loop'):
+            for k in trange(50, desc='3rd loop', leave=False):
+                sleep(0.01)
+
+For manual control over positioning (e.g. for multi-processing use),
+you may specify ``position=n`` where ``n=0`` for the outermost bar,
+``n=1`` for the next, and so on.
+However, it's best to check if ``tqdm`` can work without manual ``position``
+first.
+
+.. code:: python
+
+    from time import sleep
+    from tqdm import trange, tqdm
+    from multiprocessing import Pool, RLock, freeze_support
+
+    L = list(range(9))
+
+    def progresser(n):
+        interval = 0.001 / (n + 2)
+        total = 5000
+        text = f"#{n}, est. {interval * total:<04.2}s"
+        for _ in trange(total, desc=text, position=n):
+            sleep(interval)
+
+    if __name__ == '__main__':
+        freeze_support()  # for Windows support
+        tqdm.set_lock(RLock())  # for managing output contention
+        p = Pool(initializer=tqdm.set_lock, initargs=(tqdm.get_lock(),))
+        p.map(progresser, L)
+
+Note that in Python 3, ``tqdm.write`` is thread-safe:
+
+.. code:: python
+
+    from time import sleep
+    from tqdm import tqdm, trange
+    from concurrent.futures import ThreadPoolExecutor
+
+    L = list(range(9))
+
+    def progresser(n):
+        interval = 0.001 / (n + 2)
+        total = 5000
+        text = f"#{n}, est. {interval * total:<04.2}s"
+        for _ in trange(total, desc=text):
+            sleep(interval)
+        if n == 6:
+            tqdm.write("n == 6 completed.")
+            tqdm.write("`tqdm.write()` is thread-safe in py3!")
+
+    if __name__ == '__main__':
+        with ThreadPoolExecutor() as p:
+            p.map(progresser, L)
+
+Hooks and callbacks
+~~~~~~~~~~~~~~~~~~~
+
+``tqdm`` can easily support callbacks/hooks and manual updates.
+Here's an example with ``urllib``:
+
+**``urllib.urlretrieve`` documentation**
+
+    | [...]
+    | If present, the hook function will be called once
+    | on establishment of the network connection and once after each block read
+    | thereafter. The hook will be passed three arguments; a count of blocks
+    | transferred so far, a block size in bytes, and the total size of the file.
+    | [...]
+
+.. code:: python
+
+    import urllib, os
+    from tqdm import tqdm
+    urllib = getattr(urllib, 'request', urllib)
+
+    class TqdmUpTo(tqdm):
+        """Provides `update_to(n)` which uses `tqdm.update(delta_n)`."""
+        def update_to(self, b=1, bsize=1, tsize=None):
+            """
+            b  : int, optional
+                Number of blocks transferred so far [default: 1].
+            bsize  : int, optional
+                Size of each block (in tqdm units) [default: 1].
+            tsize  : int, optional
+                Total size (in tqdm units). If [default: None] remains unchanged.
+            """
+            if tsize is not None:
+                self.total = tsize
+            return self.update(b * bsize - self.n)  # also sets self.n = b * bsize
+
+    eg_link = "https://cgi.cdcl.ml/matryoshka.zip"
+    with TqdmUpTo(unit='B', unit_scale=True, unit_divisor=1024, miniters=1,
+                  desc=eg_link.split('/')[-1]) as t:  # all optional kwargs
+        urllib.urlretrieve(eg_link, filename=os.devnull,
+                           reporthook=t.update_to, data=None)
+        t.total = t.n
+
+Inspired by `twine#242 <https://github.com/pypa/twine/pull/242>`__.
+Functional alternative in
+`examples/tqdm_wget.py <https://github.com/tqdm/tqdm/blob/master/examples/tqdm_wget.py>`__.
+
+It is recommend to use ``miniters=1`` whenever there is potentially
+large differences in iteration speed (e.g. downloading a file over
+a patchy connection).
+
+**Wrapping read/write methods**
+
+To measure throughput through a file-like object's ``read`` or ``write``
+methods, use ``CallbackIOWrapper``:
+
+.. code:: python
+
+    from tqdm.auto import tqdm
+    from tqdm.utils import CallbackIOWrapper
+
+    with tqdm(total=file_obj.size,
+              unit='B', unit_scale=True, unit_divisor=1024) as t:
+        fobj = CallbackIOWrapper(t.update, file_obj, "read")
+        while True:
+            chunk = fobj.read(chunk_size)
+            if not chunk:
+                break
+        t.reset()
+        # ... continue to use `t` for something else
+
+Alternatively, use the even simpler ``wrapattr`` convenience function,
+which would condense both the ``urllib`` and ``CallbackIOWrapper`` examples
+down to:
+
+.. code:: python
+
+    import urllib, os
+    from tqdm import tqdm
+
+    eg_link = "https://cgi.cdcl.ml/matryoshka.zip"
+    response = getattr(urllib, 'request', urllib).urlopen(eg_link)
+    with tqdm.wrapattr(open(os.devnull, "wb"), "write",
+                       miniters=1, desc=eg_link.split('/')[-1],
+                       total=getattr(response, 'length', None)) as fout:
+        for chunk in response:
+            fout.write(chunk)
+
+The ``requests`` equivalent is nearly identical:
+
+.. code:: python
+
+    import requests, os
+    from tqdm import tqdm
+
+    eg_link = "https://cgi.cdcl.ml/matryoshka.zip"
+    response = requests.get(eg_link, stream=True)
+    with tqdm.wrapattr(open(os.devnull, "wb"), "write",
+                       miniters=1, desc=eg_link.split('/')[-1],
+                       total=int(response.headers.get('content-length', 0))) as fout:
+        for chunk in response.iter_content(chunk_size=4096):
+            fout.write(chunk)
+
+**Custom callback**
+
+``tqdm`` is known for intelligently skipping unnecessary displays. To make a
+custom callback take advantage of this, simply use the return value of
+``update()``. This is set to ``True`` if a ``display()`` was triggered.
+
+.. code:: python
+
+    from tqdm.auto import tqdm as std_tqdm
+
+    def external_callback(*args, **kwargs):
+        ...
+
+    class TqdmExt(std_tqdm):
+        def update(self, n=1):
+            displayed = super().update(n)
+            if displayed:
+                external_callback(**self.format_dict)
+            return displayed
+
+``asyncio``
+~~~~~~~~~~~
+
+Note that ``break`` isn't currently caught by asynchronous iterators.
+This means that ``tqdm`` cannot clean up after itself in this case:
+
+.. code:: python
+
+    from tqdm.asyncio import tqdm
+
+    async for i in tqdm(range(9)):
+        if i == 2:
+            break
+
+Instead, either call ``pbar.close()`` manually or use the context manager syntax:
+
+.. code:: python
+
+    from tqdm.asyncio import tqdm
+
+    with tqdm(range(9)) as pbar:
+        async for i in pbar:
+            if i == 2:
+                break
+
+Pandas Integration
+~~~~~~~~~~~~~~~~~~
+
+Due to popular demand we've added support for ``pandas`` -- here's an example
+for ``DataFrame.progress_apply`` and ``DataFrameGroupBy.progress_apply``:
+
+.. code:: python
+
+    import pandas as pd
+    import numpy as np
+    from tqdm import tqdm
+
+    df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))
+
+    # Register `pandas.progress_apply` and `pandas.Series.map_apply` with `tqdm`
+    # (can use `tqdm.gui.tqdm`, `tqdm.notebook.tqdm`, optional kwargs, etc.)
+    tqdm.pandas(desc="my bar!")
+
+    # Now you can use `progress_apply` instead of `apply`
+    # and `progress_map` instead of `map`
+    df.progress_apply(lambda x: x**2)
+    # can also groupby:
+    # df.groupby(0).progress_apply(lambda x: x**2)
+
+In case you're interested in how this works (and how to modify it for your
+own callbacks), see the
+`examples <https://github.com/tqdm/tqdm/tree/master/examples>`__
+folder or import the module and run ``help()``.
+
+Keras Integration
+~~~~~~~~~~~~~~~~~
+
+A ``keras`` callback is also available:
+
+.. code:: python
+
+    from tqdm.keras import TqdmCallback
+
+    ...
+
+    model.fit(..., verbose=0, callbacks=[TqdmCallback()])
+
+Dask Integration
+~~~~~~~~~~~~~~~~
+
+A ``dask`` callback is also available:
+
+.. code:: python
+
+    from tqdm.dask import TqdmCallback
+
+    with TqdmCallback(desc="compute"):
+        ...
+        arr.compute()
+
+    # or use callback globally
+    cb = TqdmCallback(desc="global")
+    cb.register()
+    arr.compute()
+
+IPython/Jupyter Integration
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+IPython/Jupyter is supported via the ``tqdm.notebook`` submodule:
+
+.. code:: python
+
+    from tqdm.notebook import trange, tqdm
+    from time import sleep
+
+    for i in trange(3, desc='1st loop'):
+        for j in tqdm(range(100), desc='2nd loop'):
+            sleep(0.01)
+
+In addition to ``tqdm`` features, the submodule provides a native Jupyter
+widget (compatible with IPython v1-v4 and Jupyter), fully working nested bars
+and colour hints (blue: normal, green: completed, red: error/interrupt,
+light blue: no ETA); as demonstrated below.
+
+|Screenshot-Jupyter1|
+|Screenshot-Jupyter2|
+|Screenshot-Jupyter3|
+
+The ``notebook`` version supports percentage or pixels for overall width
+(e.g.: ``ncols='100%'`` or ``ncols='480px'``).
+
+It is also possible to let ``tqdm`` automatically choose between
+console or notebook versions by using the ``autonotebook`` submodule:
+
+.. code:: python
+
+    from tqdm.autonotebook import tqdm
+    tqdm.pandas()
+
+Note that this will issue a ``TqdmExperimentalWarning`` if run in a notebook
+since it is not meant to be possible to distinguish between ``jupyter notebook``
+and ``jupyter console``. Use ``auto`` instead of ``autonotebook`` to suppress
+this warning.
+
+Note that notebooks will display the bar in the cell where it was created.
+This may be a different cell from the one where it is used.
+If this is not desired, either
+
+- delay the creation of the bar to the cell where it must be displayed, or
+- create the bar with ``display=False``, and in a later cell call
+  ``display(bar.container)``:
+
+.. code:: python
+
+    from tqdm.notebook import tqdm
+    pbar = tqdm(..., display=False)
+
+.. code:: python
+
+    # different cell
+    display(pbar.container)
+
+The ``keras`` callback has a ``display()`` method which can be used likewise:
+
+.. code:: python
+
+    from tqdm.keras import TqdmCallback
+    cbk = TqdmCallback(display=False)
+
+.. code:: python
+
+    # different cell
+    cbk.display()
+    model.fit(..., verbose=0, callbacks=[cbk])
+
+Another possibility is to have a single bar (near the top of the notebook)
+which is constantly re-used (using ``reset()`` rather than ``close()``).
+For this reason, the notebook version (unlike the CLI version) does not
+automatically call ``close()`` upon ``Exception``.
+
+.. code:: python
+
+    from tqdm.notebook import tqdm
+    pbar = tqdm()
+
+.. code:: python
+
+    # different cell
+    iterable = range(100)
+    pbar.reset(total=len(iterable))  # initialise with new `total`
+    for i in iterable:
+        pbar.update()
+    pbar.refresh()  # force print final status but don't `close()`
+
+Custom Integration
+~~~~~~~~~~~~~~~~~~
+
+To change the default arguments (such as making ``dynamic_ncols=True``),
+simply use built-in Python magic:
+
+.. code:: python
+
+    from functools import partial
+    from tqdm import tqdm as std_tqdm
+    tqdm = partial(std_tqdm, dynamic_ncols=True)
+
+For further customisation,
+``tqdm`` may be inherited from to create custom callbacks (as with the
+``TqdmUpTo`` example `above <#hooks-and-callbacks>`__) or for custom frontends
+(e.g. GUIs such as notebook or plotting packages). In the latter case:
+
+1. ``def __init__()`` to call ``super().__init__(..., gui=True)`` to disable
+   terminal ``status_printer`` creation.
+2. Redefine: ``close()``, ``clear()``, ``display()``.
+
+Consider overloading ``display()`` to use e.g.
+``self.frontend(**self.format_dict)`` instead of ``self.sp(repr(self))``.
+
+Some submodule examples of inheritance:
+
+- `tqdm/notebook.py <https://github.com/tqdm/tqdm/blob/master/tqdm/notebook.py>`__
+- `tqdm/gui.py <https://github.com/tqdm/tqdm/blob/master/tqdm/gui.py>`__
+- `tqdm/tk.py <https://github.com/tqdm/tqdm/blob/master/tqdm/tk.py>`__
+- `tqdm/contrib/slack.py <https://github.com/tqdm/tqdm/blob/master/tqdm/contrib/slack.py>`__
+- `tqdm/contrib/discord.py <https://github.com/tqdm/tqdm/blob/master/tqdm/contrib/discord.py>`__
+- `tqdm/contrib/telegram.py <https://github.com/tqdm/tqdm/blob/master/tqdm/contrib/telegram.py>`__
+
+Dynamic Monitor/Meter
+~~~~~~~~~~~~~~~~~~~~~
+
+You can use a ``tqdm`` as a meter which is not monotonically increasing.
+This could be because ``n`` decreases (e.g. a CPU usage monitor) or ``total``
+changes.
+
+One example would be recursively searching for files. The ``total`` is the
+number of objects found so far, while ``n`` is the number of those objects which
+are files (rather than folders):
+
+.. code:: python
+
+    from tqdm import tqdm
+    import os.path
+
+    def find_files_recursively(path, show_progress=True):
+        files = []
+        # total=1 assumes `path` is a file
+        t = tqdm(total=1, unit="file", disable=not show_progress)
