repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/utils/diff_formats/change_extractor.py | transcript-fixer/scripts/utils/diff_formats/change_extractor.py | #!/usr/bin/env python3
"""
Change extraction and summarization
SINGLE RESPONSIBILITY: Extract and summarize changes between text versions
"""
from __future__ import annotations
import difflib
from .text_splitter import split_into_words
def extract_changes(original: str, fixed: str) -> list[dict]:
"""
Extr... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/utils/diff_formats/markdown_format.py | transcript-fixer/scripts/utils/diff_formats/markdown_format.py | #!/usr/bin/env python3
"""
Markdown report generator
SINGLE RESPONSIBILITY: Generate detailed Markdown comparison report
"""
from __future__ import annotations
from datetime import datetime
from pathlib import Path
from .change_extractor import extract_changes, generate_change_summary
def generate_markdown_report... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/examples/bulk_import.py | transcript-fixer/scripts/examples/bulk_import.py | #!/usr/bin/env python3
"""
Example: Bulk Import Corrections to SQLite Database
This script demonstrates how to import corrections from various sources
into the transcript-fixer SQLite database.
Usage:
uv run scripts/examples/bulk_import.py
"""
from pathlib import Path
from core import CorrectionRepository, Corre... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/correction_service.py | transcript-fixer/scripts/core/correction_service.py | #!/usr/bin/env python3
"""
Correction Service - Business Logic Layer
SINGLE RESPONSIBILITY: Implement business rules and validation
Orchestrates repository operations with comprehensive validation,
error handling, and business logic enforcement.
"""
from __future__ import annotations
import re
import os
import logg... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/dictionary_processor.py | transcript-fixer/scripts/core/dictionary_processor.py | #!/usr/bin/env python3
"""
Dictionary Processor - Stage 1: Dictionary-based Text Corrections
SINGLE RESPONSIBILITY: Apply dictionary and regex-based corrections to text
Features:
- Apply simple dictionary replacements
- Apply context-aware regex rules
- Track all changes for history
- Case-sensitive and insensitive m... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/ai_processor_async.py | transcript-fixer/scripts/core/ai_processor_async.py | #!/usr/bin/env python3
"""
AI Processor with Async/Parallel Support - Stage 2: AI-powered Text Corrections
ENHANCEMENT: Process chunks in parallel for 5-10x speed improvement on large files
Key improvements over ai_processor.py:
- Asyncio-based parallel chunk processing
- Configurable concurrency limit (default: 5 co... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/learning_engine.py | transcript-fixer/scripts/core/learning_engine.py | #!/usr/bin/env python3
"""
Learning Engine - Pattern Detection from Correction History
SINGLE RESPONSIBILITY: Analyze history and suggest new corrections
Features:
- Analyze correction history for patterns
- Detect frequently occurring corrections
- Calculate confidence scores
- Generate suggestions for user review
-... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/__init__.py | transcript-fixer/scripts/core/__init__.py | """
Core Module - Business Logic and Data Access
This module contains the core business logic for transcript correction:
- CorrectionRepository: Data access layer with ACID transactions
- CorrectionService: Business logic layer with validation
- DictionaryProcessor: Stage 1 dictionary-based corrections
- AIProcessor: ... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/correction_repository.py | transcript-fixer/scripts/core/correction_repository.py | #!/usr/bin/env python3
"""
Correction Repository - SQLite Data Access Layer
SINGLE RESPONSIBILITY: Manage database operations with ACID guarantees
Thread-safe, transactional, and follows Repository pattern.
All database operations are atomic and properly handle errors.
"""
from __future__ import annotations
import ... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/change_extractor.py | transcript-fixer/scripts/core/change_extractor.py | #!/usr/bin/env python3
"""
Change Extractor - Extract Precise From→To Changes
CRITICAL FEATURE: Extract specific corrections from AI results for learning
This enables the learning loop:
1. AI makes corrections → Extract specific from→to pairs
2. High-frequency patterns → Auto-add to dictionary
3. Next run → Dictionar... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/connection_pool.py | transcript-fixer/scripts/core/connection_pool.py | #!/usr/bin/env python3
"""
Thread-Safe SQLite Connection Pool
CRITICAL FIX: Replaces unsafe check_same_thread=False pattern
ISSUE: Critical-1 in Engineering Excellence Plan
This module provides:
1. Thread-safe connection pooling
2. Proper connection lifecycle management
3. Timeout and limit enforcement
4. WAL mode fo... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/core/ai_processor.py | transcript-fixer/scripts/core/ai_processor.py | #!/usr/bin/env python3
"""
AI Processor - Stage 2: AI-powered Text Corrections
SINGLE RESPONSIBILITY: Process text using GLM API for intelligent corrections
Features:
- Split text into chunks for API processing
- Call GLM-4.6 for context-aware corrections
- Track AI-suggested changes
- Handle API errors gracefully
""... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/cli/argument_parser.py | transcript-fixer/scripts/cli/argument_parser.py | #!/usr/bin/env python3
"""
Argument Parser - CLI Argument Configuration
SINGLE RESPONSIBILITY: Configure command-line argument parsing
"""
from __future__ import annotations
import argparse
def create_argument_parser() -> argparse.ArgumentParser:
"""
Create and configure the argument parser for transcript-... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/cli/commands.py | transcript-fixer/scripts/cli/commands.py | #!/usr/bin/env python3
"""
CLI Commands - Command Handler Functions
SINGLE RESPONSIBILITY: Handle CLI command execution
All cmd_* functions take parsed args and execute the requested operation.
