The 2Captcha official Python module remains a top choice for developers. It is highly portable, reliable, and supports nearly every type of CAPTCHA, including: FunCaptcha GeeTest Cloudflare Turnstile
Before exploring GitHub repositories, understand the three archetypes of solvers:
🔒 5. Handling Complex CAPTCHAs (reCAPTCHA, hCaptcha, Turnstile)
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Create a portable_captcha/ folder that can be copied anywhere:
portable-captcha-solver/ │ ├── python_embed/ # The extracted Python embeddable zip │ ├── python.exe │ └── ... ├── src/ │ ├── main.py # Main automation script │ └── solver.py # CAPTCHA solving logic ├── lib/ # Locally installed site-packages ├── run.bat # Windows batch file to trigger execution └── requirements.txt # List of dependencies Use code with caution. Step 1: Setting Up the Portable Python Core
Combining the power of Python's embeddable packages with advanced machine learning libraries found across GitHub makes creating a fully self-contained, portable CAPTCHA solver highly achievable. By modularizing your code, ensuring browser drivers remain local, and relying on lightweight OCR engines, you gain a robust automated utility capable of running on virtually any host machine with zero setup friction. captcha solver python github portable
When working with automated solvers, always adhere to ethical scraping guidelines and legal boundaries:
pip install playwright pillow opencv-python-headless numpyonnxruntime playwright install chromium Use code with caution.
pip install numpy opencv-python pillow easyocr python gen_templates_arial.py # Generate character templates python solve_captcha.py # Batch OCR on images in imgs/ folder The 2Captcha official Python module remains a top
Completcha is specifically designed for bypassing Arkose Labs/FunCaptcha challenges using a bypass method that avoids image solving, resulting in extremely high success rates. Unlike traditional approaches, it offers "bypass resolution" that solves challenges without requiring image solving—the system accurately replicates real browser behavior.
To build an effective solver, you do not need to train a machine learning model from scratch. The GitHub community provides pre-trained models optimized for text, audio, and image-selection CAPTCHAs. 1. DDRMP / UnCAPTCHA (Audio-Based Bypassing)
To ensure your script runs on any machine (from a Raspberry Pi to a cloud VM) without complex installation: ├── src/ │ ├── main
: Solving simple, clean text-based CAPTCHAs where the characters aren't heavily distorted.
If you are currently designing a specialized script, let me know you are targeting (e.g., text images, sliding puzzles, or reCAPTCHA v2) so I can provide customized optimization routines! Share public link