code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
value |
|---|---|---|---|---|---|
from sqlalchemy import create_engine
import numpy as np
def get_engine(dbms:str, username:str, password:str, host:str, port:int, database:str):
"""
Parameter
----------
dbms : {"mysql", "postgres"}
"""
assert dbms in ["mysql", "postgresql"], "available dbms values are mysql and postgresql on... | /sa_package-0.0.80-py3-none-any.whl/sa_package/mydatabase/__init__.py | 0.497315 | 0.353261 | __init__.py | pypi |
import typing as t
import more_itertools
import sqlalchemy as sa
from sqlalchemy import ColumnElement
from sqlalchemy.exc import NoResultFound
from sqlalchemy.orm import DeclarativeBase, Session, joinedload
__all__ = ['BaseRepository']
T = t.TypeVar('T', bound=DeclarativeBase)
class BaseRepository(t.Generic[T]):
... | /sa_repository-1.1.0.tar.gz/sa_repository-1.1.0/sa_repository/base.py | 0.466603 | 0.195287 | base.py | pypi |
from __future__ import print_function
import time
from datetime import datetime
from elasticsearch import Elasticsearch, __version__ as es_client_version
class ESQuery(object):
def __init__(self, es_hosts, index_prefix, timestamp_field, index_time_format='%Y.%m.%d', es_user='', es_passwd=''):
self.clie... | /sa_tools_core-0.6.0-py3-none-any.whl/sa_tools_core/libs/es.py | 0.675872 | 0.285167 | es.py | pypi |
from collections import deque
class Sa2SeedKey:
register: int
carry_flag: int = 0
instruction_tape: bytearray
instruction_pointer: int = 0
for_pointers: deque = deque()
for_iterations: deque = deque()
def __init__(self, instruction_tape, seed):
self.instruction_tape = instruction_tape
self.regis... | /sa2-seed-key-0.0.1.tar.gz/sa2-seed-key-0.0.1/sa2_seed_key/sa2_seed_key.py | 0.425844 | 0.261794 | sa2_seed_key.py | pypi |
# Saa
> _Making Time Speak!_ 🎙️
Translating time into human-friendly spoken expressions
**Saa** allows you to effortlessly translate time into human-friendly spoken expressions. The word `saa` means `hour` in Swahili, and this package aims to humanify time expression across languages. It... | /saa-0.0.5.tar.gz/saa-0.0.5/README.md | 0.747708 | 0.864996 | README.md | pypi |
from typing import Any, Text, Dict, List
from rasa_sdk import Action, Tracker
from rasa_sdk.events import UserUtteranceReverted
from rasa_sdk.executor import CollectingDispatcher
from pprint import pprint
import logging
import json
class ActionHelloWorld(Action):
def name(self) -> Text:
return "action_he... | /saai-0.3.0-py3-none-any.whl/bots/genesis/actions/actions.py | 0.699665 | 0.207415 | actions.py | pypi |
from typing import Text, Any, Dict, List
from sagas.nlu.inspector_common import Inspector, Context
import logging
logger = logging.getLogger(__name__)
# 代码整理自notebook: procs-rasa-entity-iob.ipynb
def get_entities(sents:Text):
from saai.tool import rasa_nlu_parse
result = rasa_nlu_parse(sents, 'http://localhos... | /saai-0.3.0-py3-none-any.whl/bots/agent_dispatcher/inspectors/cust_entity_inspector.py | 0.494629 | 0.220437 | cust_entity_inspector.py | pypi |
```
import pyrata.re as pyrata_re
data = [{'pos': 'PRP', 'raw': 'It'}, {'pos': 'VBZ', 'raw': 'is'},
{'pos': 'JJ', 'raw': 'fast'}, {'pos': 'JJ', 'raw': 'easy'},
{'pos': 'CC', 'raw': 'and'}, {'pos': 'JJ', 'raw': 'funny'},
{'pos': 'TO', 'raw': 'to'}, {'pos': 'VB', 'raw': 'write'},
{'pos... | /saai-0.3.0-py3-none-any.whl/notebook/procs-pyrata.ipynb | 0.622804 | 0.804905 | procs-pyrata.ipynb | pypi |
```
import sagas
sagas.print_rs([('tom',5)], ['name','age'])
from rasa.nlu import config
conf=config.load('saai/sample_configs/config_crf_custom_features.yml')
# conf.for_component('DucklingHTTPExtractor')
conf.component_names
conf.language
# print(conf.get('DucklingHTTPExtractor'))
from rasa.nlu.training_data imp... | /saai-0.3.0-py3-none-any.whl/notebook/procs-tokenizers.ipynb | 0.519765 | 0.176423 | procs-tokenizers.ipynb | pypi |
```
from rasa.utils.endpoints import ClientResponseError, EndpointConfig
from rasa.core.agent import Agent
from rasa.core.interpreter import RasaNLUInterpreter
from rasa.model import get_model, get_latest_model
# preq: $ start actions
bot='saya'
endpoint = EndpointConfig("http://localhost:5055/webhook")
bot_locs={'s... | /saai-0.3.0-py3-none-any.whl/notebook/procs-bots-saya.ipynb | 0.426799 | 0.665645 | procs-bots-saya.ipynb | pypi |
```
from flair.data import Sentence
from flair.models import SequenceTagger
# make a sentence
sentence = Sentence('I love Berlin .')