+        if not os.path.exists(path):
+            raise IOError("Cannot find:" + path)
+
+        def append_found_file(f):
+            files.append(f)
+            t.update()
+
+        def list_found_dir(path):
+            """returns os.listdir(path) assuming os.path.isdir(path)"""
+            listing = os.listdir(path)
+            # subtract 1 since a "file" we found was actually this directory
+            t.total += len(listing) - 1
+            # fancy way to give info without forcing a refresh
+            t.set_postfix(dir=path[-10:], refresh=False)
+            t.update(0)  # may trigger a refresh
+            return listing
+
+        def recursively_search(path):
+            if os.path.isdir(path):
+                for f in list_found_dir(path):
+                    recursively_search(os.path.join(path, f))
+            else:
+                append_found_file(path)
+
+        recursively_search(path)
+        t.set_postfix(dir=path)
+        t.close()
+        return files
+
+Using ``update(0)`` is a handy way to let ``tqdm`` decide when to trigger a
+display refresh to avoid console spamming.
+
+Writing messages
+~~~~~~~~~~~~~~~~
+
+This is a work in progress (see
+`#737 <https://github.com/tqdm/tqdm/issues/737>`__).
+
+Since ``tqdm`` uses a simple printing mechanism to display progress bars,
+you should not write any message in the terminal using ``print()`` while
+a progress bar is open.
+
+To write messages in the terminal without any collision with ``tqdm`` bar
+display, a ``.write()`` method is provided:
+
+.. code:: python
+
+    from tqdm.auto import tqdm, trange
+    from time import sleep
+
+    bar = trange(10)
+    for i in bar:
+        # Print using tqdm class method .write()
+        sleep(0.1)
+        if not (i % 3):
+            tqdm.write("Done task %i" % i)
+        # Can also use bar.write()
+
+By default, this will print to standard output ``sys.stdout``. but you can
+specify any file-like object using the ``file`` argument. For example, this
+can be used to redirect the messages writing to a log file or class.
+
+Redirecting writing
+~~~~~~~~~~~~~~~~~~~
+
+If using a library that can print messages to the console, editing the library
+by  replacing ``print()`` with ``tqdm.write()`` may not be desirable.
+In that case, redirecting ``sys.stdout`` to ``tqdm.write()`` is an option.
+
+To redirect ``sys.stdout``, create a file-like class that will write
+any input string to ``tqdm.write()``, and supply the arguments
+``file=sys.stdout, dynamic_ncols=True``.
+
+A reusable canonical example is given below:
+
+.. code:: python
+
+    from time import sleep
+    import contextlib
+    import sys
+    from tqdm import tqdm
+    from tqdm.contrib import DummyTqdmFile
+
+
+    @contextlib.contextmanager
+    def std_out_err_redirect_tqdm():
+        orig_out_err = sys.stdout, sys.stderr
+        try:
+            sys.stdout, sys.stderr = map(DummyTqdmFile, orig_out_err)
+            yield orig_out_err[0]
+        # Relay exceptions
+        except Exception as exc:
+            raise exc
+        # Always restore sys.stdout/err if necessary
+        finally:
+            sys.stdout, sys.stderr = orig_out_err
+
+    def some_fun(i):
+        print("Fee, fi, fo,".split()[i])
+
+    # Redirect stdout to tqdm.write() (don't forget the `as save_stdout`)
+    with std_out_err_redirect_tqdm() as orig_stdout:
+        # tqdm needs the original stdout
+        # and dynamic_ncols=True to autodetect console width
+        for i in tqdm(range(3), file=orig_stdout, dynamic_ncols=True):
+            sleep(.5)
+            some_fun(i)
+
+    # After the `with`, printing is restored
+    print("Done!")
+
+Redirecting ``logging``
+~~~~~~~~~~~~~~~~~~~~~~~
+
+Similar to ``sys.stdout``/``sys.stderr`` as detailed above, console ``logging``
+may also be redirected to ``tqdm.write()``.
+
+Warning: if also redirecting ``sys.stdout``/``sys.stderr``, make sure to
+redirect ``logging`` first if needed.
+
+Helper methods are available in ``tqdm.contrib.logging``. For example:
+
+.. code:: python
+
+    import logging
+    from tqdm import trange
+    from tqdm.contrib.logging import logging_redirect_tqdm
+
+    LOG = logging.getLogger(__name__)
+
+    if __name__ == '__main__':
+        logging.basicConfig(level=logging.INFO)
+        with logging_redirect_tqdm():
+            for i in trange(9):
+                if i == 4:
+                    LOG.info("console logging redirected to `tqdm.write()`")
+        # logging restored
+
+Monitoring thread, intervals and miniters
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+``tqdm`` implements a few tricks to increase efficiency and reduce overhead.
+
+- Avoid unnecessary frequent bar refreshing: ``mininterval`` defines how long
+  to wait between each refresh. ``tqdm`` always gets updated in the background,
+  but it will display only every ``mininterval``.
+- Reduce number of calls to check system clock/time.
+- ``mininterval`` is more intuitive to configure than ``miniters``.
+  A clever adjustment system ``dynamic_miniters`` will automatically adjust
+  ``miniters`` to the amount of iterations that fit into time ``mininterval``.
+  Essentially, ``tqdm`` will check if it's time to print without actually
+  checking time. This behaviour can be still be bypassed by manually setting
+  ``miniters``.
+
+However, consider a case with a combination of fast and slow iterations.
+After a few fast iterations, ``dynamic_miniters`` will set ``miniters`` to a
+large number. When iteration rate subsequently slows, ``miniters`` will
+remain large and thus reduce display update frequency. To address this:
+
+- ``maxinterval`` defines the maximum time between display refreshes.
+  A concurrent monitoring thread checks for overdue updates and forces one
+  where necessary.
+
+The monitoring thread should not have a noticeable overhead, and guarantees
+updates at least every 10 seconds by default.
+This value can be directly changed by setting the ``monitor_interval`` of
+any ``tqdm`` instance (i.e. ``t = tqdm.tqdm(...); t.monitor_interval = 2``).
+The monitor thread may be disabled application-wide by setting
+``tqdm.tqdm.monitor_interval = 0`` before instantiation of any ``tqdm`` bar.
+
+
+Merch
+-----
+
+You can buy `tqdm branded merch <https://tqdm.github.io/merch>`__ now!
+
+Contributions
+-------------
+
+|GitHub-Commits| |GitHub-Issues| |GitHub-PRs| |OpenHub-Status| |GitHub-Contributions| |CII Best Practices|
+
+All source code is hosted on `GitHub <https://github.com/tqdm/tqdm>`__.
+Contributions are welcome.
+
+See the
+`CONTRIBUTING <https://github.com/tqdm/tqdm/blob/master/CONTRIBUTING.md>`__
+file for more information.
+
+Developers who have contributed more that 5 *loc* (surviving lines of code):
+
+|git-fame|
+
+Honourable mentions:
+
+- Casper da Costa-Luis `casperdcl <https://github.com/casperdcl>`__ primary maintainer |Gift-Casper|
+- Stephen Larroque `lrq3000 <https://github.com/lrq3000>`__ maintainer
+- Hadrien Mary `hadim <https://github.com/hadim>`__ maintainer
+- Mikhail Korobov `kmike <https://github.com/kmike>`__ maintainer
+- Noam Yorav-Raphael `noamraph <https://github.com/noamraph>`__ original author
+
+Ports to Other Languages
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+A list is available on
+`this wiki page <https://github.com/tqdm/tqdm/wiki/tqdm-ports>`__.
+
+
+LICENCE
+-------
+
+Open Source (OSI approved): |LICENCE|
+
+Citation information: |DOI|
+
+|README-Hits| (Since 19 May 2016)
+
+.. |Logo| image:: https://tqdm.github.io/img/logo.gif
+.. |Screenshot| image:: https://tqdm.github.io/img/tqdm.gif
+.. |Video| image:: https://tqdm.github.io/img/video.jpg
+   :target: https://tqdm.github.io/video
+.. |Slides| image:: https://tqdm.github.io/img/slides.jpg
+   :target: https://tqdm.github.io/PyData2019/slides.html
+.. |Merch| image:: https://tqdm.github.io/img/merch.jpg
+   :target: https://tqdm.github.io/merch
+.. |Build-Status| image:: https://img.shields.io/github/actions/workflow/status/tqdm/tqdm/test.yml?branch=master&label=tqdm&logo=GitHub
+   :target: https://github.com/tqdm/tqdm/actions/workflows/test.yml
+.. |Coverage-Status| image:: https://img.shields.io/coveralls/github/tqdm/tqdm/master?logo=coveralls
+   :target: https://coveralls.io/github/tqdm/tqdm
+.. |Branch-Coverage-Status| image:: https://codecov.io/gh/tqdm/tqdm/branch/master/graph/badge.svg
+   :target: https://codecov.io/gh/tqdm/tqdm
+.. |Codacy-Grade| image:: https://app.codacy.com/project/badge/Grade/3f965571598f44549c7818f29cdcf177
+   :target: https://app.codacy.com/gh/tqdm/tqdm/dashboard
+.. |CII Best Practices| image:: https://bestpractices.coreinfrastructure.org/projects/3264/badge
+   :target: https://bestpractices.coreinfrastructure.org/projects/3264
+.. |GitHub-Status| image:: https://img.shields.io/github/tag/tqdm/tqdm.svg?maxAge=86400&logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/releases
+.. |GitHub-Forks| image:: https://img.shields.io/github/forks/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/network
+.. |GitHub-Stars| image:: https://img.shields.io/github/stars/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/stargazers
+.. |GitHub-Commits| image:: https://img.shields.io/github/commit-activity/y/tqdm/tqdm.svg?logo=git&logoColor=white
+   :target: https://github.com/tqdm/tqdm/graphs/commit-activity
+.. |GitHub-Issues| image:: https://img.shields.io/github/issues-closed/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/issues?q=
+.. |GitHub-PRs| image:: https://img.shields.io/github/issues-pr-closed/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/pulls
+.. |GitHub-Contributions| image:: https://img.shields.io/github/contributors/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/graphs/contributors
+.. |GitHub-Updated| image:: https://img.shields.io/github/last-commit/tqdm/tqdm/master.svg?logo=github&logoColor=white&label=pushed
+   :target: https://github.com/tqdm/tqdm/pulse
+.. |git-fame| image:: https://git-fame.cdcl.ml/gh/tqdm/tqdm?min=5&w=1&M=1&C=1&excl=(png|gif|jpg)$&enum=1
+   :alt: git-fame.cdcl.ml/gh/tqdm/tqdm
+   :target: https://git-fame.cdcl.ml/gh/tqdm/tqdm?w=1&M=1&C=1&excl=(png|gif|jpg)$&enum=1
+.. |Gift-Casper| image:: https://img.shields.io/badge/sponsor-casper-ff69b4.svg
+   :target: https://cdcl.ml/sponsor
+.. |Versions| image:: https://img.shields.io/pypi/v/tqdm.svg
+   :target: https://tqdm.github.io/releases
+.. |PyPI-Downloads| image:: https://static.pepy.tech/personalized-badge/tqdm?left_text=downloads%2Fmonth
+   :target: https://pepy.tech/project/tqdm
+.. |Py-Versions| image:: https://img.shields.io/pypi/pyversions/tqdm.svg?logo=python&logoColor=white
+   :target: https://pypi.org/project/tqdm
+.. |Conda-Forge-Status| image:: https://img.shields.io/conda/v/conda-forge/tqdm.svg?label=conda-forge&logo=conda-forge
+   :target: https://anaconda.org/conda-forge/tqdm
+.. |Snapcraft| image:: https://img.shields.io/badge/snap-install-82BEA0.svg?logo=snapcraft
+   :target: https://snapcraft.io/tqdm
+.. |Docker| image:: https://img.shields.io/badge/docker-pull-blue.svg?logo=docker&logoColor=white
+   :target: https://hub.docker.com/r/tqdm/tqdm
+.. |Libraries-Rank| image:: https://img.shields.io/librariesio/sourcerank/pypi/tqdm.svg?logo=koding&logoColor=white
+   :target: https://libraries.io/pypi/tqdm
+.. |Libraries-Dependents| image:: https://img.shields.io/librariesio/dependent-repos/pypi/tqdm.svg?logo=koding&logoColor=white
+    :target: https://github.com/tqdm/tqdm/network/dependents
+.. |OpenHub-Status| image:: https://www.openhub.net/p/tqdm/widgets/project_thin_badge?format=gif
+   :target: https://www.openhub.net/p/tqdm?ref=Thin+badge
+.. |awesome-python| image:: https://awesome.re/mentioned-badge.svg
+   :target: https://github.com/vinta/awesome-python
+.. |LICENCE| image:: https://img.shields.io/pypi/l/tqdm.svg
+   :target: https://raw.githubusercontent.com/tqdm/tqdm/master/LICENCE
+.. |DOI| image:: https://img.shields.io/badge/DOI-10.5281/zenodo.595120-blue.svg
+   :target: https://doi.org/10.5281/zenodo.595120
+.. |colab-demo| image:: https://colab.research.google.com/assets/colab-badge.svg
+   :target: https://colab.research.google.com/github/tqdm/tqdm/blob/master/DEMO.ipynb
+.. |binder-demo| image:: https://mybinder.org/badge_logo.svg
+   :target: https://mybinder.org/v2/gh/tqdm/tqdm/master?filepath=DEMO.ipynb
+.. |Screenshot-Jupyter1| image:: https://tqdm.github.io/img/jupyter-1.gif
+.. |Screenshot-Jupyter2| image:: https://tqdm.github.io/img/jupyter-2.gif
+.. |Screenshot-Jupyter3| image:: https://tqdm.github.io/img/jupyter-3.gif
+.. |README-Hits| image:: https://cgi.cdcl.ml/hits?q=tqdm&style=social&r=https://github.com/tqdm/tqdm&l=https://tqdm.github.io/img/favicon.png&f=https://tqdm.github.io/img/logo.gif
+   :target: https://cgi.cdcl.ml/hits?q=tqdm&a=plot&r=https://github.com/tqdm/tqdm&l=https://tqdm.github.io/img/favicon.png&f=https://tqdm.github.io/img/logo.gif&style=social