"""
from __future__ import annotations
import argparse
import os
import sys
from pathlib import Path
from core import (
... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/transcript-fixer/scripts/cli/__init__.py | transcript-fixer/scripts/cli/__init__.py | """
CLI Module - Command-Line Interface Handlers
This module contains command handlers and argument parsing:
- commands: Command handler functions (cmd_*)
- argument_parser: CLI argument configuration
"""
from .commands import (
cmd_init,
cmd_add_correction,
cmd_list_corrections,
cmd_run_correction,
... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/repomix-safe-mixer/scripts/scan_secrets.py | repomix-safe-mixer/scripts/scan_secrets.py | #!/usr/bin/env python3
"""
Security scanner for detecting hardcoded credentials in code.
Scans a directory for common credential patterns and reports findings.
"""
import os
import re
import sys
import json
from pathlib import Path
from typing import List, Dict, Tuple
# Common secret patterns (regex)
SECRET_PATTERNS... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/repomix-safe-mixer/scripts/safe_pack.py | repomix-safe-mixer/scripts/safe_pack.py | #!/usr/bin/env python3
"""
Safe packaging workflow for repomix.
Scans for secrets, reports findings, and optionally packs after user confirmation.
"""
import os
import sys
import subprocess
import json
from pathlib import Path
def run_secret_scan(directory: Path, exclude_patterns: list = None):
"""Run secret sca... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/markdown-tools/scripts/convert_path.py | markdown-tools/scripts/convert_path.py | #!/usr/bin/env python3
"""
Convert Windows paths to WSL format.
Usage:
python convert_path.py "C:\\Users\\username\\Downloads\\file.doc"
Output:
/mnt/c/Users/username/Downloads/file.doc
"""
import sys
import re
def convert_windows_to_wsl(windows_path: str) -> str:
"""
Convert a Windows path to WSL ... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/markdown-tools/scripts/extract_pdf_images.py | markdown-tools/scripts/extract_pdf_images.py | #!/usr/bin/env python3
"""
Extract images from PDF files using PyMuPDF.
Usage:
uv run --with pymupdf python extract_pdf_images.py <pdf_path> [output_dir]
Examples:
uv run --with pymupdf python extract_pdf_images.py document.pdf
uv run --with pymupdf python extract_pdf_images.py document.pdf ./assets
Outp... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/qa-expert/scripts/init_qa_project.py | qa-expert/scripts/init_qa_project.py | #!/usr/bin/env python3
"""
Initialize QA Project Structure
Creates complete QA testing infrastructure including documentation templates,
tracking CSVs, and baseline metrics for any software project.
Usage:
python scripts/init_qa_project.py <project-name> [output-dir]
Example:
python scripts/init_qa_project.p... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/qa-expert/scripts/calculate_metrics.py | qa-expert/scripts/calculate_metrics.py | #!/usr/bin/env python3
"""
Calculate QA Metrics
Analyzes TEST-EXECUTION-TRACKING.csv and generates quality metrics.
Usage:
python scripts/calculate_metrics.py <tracking-csv-path>
"""
import sys
import csv
from pathlib import Path
from collections import Counter
def calculate_metrics(csv_path):
"""Calculate ... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/skill-creator/scripts/quick_validate.py | skill-creator/scripts/quick_validate.py | #!/usr/bin/env python3
"""
Quick validation script for skills - minimal version
"""
import sys
import os
import re
from pathlib import Path
def find_path_references(content: str) -> list[str]:
"""
Extract path references from SKILL.md content.
Looks for patterns like scripts/xxx, references/xxx, assets/x... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/skill-creator/scripts/security_scan.py | skill-creator/scripts/security_scan.py | #!/usr/bin/env python3
"""
Security Scanner for Claude Code Skills
Validates skills before packaging to prevent secret leakage and security issues.