# load the NER tagger
# download from: https://s3.eu-central-1.amazonaws.com//alan-nlp/resources/models-v0.4/NER-conll03-english/en-ner-conll03-v0.4.pt
# tagger = SequenceTagger.load('n... | /saai-0.3.0-py3-none-any.whl/notebook/procs-flair.ipynb | 0.483648 | 0.163179 | procs-flair.ipynb | pypi |
from datetime import date, datetime, timedelta
import sys
import pandas as pd
# https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes
class Holidays:
@classmethod
def to_datetime(self, datestr:str) -> datetime:
"""
Convert date strings like "20210506" to datetime ... | /saaltfiish_boilerplate-0.1.3.tar.gz/saaltfiish_boilerplate-0.1.3/saaltfiish_boilerplate/holidays.py | 0.655557 | 0.284977 | holidays.py | pypi |
from ..._private._utilities import *
from ... import Event
from copy import deepcopy
SIMPLE_CHANGE_INDICATOR = lambda x, y: x != y
class DataStore(ABC):
@abstractmethod
def get_value(self, key: str) -> Optional[Any]:
raise NotImplementedError()
@abstractmethod
def set_value(self, key: str, ... | /saba-pipeline-1.0.2.tar.gz/saba-pipeline-1.0.2/src/sabapipeline/config/_private/_store.py | 0.753648 | 0.258367 | _store.py | pypi |
.. include:: references.txt
Saba: Sherpa-Astropy Bridge
===========================
The Saba package provides a bridge between the convenient model definition
language provided in the `astropy.modeling` package and the powerful fitting
capabilities of the Sherpa_ modeling and fitting package. In particular,
Sherpa h... | /saba-0.1.1a0.tar.gz/saba-0.1.1a0/docs/index.rst | 0.945889 | 0.777807 | index.rst | pypi |
.. include:: references.txt
Usage details
==============
Now that you have the basics let's move on to some more complex usage of the fitter interface.
First a quick preamble to do some imports and create our |SherpaFitter| object.
.. code-block:: ipython
from astropy.modeling.fitting import SherpaFitter
sf... | /saba-0.1.1a0.tar.gz/saba-0.1.1a0/docs/examples_complex.rst | 0.923256 | 0.69383 | examples_complex.rst | pypi |
from astropy.modeling.fitting import SherpaFitter
from astropy.modeling.models import Gaussian1D, Gaussian2D
import numpy as np
import matplotlib.pyplot as plt
sfitter = SherpaFitter(statistic='chi2', optimizer='levmar', estmethod='confidence')
sfitter.est_config['max_rstat'] = 4
np.random.seed(0x1337)
true = Gaussi... | /saba-0.1.1a0.tar.gz/saba-0.1.1a0/docs/gen_plots.py | 0.569613 | 0.645762 | gen_plots.py | pypi |
```
from astropy.modeling.core import Fittable1DModel
from sherpa.utils import interpolate
from sherpa.astro.utils import rmf_fold
from astropy.modeling.models import Gaussian1D,Gaussian2D
import numpy as n
%pylab inline
gmodel = Gaussian1D(mean=30,amplitude=10,stddev=5)
x_in = np.linspace(1,100,200)
y_in = gmodel(x_i... | /saba-0.1.1a0.tar.gz/saba-0.1.1a0/docs/.ipynb_checkpoints/Untitled-checkpoint.ipynb | 0.608478 | 0.470128 | Untitled-checkpoint.ipynb | pypi |
# Do not remove the following comment; it is used by
# astropy_helpers.version_helpers to determine the beginning of the code in
# this module
# BEGIN
import locale
import os
import subprocess
import warnings
def _decode_stdio(stream):
try:
stdio_encoding = locale.getdefaultlocale()[1] or 'utf-8'
ex... | /saba-0.1.1a0.tar.gz/saba-0.1.1a0/astropy_helpers/astropy_helpers/git_helpers.py | 0.55447 | 0.156105 | git_helpers.py | pypi |
import inspect
import sys
import re
import os
from warnings import warn
from sphinx.ext.autosummary.generate import find_autosummary_in_docstring
def find_mod_objs(modname, onlylocals=False):
""" Returns all the public attributes of a module referenced by name.
.. note::
The returned list *not* incl... | /saba-0.1.1a0.tar.gz/saba-0.1.1a0/astropy_helpers/astropy_helpers/sphinx/ext/utils.py | 0.435421 | 0.27197 | utils.py | pypi |
# Implementation note:
# The 'automodapi' directive is not actually implemented as a docutils
# directive. Instead, this extension searches for the 'automodapi' text in
# all sphinx documents, and replaces it where necessary from a template built
# into this extension. This is necessary because automodsumm (and autosum... | /saba-0.1.1a0.tar.gz/saba-0.1.1a0/astropy_helpers/astropy_helpers/sphinx/ext/automodapi.py | 0.526586 | 0.176069 | automodapi.py | pypi |
# Example PyPI (Python Package Index) Package & Tutorial / Instruction / Workflow for 2021
[](https://pypi.org/project/example-pypi-package/) [ -> pd.DataFrame:
"""
Compute flow duration curve (exceedan... | /saber_hbc-0.9.0-py3-none-any.whl/saber/fdc.py | 0.69285 | 0.617037 | fdc.py | pypi |
import glob
import logging
import math
import os
from collections.abc import Iterable
import joblib
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from kneed import KneeLocator
from natsort import natsorted
from sklearn.cluster import MiniBatchKMeans
from sklearn.metr... | /saber_hbc-0.9.0-py3-none-any.whl/saber/cluster.py | 0.811788 | 0.363506 | cluster.py | pypi |
import logging
import os
import contextily as cx
import geopandas as gpd
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from .io import COL_ASN_REASON
from .io import COL_CID
from .io import COL_GID
from .io import COL_MID
from .io import get_dir
from .io import read_g... | /saber_hbc-0.9.0-py3-none-any.whl/saber/gis.py | 0.785555 | 0.343713 | gis.py | pypi |
<p align="center">
<img src="img/saber_logo.png", style="height:150px">
</p>
<h1 align="center">
Saber
</h1>
<p align="center">
<a href="https://travis-ci.org/BaderLab/saber">
<img src="https://travis-ci.org/BaderLab/saber.svg?branch=master"
alt="Travis CI">
</a>
<a href="https://www.codacy.com... | /saber-0.1.0.tar.gz/saber-0.1.0/README.md | 0.663887 | 0.920074 | README.md | pypi |
# Quick Start
If your goal is simply to use Saber to annotate biomedical text, then you can either use the [web-service](#web-service) or a [pre-trained model](#pre-trained-models).
