Python
All Qodana linters are based on JetBrains IDEs designed for particular programming languages and frameworks. To analyze Python projects, you can use the following linters:
Qodana for Python is based on PyCharm Professional and available under the Ultimate and Ultimate Plus licenses,
Qodana Community for Python is based on PyCharm Community Edition and available under the Community license.
To see the list of supported technologies and features, you can navigate to the Supported technologies and features chapter of this section.
Before you start
Install dependencies
If your project has external pip
dependencies, 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, go into the configuration file and add the following line:
Qodana Cloud
Depending on the specific linter you're using, you may need to obtain a project token that will be used by Qodana for identifying and verifying a license. To do this, follow the steps below:
Navigate to Qodana Cloud and create an account there.
In Qodana Cloud, create an organization, a team, and a project.
On the project card, you can find the project token that you will be using further in this section.
Prepare your software
On the
tab of the GitHub UI, create theQODANA_TOKEN
encrypted secret and save the project token as its value.On the
tab of the GitHub UI, set up a new workflow and save the following workflow configuration to the.github/workflows/code_quality.yml
file:name: Qodana on: workflow_dispatch: pull_request: push: branches: - main jobs: qodana: runs-on: ubuntu-latest permissions: contents: write pull-requests: write checks: write steps: - uses: actions/checkout@v3 with: ref: ${{ github.event.pull_request.head.sha }} # to check out the actual pull request commit, not the merge commit fetch-depth: 0 # a full history is required for pull request analysis - name: 'Qodana Scan' uses: JetBrains/qodana-action@v2024.2 with: # Specify the linter that you would like to run args: --linter,jetbrains/qodana-python<-community>:2024.2 env: QODANA_TOKEN: ${{ secrets.QODANA_TOKEN }}This configuration sample will be modified throughout the section.
In Jenkins, make sure that these plugins are up and running:
Docker and Docker Pipeline are required for running Docker images,
Git is required for Git operations in Jenkins projects.
Make sure that Docker is installed and accessible to Jenkins.
If applicable, make sure that Docker is accessible to the
jenkins
user as described in the Manage Docker as a non-root user section of the Docker documentation.In Jenkins, create the
qodana-token
credential and save the project token as its value.In Jenkins, create a Multibranch Pipeline project as described on the Jenkins documentation portal.
Make sure that your project repository is accessible to GitLab CI/CD.
In GitLab CI/CD, create the
$qodana_token
variable and save the project token as its value.
In TeamCity, Create a project and a build configuration.
Install Docker on the machine you are going to run Qodana.
If you are using Linux, you should be able to run Docker under your current non-root user.
Follow the instructions from the Qodana CLI page on GitHub.
Run the command to pull the Docker image of the Qodana for Python or Qodana Community for Python linter:
Run Qodana
You can run the linters in two modes:
Native mode is the recommended method that lets you run linters without using Docker containers,
Container mode is an alternative that involves Docker containers.
The qodana.yaml
file is a universal method of native mode configuration. Alternatively, you can configure it without using the qodana.yaml
file.
Save the following configuration in the
qodana.yaml
file:ide: QDPY
for the Qodana for Python linter,ide: QDPYC
for the Qodana Community for Python linter.
You can run Qodana using the Qodana Scan GitHub action.
To inspect the
main
branch, release branches and the pull requests coming to your repository in native mode, save this workflow configuration to the.github/workflows/code_quality.yml
file:name: Qodana on: workflow_dispatch: pull_request: push: branches: # Specify your branches here - main # The 'main' branch - 'releases/*' # The release branches jobs: qodana: runs-on: ubuntu-latest permissions: contents: write pull-requests: write checks: write steps: - uses: actions/checkout@v3 with: ref: ${{ github.event.pull_request.head.sha }} # to check out the actual pull request commit, not the merge commit fetch-depth: 0 # a full history is required for pull request analysis - name: 'Qodana Scan' uses: JetBrains/qodana-action@v2024.2 env: QODANA_TOKEN: ${{ secrets.QODANA_TOKEN }}
You can run Qodana using the Qodana Scan GitHub action.
To inspect the main
branch, release branches and the pull requests coming to your repository in native mode, save this workflow configuration to the .github/workflows/code_quality.yml
file:
Here, <linter-code>
refers to one of the following linters:
| Linter |
---|---|
| Qodana for Python |
| Qodana Community for Python |
More configuration examples are available in the GitHub Actions section.