SINGLE RESPONSIBILITY: Validate skill security before distribution
ARCHITECTURE:
- Detection Layer: Gitleaks (secrets) + Pattern matching (code smells)
- Reporting Lay... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/skill-creator/scripts/init_skill.py | skill-creator/scripts/init_skill.py | #!/usr/bin/env python3
"""
Skill Initializer - Creates a new skill from template
Usage:
init_skill.py <skill-name> --path <path>
Examples:
init_skill.py my-new-skill --path skills/public
init_skill.py my-api-helper --path skills/private
init_skill.py custom-skill --path /custom/location
"""
import sy... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/skill-creator/scripts/package_skill.py | skill-creator/scripts/package_skill.py | #!/usr/bin/env python3
"""
Skill Packager - Creates a distributable zip file of a skill folder
Usage:
python utils/package_skill.py <path/to/skill-folder> [output-directory]
Example:
python utils/package_skill.py skills/public/my-skill
python utils/package_skill.py skills/public/my-skill ./dist
"""
impor... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/mermaid-tools/scripts/extract_diagrams.py | mermaid-tools/scripts/extract_diagrams.py | #!/usr/bin/env python3
"""
Extract Mermaid diagrams from markdown file and create numbered .mmd files
"""
import re
import sys
from pathlib import Path
def extract_mermaid_diagrams(markdown_file, output_dir):
"""Extract Mermaid diagrams from markdown file and create numbered .mmd files"""
try:
wi... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/pdf-creator/scripts/md_to_pdf.py | pdf-creator/scripts/md_to_pdf.py | #!/usr/bin/env python3
"""
Markdown to PDF converter with Chinese font support.
Converts markdown files to PDF using weasyprint, with proper Chinese typography.
Designed for formal documents (trademark filings, legal documents, reports).
Usage:
python md_to_pdf.py input.md output.pdf
python md_to_pdf.py input... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/pdf-creator/scripts/batch_convert.py | pdf-creator/scripts/batch_convert.py | #!/usr/bin/env python3
"""
Batch convert multiple markdown files to PDF.
Usage:
python batch_convert.py file1.md file2.md file3.md
python batch_convert.py *.md
python batch_convert.py --output-dir ./pdfs file1.md file2.md
Requirements:
pip install weasyprint markdown
"""
import argparse
import sys
fr... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/ppt-creator/scripts/chartkit.py | ppt-creator/scripts/chartkit.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
chartkit.py - Minimal chart renderer for ppt-creator
Usage:
python resources/scripts/chartkit.py \
--data path/to/data.csv \
--type line \
--x date \
--y sales profit \
--out output/assets \
--filename kpi_trend.png \
--title "Monthly KPIs... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/repomix-unmixer/scripts/unmix_repomix.py | repomix-unmixer/scripts/unmix_repomix.py | #!/usr/bin/env python3
"""Unmix a repomix file to restore original file structure.
Supports XML, Markdown, and JSON repomix output formats.
"""
import re
import os
import sys
import json
from pathlib import Path
def unmix_xml(content, output_dir):
"""Extract files from repomix XML format."""
# Pattern: <fil... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/video-comparer/scripts/compare.py | video-comparer/scripts/compare.py | #!/usr/bin/env python3
"""
Video Comparison Tool
Compare two videos (original vs compressed) and generate interactive HTML report.
Analyzes video metadata, quality metrics (PSNR/SSIM), and creates frame-by-frame
comparison UI with slider, side-by-side, and grid viewing modes.
Security features:
- Path validation and ... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | true |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/cloudflare-troubleshooting/scripts/check_cloudflare_config.py | cloudflare-troubleshooting/scripts/check_cloudflare_config.py | #!/usr/bin/env python3
"""
Comprehensive Cloudflare configuration checker.
This script diagnoses common Cloudflare issues including:
- SSL/TLS mode mismatches
- DNS configuration problems
- Cache settings
- Page rules and redirect loops
Requires:
- requests library
- Cloudflare API credentials (email + Global API Key... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/cloudflare-troubleshooting/scripts/fix_ssl_mode.py | cloudflare-troubleshooting/scripts/fix_ssl_mode.py | #!/usr/bin/env python3
"""
Fix Cloudflare SSL/TLS mode to resolve redirect loops.
This script changes the SSL mode to resolve common redirect loop issues
caused by SSL mode mismatches between Cloudflare and origin servers.
Common scenarios:
- GitHub Pages + Flexible mode → Change to Full
- Netlify/Vercel + Flexible m... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/cli-demo-generator/scripts/auto_generate_demo.py | cli-demo-generator/scripts/auto_generate_demo.py | #!/usr/bin/env python3
"""
Auto-generate CLI demos from command descriptions.
This script creates VHS tape files and generates GIF demos automatically.
"""
import argparse
import subprocess
import sys
from pathlib import Path
from typing import List, Optional
def create_tape_file(
commands: List[str],
outpu... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/cli-demo-generator/scripts/batch_generate.py | cli-demo-generator/scripts/batch_generate.py | #!/usr/bin/env python3
"""
Batch generate multiple CLI demos from a configuration file.
Supports YAML and JSON formats for defining multiple demos.
"""
import argparse
import json
import subprocess
import sys
from pathlib import Path
from typing import Dict, List
try:
import yaml
YAML_AVAILABLE = True
except... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/youtube-downloader/scripts/download_video.py | youtube-downloader/scripts/download_video.py | #!/usr/bin/env python3
"""
YouTube video downloader using yt-dlp with robust error handling.
This script handles common issues like nsig extraction failures and network problems,
especially useful for users behind proxies or in regions with YouTube access issues.
Requirements:
- yt-dlp: Install via `brew install ... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/claude-code-history-files-finder/scripts/analyze_sessions.py | claude-code-history-files-finder/scripts/analyze_sessions.py | #!/usr/bin/env python3
"""
Analyze Claude Code session files to find relevant sessions and statistics.