## Web-service
To use Saber as a **local** web-service, run
```
(saber) $ python -m saber.cli.app
```
or, if you prefer, you can pull... | /saber-0.1.0.tar.gz/saber-0.1.0/docs/quick_start.md | 0.793586 | 0.859899 | quick_start.md | pypi |
# Guide to the Saber API
You can interact with Saber as a web-service (explained in [Quick start](https://baderlab.github.io/saber/quick_start/)), command line tool, python package, or via the Juypter notebooks. If you created a virtual environment, _remember to activate it first_.
### Command line tool
Currently, t... | /saber-0.1.0.tar.gz/saber-0.1.0/docs/guide_to_saber_api.md | 0.742422 | 0.902266 | guide_to_saber_api.md | pypi |
# Move your playlists to Beat Saber!
`pip3 install saberio-rewind`
[:
home = str(Path.home())
output_dir = os.path.join(
home,
'.sabhi_utils/weights/'
)
... | /sabhi_utils-2.0.8-py3-none-any.whl/sabhi_utils/face_utility.py | 0.545044 | 0.199444 | face_utility.py | pypi |
import cv2
import numpy as np
import imutils
from sabhi_utils.image_utils.utils import load_image
class TemplateMatching:
def __init__(
self,
method=cv2.TM_CCOEFF_NORMED,
matching_threshold=0.75,
scales=np.linspace(0.2, 1.0, 20)[::-1],
debug=False
):
self._met... | /sabhi_utils-2.0.8-py3-none-any.whl/sabhi_utils/image_utils/template_matching.py | 0.526343 | 0.199776 | template_matching.py | pypi |
import numpy as np
from sabhi_utils.image_utils.processors import Closer
from sabhi_utils.image_utils.processors import EdgeDetector
from sabhi_utils.image_utils.processors import Opener
from collections import defaultdict
import itertools
import cv2
import time
from sklearn.cluster import KMeans
class HoughLineCorn... | /sabhi_utils-2.0.8-py3-none-any.whl/sabhi_utils/image_utils/hough_line_corner_detector.py | 0.802942 | 0.409634 | hough_line_corner_detector.py | pypi |
from collections import Counter
import matplotlib.pyplot as plt
import numpy as np
from sklearn.metrics import (calinski_harabasz_score, davies_bouldin_score,
pairwise_distances, silhouette_score)
def convertion_to_array(emb):
"""Converte a matriz de embeddings para um array numpy
... | /sabia-utils-0.2.0.tar.gz/sabia-utils-0.2.0/sabia_utils/evaluate.py | 0.834238 | 0.628806 | evaluate.py | pypi |
import matplotlib.pyplot as plt
import numpy as np
class EvaluateExperiments:
def __init__(self, metrics):
"""
Construtor EvaluateExperiments.
:param metrics: As métricas de avaliação dos clusters.
:type metrics: list
"""
self.metrics = metrics
self.inertia... | /sabia-utils-0.2.0.tar.gz/sabia-utils-0.2.0/sabia_utils/evaluateExperiments.py | 0.79999 | 0.577674 | evaluateExperiments.py | pypi |
import datetime
import difflib
import pytz
class Sablier(object):
"""Date, time and timezone for the rest of us."""
def __init__(self, date=None, time=datetime.time(0), timezone=None):
self.date = date
self.time = time
self.timezone = pytz.timezone(disambiguate(timezone)) if timezone... | /sablier-0.2.2.tar.gz/sablier-0.2.2/sablier.py | 0.745676 | 0.41745 | sablier.py | pypi |
import math
import matplotlib.pyplot as plt
from .Generaldistribution import Distribution
class Gaussian(Distribution):
""" Gaussian distribution class for calculating and
visualizing a Gaussian distribution.
Attributes:
mean (float) representing the mean value of the distribution
stdev (float) representing ... | /saboohi_dsnd-0.1.tar.gz/saboohi_dsnd-0.1/saboohi_dsnd/Gaussiandistribution.py | 0.688364 | 0.853058 | Gaussiandistribution.py | pypi |
# SABRmetrics
<div>
<a href="https://github.com/JacobLee23/SABRmetrics/blob/master/LICENSE" target="_blank">
<img src="https://img.shields.io/github/license/JacobLee23/SABRmetrics" alt="LICENSE">
</a>
<img src="https://img.shields.io/pypi/pyversions/SABRmetrics" alt="PyPI - Python Version">
<a href="https:... | /sabrmetrics-0.5.3.tar.gz/sabrmetrics-0.5.3/README.md | 0.41478 | 0.914977 | README.md | pypi |
# SACAD
## Smart Automatic Cover Art Downloader
[](https://pypi.python.org/pypi/sacad/)
[](https://aur.archlinux.org/packages/sacad/)
[:
pass
class InvalidOption(Exception):
pass
class SACADA(object):
"""SACADA boards Python interface
Right now it just implements support for SACADA Mini using SCPI
over USB-CDC. The p... | /sacada-python-0.0.7.tar.gz/sacada-python-0.0.7/sacada/SACADA.py | 0.800848 | 0.224757 | SACADA.py | pypi |
# Creating a SACC file with the library
In this example we will make a Sacc data file using simulated data from CCL, the Core Cosmology Library.
```
pylab inline
import sacc
import pyccl as ccl
import datetime
import time
```
# Getting input data
We will make some fake window ranges and data vectors from theory p... | /sacc-0.12.tar.gz/sacc-0.12/examples/Create_Sacc.ipynb | 0.672117 | 0.934873 | Create_Sacc.ipynb | pypi |
# SACC file for CMB and LSS data
This example shows how to use the different functionality in SACC to write data from LSS-like and CMB-like experiments.
