Do this:
uvx --from pillow python -c "from PIL import Image; Image.open('README-assets/ad-example-1.png').save('README-assets/ad-example-1-better.webp', quality=75)"| import traceback | |
| def objetivo(): | |
| stack = traceback.extract_stack() | |
| caller = stack[-2] # quien llamó a esta función | |
| print(f"{caller.filename}:{caller.lineno} -> {caller.name}") | |
| def a(): | |
| objetivo() |
| # USE IT LIKE THIS in main.py, for example: | |
| """ | |
| _TRACE_CALLS = install_call_tracing(app_root=ROOT, source_root=ROOT.parent) | |
| """ | |
| from __future__ import annotations | |
| import atexit | |
| import os | |
| import sys | |
| import time |
Do this:
uvx --from pillow python -c "from PIL import Image; Image.open('README-assets/ad-example-1.png').save('README-assets/ad-example-1-better.webp', quality=75)"| // Generated from src/extraction-engine.js by scripts/build-exporters.js. | |
| // Edit the source engine or this build script, then run npm run build. | |
| (() => { | |
| 'use strict'; | |
| (function initChatExporterEngine(root, factory) { | |
| const engine = factory(); | |
| if (root) { |
| """ | |
| analyse_functions.py | |
| -------------------- | |
| Statically analyses a Python file and outputs: | |
| - A Markdown report of all functions (with signatures, docstrings, line numbers) | |
| - A Mermaid call-graph diagram (who calls whom) | |
| Usage: | |
| python analyse_functions.py <target_file.py> [--out report.md] | |
| """ |
| unalias act 2>/dev/null | |
| # Activate virtual environments | |
| act() { | |
| for d in .venv env venv .env; do | |
| if [ -d "$d" ]; then | |
| if [ -f "$d/bin/activate" ]; then | |
| source "$d/bin/activate" | |
| echo "Virtual Environment activated: $d" | |
| return |