This script helps locate sessions containing specific keywords, analyze
session activity, and generate reports about session content.
"""
import json
import os
import sys
from pathlib import Path
from typing import ... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
daymade/claude-code-skills | https://github.com/daymade/claude-code-skills/blob/8b4a2ce8dc007cdd222a6fcde73338b82ea32459/claude-code-history-files-finder/scripts/recover_content.py | claude-code-history-files-finder/scripts/recover_content.py | #!/usr/bin/env python3
"""
Recover content from Claude Code history session files.
This script extracts Write tool calls, Edit operations, and text content
from Claude Code's JSONL session history files.
"""
import json
import sys
import os
from pathlib import Path
from typing import Dict, List, Any, Optional
from da... | python | MIT | 8b4a2ce8dc007cdd222a6fcde73338b82ea32459 | 2026-01-05T07:10:41.501036Z | false |
LukeDitria/CNN-VAE | https://github.com/LukeDitria/CNN-VAE/blob/c2e6419905660e617f9bb1e11af07e5affb49a30/RES_VAE.py | RES_VAE.py | import torch
import torch.nn as nn
import torch.utils.data
class ResDown(nn.Module):
"""
Residual down sampling block for the encoder
"""
def __init__(self, channel_in, channel_out, kernel_size=3):
super(ResDown, self).__init__()
self.conv1 = nn.Conv2d(channel_in, channel_out // 2, ke... | python | MIT | c2e6419905660e617f9bb1e11af07e5affb49a30 | 2026-01-05T07:10:39.877153Z | false |
LukeDitria/CNN-VAE | https://github.com/LukeDitria/CNN-VAE/blob/c2e6419905660e617f9bb1e11af07e5affb49a30/RES_VAE_64_old.py | RES_VAE_64_old.py | import torch
import torch.nn as nn
import torch.utils.data
import torch.nn.functional as F
#Residual down sampling block for the encoder
#Average pooling is used to perform the downsampling
class Res_down(nn.Module):
def __init__(self, channel_in, channel_out, scale = 2):
super(Res_down, self).__init__()
... | python | MIT | c2e6419905660e617f9bb1e11af07e5affb49a30 | 2026-01-05T07:10:39.877153Z | false |
LukeDitria/CNN-VAE | https://github.com/LukeDitria/CNN-VAE/blob/c2e6419905660e617f9bb1e11af07e5affb49a30/Helpers.py | Helpers.py | import torch.nn.functional as F
def kl_loss(mu, logvar):
return -0.5 * (1 + logvar - mu.pow(2) - logvar.exp()).mean() | python | MIT | c2e6419905660e617f9bb1e11af07e5affb49a30 | 2026-01-05T07:10:39.877153Z | false |
LukeDitria/CNN-VAE | https://github.com/LukeDitria/CNN-VAE/blob/c2e6419905660e617f9bb1e11af07e5affb49a30/train_vae.py | train_vae.py | import torch
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
import torchvision.datasets as Datasets
import torchvision.transforms as transforms
import torch.nn.functional as F
import torchvision.utils as vutils
import os
import shutil
from tqdm import trange, tqdm
from collections import ... | python | MIT | c2e6419905660e617f9bb1e11af07e5affb49a30 | 2026-01-05T07:10:39.877153Z | false |
LukeDitria/CNN-VAE | https://github.com/LukeDitria/CNN-VAE/blob/c2e6419905660e617f9bb1e11af07e5affb49a30/vgg19.py | vgg19.py | import torch.nn as nn
import torch
class VGG19(nn.Module):
"""
Simplified version of the VGG19 "feature" block
This module's only job is to return the "feature loss" for the inputs
"""
def __init__(self, channel_in=3, width=64):
super(VGG19, self).__init__()
self.conv1 = nn.Con... | python | MIT | c2e6419905660e617f9bb1e11af07e5affb49a30 | 2026-01-05T07:10:39.877153Z | false |
LukeDitria/CNN-VAE | https://github.com/LukeDitria/CNN-VAE/blob/c2e6419905660e617f9bb1e11af07e5affb49a30/RES_VAE_Dynamic.py | RES_VAE_Dynamic.py | import torch
import torch.nn as nn
import torch.utils.data
def get_norm_layer(channels, norm_type="bn"):
if norm_type == "bn":
return nn.BatchNorm2d(channels, eps=1e-4)
elif norm_type == "gn":
return nn.GroupNorm(8, channels, eps=1e-4)
else:
ValueError("norm_type must be bn or gn")... | python | MIT | c2e6419905660e617f9bb1e11af07e5affb49a30 | 2026-01-05T07:10:39.877153Z | false |
gbaydin/hypergradient-descent | https://github.com/gbaydin/hypergradient-descent/blob/020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16/train.py | train.py | import traceback
import argparse
import sys
import os
import csv
import time
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
from torchvision import datasets, transforms
import vgg
from torch.utils.data import DataLoader
from torch.optim import SGD, Adam
from hype... | python | MIT | 020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16 | 2026-01-05T07:10:43.134916Z | false |
gbaydin/hypergradient-descent | https://github.com/gbaydin/hypergradient-descent/blob/020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16/vgg.py | vgg.py | '''
Modified from https://github.com/pytorch/vision.git
'''
import math
import torch.nn as nn
import torch.nn.init as init
__all__ = [
'VGG', 'vgg11', 'vgg11_bn', 'vgg13', 'vgg13_bn', 'vgg16', 'vgg16_bn',
'vgg19_bn', 'vgg19',
]
class VGG(nn.Module):
'''
VGG model
'''
def __init__(self, featu... | python | MIT | 020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16 | 2026-01-05T07:10:43.134916Z | false |
gbaydin/hypergradient-descent | https://github.com/gbaydin/hypergradient-descent/blob/020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16/setup.py | setup.py | import setuptools
with open("README.md", "r") as f:
long_description = f.read()
setuptools.setup(
name="hypergrad",
version="0.1",
author="Atılım Güneş Baydin",
author_email="",
description="Hypergradient descent",
long_description=long_description,
long_description_content_type="text/... | python | MIT | 020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16 | 2026-01-05T07:10:43.134916Z | false |
gbaydin/hypergradient-descent | https://github.com/gbaydin/hypergradient-descent/blob/020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16/plot.py | plot.py | import numpy as np
