Dodgy is a basic static analysis tool designed to scan Python codebases for 'dodgy' looking values. It uses simple regular expressions to detect patterns such as accidentally committed SCM diffs, hardcoded passwords, or secret keys. While initially developed for open-source projects to prevent public exposure of sensitive data, it can also be used in private projects, though its configurability is limited. The project appears to be inactive since its last release in 2019.
pip install dodgyNo compatibility data collected yet for this library.
Run Dodgy from the command line against your project directory to scan for problematic patterns. It's often recommended to integrate this as a pre-commit hook.
Consider using more actively maintained static analysis tools for sensitive data detection, such as 'bandit' or custom regular expression-based linters.
Test thoroughly if using with newer Python versions, or consider migrating to a more modern tool. The `prospector` tool (which used to integrate `dodgy`) might offer a more up-to-date solution.
Always verify the package name, author, and version on PyPI before installation. Cross-reference with the official GitHub repository (github.com/landscapeio/dodgy) to confirm authenticity.
Understand that `dodgy` is a basic tool. Supplement its use with manual code reviews or more sophisticated, configurable secrets detection tools that allow for custom rule sets and exclusions.
Install the package using `pip install dodgy` and ensure you are running your script in the correct Python environment.
Ensure that the directory where pip installs scripts (e.g., `~/.local/bin` on Linux/macOS or `Scripts` folder within your Python installation on Windows) is added to your system's PATH. Alternatively, you can run it using `python -m dodgy` from your terminal.
Verify the exact name and path of the component you wish to import by consulting the library's source code or documentation (if available). For general use, simply `import dodgy` may be sufficient, or you may not need to import specific internal components for its command-line functionality.
Review the available public API of the 'dodgy' module (e.g., by using `dir(dodgy)` after importing it, or by examining the source code) to ensure you are calling an existing and intended function or attribute. The library is primarily a command-line tool, so direct programmatic access to all internal functions may not be supported or documented.
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