# Python The Python analyser is triggered when one of these conditions are met: * a “Pipfile”, a “Pipfile.lock” or “requirements.txt” (pipenv was used) * a "pyproject.toml" or "poetry.lock" (poetry was used) * a "pyproject.toml" or "uv.lock" (uv was used) **A pipfile or requirements.txt** When operating on a Python project powered by pipenv the analyser will either load the dependencies from the lock file, if available, or it will use Pipenv in order to generate a new one, from the Pipfile or the requirements file. This analyser cannot work remotely. **A "pyproject.toml" and "poetry.lock"** When a set of Poetry files are detected the analyser will load the dependencies from such files. There's no automation to generate a lock file if missing: both files have to be present. This analyser cannot work remotely. **A "pyproject.toml" and "uv.lock"** When a set of uv files are detected the analyser will load the dependencies from such files. If the lock file is missing, the system will attempt to automatically generate a lock file. This analyser cannot work remotely. **Special case: Jupyter/Python Notebooks** Meterian is also able to process Jupyter Notebooks that contain Python code. The only requirement, assuming your license has the feature enabled, is to add the parameter `"--process-notebooks"` to the client when running. We also recommend the use of [the dockerized client](/the-client/the-meterian-client-dockerized.md) as it contains all the necessary tools. If not, you may need to install extra packages in the Python environment. Please find all the relevant information on the[ documentation page](/jupyter-notebooks.md). Remember that when using the [thin client](/the-client/client.md), the required tools will have to be installed and configured. This is not required when using the [dockerized client](/the-client/the-meterian-client-dockerized.md). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.meterian.io/languages-support/python.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.