```
import sacc
import pyccl as ccl
import numpy as np
import matplotlib.pyplot as plt
```
## Generate the data
We will first use CCL to generate some data. This wil... | /sacc-0.12.tar.gz/sacc-0.12/examples/CMB_LSS_write.ipynb | 0.583085 | 0.966379 | CMB_LSS_write.ipynb | pypi |
# Reading a SACC file with CMB and LSS data
This example shows how to read LSS and CMB-like data from a SACC file. You should run the `CMB_LSS_write` notebook before this one in order to have some data to read!
```
import sacc
import numpy as np
import matplotlib.pyplot as plt
```
## Reading the data
This is as simpl... | /sacc-0.12.tar.gz/sacc-0.12/examples/CMB_LSS_read.ipynb | 0.463201 | 0.975693 | CMB_LSS_read.ipynb | pypi |
# SACC with clusters
The default SACC scripts in the directory above show how one can make a SACC object for a 3x2 point analysis. The constructor for a SACC object has additional fields for handling clusters. This notebook details how one can use those fields to create/load/split a SACC that has cluster information.
... | /sacc-0.12.tar.gz/sacc-0.12/examples/SACC_for_clusters.ipynb | 0.513912 | 0.92421 | SACC_for_clusters.ipynb | pypi |
```
import sacc
import numpy as np
import matplotlib.pyplot as plt
```
# Read SACC files
This notebook illustrates how to read and interpret data from a SACC file.
We will read the BK15 data we wrote into SACC format in SACC_write.ipynb (so run that notebook first!).
Reading the file is as simple as:
```
# First, ... | /sacc-0.12.tar.gz/sacc-0.12/examples/SACC_read.ipynb | 0.406744 | 0.974749 | SACC_read.ipynb | pypi |
================
saccademodel-py
================
A least-squares optimal offline method to find saccadic reaction time and saccade duration from tracked gaze points.
You have tracked the gaze points of the following event sequence:
1. A person looks at point (A). An image appears at (B).
2. The person reacts to the... | /saccademodel-0.1.0.tar.gz/saccademodel-0.1.0/README.rst | 0.89358 | 0.717198 | README.rst | pypi |
import numpy as np
import os
import joblib
import logging
class Perceptron:
# constructor
def __init__(self,eta:float=None, epochs:int=None):
self.weights = np.random.random(3) * 1e-4 #small random weights
training = (eta is not None) and (epochs is not None)
if training:
... | /sachin_pkg-Sachinsen1295-0.0.3.tar.gz/sachin_pkg-Sachinsen1295-0.0.3/src/sachin/perceptron.py | 0.557604 | 0.253081 | perceptron.py | pypi |
import re
from functools import lru_cache
from .tokenizer_base import BaseTokenizer
def _normalize_general_and_western(sent: str) -> str:
# language-independent (general) part
# strip end-of-line hyphenation and join lines
sent = re.sub(r"\n-", "", sent)
# join lines
sent = re.sub(r"\n", " ",... | /sacrebleu_macrof-2.0.1-py3-none-any.whl/sacrebleu/tokenizers/tokenizer_ter.py | 0.685844 | 0.385895 | tokenizer_ter.py | pypi |
from typing import List, Sequence, Optional, Dict
from collections import Counter
from ..utils import sum_of_lists
from .base import Score, Signature, Metric
from .helpers import extract_all_char_ngrams, extract_word_ngrams
class CHRFSignature(Signature):
"""A convenience class to represent the reproducibility ... | /sacrebleu_macrof-2.0.1-py3-none-any.whl/sacrebleu/metrics/chrf.py | 0.961416 | 0.396652 | chrf.py | pypi |
from collections import Counter
from typing import List, Tuple
def extract_all_word_ngrams(line: str, min_order: int, max_order: int) -> Tuple[Counter, int]:
"""Extracts all ngrams (min_order <= n <= max_order) from a sentence.
:param line: A string sentence.
:param min_order: Minimum n-gram order.
... | /sacrebleu_macrof-2.0.1-py3-none-any.whl/sacrebleu/metrics/helpers.py | 0.93117 | 0.624007 | helpers.py | pypi |
import math
import logging
from importlib import import_module
from typing import List, Sequence, Optional, Dict, Any
from ..utils import my_log, sum_of_lists
from .base import Score, Signature, Metric
from .helpers import extract_all_word_ngrams
sacrelogger = logging.getLogger('sacrebleu')
# The default for the m... | /sacrebleu_macrof-2.0.1-py3-none-any.whl/sacrebleu/metrics/bleu.py | 0.902037 | 0.236527 | bleu.py | pypi |
from __future__ import print_function
import os
import sys
import numpy as np
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.utils import to_categorical
from keras.layers import Dense, Input, Flatten
from keras.layers import Conv1D, MaxPooling1D, Embedd... | /sacred-nbextension-0.1.0.tar.gz/sacred-nbextension-0.1.0/deep-dostoewskiy/pretrained_word_embeddings.py | 0.555676 | 0.291226 | pretrained_word_embeddings.py | pypi |
# In[1]:
'''Train a simple deep CNN on the CIFAR10 small images dataset.
GPU run command with Theano backend (with TensorFlow, the GPU is automatically used):
THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatx=float32 python cifar10_cnn.py
It gets down to 0.65 test logloss in 25 epochs, and down to 0.55 after 50 epochs... | /sacred-nbextension-0.1.0.tar.gz/sacred-nbextension-0.1.0/deep-dostoewskiy/Untitled2.py | 0.90808 | 0.590838 | Untitled2.py | pypi |
# In[2]:
"""VGG16 model for Keras.