import pandas as pd
import argparse
import csv
import os
import glob
import matplotlib
# Force matplotlib to not use any Xwindows backend.
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
from mpl_toolkits.axes_grid.inset_locator import inset_axes
color... | python | MIT | 020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16 | 2026-01-05T07:10:43.134916Z | false |
gbaydin/hypergradient-descent | https://github.com/gbaydin/hypergradient-descent/blob/020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16/hypergrad/sgd_hd.py | hypergrad/sgd_hd.py | import torch
from functools import reduce
from torch.optim.optimizer import Optimizer, required
class SGDHD(Optimizer):
r"""Implements stochastic gradient descent (optionally with momentum).
Nesterov momentum is based on the formula from
`On the importance of initialization and momentum in deep learning`... | python | MIT | 020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16 | 2026-01-05T07:10:43.134916Z | false |
gbaydin/hypergradient-descent | https://github.com/gbaydin/hypergradient-descent/blob/020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16/hypergrad/__init__.py | hypergrad/__init__.py | from .adam_hd import AdamHD
from .sgd_hd import SGDHD
| python | MIT | 020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16 | 2026-01-05T07:10:43.134916Z | false |
gbaydin/hypergradient-descent | https://github.com/gbaydin/hypergradient-descent/blob/020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16/hypergrad/adam_hd.py | hypergrad/adam_hd.py | import math
import torch
from torch.optim.optimizer import Optimizer
class AdamHD(Optimizer):
"""Implements Adam algorithm.
It has been proposed in `Adam: A Method for Stochastic Optimization`_.
Arguments:
params (iterable): iterable of parameters to optimize or dicts defining
parame... | python | MIT | 020d6080c4cedfbc88d5cdb7a2a53f92b34c2b16 | 2026-01-05T07:10:43.134916Z | false |
lucidrains/dreamer4 | https://github.com/lucidrains/dreamer4/blob/5bb027b3869129adea79c68104e1c4c923749688/dreamer4/dreamer4.py | dreamer4/dreamer4.py | from __future__ import annotations
from typing import Callable
import math
from math import ceil, log2
from random import random
from contextlib import nullcontext
from collections import namedtuple
from functools import partial, wraps
from dataclasses import dataclass, asdict
import torch
import torch.nn.functional ... | python | MIT | 5bb027b3869129adea79c68104e1c4c923749688 | 2026-01-05T07:10:49.075008Z | true |
lucidrains/dreamer4 | https://github.com/lucidrains/dreamer4/blob/5bb027b3869129adea79c68104e1c4c923749688/dreamer4/__init__.py | dreamer4/__init__.py | from dreamer4.dreamer4 import (
VideoTokenizer,
DynamicsWorldModel,
AxialSpaceTimeTransformer
)
from dreamer4.trainers import (
VideoTokenizerTrainer,
BehaviorCloneTrainer,
DreamTrainer
)
| python | MIT | 5bb027b3869129adea79c68104e1c4c923749688 | 2026-01-05T07:10:49.075008Z | false |
lucidrains/dreamer4 | https://github.com/lucidrains/dreamer4/blob/5bb027b3869129adea79c68104e1c4c923749688/dreamer4/mocks.py | dreamer4/mocks.py | from __future__ import annotations
from random import choice
import torch
from torch import tensor, empty, randn, randint
from torch.nn import Module
from einops import repeat
# helpers
def exists(v):
return v is not None
# mock env
class MockEnv(Module):
def __init__(
self,
image_shape,
... | python | MIT | 5bb027b3869129adea79c68104e1c4c923749688 | 2026-01-05T07:10:49.075008Z | false |
lucidrains/dreamer4 | https://github.com/lucidrains/dreamer4/blob/5bb027b3869129adea79c68104e1c4c923749688/dreamer4/trainers.py | dreamer4/trainers.py | from __future__ import annotations
import torch
from torch import is_tensor
from torch.nn import Module
from torch.optim import AdamW
from torch.utils.data import Dataset, TensorDataset, DataLoader
from accelerate import Accelerator
from adam_atan2_pytorch import MuonAdamAtan2
from dreamer4.dreamer4 import (
Vi... | python | MIT | 5bb027b3869129adea79c68104e1c4c923749688 | 2026-01-05T07:10:49.075008Z | false |
lucidrains/dreamer4 | https://github.com/lucidrains/dreamer4/blob/5bb027b3869129adea79c68104e1c4c923749688/tests/test_dreamer.py | tests/test_dreamer.py | import pytest
param = pytest.mark.parametrize
import torch
def exists(v):
return v is not None
@param('pred_orig_latent', (False, True))
@param('grouped_query_attn', (False, True))
@param('dynamics_with_video_input', (False, True))
@param('prob_no_shortcut_train', (None, 0., 1.))