MODEL_RUN_COMMANDS.md

@@ -0,0 +1,121 @@
+# Per-model run commands — `foldsrunner_simplified_after_ablation.py`
+
+Base config is already set in the file: `STRATEGIES=[2,3]`, 10 phases (`PHASE_EXECUTION_MODE="auto"`),
+100% data, `BATCH_SIZE=48`, `NUM_WORKERS=12`, `STRATEGY_2_MAX_EPOCHS=100`, `STRATEGY_3_MAX_EPOCHS=120`,
+`RUN_OPTUNA=False`, `STRATEGY2_CHECKPOINT_MODE="best"` (strategy 3 uses the strategy-2 base trained in
+the same run — no checkpoint wiring needed).
+
+**Validated at 128px:** DPT+ViT-tiny and UPerNet+Swin-tiny were dropped (weights locked to 224px) and
+replaced with **PVTv2 + UPerNet** (b1 and b2), which run natively at 128px. Re-run
+`python validate_models.py` to confirm all 6 pass on your box before launching.
+
+---
+
+## 1. SegFormer-B0  (transformer → SegFormer params, proj 192)
+
+```bash
+cd /workspace
+sed -i -E \
+  -e 's/^SMP_ENCODER_NAME = .*/SMP_ENCODER_NAME = "mit_b0"/' \
+  -e 's/^SMP_DECODER_TYPE = .*/SMP_DECODER_TYPE = "Segformer"/' \
+  -e 's/^SMP_ENCODER_PROJ_DIM = .*/SMP_ENCODER_PROJ_DIM = 192/' \
+  -e 's/^SMP_ENCODER_DEPTH = .*/SMP_ENCODER_DEPTH = 5/' \
+  -e 's/^MODEL_NAME = .*/MODEL_NAME = "Segformer_B0"/' \
+  -e 's#"2:100": "[^"]*"#"2:100": "params/segformer_b0/best_params_strat2.json"#' \
+  -e 's#"3:100": "[^"]*"#"3:100": "params/segformer_b0/best_params_strat3.json"#' \
+  foldsrunner_simplified_after_ablation.py
+python foldsrunner_simplified_after_ablation.py
+```
+
+## 2. U-Net + EfficientNet-B0  (CNN → U-Net params, proj 256)
+
+```bash
+cd /workspace
+sed -i -E \
+  -e 's/^SMP_ENCODER_NAME = .*/SMP_ENCODER_NAME = "efficientnet-b0"/' \
+  -e 's/^SMP_DECODER_TYPE = .*/SMP_DECODER_TYPE = "Unet"/' \
+  -e 's/^SMP_ENCODER_PROJ_DIM = .*/SMP_ENCODER_PROJ_DIM = 256/' \
+  -e 's/^SMP_ENCODER_DEPTH = .*/SMP_ENCODER_DEPTH = 5/' \
+  -e 's/^MODEL_NAME = .*/MODEL_NAME = "Unet_EffB0"/' \
+  -e 's#"2:100": "[^"]*"#"2:100": "params/unet_effb0/best_params_strat2.json"#' \
+  -e 's#"3:100": "[^"]*"#"3:100": "params/unet_effb0/best_params_strat3.json"#' \
+  foldsrunner_simplified_after_ablation.py
+python foldsrunner_simplified_after_ablation.py
+```
+
+## 3. DeepLabV3+ + ResNet34  (CNN → U-Net params, proj 256)
+
+```bash
+cd /workspace
+sed -i -E \
+  -e 's/^SMP_ENCODER_NAME = .*/SMP_ENCODER_NAME = "resnet34"/' \
+  -e 's/^SMP_DECODER_TYPE = .*/SMP_DECODER_TYPE = "DeepLabV3Plus"/' \
+  -e 's/^SMP_ENCODER_PROJ_DIM = .*/SMP_ENCODER_PROJ_DIM = 256/' \
+  -e 's/^SMP_ENCODER_DEPTH = .*/SMP_ENCODER_DEPTH = 5/' \
+  -e 's/^MODEL_NAME = .*/MODEL_NAME = "DeepLabV3Plus_ResNet34"/' \
+  -e 's#"2:100": "[^"]*"#"2:100": "params/deeplabv3plus_r34/best_params_strat2.json"#' \
+  -e 's#"3:100": "[^"]*"#"3:100": "params/deeplabv3plus_r34/best_params_strat3.json"#' \
+  foldsrunner_simplified_after_ablation.py
+python foldsrunner_simplified_after_ablation.py
+```
+
+## 4. LinkNet + MobileNetV3-Large  (CNN → U-Net params, proj 256)
+
+```bash
+cd /workspace
+sed -i -E \
+  -e 's/^SMP_ENCODER_NAME = .*/SMP_ENCODER_NAME = "timm-mobilenetv3_large_100"/' \
+  -e 's/^SMP_DECODER_TYPE = .*/SMP_DECODER_TYPE = "Linknet"/' \
+  -e 's/^SMP_ENCODER_PROJ_DIM = .*/SMP_ENCODER_PROJ_DIM = 256/' \
+  -e 's/^SMP_ENCODER_DEPTH = .*/SMP_ENCODER_DEPTH = 5/' \
+  -e 's/^MODEL_NAME = .*/MODEL_NAME = "Linknet_MobileNetV3"/' \
+  -e 's#"2:100": "[^"]*"#"2:100": "params/linknet_mbv3/best_params_strat2.json"#' \
+  -e 's#"3:100": "[^"]*"#"3:100": "params/linknet_mbv3/best_params_strat3.json"#' \
+  foldsrunner_simplified_after_ablation.py
+python foldsrunner_simplified_after_ablation.py
+```
+
+## 5. UPerNet + PVTv2-b1  (transformer → SegFormer params, proj 192)
+
+```bash
+cd /workspace
+sed -i -E \
+  -e 's/^SMP_ENCODER_NAME = .*/SMP_ENCODER_NAME = "tu-pvt_v2_b1"/' \
+  -e 's/^SMP_DECODER_TYPE = .*/SMP_DECODER_TYPE = "UPerNet"/' \
+  -e 's/^SMP_ENCODER_PROJ_DIM = .*/SMP_ENCODER_PROJ_DIM = 192/' \
+  -e 's/^SMP_ENCODER_DEPTH = .*/SMP_ENCODER_DEPTH = 5/' \
+  -e 's/^MODEL_NAME = .*/MODEL_NAME = "UPerNet_PVTv2_b1"/' \
+  -e 's#"2:100": "[^"]*"#"2:100": "params/upernet_pvtv2_b1/best_params_strat2.json"#' \
+  -e 's#"3:100": "[^"]*"#"3:100": "params/upernet_pvtv2_b1/best_params_strat3.json"#' \
+  foldsrunner_simplified_after_ablation.py
+python foldsrunner_simplified_after_ablation.py
+```
+
+## 6. UPerNet + PVTv2-b2  (transformer → SegFormer params, proj 192)
+
+```bash
+cd /workspace
+sed -i -E \
+  -e 's/^SMP_ENCODER_NAME = .*/SMP_ENCODER_NAME = "tu-pvt_v2_b2"/' \
+  -e 's/^SMP_DECODER_TYPE = .*/SMP_DECODER_TYPE = "UPerNet"/' \
+  -e 's/^SMP_ENCODER_PROJ_DIM = .*/SMP_ENCODER_PROJ_DIM = 192/' \
+  -e 's/^SMP_ENCODER_DEPTH = .*/SMP_ENCODER_DEPTH = 5/' \
+  -e 's/^MODEL_NAME = .*/MODEL_NAME = "UPerNet_PVTv2_b2"/' \
+  -e 's#"2:100": "[^"]*"#"2:100": "params/upernet_pvtv2_b2/best_params_strat2.json"#' \
+  -e 's#"3:100": "[^"]*"#"3:100": "params/upernet_pvtv2_b2/best_params_strat3.json"#' \
+  foldsrunner_simplified_after_ablation.py
+python foldsrunner_simplified_after_ablation.py
+```
+
+---
+
+## After the runs — plots
+
+```bash
+cd /workspace
+python plot_s2_vs_s3.py
+```
+
+One titled figure per model → `runs/_plots/<MODEL_NAME>__s2_vs_s3.png` (6 panels: BIoU band, BIoU
+contour, inference time, total training time, time per epoch, time to best checkpoint — S2 vs S3,
+mean ± std across the 10 phases, Δ annotated), plus `runs/_plots/summary_s2_vs_s3.csv`.