# Reference
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://arxiv.org/abs/1409.1556)
"""
from __future__ import print_function
from __future__ import absolute_import
import warnings
from keras.models import Model
from keras.layers import Flatten,... | /sacred-nbextension-0.1.0.tar.gz/sacred-nbextension-0.1.0/deep-dostoewskiy/Untitled3.py | 0.952673 | 0.727431 | Untitled3.py | pypi |
# In[8]:
'''Trains a simple convnet on the MNIST dataset.
Gets to 99.25% test accuracy after 12 epochs
(there is still a lot of margin for parameter tuning).
16 seconds per epoch on a GRID K520 GPU.
'''
from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Seque... | /sacred-nbextension-0.1.0.tar.gz/sacred-nbextension-0.1.0/deep-dostoewskiy/keras-mnis.py | 0.873201 | 0.637115 | keras-mnis.py | pypi |
# sacred-tui 
ASCII art import and terminal graphics made simple.
Let's say you want something like this in your script:
```
_____________________________,----,__
|==============================<| /___\ ____,------... | /sacred_tui-0.2.1.tar.gz/sacred_tui-0.2.1/README.md | 0.802633 | 0.716677 | README.md | pypi |
try: # Python3
from itertools import zip_longest
except ImportError: # Python2
from itertools import izip_longest as zip_longest
from xml.sax.saxutils import escape, unescape
from joblib import Parallel, delayed
from tqdm import tqdm
class CJKChars(object):
"""
An object that enumerates the code ... | /sacremoses_xt-0.0.44-py3-none-any.whl/sacremoses/util.py | 0.671578 | 0.365825 | util.py | pypi |
import re
import regex
from six import text_type
from itertools import chain
class MosesPunctNormalizer:
"""
This is a Python port of the Moses punctuation normalizer from
https://github.com/moses-smt/mosesdecoder/blob/master/scripts/tokenizer/normalize-punctuation.perl
"""
EXTRA_WHITESPACE = [... | /sacremoses_xt-0.0.44-py3-none-any.whl/sacremoses/normalize.py | 0.567337 | 0.407216 | normalize.py | pypi |
import os
import pkgutil
class Perluniprops:
"""
This class is used to read lists of characters from the Perl Unicode
Properties (see http://perldoc.perl.org/perluniprops.html).
The files in the perluniprop.zip are extracted using the Unicode::Tussle
module from http://search.cpan.org/~bdfoy/Unic... | /sacremoses_xt-0.0.44-py3-none-any.whl/sacremoses/corpus.py | 0.599602 | 0.330958 | corpus.py | pypi |
import os
from functools import partial
# gbk <-> big5 mappings from Mafan + Jianfan
# https://github.com/hermanschaaf/mafan
# https://code.google.com/archive/p/python-jianfan/
simplified_chinese = gbk = u"\u9515\u7691\u853c\u788d\u7231\u55f3\u5ad2\u7477\u66a7\u972d\u8c19\u94f5\u9e4c\u80ae\u8884\u5965\u5aaa\u9a9c\u9... | /sacremoses_xt-0.0.44-py3-none-any.whl/sacremoses/chinese.py | 0.436982 | 0.150216 | chinese.py | pypi |
import re
from six import text_type
from sacremoses.corpus import Perluniprops
from sacremoses.corpus import NonbreakingPrefixes
from sacremoses.util import is_cjk
perluniprops = Perluniprops()
nonbreaking_prefixes = NonbreakingPrefixes()
class MosesSentTokenizer(object):
"""
This is a Python port of the ... | /sacremoses_xt-0.0.44-py3-none-any.whl/sacremoses/sent_tokenize.py | 0.488527 | 0.167797 | sent_tokenize.py | pypi |
# Sacremoses
[](https://travis-ci.org/alvations/sacremoses)
[](https://ci.appveyor.com/project/alvations/sacremoses)
# License
MIT License.
# Install
``... | /sacremoses-0.0.53.tar.gz/sacremoses-0.0.53/README.md | 0.556882 | 0.727564 | README.md | pypi |
import datetime
import time
from .interfaces import ITimeZone
from zope.interface import implementer
from zope.component import queryUtility
ZERO = datetime.timedelta(seconds=0)
def is_dst(dt):
"""Return True or False depending of tm_isdst value
Convert dt in timestamp, and get time object with this time... | /sact.epoch-1.3.0.tar.gz/sact.epoch-1.3.0/src/sact/epoch/timezone.py | 0.82108 | 0.395426 | timezone.py | pypi |
import datetime
from typing import Any, Dict, List, Optional, Union
import httpx
from ...client import Client
from ...models.get_object_consumption_response_200_item import GetObjectConsumptionResponse200Item
from ...types import UNSET, Response, Unset
def _get_kwargs(
*,
client: Client,
o_eic: str,
... | /sadales-tikls-m2m-1.0.0.tar.gz/sadales-tikls-m2m-1.0.0/sadales_tikls_m2m_api_client/api/default/get_object_consumption.py | 0.81841 | 0.231093 | get_object_consumption.py | pypi |
from typing import Any, Dict, List, Type, TypeVar
import attr
from ..models.error_invalid_params_item import ErrorInvalidParamsItem
T = TypeVar("T", bound="Error")
@attr.s(auto_attribs=True)
class Error:
""" """
title: str
invalid_params: List[ErrorInvalidParamsItem]
additional_properties: Dict[st... | /sadales-tikls-m2m-1.0.0.tar.gz/sadales-tikls-m2m-1.0.0/sadales_tikls_m2m_api_client/models/error.py | 0.749912 | 0.192748 | error.py | pypi |
<!-- markdownlint-disable -->
<h2 align="center" style="font-family:verdana;font-size:150%"> <b>S</b>equencing <b>A</b>nalysis and <b>D</b>ata Library for <b>I</b>mmunoinformatics <b>E</b>xploration</h2>
<div align="center">
<img src="https://sadiestaticcrm.s3.us-west-2.amazonaws.com/Sadie.svg" alt="SADIE" style="ma... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/README.md | 0.458349 | 0.725746 | README.md | pypi |
import re
from functools import lru_cache
from typing import Any, List, Optional, Set, Union
from uuid import UUID, uuid4
from Bio.Seq import Seq
from pandas._libs.missing import NAType
from pydantic import BaseModel, validator
@lru_cache(maxsize=1)
def get_nt_validator_regex() -> Any:
return re.compile(r"^[ACNT... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/receptor/rearrangment.py | 0.897936 | 0.481027 | rearrangment.py | pypi |
scheme_numbering = {
"imgt": {
"heavy": {
"imgt": {
"fwr1_aa_start": 1,
"fwr1_aa_end": 26,
"cdr1_aa_start": 27,
"cdr1_aa_end": 38,
"fwr2_aa_start": 39,
"fwr2_aa_end": 55,
"cdr2_aa_star... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/numbering/scheme_numbering.py | 0.411466 | 0.393094 | scheme_numbering.py | pypi |
from __future__ import annotations
import logging
import re