Save the following configuration in the
qodana.yaml
file:ide: QDPY
for the Qodana for Python linter,ide: QDPYC
for the Qodana Community for Python linter.
Run this command in the project root directory:
qodana scan \ -e QODANA_TOKEN="<qodana-cloud-token>"In your browser, open Qodana Cloud to examine the analysis results and reconfigure the analysis. See the Inspection report section of the documentation for full details.
Run this command in the project root directory:
Here, <linter-code>
refers to one of the following linters:
| Linter |
---|---|
| Qodana for Python |
| Qodana Community for Python |
In your browser, open Qodana Cloud to examine the analysis results and reconfigure the analysis. See the Inspection report section of the documentation for full details.
Container mode is available for all linters; however, we recommend that you use native mode whenever possible.
To analyze the main
branch, release branches and the pull requests coming to your repository in container mode, save this workflow configuration to the .github/workflows/code_quality.yml
file:
More configuration examples are available in the GitHub Actions section.
Save this configuration to the Jenkinsfile
:
More configuration examples are available in the Jenkins section.
In the root directory of your project, save this snippet to the .gitlab-ci.yml
file:
In this snippet:
The
cache
keyword configures GitLab CI/CD caches to store the Qodana cache, so subsequent runs will be faster,The
script
keyword runs theqodana
command and enumerates the Qodana configuration options described in the Shell commands section,The
variables
keyword defines theQODANA_TOKEN
variable referring to the project token.
More configuration examples are available in the GitLab CI/CD section.
In the TeamCity UI, navigate to the configuration page of a build where you would like to run Qodana.
- page, navigate to the
On the
page, click the button.On the page that opens, select the
runner.On the
page, click and configure the runner:uniquely identifies this step among other build steps.
uniquely identifies this step among other build steps.
configures the build condition that will trigger this build step.
TeamCity documentation for details. You can leave this field empty if the
sets the directory for the build process, see theCheckout directory
parameter is specified on the tab.uniquely identifies the report to let you distinguish between multiple reports when several inspection steps are configured within a single build.
The Test tab of the TeamCity UI. Using this option, you can view codebase problems along with other problems detected.
checkbox configures Qodana report availability in the- configures the
Here, select either the Qodana for Python or Qodana Community for Python linter.
is by default set toLatest
.- defines an
Recommended (default)
is one of the default profiles.Embedded profile
lets you select a default profile, see the Existing Qodana profiles section for details.Path to the IntelliJ profile
lets you specify the path to your custom profile. To use this option, make sure that you also configure the custom profile in theqodana.yaml
file.
project token generated in Qodana Cloud.
configures aShell commands section for details.
configures the arguments accepted by a Docker image, see theOptions section for details.
lets you extend the default Qodana functionality, see the
Click the
button.
More configuration examples are available in the TeamCity section.
In your browser, open Qodana Cloud to examine the analysis results and reconfigure the analysis. See the Inspection report section of the documentation for full details.
In PyCharm, navigate to
.On the
dialog, you can configure Qodana.This dialog contains the following components:
Name
Description
The
qodana.yaml
fileIn the text field, you can set up code analysis used by Qodana in this file. You can learn more about available configuration options
The
optionIf you want to send reports to Qodana Cloud, you can check this option and paste the project token generated in Qodana Cloud
The
optionBy checking this option, you can save the Qodana configuration made on this dialog to the
qodana.yaml
file in the project root of your projectThe
optionUsing the baseline feature, you can skip analysis for specific problems
Click
for analyzing your code.On the inspection results.
tab of the tool window, see the
Explore analysis results
You can load the latest Qodana report from Qodana Cloud to your IDE as explained below.
In your IDE, navigate to
.On the
dialog, click .This will redirect you to the authentication page.
Select the Qodana Cloud project to link your local project with.
If you check the
option, you will be able to receive the most up-to-date and relevant reports from Qodana Cloud.In this case, the IDE will search Qodana Cloud and fetch the report with the revision ID corresponding to the current revision ID (HEAD). If this report is not found, the IDE will select the previous report with the revision ID closest to the current revision ID (HEAD). Otherwise, the IDE retrieves the latest available report from Qodana Cloud.
On the analysis results.
tab of the tool window, you can view the
After Qodana analyzed your project and uploaded the analysis results to Qodana Cloud, in Qodana Cloud navigate to your project and review the analysis results report.
To learn more about Qodana report UI, see the Inspection report section.
