Qodana for Python
Qodana for Python is based on PyCharm Professional and provides static analysis for Python projects.
note
This linter requires the Qodana Cloud project token.
Qodana for Python provides inspections for the following technologies.
Programming languages | Python |
Markup languages | CSS HTML JSON and JSON5 RELAX NG XML YAML |
Scripting languages | Shell script |
Databases and ORM | MongoDB MySQL Oracle PostgreSQL SQL SQL Server |
Frameworks and libraries | Django Google App Engine Jupyter Pyramid |
The Qodana for Python linter provides the following Qodana features:
Feature | Available under licenses |
|---|---|
Ultimate and Ultimate Plus | |
Ultimate and Ultimate Plus | |
Ultimate and Ultimate Plus | |
Ultimate Plus | |
Ultimate and Ultimate Plus | |
Ultimate and Ultimate Plus | |
Ultimate Plus |
For a basic Python project that has no external dependencies, no preliminary steps are required.
In case the project has external pip dependencies, you can set them up using the bootstrap key in the qodana.yaml file.
For example, if your project dependencies are specified by the requirements.txt file in your project root, add the following line to qodana.yaml:
bootstrap: pip install -r requirements.txtThe command will be automatically executed before the analysis.
tip
You can learn more about running Qodana as root and non-root users from the Configure root and non-root users section.
Qodana provides two options for local analysis of your code. Qodana CLI is the easiest option to start. Alternatively, you can use the Docker command from the Docker image tab.
Assuming that you have already installed Qodana CLI on your machine, you can run this command in the project root directory:
$qodana scan \ -e QODANA_TOKEN="<cloud-project-token>" \ -l jetbrains/qodana-python:2024.1
Here, the QODANA_TOKEN variable refers to the project token.
To start, pull the image from Docker Hub (only necessary to get the latest version):
$docker pull jetbrains/qodana-python:2024.1
Start local analysis with source-directory pointing to the root of your project and QODANA_TOKEN referring to the project token:
$docker run \ -v <source-directory>/:/data/project/ \ -e QODANA_TOKEN="<cloud-project-token>" \ jetbrains/qodana-python:2024.1
In your browser, open Qodana Cloud to examine inspection results. Here, you can also reconfigure the analysis, see the Inspection report section for details.