from typing import Any, Iterable, List, Optional, Union
import numpy as np
import numpy.typing as npt
import pandas as pd
from Levenshtein import distance as lev_distance
from sklearn.cluster import AgglomerativeClustering
from sklearn.metrics import pairwis... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/cluster/cluster.py | 0.907975 | 0.422147 | cluster.py | pypi |
import logging
from ast import literal_eval
import pandas as pd
from numpy import nan
from sadie.numbering.scheme_numbering import scheme_numbering
from .constants import NUMBERING_RESULTS
logger = logging.getLogger("NUMBERING")
class NumberingResults(pd.DataFrame):
def __init__(self, *args, scheme="", region... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/renumbering/result.py | 0.863809 | 0.290713 | result.py | pypi |
from collections import UserString
from typing import Callable, Generator
from pydantic.fields import ModelField
# TODO: go through and see which are viable to use; tests need to be fixed first in test_g3 to handle this
SPECIES = {
"rhesus": "macaque",
"homo_sapiens": "human",
"mus": "mouse",
"rattus_... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/typing/species.py | 0.401336 | 0.403802 | species.py | pypi |
from __future__ import annotations
import warnings
from pathlib import Path
from typing import Optional, Set
from sadie.airr.igblast.igblast import ensure_prefix_to
# package/module level
from sadie.reference import YamlRef
class GermlineData:
"""
The germline data paths are extremely cumbersome to workwit... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/airr/igblast/germline.py | 0.850903 | 0.210219 | germline.py | pypi |
import datetime
from typing import Dict, List, Union
from Bio.Seq import Seq
from Bio.SeqFeature import FeatureLocation, SeqFeature
from Bio.SeqRecord import SeqRecord
# Qualifier Dictionary
example_qualifiers_dict = {
"gene": "gene",
"latin": "latin",
"organism": "species",
"functional": "functional"... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/airr/airrtable/genbank.py | 0.827932 | 0.335052 | genbank.py | pypi |
from typing import Any, Dict
IGBLAST_AIRR: Dict[Any, str] = {
"sequence_id": "object",
"sequence": "object",
"locus": "object",
"stop_codon": "object",
"vj_in_frame": "object",
"v_frameshift": "object",
"productive": "object",
"rev_comp": "object",
"complete_vdj": "object",
"seq... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/airr/airrtable/constants.py | 0.723895 | 0.350644 | constants.py | pypi |
from __future__ import annotations
from pathlib import Path
from typing import Any, Dict, List, Set, Type
import pandas as pd
from yaml import load
try:
from yaml import CLoader, Loader
cload: Type[CLoader] | Type[Loader] = CLoader
except ImportError:
from yaml import Loader
cload = Loader
class ... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/reference/yaml.py | 0.926959 | 0.325923 | yaml.py | pypi |
from typing import Dict, List
from pydantic import BaseModel, validator
class Species(BaseModel):
"""What species to retrieve"""
species: str
class Source(BaseModel):
"""What database to retrieve"""
source: str
class GeneEntry(BaseModel):
"""V,D or J Gene Entry with validation"""
speci... | /sadie_antibody-1.0.2.tar.gz/sadie_antibody-1.0.2/src/sadie/reference/models.py | 0.90957 | 0.45302 | models.py | pypi |
from collections import deque
from unittest.mock import Mock
class MockTmpFile(object):
_fn = None
def __init__(self, suffix = None, prefix = None, dir = None, remove = False):
if suffix is None:
suffix = '.mock'
if prefix is None:
prefix = __name__
if dir is None:
dir = '/tmp'
self._fn = '/'.join... | /sadm-0.21.tar.gz/sadm-0.21/tlib/_sadmtest/mock/utils/sh.py | 0.461988 | 0.172939 | sh.py | pypi |
import matplotlib.pyplot as plt
import numpy as np
import .plotHelper as pH
try:
plt.style.use('scientific_grid_no_space')
except:
pass
# -------------------------------------------------------------------------
# Modular plotting functions
# ---------------------------------------------------------------------... | /sadtools-0.0.2-py3-none-any.whl/analysis/plotting.py | 0.76856 | 0.63324 | plotting.py | pypi |
import numpy as np
from scipy.interpolate import splrep, splev
import math
# -------------------------------------------------------------------------
# Grid functions
# -------------------------------------------------------------------------
def create_grid(x_range, y_range, num_x_points=50, num_y_points=50):
# U... | /sadtools-0.0.2-py3-none-any.whl/utilities/numerics.py | 0.709824 | 0.517205 | numerics.py | pypi |
import numpy as np
import utilities as util
import astropy.units as u
# -------------------------------------------------------------------------
# Derived Units
# -------------------------------------------------------------------------
cm3 = u.cm**3
dm3 = u.dm**3
m3 = u.m**3
g_cm3 = (u.g / cm3)
molar = u.mol / dm3
... | /sadtools-0.0.2-py3-none-any.whl/utilities/chemistryUtilities.py | 0.803868 | 0.427994 | chemistryUtilities.py | pypi |
from argparse import ArgumentParser, BooleanOptionalAction, Namespace
from os.path import expanduser
from sys import stdout
from uuid import UUID
from .cli import CLI
from .version import VERSION
def parse_args() -> Namespace:
parser = ArgumentParser(
prog="Safari Bookmarks CLI",
description="A u... | /safari_bookmarks_cli-0.2.0-py3-none-any.whl/safaribookmarks/main.py | 0.490968 | 0.228641 | main.py | pypi |
from contextlib import contextmanager
import plistlib
from typing import Generator, IO, Optional
import uuid
from .helpers import load, dump
from .models import WebBookmarkType, WebBookmarkTypeList, WebBookmarkTypeLeaf, WebBookmarkTypeProxy
DEFAULT_LIST_FORMAT = "{prefix: <{depth}}{title: <50}{type: <6}{id: <38}{url}"... | /safari_bookmarks_cli-0.2.0-py3-none-any.whl/safaribookmarks/cli.py | 0.708313 | 0.185947 | cli.py | pypi |
import abc
from typing import Tuple, Union
import numpy as np
import scipy.integrate
import scipy.spatial
from pydantic import BaseModel
class BaseEntityValidator(BaseModel):
"""
Validator for BaseEntity's config member.