Extend Qodana configuration
Adjusting the scope of analysis
Out of the box, Qodana provides two predefined profiles hosted on GitHub:
qodana.starter
is the default profile and a subset of the more comprehensiveqodana.recommended
profile.qodana.recommended
is suitable for running in CI/CD pipelines and mostly implements the default PyCharm profile; see the PyCharm documentation for details.
You can customize Qodana profiles using configurations in YAML and XML formats. To learn more about configuration basics, visit the Configure Qodana your way section of the documentation.
Enabling the baseline feature
You can skip analysis for specific problems by using the baseline feature. Information about a baseline is contained in a SARIF-formatted file.
Save the following configuration in the
qodana.yaml
file:ide: QDPY
for the Qodana for Python linter,ide: QDPYC
for the Qodana Community for Python linter.
Save the snippet to the
.github/workflows/code_quality.yml
file containing theargs: --baseline,qodana.sarif.json
option that specifies the path to the SARIF-formatted baseline file:name: Qodana on: workflow_dispatch: pull_request: push: branches: # Specify your branches here - main # The 'main' branch - 'releases/*' # The release branches jobs: qodana: runs-on: ubuntu-latest permissions: contents: write pull-requests: write checks: write steps: - uses: actions/checkout@v3 with: ref: ${{ github.event.pull_request.head.sha }} # to check out the actual pull request commit, not the merge commit fetch-depth: 0 # a full history is required for pull request analysis - name: 'Qodana Scan' uses: JetBrains/qodana-action@v2024.2 env: QODANA_TOKEN: ${{ secrets.QODANA_TOKEN }}
Save the snippet to the .github/workflows/code_quality.yml
file containing the args: --baseline,qodana.sarif.json
option that specifies the path to the SARIF-formatted baseline file:
Here, <linter-code>
refers to one of the following linters:
| Linter |
---|---|
| Qodana for Python |
| Qodana Community for Python |
Save the following configuration in the
qodana.yaml
file:ide: QDPY
for the Qodana for Python linter,ide: QDPYC
for the Qodana Community for Python linter.
Run this command in the project root directory using the
--baseline,<path/to/qodana.sarif.json>
option to specify the path to a SARIF-formatted file containing a baseline:qodana scan \ -e QODANA_TOKEN="<qodana-cloud-token>" \ --baseline <path/to/qodana.sarif.json>In your browser, open Qodana Cloud to examine the analysis results and reconfigure the analysis. See the Inspection report section of the documentation for full details.
Run this command in the project root directory using the --baseline,<path/to/qodana.sarif.json>
option to specify the path to a SARIF-formatted file containing a baseline:
Here, <linter-code>
refers to one of the following linters:
| Linter |
---|---|
| Qodana for Python |
| Qodana Community for Python |
In your browser, open Qodana Cloud to examine the analysis results and reconfigure the analysis. See the Inspection report section of the documentation for full details.
Save this snippet to the .github/workflows/code_quality.yml
file containing the args: --baseline,qodana.sarif.json
option that specifies the path to the SARIF-formatted baseline file:
In the Jenkinsfile
, save the configuration containing the --baseline <path/to/qodana.sarif.json>
line that specifies the path to the SARIF-formatted baseline file:
In the root directory of your project, save this snippet to the .gitlab-ci.yml
file:
The --baseline <path/to/qodana.sarif.json>
line in the script
block invokes the baseline feature.
In the TeamCity UI, navigate to the configuration page of a build where you would like to run Qodana.
- page, navigate to the
On the
page, click the button.On the page that opens, select the
runner.On the
page, click and configure the runner:uniquely identifies this step among other build steps.
uniquely identifies this step among other build steps.
configures the build condition that will trigger this build step.
TeamCity documentation for details. You can leave this field empty if the
sets the directory for the build process, see theCheckout directory
parameter is specified on the tab.uniquely identifies the report to let you distinguish between multiple reports when several inspection steps are configured within a single build.
The Test tab of the TeamCity UI. Using this option, you can view codebase problems along with other problems detected.
checkbox configures Qodana report availability in the- configures the
Here, select either the Qodana for Python or Qodana Community for Python linter.
is by default set toLatest
.- defines an
Recommended (default)
is one of the default profiles.Embedded profile
lets you select a default profile, see the Existing Qodana profiles section for details.Path to the IntelliJ profile
lets you specify the path to your custom profile. To use this option, make sure that you also configure the custom profile in theqodana.yaml
file.
project token generated in Qodana Cloud.
configures aShell commands section for details.
configures the arguments accepted by a Docker image, see theOptions section for details.
lets you extend the default Qodana functionality, see theIn this field, specify the baseline feature using the
--baseline <path/to/qodana.sarif.json>
option.