model_stats_s2_vs_s3.py

@@ -0,0 +1,392 @@
+"""Paired S3-vs-S2 statistics for each model under runs/, at TWO levels:
+
+    * per_image   (Method 1)  -- pool every test image across all phases, pair
+                                 S3 vs S2 by (phase, sample_id).
+    * phase_level (Method 2)  -- one paired value per phase = the phase-mean of
+                                 the metric; pair S3-mean vs S2-mean across phases.
+
+Same paired machinery as ablation_stats.py: paired t-test, Wilcoxon signed-rank
+(zero_method="wilcox"), sign-flip permutation, bootstrap CI for the mean delta,
+Hodges-Lehmann estimate + CI, Cohen's dz, rank-biserial r, Shapiro-Wilk on the
+diffs, Holm correction. HD95 is the only lower-is-better metric.
+
+Auto-discovers every model folder directly under runs/ (each distinct MODEL_NAME).
+One .xlsx per model + a combined cross-model summary.
+
+Usage:
+    python model_stats_s2_vs_s3.py                 # scans ./runs
+    python model_stats_s2_vs_s3.py --runs-root X
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import pathlib
+import re
+from collections import defaultdict
+
+import numpy as np
+import pandas as pd
+from scipy import stats
+
+# metric -> higher_is_better
+METRICS = {
+    "biou_contour": True,   # manuscript's reported "BIoU" (1-px contour)
+    "biou": True,           # Cheng et al. CVPR 2021 d-pixel band Boundary IoU
+    "dice": True,
+    "iou": True,
+    "ppv": True,
+    "sen": True,
+    "hd95": False,          # lower is better
+}
+PRIMARY = "biou_contour"
+ALPHA = 0.05
+N_BOOT = 20000
+N_BOOT_HL = 4000
+N_PERM = 20000
+SEED = 20260709
+
+# S3 is the first arm, S2 the second: Mean_delta = S3 - S2, positive favours S3
+LABEL = {2: "S2 (baseline)", 3: "S3 (refinement)"}
+
+
+# ---------------------------------------------------------------- stats helpers
+def holm(pvals):
+    pvals = np.asarray(pvals, dtype=float)
+    order = np.argsort(pvals)
+    m = len(pvals)
+    adj = np.empty(m)
+    running = 0.0
+    for rank, idx in enumerate(order):
+        running = max(running, (m - rank) * pvals[idx])
+        adj[idx] = min(running, 1.0)
+    return adj
+
+
+def boot_ci_mean(d, rng):
+    idx = rng.integers(0, len(d), size=(N_BOOT, len(d)))
+    return np.percentile(d[idx].mean(axis=1), [2.5, 97.5])
+
+
+def hodges_lehmann(d):
+    i, j = np.triu_indices(len(d), k=0)
+    return float(np.median((d[i] + d[j]) / 2.0))
+
+
+def boot_ci_hl(d, rng):
+    idx = rng.integers(0, len(d), size=(N_BOOT_HL, len(d)))
+    return np.percentile([hodges_lehmann(d[r]) for r in idx], [2.5, 97.5])
+
+
+def sign_flip_perm_p(d, rng):
+    obs = abs(d.mean())
+    signs = rng.choice([-1.0, 1.0], size=(N_PERM, len(d)))
+    null = np.abs((signs * d).mean(axis=1))
+    return (np.sum(null >= obs - 1e-15) + 1) / (N_PERM + 1)
+
+
+def rank_biserial(d):
+    nz = d[d != 0]
+    if len(nz) == 0:
+        return 0.0
+    r = stats.rankdata(np.abs(nz))
+    rp, rm = r[nz > 0].sum(), r[nz < 0].sum()
+    return float((rp - rm) / (rp + rm))
+
+
+def analyse(x, y, metric, higher_better, level, rng):
+    """x = S3 vector, y = S2 vector (paired). Returns (rows, delta)."""
+    d = np.asarray(x, float) - np.asarray(y, float)
+    n = len(d)
+    mean_d, sd_d = float(d.mean()), float(d.std(ddof=1)) if n > 1 else float("nan")
+    se = sd_d / np.sqrt(n) if n > 1 else float("nan")
+
+    if n >= 2:
+        t_stat, p_t = stats.ttest_rel(x, y)
+        crit = stats.t.ppf(1 - ALPHA / 2, df=n - 1)
+        t_ci = (mean_d - crit * se, mean_d + crit * se)
+    else:
+        t_stat, p_t, t_ci = np.nan, 1.0, (np.nan, np.nan)
+
+    if n >= 1 and not np.allclose(d, 0):
+        try:
+            w_stat, p_w = stats.wilcoxon(x, y, zero_method="wilcox", alternative="two-sided")
+        except ValueError:
+            w_stat, p_w = np.nan, 1.0
+    else:
+        w_stat, p_w = np.nan, 1.0
+
+    p_perm = sign_flip_perm_p(d, rng) if n >= 1 else 1.0
+    b_lo, b_hi = boot_ci_mean(d, rng) if n >= 2 else (np.nan, np.nan)
+    hl = hodges_lehmann(d) if n >= 1 else np.nan
+    hl_lo, hl_hi = boot_ci_hl(d, rng) if n >= 2 else (np.nan, np.nan)
+    shapiro_p = float(stats.shapiro(d).pvalue) if (n >= 3 and not np.allclose(d, 0)) else np.nan
+    p_holm_c = holm([p_t, p_w, p_perm])
+
+    better = (mean_d > 0) == higher_better
+    winner = LABEL[3] if better else LABEL[2]
+
+    rows = []
+    for name, stat, p_raw, p_adj in [
+        ("Paired t-test", float(t_stat), float(p_t), p_holm_c[0]),
+        ("Wilcoxon signed-rank", float(w_stat), float(p_w), p_holm_c[1]),
+        ("Sign-flip permutation", mean_d, float(p_perm), p_holm_c[2]),
+    ]:
+        rows.append({
+            "Level": level, "Metric": metric, "Higher_is_better": higher_better,
+            "Contrast": "S3 - S2", "Test": name, "n_pairs": n,
+            "n_zero_diff": int(np.sum(d == 0)), "Statistic": stat,
+            "Mean_delta": mean_d, "SD_delta": sd_d, "p_raw": p_raw,
+            "p_Holm_within_metric_level": p_adj,
+            "Sig_within_metric_level": "Yes" if p_adj < ALPHA else "No",
+            "Better_arm": winner if p_adj < ALPHA else "n.s.",
+            "t_CI_low": t_ci[0], "t_CI_high": t_ci[1],
+            "boot_CI_low": b_lo, "boot_CI_high": b_hi,
+            "CI_excludes_zero": "Yes" if (b_lo > 0) or (b_hi < 0) else "No",
+            "HodgesLehmann_delta": hl, "HL_CI_low": hl_lo, "HL_CI_high": hl_hi,
+            "Cohens_dz": mean_d / sd_d if (sd_d and sd_d > 0) else np.nan,
+            "Rank_biserial_r": rank_biserial(d),
+            "Shapiro_p_on_diffs": shapiro_p,
+            "Diffs_normal_at_0.05": "n/a" if np.isnan(shapiro_p) else ("No" if shapiro_p < ALPHA else "Yes"),
+        })
+    return rows, d
+
+
+# ---------------------------------------------------------------- discovery
+def read_threshold(final_dir: pathlib.Path):
+    rc = final_dir / "run_config.json"
+    if rc.exists():
+        try:
+            return json.loads(rc.read_text()).get("threshold")
+        except Exception:
+            return None
+    return None
+
+
+def discover(runs_root: pathlib.Path):
+    """model -> phase -> strategy -> {'per_sample': {sid: row}, 'threshold': float}"""
+    data: dict[str, dict[int, dict[int, dict]]] = defaultdict(lambda: defaultdict(dict))
+    for ev in runs_root.glob("*/**/strategy_*/final/evaluation.json"):
+        final_dir = ev.parent
+        ms = re.search(r"strategy_(\d+)", final_dir.parent.name)
+        if not ms:
+            continue
+        s = int(ms.group(1))
+        if s not in (2, 3):
+            continue
+        try:
+            model = ev.relative_to(runs_root).parts[0]
+        except ValueError:
+            continue
+        pm = re.search(r"phase_(\d+)", str(ev))
+        phase = int(pm.group(1)) if pm else 1
+        try:
+            payload = json.loads(ev.read_text())
+        except Exception:
+            continue
+        data[model][phase][s] = {
+            "per_sample": {row["sample_id"]: row for row in payload.get("per_sample", [])},
+            "threshold": read_threshold(final_dir),
+        }
+    return data
+
+
+# ---------------------------------------------------------------- per model
+def analyse_model(model, phase_map, rng):
+    phases = sorted(p for p in phase_map if 2 in phase_map[p] and 3 in phase_map[p])
+    if not phases:
+        return None
+
+    # per-image pooled arrays + per-phase means
+    img = {m: {2: [], 3: []} for m in METRICS}
+    phase_mean = {m: {2: [], 3: []} for m in METRICS}
+    phase_used, n_img_per_phase, split_warnings = [], [], []
+    thr = {2: None, 3: None}
+
+    for p in phases:
+        s2, s3 = phase_map[p][2], phase_map[p][3]
+        thr[2] = thr[2] or s2.get("threshold")
+        thr[3] = thr[3] or s3.get("threshold")
+        set2, set3 = set(s2["per_sample"]), set(s3["per_sample"])
+        if set2 != set3:
+            split_warnings.append(f"phase {p}: S2/S3 sample_id sets differ "
+                                  f"(|S2|={len(set2)}, |S3|={len(set3)}, common={len(set2 & set3)})")
+        ids = sorted(set2 & set3)
+        if not ids:
+            continue
+        phase_used.append(p)
+        n_img_per_phase.append(len(ids))
+        for m in METRICS:
+            v2 = np.array([s2["per_sample"][i][m] for i in ids], float)
+            v3 = np.array([s3["per_sample"][i][m] for i in ids], float)
+            img[m][2].append(v2)
+            img[m][3].append(v3)
+            phase_mean[m][2].append(float(v2.mean()))
+            phase_mean[m][3].append(float(v3.mean()))
+
+    test_rows, desc_rows = [], []
+    per_image = {"phase": np.concatenate([[p] * n for p, n in zip(phase_used, n_img_per_phase)]).astype(int)}
+    per_phase = {"phase": np.array(phase_used, int)}
+
+    for m, hib in METRICS.items():
+        x_img = np.concatenate(img[m][3]) if img[m][3] else np.array([])
+        y_img = np.concatenate(img[m][2]) if img[m][2] else np.array([])
+        pm2 = np.array(phase_mean[m][2], float)
+        pm3 = np.array(phase_mean[m][3], float)
+
+        # descriptives, both levels
+        for s, arr_img, arr_ph in [(2, y_img, pm2), (3, x_img, pm3)]:
+            desc_rows.append({
+                "Metric": m, "Higher_is_better": hib, "Arm": LABEL[s],
+                "n_images": len(arr_img), "img_Mean": arr_img.mean() if len(arr_img) else np.nan,
+                "img_SD": arr_img.std(ddof=1) if len(arr_img) > 1 else np.nan,
+                "img_Median": np.median(arr_img) if len(arr_img) else np.nan,
+                "n_phases": len(arr_ph), "phase_Mean": arr_ph.mean() if len(arr_ph) else np.nan,
+                "phase_SD": arr_ph.std(ddof=1) if len(arr_ph) > 1 else np.nan,
+            })
+
+        # per_image tests
+        rows, d_img = analyse(x_img, y_img, m, hib, "per_image", rng)
+        test_rows.extend(rows)
+        per_image[f"{m}__S2"] = y_img
+        per_image[f"{m}__S3"] = x_img
+        per_image[f"{m}__delta_S3_minus_S2"] = d_img
+
+        # phase_level tests
+        rows_ph, d_ph = analyse(pm3, pm2, m, hib, "phase_level", rng)
+        test_rows.extend(rows_ph)
+        per_phase[f"{m}__S2_phase_mean"] = pm2
+        per_phase[f"{m}__S3_phase_mean"] = pm3
+        per_phase[f"{m}__delta_S3_minus_S2"] = d_ph
+
+    tests_df = pd.DataFrame(test_rows)
+    # global Holm across this model's whole workbook (metrics x 2 levels x 3 tests)
+    tests_df["p_Holm_global"] = holm(tests_df["p_raw"].values)
+    tests_df["Sig_global"] = np.where(tests_df["p_Holm_global"] < ALPHA, "Yes", "No")
+
+    return {
+        "phases": phase_used,
+        "thr": thr,
+        "split_warnings": split_warnings,
+        "tests": tests_df,
+        "descriptives": pd.DataFrame(desc_rows),
+        "per_image": pd.DataFrame(per_image),
+        "per_phase": pd.DataFrame(per_phase),
+    }
+
+
+def readme_frame(model, res):
+    return pd.DataFrame({"Field": [
+        "Model", "Contrast", "Phases used", "n phases", "S2 threshold", "S3 threshold",
+        "per_image level", "phase_level level", "Metrics", "PRIMARY", "hd95 direction",
+        "Wilcoxon zero handling", "Bootstrap", "Permutation", "Holm scope",
+        "Split check", "Split warnings", "Seed",
+    ], "Value": [
+        model, "S3 (refinement) - S2 (baseline); positive delta favours S3",
+        ", ".join(map(str, res["phases"])), len(res["phases"]),
+        str(res["thr"][2]), str(res["thr"][3]),
+        "pool all test images across phases, paired by (phase, sample_id) [manuscript Method 1]",
+        "one paired value per phase = phase-mean of the metric, paired across phases [manuscript Method 2]",
+        ", ".join(METRICS), PRIMARY, "LOWER is better; direction handled in Better_arm",
+        "zero_method='wilcox' (zero diffs dropped)",
+        f"{N_BOOT} resamples for mean-delta CI; {N_BOOT_HL} for Hodges-Lehmann",
+        f"{N_PERM} sign flips; p floor ~= 1/{N_PERM + 1}",
+        "Holm across every test in this workbook (metrics x 2 levels x 3 tests) = p_Holm_global",
+        "asserted S2 and S3 test sample_id sets identical within each phase",
+        "; ".join(res["split_warnings"]) if res["split_warnings"] else "none",
+        f"numpy default_rng({SEED})",
+    ]})
+
+
+def write_workbook(model, res, out_dir):
+    out = out_dir / f"{model}__s2_vs_s3_stats.xlsx"
+    try:
+        with pd.ExcelWriter(out, engine="openpyxl") as xl:
+            readme_frame(model, res).to_excel(xl, sheet_name="README", index=False)
+            res["descriptives"].to_excel(xl, sheet_name="Descriptives", index=False)
+            res["tests"].to_excel(xl, sheet_name="Tests", index=False)
+            res["per_phase"].to_excel(xl, sheet_name="PerPhase", index=False)
+            res["per_image"].to_excel(xl, sheet_name="PerImage", index=False)
+            for sh in xl.book.worksheets:
+                for col in sh.columns:
+                    w = max((len(str(c.value)) if c.value is not None else 0) for c in col)
+                    sh.column_dimensions[col[0].column_letter].width = min(max(w + 2, 12), 62)
+                sh.freeze_panes = "A2"
+        return out
+    except Exception as exc:  # openpyxl missing -> CSV fallback
+        print(f"[stats] xlsx failed for {model} ({exc}); writing CSVs instead")
+        res["tests"].to_csv(out_dir / f"{model}__tests.csv", index=False)
+        res["descriptives"].to_csv(out_dir / f"{model}__descriptives.csv", index=False)
+        res["per_phase"].to_csv(out_dir / f"{model}__per_phase.csv", index=False)
+        return None
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--runs-root", default="runs")
+    args = ap.parse_args()
+
+    runs_root = pathlib.Path(args.runs_root).resolve()
+    if not runs_root.is_dir():
+        print(f"[stats] runs root not found: {runs_root}")
+        return 1
+
+    data = discover(runs_root)
+    if not data:
+        print(f"[stats] no evaluation.json found under {runs_root}")
+        return 1
+
+    out_dir = runs_root / "_stats"
+    out_dir.mkdir(parents=True, exist_ok=True)
+    rng = np.random.default_rng(SEED)
+
+    summary_rows = []
+    for model in sorted(data):
+        res = analyse_model(model, data[model], rng)
+        if res is None:
+            print(f"[stats] {model}: no phase has both S2 and S3 -- skipped")
+            continue
+        wb = write_workbook(model, res, out_dir)
+        print(f"[stats] {model:28s} phases={len(res['phases'])}  -> {wb.name if wb else '(csv)'}"
+              + ("  [SPLIT WARNINGS]" if res["split_warnings"] else ""))
+
+        # headline: Wilcoxon row per metric per level for the cross-model summary
+        t = res["tests"]
+        for m in METRICS:
+            for level in ("per_image", "phase_level"):
+                r = t[(t.Metric == m) & (t.Level == level) & (t.Test == "Wilcoxon signed-rank")]
+                if r.empty:
+                    continue
+                r = r.iloc[0]
+                summary_rows.append({
+                    "Model": model, "Metric": m, "Level": level, "n_pairs": int(r.n_pairs),
+                    "S3_minus_S2": r.Mean_delta, "Wilcoxon_p_raw": r.p_raw,
+                    "p_Holm_global": r.p_Holm_global, "Sig_global": r.Sig_global,
+                    "Better_arm": r.Better_arm, "Cohens_dz": r.Cohens_dz,
+                    "boot_CI_low": r.boot_CI_low, "boot_CI_high": r.boot_CI_high,
+                })
+
+    summary_df = pd.DataFrame(summary_rows)
+    summary_df.to_csv(out_dir / "ALL_MODELS_summary.csv", index=False)
+    try:
+        with pd.ExcelWriter(out_dir / "ALL_MODELS_summary.xlsx", engine="openpyxl") as xl:
+            summary_df.to_excel(xl, sheet_name="Summary", index=False)
+            for sh in xl.book.worksheets:
+                for col in sh.columns:
+                    w = max((len(str(c.value)) if c.value is not None else 0) for c in col)
+                    sh.column_dimensions[col[0].column_letter].width = min(max(w + 2, 12), 40)
+                sh.freeze_panes = "A2"
+    except Exception:
+        pass
+
+    print(f"\n[stats] wrote per-model workbooks + ALL_MODELS_summary to {out_dir}")
+    if not summary_df.empty:
+        pd.set_option("display.width", 240, "display.max_columns", 40)
+        prim = summary_df[summary_df.Metric == PRIMARY]
+        print(f"\n=== PRIMARY ({PRIMARY}) S3-vs-S2, both levels ===")
+        print(prim.to_string(index=False, float_format=lambda v: f"{v:.4g}"))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