Parameters
----------
name : str
Name of entity
"""
name: s... | /safe-autonomy-dynamics-1.0.1.tar.gz/safe-autonomy-dynamics-1.0.1/safe_autonomy_dynamics/base_models.py | 0.933089 | 0.511961 | base_models.py | pypi |
import abc
from typing import Tuple
import numpy as np
from safe_autonomy_dynamics.base_models import BaseEntity, BaseEntityValidator, BaseLinearODESolverDynamics
M_DEFAULT = 1
DAMPING_DEFAULT = 0
class BaseIntegratorValidator(BaseEntityValidator):
"""
Validator for Integrator kwargs.
Parameters
-... | /safe-autonomy-dynamics-1.0.1.tar.gz/safe-autonomy-dynamics-1.0.1/safe_autonomy_dynamics/integrators.py | 0.934939 | 0.381853 | integrators.py | pypi |
import math
from typing import Union
import numpy as np
from scipy.spatial.transform import Rotation
from safe_autonomy_dynamics.base_models import BaseEntityValidator, BaseODESolverDynamics, BaseRotationEntity
from safe_autonomy_dynamics.cwh import M_DEFAULT, N_DEFAULT, generate_cwh_matrices
INERTIA_DEFAULT = 0.057... | /safe-autonomy-dynamics-1.0.1.tar.gz/safe-autonomy-dynamics-1.0.1/safe_autonomy_dynamics/cwh/rotational_model.py | 0.922124 | 0.54056 | rotational_model.py | pypi |
from typing import Union
import numpy as np
from scipy.spatial.transform import Rotation
from safe_autonomy_dynamics.base_models import BaseEntityValidator, BaseODESolverDynamics, BaseRotationEntity
from safe_autonomy_dynamics.cwh import generate_cwh_matrices
from safe_autonomy_dynamics.utils import number_list_to_np... | /safe-autonomy-dynamics-1.0.1.tar.gz/safe-autonomy-dynamics-1.0.1/safe_autonomy_dynamics/cwh/sixdof_model.py | 0.935678 | 0.568775 | sixdof_model.py | pypi |
from typing import Tuple
import numpy as np
from scipy.spatial.transform import Rotation
from safe_autonomy_dynamics.base_models import BaseEntity, BaseEntityValidator, BaseLinearODESolverDynamics
M_DEFAULT = 12
N_DEFAULT = 0.001027
class CWHSpacecraftValidator(BaseEntityValidator):
"""
Validator for CWHSp... | /safe-autonomy-dynamics-1.0.1.tar.gz/safe-autonomy-dynamics-1.0.1/safe_autonomy_dynamics/cwh/point_model.py | 0.961043 | 0.643413 | point_model.py | pypi |