@param('add_task_embeds', (False,... | python | MIT | 5bb027b3869129adea79c68104e1c4c923749688 | 2026-01-05T07:10:49.075008Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/tools/serp.py | src/tools/serp.py | from src.config.logging import logger
from src.utils.io import load_yaml
from typing import Tuple
from typing import Union
from typing import Dict
from typing import List
from typing import Any
import requests
import json
# Static paths
CREDENTIALS_PATH = './credentials/key.yml'
class SerpAPIClient:
"""
A c... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/tools/wiki.py | src/tools/wiki.py | from src.config.logging import logger
from typing import Optional
import wikipediaapi
import json
def search(query: str) -> Optional[str]:
"""
Fetch Wikipedia information for a given search query using Wikipedia-API and return as JSON.
Args:
query (str): The search query string.
Returns:
... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/tools/manager.py | src/tools/manager.py | from src.tools.serp import search as google_search
from src.tools.wiki import search as wiki_search
from src.config.logging import logger
from pydantic import BaseModel
from typing import Callable
from pydantic import Field
from typing import Union
from typing import Dict
from enum import Enum
from enum import auto ... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/utils/io.py | src/utils/io.py | from src.config.logging import logger
from typing import Optional
from typing import Dict
from typing import Any
import json
import yaml
def read_file(path: str) -> Optional[str]:
"""
Reads the content of a markdown file and returns it as a text object.
Args:
path (str): The path to the markdo... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/llm/gemini.py | src/llm/gemini.py | from vertexai.generative_models import HarmBlockThreshold
from vertexai.generative_models import GenerationConfig
from vertexai.generative_models import GenerativeModel
from vertexai.generative_models import HarmCategory
from vertexai.generative_models import Part
from src.config.logging import logger
from typing impor... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/config/setup.py | src/config/setup.py | from src.config.logging import logger
from typing import Dict
from typing import Any
import yaml
import os
class Config:
_instance = None
def __new__(cls, *args, **kwargs):
if not cls._instance:
cls._instance = super(Config, cls).__new__(cls)
# The following line ensures that ... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/config/logging.py | src/config/logging.py | import logging
import os
def custom_path_filter(path):
# Define the project root name
project_root = "react-from-scratch"
# Find the index of the project root in the path
idx = path.find(project_root)
if idx != -1:
# Extract the portion of the path after the project root
path ... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/config/__init__.py | src/config/__init__.py | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false | |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/react/__init__.py | src/react/__init__.py | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false | |
arunpshankar/react-from-scratch | https://github.com/arunpshankar/react-from-scratch/blob/88ad3659a8a10110ad8cbf8f587a52f9854da696/src/react/agent.py | src/react/agent.py | from vertexai.generative_models import GenerativeModel
from src.tools.serp import search as google_search
from src.tools.wiki import search as wiki_search
from vertexai.generative_models import Part
from src.utils.io import write_to_file
from src.config.logging import logger
from src.config.setup import config
from s... | python | Apache-2.0 | 88ad3659a8a10110ad8cbf8f587a52f9854da696 | 2026-01-05T07:10:50.087100Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/setup.py | setup.py | import codecs
from setuptools import find_packages, setup
import os
base_dir = os.path.dirname(__file__)
about = {}
with open(os.path.join(base_dir, "ITMO_FS", "__about__.py")) as f:
exec(f.read(), about)
DISTNAME = 'ITMO_FS'
DESCRIPTION = 'Python Feature Selection library from ITMO University.'
with codecs.open... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/__about__.py | ITMO_FS/__about__.py | __all__ = ["__title__", "__uri__", "__version__"]
__title__ = "ITMO_FS"
__uri__ = "https://github.com/ctlab/ITMO_FS"
__version__ = "0.3.5"
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/__init__.py | ITMO_FS/__init__.py | from .embedded import *
from .ensembles import *
from .filters import *
from .hybrid import *
from .wrappers import *
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/__init__.py | ITMO_FS/ensembles/__init__.py | from .measure_based import *
from .model_based import *
from .ranking_based import *
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/model_based/best_sum.py | ITMO_FS/ensembles/model_based/best_sum.py | import numpy as np
from sklearn.base import clone
from sklearn.model_selection import cross_val_score
from logging import getLogger
from ...utils import BaseTransformer, apply_cr
class BestSum(BaseTransformer):
"""Best weighted sum ensemble. The ensemble fits the input models and
computes the feature scores a... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/model_based/__init__.py | ITMO_FS/ensembles/model_based/__init__.py | from .best_sum import BestSum
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/measure_based/fusion_functions.py | ITMO_FS/ensembles/measure_based/fusion_functions.py | from numpy import dot
def weight_fusion(filter_scores, weights):
"""Calculate the weighted score of each feature.