Click the
button.
Choose how you would like to run the baseline feature from the command line:
In your IDE, navigate to the
tool window.In the
tool window, click the tab.On the
tab, click the button.On the dialog that opens, expand the
section and specify the path to the baseline file, and then click .
Enabling the quality gate
You can configure quality gates for the total number of project problems, specific problem severities, and code coverage by saving this snippet to the qodana.yaml
file:
You can configure quality gates for the total number of project problems and specific problem severities by saving this snippet to the qodana.yaml
file:
Analyzing pull requests
Save the following configuration in the
qodana.yaml
file:ide: QDPY
for the Qodana for Python linter,ide: QDPYC
for the Qodana Community for Python linter.
The Qodana Scan GitHub action automatically analyzes all pull requests, so you do not have to provide any additional configuration. Save this configuration to the
.github/workflows/code_quality.yml
file:name: Qodana on: workflow_dispatch: pull_request: push: branches: # Specify your branches here - main # The 'main' branch - 'releases/*' # The release branches jobs: qodana: runs-on: ubuntu-latest permissions: contents: write pull-requests: write checks: write steps: - uses: actions/checkout@v3 with: ref: ${{ github.event.pull_request.head.sha }} # to check out the actual pull request commit, not the merge commit fetch-depth: 0 # a full history is required for pull request analysis - name: 'Qodana Scan' uses: JetBrains/qodana-action@v2024.2 env: QODANA_TOKEN: ${{ secrets.QODANA_TOKEN }}
The Qodana Scan GitHub action automatically analyzes all pull requests, so you do not have to provide any additional configuration. Save this configuration to the .github/workflows/code_quality.yml
file:
Here, <linter-code>
refers to one of the following linters:
| Linter |
---|---|
| Qodana for Python |
| Qodana Community for Python |
Save the following configuration in the
qodana.yaml
file:ide: QDPY
for the Qodana for Python linter,ide: QDPYC
for the Qodana Community for Python linter.
To analyze changes in your code, employ the
--diff-start
option and specify a hash of the commit that will act as a base for comparison:qodana scan \ -e QODANA_TOKEN="<cloud-project-token>" \ --diff-start=<GIT_START_HASH>In your browser, open Qodana Cloud to examine the analysis results and reconfigure the analysis. See the Inspection report section of the documentation for full details.
To analyze changes in your code, employ the --diff-start
option and specify a hash of the commit that will act as a base for comparison:
Here, <linter-code>
refers to one of the following linters:
| Linter |
---|---|
| Qodana for Python |
| Qodana Community for Python |
In your browser, open Qodana Cloud to examine the analysis results and reconfigure the analysis. See the Inspection report section of the documentation for full details.
The Qodana Scan GitHub action automatically analyzes all pull requests, so you do not have to provide any additional configuration. Save this configuration to the .github/workflows/code_quality.yml
file:
In the root directory of your project, save the .gitlab-ci.yml
file containing the following snippet:
Here, the --diff-start
option specifies a hash of the commit that will act as a base for comparison.
Information about configuring TeamCity for analyzing pull and merge requests is available on the TeamCity documentation portal.
To analyze changes in your code, employ the --diff-start
option and specify a hash of the commit that will act as a base for comparison:
Supported technologies and features
This table contains the list of technologies and Qodana features supported by both linters.
Support for | Name | Qodana for Python | Qodana Community for Python |
---|---|---|---|
Programming languages | Python JavaScript and TypeScript | ✔ ✔ | ✔
|
Frameworks and libraries | Pyramid Node.js React Vue | ✔ ✔ ✔ ✔ |
|
Databases and ORM | MySQL MongoDB Oracle SQL SQL Server PostgreSQL | ✔ ✔ ✔ ✔ ✔ ✔ |
|
Markup languages | HTML JSON and JSON5 RELAX NG XML YAML TOML SASS/SCSS PostCSS Less CSS | ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ | ✔ ✔ ✔ ✔ ✔ ✔
|
Scripting languages | Shell script | ✔ | ✔ |
Other | Regular expressions Structural search HTTP Client | ✔ ✔ ✔ | ✔
|
Qodana features | ✔ ✔ ✔ ✔ ✔ ✔ | ✔ ✔
|