params/models_manifest.json

@@ -0,0 +1,50 @@
+{
+  "segformer_b0": {
+    "family": "transformer",
+    "model_name": "Segformer_B0",
+    "arch": "Segformer",
+    "encoder": "mit_b0",
+    "proj_dim": 192,
+    "params_dir": "params/segformer_b0"
+  },
+  "unet_effb0": {
+    "family": "cnn",
+    "model_name": "Unet_EffB0",
+    "arch": "Unet",
+    "encoder": "efficientnet-b0",
+    "proj_dim": 256,
+    "params_dir": "params/unet_effb0"
+  },
+  "deeplabv3plus_r34": {
+    "family": "cnn",
+    "model_name": "DeepLabV3Plus_ResNet34",
+    "arch": "DeepLabV3Plus",
+    "encoder": "resnet34",
+    "proj_dim": 256,
+    "params_dir": "params/deeplabv3plus_r34"
+  },
+  "linknet_mbv3": {
+    "family": "cnn",
+    "model_name": "Linknet_MobileNetV3",
+    "arch": "Linknet",
+    "encoder": "timm-mobilenetv3_large_100",
+    "proj_dim": 256,
+    "params_dir": "params/linknet_mbv3"
+  },
+  "upernet_pvtv2_b1": {
+    "family": "transformer",
+    "model_name": "UPerNet_PVTv2_b1",
+    "arch": "UPerNet",
+    "encoder": "tu-pvt_v2_b1",
+    "proj_dim": 192,
+    "params_dir": "params/upernet_pvtv2_b1"
+  },
+  "upernet_pvtv2_b2": {
+    "family": "transformer",
+    "model_name": "UPerNet_PVTv2_b2",
+    "arch": "UPerNet",
+    "encoder": "tu-pvt_v2_b2",
+    "proj_dim": 192,
+    "params_dir": "params/upernet_pvtv2_b2"
+  }
+}

plot_s2_vs_s3.py

@@ -0,0 +1,216 @@
+"""Scan runs/ and, for every model, plot Strategy 2 (supervised baseline) vs
+Strategy 3 (refinement), AVERAGED ACROSS ALL PHASES found for that model.
+
+Six measures per model (mean across phases, error bars = std across phases):
+
+    * BIoU (band, d-pixel)       evaluation.json -> metrics.biou.mean
+    * BIoU (contour, 1-pixel)    evaluation.json -> metrics.biou_contour.mean
+    * Total training time (min)  summary.json    -> elapsed_seconds
+    * Inference time (ms/image)  evaluation.json -> timing.mean_per_image_inference_ms
+    * Time per epoch (s)         summary.json    -> seconds_per_epoch
+    * Time to best ckpt (min)    best.pt.meta.json -> epoch  x  seconds_per_epoch
+                                 (falls back to argmax of selection_metric_value in history.json)
+
+Usage:
+    python plot_s2_vs_s3.py                 # scans ./runs
+    python plot_s2_vs_s3.py --runs-root X
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import pathlib
+import re
+from collections import defaultdict
+
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import numpy as np
+
+STRATEGY_LABEL = {2: "S2 (baseline)", 3: "S3 (refinement)"}
+BAR_COLORS = {2: "#4C78A8", 3: "#F58518"}
+
+# key, title, ylabel, higher_is_better, value format
+PANELS = [
+    ("biou",             "Boundary IoU (band)",     "BIoU",         True,  "{:.4f}"),
+    ("biou_contour",     "Boundary IoU (contour)",  "BIoU contour", True,  "{:.4f}"),
+    ("infer_ms",         "Inference time",          "ms / image",   False, "{:.2f}"),
+    ("train_min",        "Total training time",     "minutes",      False, "{:.1f}"),
+    ("epoch_sec",        "Time per epoch",          "seconds",      False, "{:.1f}"),
+    ("time_to_best_min", "Time to best checkpoint", "minutes",      False, "{:.1f}"),
+]
+
+
+def load_json(path: pathlib.Path):
+    try:
+        return json.loads(path.read_text(encoding="utf-8"))
+    except Exception:
+        return None
+
+
+def best_epoch_for(final_dir: pathlib.Path) -> int | None:
+    """Epoch at which the best checkpoint was saved."""
+    meta = load_json(final_dir / "checkpoints" / "best.pt.meta.json")
+    if meta and meta.get("epoch") is not None:
+        return int(meta["epoch"])
+
+    # fallback: argmax of the selection metric recorded in history
+    hist = load_json(final_dir / "history.json")
+    if isinstance(hist, list) and hist:
+        best_ep, best_val = None, None
+        for row in hist:
+            val = row.get("selection_metric_value")
+            if val is None:
+                continue
+            if best_val is None or float(val) > float(best_val):
+                best_val, best_ep = float(val), int(row.get("epoch", 0))
+        return best_ep
+    return None
+
+
+def collect(runs_root: pathlib.Path) -> dict[str, dict[int, dict[str, list[float]]]]:
+    """model -> strategy -> metric -> [one value per phase]"""
+    data: dict[str, dict[int, dict[str, list[float]]]] = defaultdict(
+        lambda: defaultdict(lambda: defaultdict(list))
+    )
+    for eval_path in runs_root.glob("*/**/strategy_*/final/evaluation.json"):
+        final_dir = eval_path.parent
+        m = re.search(r"strategy_(\d+)", final_dir.parent.name)
+        if not m:
+            continue
+        strategy = int(m.group(1))
+        if strategy not in (2, 3):
+            continue
+        try:
+            model = eval_path.relative_to(runs_root).parts[0]
+        except ValueError:
+            continue
+
+        ev = load_json(eval_path)
+        if not ev:
+            continue
+        bucket = data[model][strategy]
+        metrics = ev.get("metrics", {}) or {}
+
+        for key in ("biou", "biou_contour"):
+            val = (metrics.get(key) or {}).get("mean")
+            if val is not None:
+                bucket[key].append(float(val))
+
+        infer = (ev.get("timing", {}) or {}).get("mean_per_image_inference_ms")
+        if infer is not None:
+            bucket["infer_ms"].append(float(infer))
+
+        summary = load_json(final_dir / "summary.json")
+        if summary:
+            if summary.get("elapsed_seconds") is not None:
+                bucket["train_min"].append(float(summary["elapsed_seconds"]) / 60.0)
+            spe = summary.get("seconds_per_epoch")
+            if spe is not None:
+                bucket["epoch_sec"].append(float(spe))
+                be = best_epoch_for(final_dir)
+                if be:
+                    bucket["time_to_best_min"].append(be * float(spe) / 60.0)
+
+    return data
+
+
+def plot_model(model: str, per_strategy: dict[int, dict[str, list[float]]],
+               out_dir: pathlib.Path) -> pathlib.Path | None:
+    strategies = [s for s in (2, 3) if per_strategy.get(s)]
+    if not strategies:
+        return None
+
+    n_phases = max((len(v.get("biou", [])) for v in per_strategy.values()), default=0)
+    fig, axes = plt.subplots(2, 3, figsize=(16, 8.5))
+    fig.suptitle(f"{model}   —   Strategy 2 vs Strategy 3\n"
+                 f"mean across {n_phases} phase(s), error bars = std across phases",
+                 fontsize=14, fontweight="bold")
+
+    for ax, (key, title, ylabel, higher_better, fmt) in zip(axes.ravel(), PANELS):
+        xs, means, stds, labels, colors = [], [], [], [], []
+        for i, s in enumerate(strategies):
+            vals = per_strategy[s].get(key, [])
+            if not vals:
+                continue
+            xs.append(i)
+            means.append(float(np.mean(vals)))
+            stds.append(float(np.std(vals)) if len(vals) > 1 else 0.0)
+            labels.append(STRATEGY_LABEL[s])
+            colors.append(BAR_COLORS[s])
+
+        if not means:
+            ax.set_title(f"{title}  (no data)")
+            ax.axis("off")
+            continue
+
+        bars = ax.bar(xs, means, yerr=stds, capsize=5, color=colors, width=0.55)
+        ax.set_xticks(xs)
+        ax.set_xticklabels(labels, fontsize=9)
+        ax.set_ylabel(ylabel)
+        ax.set_title(f"{title}   ({'higher' if higher_better else 'lower'} is better)", fontsize=11)
+        ax.grid(axis="y", alpha=0.3, linestyle="--")
+        ax.margins(y=0.18)
+
+        for b, mval in zip(bars, means):
+            ax.annotate(fmt.format(mval), (b.get_x() + b.get_width() / 2, b.get_height()),
+                        textcoords="offset points", xytext=(0, 4), ha="center", fontsize=9)
+
+        if len(means) == 2:
+            delta = means[1] - means[0]
+            pct = (delta / means[0] * 100.0) if means[0] else 0.0
+            good = (delta > 0) if higher_better else (delta < 0)
+            ax.text(0.5, 0.02, f"Δ(S3−S2) = {delta:+.4g}  ({pct:+.1f}%)",
+                    transform=ax.transAxes, ha="center", fontsize=9,
+                    color=("green" if good else "red"))
+
+    fig.tight_layout(rect=(0, 0, 1, 0.93))
+    out_dir.mkdir(parents=True, exist_ok=True)
+    out_path = out_dir / f"{model}__s2_vs_s3.png"
+    fig.savefig(out_path, dpi=150)
+    plt.close(fig)
+    return out_path
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--runs-root", default="runs")
+    args = ap.parse_args()
+
+    runs_root = pathlib.Path(args.runs_root).resolve()
+    if not runs_root.is_dir():
+        print(f"[plot] runs root not found: {runs_root}")
+        return 1
+
+    data = collect(runs_root)
+    if not data:
+        print(f"[plot] no evaluation.json found under {runs_root}")
+        return 1
+
+    out_dir = runs_root / "_plots"
+    csv_rows = ["model,strategy,metric,mean,std,n_phases"]
+    made = []
+
+    for model in sorted(data):
+        p = plot_model(model, data[model], out_dir)
+        if p:
+            made.append(p)
+            n = max((len(v.get("biou", [])) for v in data[model].values()), default=0)
+            print(f"[plot] {model:34s} n_phases={n:<3d} -> {p.name}")
+        for s in sorted(data[model]):
+            for key, *_ in PANELS:
+                vals = data[model][s].get(key, [])
+                if vals:
+                    csv_rows.append(
+                        f"{model},{s},{key},{np.mean(vals):.6f},"
+                        f"{(np.std(vals) if len(vals) > 1 else 0.0):.6f},{len(vals)}"
+                    )
+
+    (out_dir / "summary_s2_vs_s3.csv").write_text("\n".join(csv_rows) + "\n", encoding="utf-8")
+    print(f"\n[plot] {len(made)} figure(s) + summary_s2_vs_s3.csv written to {out_dir}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