__title__ = 'safe-cast'
__version__ = '0.3.4'
__version_info__ = tuple(__version__.split('.'))
__author__ = 'jefft@tune.com'
__license__ = 'MIT License'
__copyright__ = 'Copyright 2018 TUNE, Inc.'
import numpy
def safe_cast(val, to_type, default=None):
"""Safely cast a value to type, and if failed, returned de... | /safe_cast-0.3.4-py3-none-any.whl/safe_cast/__init__.py | 0.858021 | 0.354964 | __init__.py | pypi |
[](https://badge.fury.io/py/safe-cli)
[](https://github.com/gnosis/safe-cli/actions/workflows/python.yml)
[![Coverage Status](https://coveralls.io/repos/github/gnosis/safe-cli/... | /safe_cli-0.7.1.tar.gz/safe_cli-0.7.1/README.md | 0.432063 | 0.942507 | README.md | pypi |
from prompt_toolkit.formatted_text import HTML
SAFE_ARGUMENT_COLOR = "em"
SAFE_EMPTY_ARGUMENT_COLOR = "ansimagenta"
safe_commands_arguments = {
"add_delegate": "<address> <label> <signer-address>",
"add_owner": "<address> [--threshold <int>]",
"approve_hash": "<safe-tx-hash> <address>",
"balances": "... | /safe_cli-0.7.1.tar.gz/safe_cli-0.7.1/safe_cli/safe_completer_constants.py | 0.4436 | 0.252565 | safe_completer_constants.py | pypi |
from typing import Optional
from hexbytes import HexBytes
from prompt_toolkit import HTML, print_formatted_text
from gnosis.eth.constants import NULL_ADDRESS
from gnosis.safe import InvalidInternalTx, SafeOperation, SafeTx
from safe_cli.utils import yes_or_no_question
from .safe_operator import SafeOperator, SafeSe... | /safe_cli-0.7.1.tar.gz/safe_cli-0.7.1/safe_cli/operators/safe_relay_operator.py | 0.8874 | 0.162979 | safe_relay_operator.py | pypi |
from typing import TypedDict
from urllib.parse import urljoin
import requests
from eth_typing import ChecksumAddress, HexStr
from gnosis.eth.ethereum_client import EthereumNetwork
from gnosis.safe import SafeTx
from gnosis.safe.signatures import signature_split
from .base_api import BaseAPI, BaseAPIException
class... | /safe_cli-0.7.1.tar.gz/safe_cli-0.7.1/safe_cli/api/relay_service_api.py | 0.741206 | 0.225204 | relay_service_api.py | pypi |
import time
from typing import Any, Dict, List, Optional, Tuple
from urllib.parse import urljoin
import requests
from eth_account.signers.local import LocalAccount
from hexbytes import HexBytes
from web3 import Web3
from gnosis.eth.ethereum_client import EthereumNetwork
from gnosis.safe import SafeTx
from .base_api ... | /safe_cli-0.7.1.tar.gz/safe_cli-0.7.1/safe_cli/api/transaction_service_api.py | 0.718693 | 0.277791 | transaction_service_api.py | pypi |
Undefined = object()
def safe_cmp(a, b, _nan_is_eq=False):
""" Python 2 compatible ``cmp`` function.
See also: https://github.com/python/cpython/blob/2.7/Objects/object.c#L768
Note: the ``_nan_is_eq`` argument is required to ensure that sorting is
consistent (ie, where ``nan`` does not mo... | /safe_cmp-0.1.1.tar.gz/safe_cmp-0.1.1/safe_cmp/safe_cmp.py | 0.80406 | 0.423339 | safe_cmp.py | pypi |
from safeds.data.tabular.containers import Table
from safeds.exceptions import UnknownColumnNameError
class ExampleTable(Table):
"""
A `Table` with descriptions for its columns.
Parameters
----------
table : Table
The table.
column_descriptions : dict[str, str]
A dictionary ma... | /safe_ds_examples-0.15.0.tar.gz/safe_ds_examples-0.15.0/src/safeds_examples/tabular/containers/_example_table.py | 0.910404 | 0.546315 | _example_table.py | pypi |
from pathlib import Path
from safeds.data.tabular.containers import Table
from safeds_examples.tabular.containers import ExampleTable
_path = Path(__file__).parent / "data" / "house_sales.csv"
def load_house_sales() -> ExampleTable:
"""
Load the "House Sales" dataset.
Returns
-------
ExampleTa... | /safe_ds_examples-0.15.0.tar.gz/safe_ds_examples-0.15.0/src/safeds_examples/tabular/_house_sales/_house_sales.py | 0.855097 | 0.49762 | _house_sales.py | pypi |
from __future__ import annotations
import copy
import io
import warnings
from pathlib import Path
from typing import Any, BinaryIO
import numpy as np
import PIL
from PIL import ImageEnhance, ImageFilter, ImageOps
from PIL.Image import Image as PillowImage
from PIL.Image import open as open_image
from skimage.util imp... | /safe_ds-0.15.0.tar.gz/safe_ds-0.15.0/src/safeds/data/image/containers/_image.py | 0.951431 | 0.563678 | _image.py | pypi |
from __future__ import annotations
import copy
import functools
import io
import warnings
from pathlib import Path
from typing import TYPE_CHECKING, Any, TypeVar
import Levenshtein
import matplotlib.pyplot as plt
import numpy as np
import openpyxl
import pandas as pd
import seaborn as sns
from pandas import DataFrame... | /safe_ds-0.15.0.tar.gz/safe_ds-0.15.0/src/safeds/data/tabular/containers/_table.py | 0.863794 | 0.346154 | _table.py | pypi |
from __future__ import annotations
import copy
from typing import TYPE_CHECKING
from safeds.data.tabular.containers import Column, Row, Table
from safeds.exceptions import (
ColumnIsTargetError,
IllegalSchemaModificationError,
UnknownColumnNameError,
)
if TYPE_CHECKING:
from collections.abc import Ca... | /safe_ds-0.15.0.tar.gz/safe_ds-0.15.0/src/safeds/data/tabular/containers/_tagged_table.py | 0.932974 | 0.430088 | _tagged_table.py | pypi |
from __future__ import annotations
import copy
import functools
from collections.abc import Callable, Mapping
from typing import TYPE_CHECKING, Any
import pandas as pd
from safeds.data.tabular.typing import ColumnType, Schema
from safeds.exceptions import UnknownColumnNameError
if TYPE_CHECKING:
from collection... | /safe_ds-0.15.0.tar.gz/safe_ds-0.15.0/src/safeds/data/tabular/containers/_row.py | 0.94353 | 0.529993 | _row.py | pypi |
from __future__ import annotations
import copy
import io
from collections.abc import Sequence
from numbers import Number
from typing import TYPE_CHECKING, Any, TypeVar, overload
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from safeds.data.image.containers import Image... | /safe_ds-0.15.0.tar.gz/safe_ds-0.15.0/src/safeds/data/tabular/containers/_column.py | 0.947442 | 0.426262 | _column.py | pypi |
from __future__ import annotations
from sklearn.preprocessing import KBinsDiscretizer as sk_KBinsDiscretizer
from safeds.data.tabular.containers import Table
from safeds.data.tabular.transformation._table_transformer import TableTransformer
from safeds.exceptions import (
ClosedBound,
NonNumericColumnError,
... | /safe_ds-0.15.0.tar.gz/safe_ds-0.15.0/src/safeds/data/tabular/transformation/_discretizer.py | 0.962027 | 0.522811 | _discretizer.py | pypi |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.