Parameters
----------
filter_scores : array-like, shape (n_filters, n_features)
Scores for all filters.
weights : array-like, shape (n_filters,)
Filter weights.
R... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/measure_based/__init__.py | ITMO_FS/ensembles/measure_based/__init__.py | from .WeightBased import *
from .fusion_functions import *
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/measure_based/WeightBased.py | ITMO_FS/ensembles/measure_based/WeightBased.py | from logging import getLogger
import numpy as np
from sklearn.base import clone
from .fusion_functions import *
from ...utils import BaseTransformer, apply_cr, check_filters
class WeightBased(BaseTransformer):
"""Weight-based filter ensemble. The ensemble first computes all filter
scores for the dataset and... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/ranking_based/fusion_functions.py | ITMO_FS/ensembles/ranking_based/fusion_functions.py | import random
import numpy as np
def best_goes_first_fusion(filter_ranks, k):
"""
Fusion function mixes filter results according feature appearance in
range of each filter. Selects first k of them.
Parameters
----------
filter_ranks : array-like, shape (n_filters, n_features)
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/ranking_based/Mixed.py | ITMO_FS/ensembles/ranking_based/Mixed.py | from logging import getLogger
import numpy as np
from .fusion_functions import *
from ...utils import BaseTransformer
class Mixed(BaseTransformer):
"""Perform feature selection based on several filters, selecting features
this way:
Get ranks from every filter from input.
Then loops through, ... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/ensembles/ranking_based/__init__.py | ITMO_FS/ensembles/ranking_based/__init__.py | from .Mixed import *
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/hybrid/Melif.py | ITMO_FS/hybrid/Melif.py | from logging import getLogger
import numpy as np
from sklearn.base import clone
from sklearn.model_selection import cross_val_score
from ITMO_FS.ensembles import WeightBased
from ITMO_FS.utils import BaseWrapper, apply_cr
from ITMO_FS.utils.data_check import *
class Melif(BaseWrapper):
"""MeLiF algorithm.
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/hybrid/filter_wrapper_hybrid.py | ITMO_FS/hybrid/filter_wrapper_hybrid.py | from logging import getLogger
from sklearn.base import clone
from ..utils import BaseTransformer
class FilterWrapperHybrid(BaseTransformer):
"""Perform the filter + wrapper hybrid algorithm by first running the
filter algorithm on the full dataset, leaving the selected features and
running the wrapper al... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/hybrid/__init__.py | ITMO_FS/hybrid/__init__.py | from .filter_wrapper_hybrid import *
from .Melif import Melif
from .IWSSr_SFLA import IWSSr_SFLA
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/hybrid/IWSSr_SFLA.py | ITMO_FS/hybrid/IWSSr_SFLA.py | from logging import getLogger
import numpy as np
from sklearn.model_selection import cross_val_score
from ITMO_FS.filters.univariate.measures import su_measure, relief_measure
from ITMO_FS.utils import BaseWrapper
class IWSSr_SFLA(BaseWrapper):
"""IWSSr-SFLA (Incremental Wrapper Subset Selection with replacemen... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/utils/data_check.py | ITMO_FS/utils/data_check.py | from numpy import array
def generate_features(X, features=None):
if features is None:
try:
if X.columns is list:
features = X.columns
else:
features = list(X.columns)
except AttributeError:
features = [i for i in range(X.shape[1])... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/utils/base_transformer.py | ITMO_FS/utils/base_transformer.py | from abc import abstractmethod
from logging import getLogger
import numpy as np
import pandas as pd
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.feature_selection import VarianceThreshold
from sklearn.utils import check_X_y, check_array
from sklearn.utils.validation import check_is_fitted
cl... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/utils/information_theory.py | ITMO_FS/utils/information_theory.py | from collections import Counter
from itertools import groupby
from math import log, fsum
from operator import itemgetter
import numpy as np
def conditional_entropy(x_j, y):
"""Calculate the conditional entropy (H(Y|X)) between two arrays.