requirements_runpod.txt

@@ -0,0 +1,13 @@
+# Use this with a RunPod PyTorch image that already includes torch/torchvision + CUDA.
+# This avoids wasting setup time reinstalling large GPU wheels.
+
+numpy>=1.24.0
+scipy>=1.10.0
+pillow>=10.0.0
+tqdm>=4.66.0
+matplotlib>=3.8.0
+pandas>=2.2.0
+openpyxl>=3.1.0
+optuna>=3.6.0
+segmentation-models-pytorch>=0.5.0
+timm>=1.0.0

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/exports/aggregated_metrics_by_percent_strategy.csv

@@ -0,0 +1,3 @@
+biou_contour_mean,biou_contour_std,biou_contour_within_run_std_mean,biou_mean,biou_std,biou_within_run_std_mean,completed_phase_count,completed_phases,dataset_percent,dice_mean,dice_std,dice_within_run_std_mean,hd95_mean,hd95_std,hd95_within_run_std_mean,iou_mean,iou_std,iou_within_run_std_mean,n_runs,ppv_mean,ppv_std,ppv_within_run_std_mean,sen_mean,sen_std,sen_within_run_std_mean,split_generation_mode,strategy
+0.10658753663301468,0.007339854717964752,0.08429641127586365,0.38765804171562196,0.018165690360599084,0.21831948757171632,5,"2,3,4,9,10",100,0.779808759689331,0.014647414633594986,0.243904447555542,12.895025062561036,1.796037401561253,21.965408325195312,0.6889553785324096,0.011983966508109928,0.25024294555187226,5,0.8218204975128174,0.009422276608595955,0.23497852087020873,0.7984434843063355,0.024920658867602998,0.25239624083042145,fixed_stratified_phases_8_1_1,2
+0.15978023707866668,0.021218451908610055,0.12744158655405044,0.45167040824890137,0.030927701615027236,0.24558151960372926,5,"2,3,4,9,10",100,0.8045141458511352,0.02037104769957007,0.2366455763578415,11.593777847290038,1.7023791352209379,18.272854232788085,0.7224233269691467,0.01810482451855519,0.2474461168050766,5,0.8372180461883545,0.008289385576892344,0.24025410711765288,0.8173958659172058,0.03127828085396388,0.23604983687400818,fixed_stratified_phases_8_1_1,3

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/exports/aggregated_metrics_by_percent_strategy.json

@@ -0,0 +1,60 @@
+[
+  {
+    "biou_contour_mean": 0.10658753663301468,
+    "biou_contour_std": 0.007339854717964752,
+    "biou_contour_within_run_std_mean": 0.08429641127586365,
+    "biou_mean": 0.38765804171562196,
+    "biou_std": 0.018165690360599084,
+    "biou_within_run_std_mean": 0.21831948757171632,
+    "completed_phase_count": 5,
+    "completed_phases": "2,3,4,9,10",
+    "dataset_percent": 100,
+    "dice_mean": 0.779808759689331,
+    "dice_std": 0.014647414633594986,
+    "dice_within_run_std_mean": 0.243904447555542,
+    "hd95_mean": 12.895025062561036,
+    "hd95_std": 1.796037401561253,
+    "hd95_within_run_std_mean": 21.965408325195312,
+    "iou_mean": 0.6889553785324096,
+    "iou_std": 0.011983966508109928,
+    "iou_within_run_std_mean": 0.25024294555187226,
+    "n_runs": 5,
+    "ppv_mean": 0.8218204975128174,
+    "ppv_std": 0.009422276608595955,
+    "ppv_within_run_std_mean": 0.23497852087020873,
+    "sen_mean": 0.7984434843063355,
+    "sen_std": 0.024920658867602998,
+    "sen_within_run_std_mean": 0.25239624083042145,
+    "split_generation_mode": "fixed_stratified_phases_8_1_1",
+    "strategy": 2
+  },
+  {
+    "biou_contour_mean": 0.15978023707866668,
+    "biou_contour_std": 0.021218451908610055,
+    "biou_contour_within_run_std_mean": 0.12744158655405044,
+    "biou_mean": 0.45167040824890137,
+    "biou_std": 0.030927701615027236,
+    "biou_within_run_std_mean": 0.24558151960372926,
+    "completed_phase_count": 5,
+    "completed_phases": "2,3,4,9,10",
+    "dataset_percent": 100,
+    "dice_mean": 0.8045141458511352,
+    "dice_std": 0.02037104769957007,
+    "dice_within_run_std_mean": 0.2366455763578415,
+    "hd95_mean": 11.593777847290038,
+    "hd95_std": 1.7023791352209379,
+    "hd95_within_run_std_mean": 18.272854232788085,
+    "iou_mean": 0.7224233269691467,
+    "iou_std": 0.01810482451855519,
+    "iou_within_run_std_mean": 0.2474461168050766,
+    "n_runs": 5,
+    "ppv_mean": 0.8372180461883545,
+    "ppv_std": 0.008289385576892344,
+    "ppv_within_run_std_mean": 0.24025410711765288,
+    "sen_mean": 0.8173958659172058,
+    "sen_std": 0.03127828085396388,
+    "sen_within_run_std_mean": 0.23604983687400818,
+    "split_generation_mode": "fixed_stratified_phases_8_1_1",
+    "strategy": 3
+  }
+]

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/exports/raw_run_metrics.csv

@@ -0,0 +1,11 @@
+biou_contour_mean,biou_contour_std,biou_mean,biou_std,dataset_percent,dice_mean,dice_std,evaluation_path,hd95_mean,hd95_std,iou_mean,iou_std,phase_index,phase_test_fold_index,phase_val_fold_index,ppv_mean,ppv_std,run_dir,sen_mean,sen_std,split_generation_mode,split_manifest_path,split_repeat_index,strategy,subset_manifest_path,subset_repeat_index
+0.10553458333015442,0.07625986635684967,0.3781984746456146,0.2127406746149063,100,0.7896647453308105,0.2421818971633911,/workspace/runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_002/pct_100/repeat_01/strategy_2/final/evaluation.json,15.18199348449707,27.79026985168457,0.7016277313232422,0.2495580017566681,2,2,3,0.824587881565094,0.23476456105709076,/workspace/runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_002/pct_100/repeat_01/strategy_2/final,0.8144153952598572,0.24154168367385864,fixed_stratified_phases_8_1_1,/workspace/runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/manifests/splits/phase_002.json,2,2,/workspace/runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/manifests/subsets/phase_002_pct_100_repeat_01.json,1
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runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_010/pct_100/repeat_01/strategy_3/final/evaluation.json

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runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_010/pct_100/repeat_01/strategy_3/final/evaluation_summary.json

@@ -0,0 +1,4 @@
+{
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+  "mean_iou": 0.7351952791213989
+}

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_010/pct_100/repeat_01/strategy_3/final/low_iou_samples.csv

@@ -0,0 +1,2 @@
+sample_id
+BUSI_0302_B

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_010/pct_100/repeat_01/strategy_3/final/run_config.json

