Python Requirements.txt Generator

Create clean, professional requirements.txt files with advanced dependency management features. Support for version pinning strategies, development vs production dependencies, package grouping with comments, and validation of package names. Perfect for maintaining reproducible Python environments and streamlining deployment workflows.
Version Pinning Dev Dependencies Package Grouping Validation
Quick Examples
PINNED: django==4.2.0
RANGE: requests>=2.28.0,<3.0.0
DEV: # Development dependencies
pytest==7.4.0
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Help & Related Tools

Everything you need to know

FAQ Frequently Asked Questions

What features does the Python Requirements.txt Generator offer?
This tool provides package management with version pinning strategies, development vs production dependency separation, alphabetical sorting, comment generation, import/export functionality, and real-time statistics. Perfect for creating clean, reproducible Python environments.
How do I use the Python Requirements Generator?
Simply add package names with optional versions, choose your version pinning strategy (exact, compatible, pessimistic), select dependency type, and the tool generates a properly formatted requirements.txt file instantly. You can also import existing requirements for editing.
Is the Requirements Generator compatible with all Python environments?
Yes, this tool generates standard requirements.txt format compatible with pip, conda, poetry, and all Python package managers. Works on all modern browsers and devices with no installation required.
Are there any limitations for the requirements generator?
The tool works entirely client-side for privacy and speed. It does not validate package names against PyPI in real-time, so ensure package names are correct. For optimal performance, manage up to 500+ packages without issues.
Can I import existing requirements.txt files for editing?
Absolutely! Paste your existing requirements.txt content in the import section, and the tool will parse and load all packages with their version constraints. Perfect for updating, reorganizing, or migrating existing Python projects.

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