Parameters
----------
x_j : array-like, shape (n,)
Th... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/utils/qpfs_body.py | ITMO_FS/utils/qpfs_body.py | import math
from functools import partial
import numpy as np
from qpsolvers import solve_qp
from scipy.linalg import sqrtm
def qpfs_body(X, y, fn, alpha=None, r=None, sigma=None, solv='quadprog',
metric_for_complex=complex.__abs__):
# TODO understand why complex double appears
# TODO find suita... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/utils/__init__.py | ITMO_FS/utils/__init__.py | from .data_check import *
from .functions import *
from .information_theory import *
from .qpfs_body import qpfs_body
from .base_transformer import BaseTransformer
from .base_wrapper import BaseWrapper
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/utils/functions.py | ITMO_FS/utils/functions.py | import numpy as np
from sklearn.metrics import f1_score
from sklearn.metrics.pairwise import euclidean_distances
def cartesian(rw, cl): # returns cartesian product for passed numpy arrays as two paired numpy array
tmp = np.array(np.meshgrid(rw, cl)).T.reshape(len(rw) * len(cl), 2)
return tmp.T[0], tmp.T[1]
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/utils/base_wrapper.py | ITMO_FS/utils/base_wrapper.py | from logging import getLogger
from sklearn.base import clone
from sklearn.utils import check_array
from sklearn.utils.validation import check_is_fitted
from . import BaseTransformer
class BaseWrapper(BaseTransformer):
def __init__(self):
pass
def fit(self, X, y=None, **fit_params):
"""Fit th... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/__init__.py | ITMO_FS/wrappers/__init__.py | from .deterministic import *
from .randomized import *
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/deterministic/BackwardSelection.py | ITMO_FS/wrappers/deterministic/BackwardSelection.py | from logging import getLogger
import numpy as np
from sklearn.model_selection import cross_val_score
from ...utils import generate_features, BaseWrapper
class BackwardSelection(BaseWrapper):
"""Backward Selection removes one feature at a time until the number of
features to be removed is reached. On each st... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/deterministic/SequentialForwardSelection.py | ITMO_FS/wrappers/deterministic/SequentialForwardSelection.py | from logging import getLogger
import numpy as np
from sklearn.model_selection import cross_val_score
from ...utils import generate_features, BaseWrapper
class SequentialForwardSelection(BaseWrapper):
"""Sequentially add features that maximize the classifying function when
combined with the features already ... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/deterministic/qpfs_wrapper.py | ITMO_FS/wrappers/deterministic/qpfs_wrapper.py | from ITMO_FS.filters.univariate.measures import pearson_corr
from ITMO_FS.utils.qpfs_body import qpfs_body
from ...utils import BaseWrapper
class QPFSWrapper(BaseWrapper):
"""
#TODO rewrite to the proper notation
Performs Quadratic Programming Feature Selection algorithm.
Note that this realization req... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/deterministic/AddDelWrapper.py | ITMO_FS/wrappers/deterministic/AddDelWrapper.py | from logging import getLogger
import random as rnd
import numpy as np
from sklearn.model_selection import cross_val_score
from ...utils import BaseWrapper, generate_features
class AddDelWrapper(BaseWrapper):
"""Add-Del feature wrapper.
Parameters
----------
estimator : object
A supervised l... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/deterministic/__init__.py | ITMO_FS/wrappers/deterministic/__init__.py | from .AddDelWrapper import AddDelWrapper
from .BackwardSelection import BackwardSelection
from .RecursiveElimination import RecursiveElimination
from .SequentialForwardSelection import SequentialForwardSelection
from .qpfs_wrapper import QPFSWrapper
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/deterministic/RecursiveElimination.py | ITMO_FS/wrappers/deterministic/RecursiveElimination.py | from logging import getLogger
import numpy as np
from sklearn.model_selection import cross_val_score
from ...utils import generate_features, BaseWrapper
class RecursiveElimination(BaseWrapper):
"""Recursive feature elimination algorithm.
Parameters
----------
estimator : object
A supervised... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/randomized/HillClimbing.py | ITMO_FS/wrappers/randomized/HillClimbing.py | from logging import getLogger
import numpy as np
from sklearn.base import clone
from sklearn.model_selection import cross_val_score
from ...utils import generate_features, BaseWrapper
class HillClimbingWrapper(BaseWrapper):
"""Hill Climbing algorithm.
Parameters
----------
estimator : object
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/randomized/TPhMGWO.py | ITMO_FS/wrappers/randomized/TPhMGWO.py | from logging import getLogger
import numpy as np
from sklearn.model_selection import cross_val_score
from ...utils import BaseWrapper, generate_features
class TPhMGWO(BaseWrapper):
"""Grey Wolf optimization with Two-Phase Mutation.
Parameters
----------
estimator : object
A supervised learn... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/randomized/__init__.py | ITMO_FS/wrappers/randomized/__init__.py | from .HillClimbing import HillClimbingWrapper
from .TPhMGWO import TPhMGWO
from .SimulatedAnnealing import SimulatedAnnealing | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/wrappers/randomized/SimulatedAnnealing.py | ITMO_FS/wrappers/randomized/SimulatedAnnealing.py | from logging import getLogger
import numpy as np
from sklearn.model_selection import cross_val_score
from ...utils import BaseWrapper, generate_features
class SimulatedAnnealing(BaseWrapper):
"""Simulated Annealing algorithm.
Parameters
----------
estimator : object
A supervised learning es... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
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