@@ -0,0 +1,112 @@
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+  "project_dir": "/workspace",
+  "refine_delta_large": 0.08,
+  "refine_delta_small": 0.03,
+  "rl_lr": 0.0001971844222061614,
+  "run_name": "phase=010 | repeat=01 | strategy=3 | pct=100%",
+  "run_type": "final",
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+  "scheduler_factor": 0.5,
+  "scheduler_min_lr": 1e-05,
+  "scheduler_patience": 5,
+  "scheduler_threshold": 0.001,
+  "selected_split_manifest_path": "/workspace/runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/manifests/subsets/phase_010_pct_100_repeat_01.json",
+  "smp_decoder_type": "UPerNet",
+  "smp_encoder_depth": 5,
+  "smp_encoder_name": "tu-pvt_v2_b2",
+  "smp_encoder_proj_dim": 192,
+  "smp_encoder_weights": "imagenet",
+  "split_generation_mode": "fixed_stratified_phases_8_1_1",
+  "split_repeat_index": 10,
+  "split_seed": 723450912,
+  "split_type": "80_10_10",
+  "strategy": 3,
+  "strategy2_checkpoint_mode": "best",
+  "strategy2_checkpoint_path": "/workspace/runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_010/pct_100/repeat_01/strategy_2/final/checkpoints/best.pt",
+  "strategy3_advantage_normalize": false,
+  "strategy3_aux_boundary_dice_weight": 0.6979509040767587,
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+  "strategy3_aux_ce_anneal_start_epoch": 25,
+  "strategy3_aux_ce_floor_fraction": 0.1,
+  "strategy3_aux_ce_weight": 0.4,
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+  "strategy3_decoder_dice_weight": 0.0,
+  "strategy3_delta_max": 0.1,
+  "strategy3_exploration_eps": 0.1,
+  "strategy3_exploration_eps_epochs": 20,
+  "strategy3_freeze_bootstrapped_segmentation": true,
+  "strategy3_mc_disk_cache_enabled": true,
+  "strategy3_mc_disk_cache_read": true,
+  "strategy3_mc_disk_cache_write": true,
+  "strategy3_mc_dropout_enabled": true,
+  "strategy3_mc_dropout_p": 0.2,
+  "strategy3_mc_dropout_samples": 5,
+  "strategy3_r1_progress_weight": 1.0,
+  "strategy3_rl_grad_clip_norm": 0.25,
+  "strategy3_rl_loss_scale": 10.0,
+  "strategy3_sam_attention_grid": 64,
+  "strategy3_variant": "lite",
+  "subset_manifest_path": "/workspace/runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/manifests/subsets/phase_010_pct_100_repeat_01.json",
+  "subset_repeat_index": 1,
+  "subset_sampling_source": "incremental_chain",
+  "subset_seed": 1653428179,
+  "threshold": 0.5922320465492188,
+  "tmax": 8,
+  "train_resume_mode": "off",
+  "train_resume_specific_checkpoint": "",
+  "train_subset_key": "100",
+  "train_subset_source": "incremental_chain",
+  "train_subset_variant": 1,
+  "vgg_feature_dilation": 1,
+  "vgg_feature_scales": 4,
+  "weight_decay": 2.7012557725439094e-06,
+  "write_epoch_diagnostic": false
+}

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_010/pct_100/repeat_01/strategy_3/final/summary.json

@@ -0,0 +1,34 @@
+{
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+  "best_model_metric": 0.5724109242210832,
+  "best_model_metric_name": "val_refine_score",
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+  "best_val_iou": 0.708380159951118,
+  "best_val_iou_gain": 0.02820180307914244,
+  "device_used": "cuda",
+  "early_stopping_best_value": 0.5724109242210832,
+  "early_stopping_min_delta": 0.0,
+  "early_stopping_monitor_mode": "max",
+  "early_stopping_monitor_name": "val_refine_score",
+  "early_stopping_patience": 30,
+  "early_stopping_start_epoch": 30,
+  "elapsed_seconds": 1276.2680625915527,
+  "epochs_to_best_checkpoint": 72,
+  "final_epoch": 102,
+  "gpu_name": "NVIDIA A100 80GB PCIe",
+  "resumed": false,
+  "run_type": "final",
+  "seconds_per_epoch": 12.512431986191693,
+  "seconds_per_epoch_measured_mean": 12.408194299632063,
+  "seconds_per_epoch_measured_std": 0.8456643552471369,
+  "strategy": 3,
+  "strategy3_bootstrap_loaded": true,
+  "strategy3_decoder_state": "frozen",
+  "strategy3_encoder_state": "frozen",
+  "strategy3_freeze_active": true,
+  "strategy3_freeze_requested": true,
+  "strategy3_segmentation_head_state": "frozen",
+  "time_to_best_seconds": 894.9727710350417
+}

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_010/pct_100/repeat_01/strategy_3/final/timing.csv

@@ -0,0 +1,2 @@
+scope,strategy,tmax,device,num_batches,num_samples,total_inference_ms,avg_batch_inference_ms,std_batch_inference_ms,avg_sample_inference_ms,std_sample_inference_ms,mean_per_image_inference_ms,std_per_image_inference_ms,mean_per_image_inference_seconds,std_per_image_inference_seconds
+test_set_evaluation,3,8,cuda,2,64,623.334601,311.667301,139.421997,9.739603,0.592205,9.739603,0.592205,0.009739603,0.000592205

runs/UPerNet_PVTv2_b2/repeated_holdout/stratified_holdout_v1/phase_timing_summary.json

@@ -0,0 +1,155 @@
+{
+  "definition": "training elapsed_seconds from summary.json, falling back to the ledger checkpoint elapsed_seconds",
+  "phase_count": 5,
+  "phases": [
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+        3
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+      "updated_at": "2026-08-03T14:08:36.540222+00:00"
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+      "updated_at": "2026-08-03T16:09:05.516969+00:00"
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+  "scope": "fixed_phase_training_time",
+  "training_elapsed_seconds_mean_across_phases": 819.6776441812515,
+  "training_elapsed_seconds_std_across_phases": 77.42354388274894,
+  "updated_at": "2026-08-03T16:09:05.517103+00:00"
+}

runs/_plots/summary_s2_vs_s3.csv

@@ -0,0 +1,13 @@
+model,strategy,metric,mean,std,n_phases
+UPerNet_PVTv2_b2,2,biou,0.387658,0.018166,5
+UPerNet_PVTv2_b2,2,biou_contour,0.106588,0.007340,5
+UPerNet_PVTv2_b2,2,infer_ms,1.381536,0.387893,5
+UPerNet_PVTv2_b2,2,train_min,3.029709,1.638305,5
+UPerNet_PVTv2_b2,2,epoch_sec,1.894138,0.952402,5
+UPerNet_PVTv2_b2,2,time_to_best_min,2.572189,1.699196,5
+UPerNet_PVTv2_b2,3,biou,0.451670,0.030928,5
+UPerNet_PVTv2_b2,3,biou_contour,0.159780,0.021218,5
+UPerNet_PVTv2_b2,3,infer_ms,9.926945,0.148849,5
+UPerNet_PVTv2_b2,3,train_min,24.292879,1.518696,5
+UPerNet_PVTv2_b2,3,epoch_sec,12.521813,0.077118,5
+UPerNet_PVTv2_b2,3,time_to_best_min,19.787100,2.816359,5

runs/_stats/ALL_MODELS_summary.csv

@@ -0,0 +1,15 @@
+Model,Metric,Level,n_pairs,S3_minus_S2,Wilcoxon_p_raw,p_Holm_global,Sig_global,Better_arm,Cohens_dz,boot_CI_low,boot_CI_high
+UPerNet_PVTv2_b2,biou_contour,per_image,323,0.05323689972250793,5.718497206218795e-26,2.287398882487518e-24,Yes,S3 (refinement),0.5976812828087569,0.04388856770935864,0.0631788819574603
+UPerNet_PVTv2_b2,biou_contour,phase_level,5,0.05319270071814397,0.0625,0.904454777261137,No,n.s.,2.7898246582797013,0.03994488089272243,0.06847578049149965
+UPerNet_PVTv2_b2,biou,per_image,323,0.06405450550476223,1.7289307098031236e-35,7.261508981173119e-34,Yes,S3 (refinement),0.7106123430299262,0.054621372643315846,0.07419702627070363
+UPerNet_PVTv2_b2,biou,phase_level,5,0.06401235940982118,0.0625,0.904454777261137,No,n.s.,3.2112497773429203,0.04877197464166473,0.07925274417797765
+UPerNet_PVTv2_b2,dice,per_image,323,0.024717042764589976,1.6137224260354095e-21,5.970772976331016e-20,Yes,S3 (refinement),0.3369163551465658,0.01758011096126462,0.033468297370947586
+UPerNet_PVTv2_b2,dice,phase_level,5,0.024705393755753292,0.0625,0.904454777261137,No,n.s.,2.355188925592429,0.01679677571245599,0.032571750830933756
+UPerNet_PVTv2_b2,iou,per_image,323,0.03349147755422749,8.927138942126266e-23,3.392312798007981e-21,Yes,S3 (refinement),0.4283906438768904,0.025532213233220028,0.04245785713177373
+UPerNet_PVTv2_b2,iou,phase_level,5,0.0334679205953595,0.0625,0.904454777261137,No,n.s.,2.6542353345316627,0.023657582805408372,0.04327825838531063
+UPerNet_PVTv2_b2,ppv,per_image,323,0.015432132519286663,9.692831383221536e-21,3.489419297959753e-19,Yes,S3 (refinement),0.14679531799469125,0.003600603527365194,0.026376065855223244
+UPerNet_PVTv2_b2,ppv,phase_level,5,0.015397503612966967,0.0625,0.904454777261137,No,n.s.,1.1086750057065942,0.005221036805826839,0.026911534432880545
+UPerNet_PVTv2_b2,sen,per_image,323,0.018927612716654368,0.028008282190094113,0.5041490794216941,No,S3 (refinement),0.22135844946187674,0.01042786989469917,0.02880240613683837
+UPerNet_PVTv2_b2,sen,phase_level,5,0.018952392346317716,0.0625,0.904454777261137,No,n.s.,1.660638095810431,0.010383693878889844,0.028426579776123572
+UPerNet_PVTv2_b2,hd95,per_image,323,-1.30639897336755,1.4906865581005058e-05,0.0004919265641731669,Yes,S3 (refinement),-0.11436884240155197,-2.6939560695612763,-0.26375395856774686
+UPerNet_PVTv2_b2,hd95,phase_level,5,-1.301247094144427,0.0625,0.904454777261137,No,n.s.,-1.4379107639344506,-2.0157415708953055,-0.5867526173935488