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Installation
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============
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.. warning::
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VulnerableCode is going through a major structural change and the
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installations are likely to not produce enough results.
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This is tracked in https://github.com/aboutcode-org/vulnerablecode/issues/597
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Welcome to **VulnerableCode** installation guide! This guide describes how to install
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VulnerableCode on various platforms.
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Please read and follow the instructions carefully to ensure your installation is
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**Run your image** as a container::
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docker compose up
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docker compose up -d \
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--scale vulnerablecode_rqworker=4 \
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--scale vulnerablecode_rqworker_high=2
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.. tip::
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Adjust the scaling factor as needed, or based on the recommendation shown in ``Load Factor`` at http://localhost:8000/pipelines/dashboard/.
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At this point, the VulnerableCode app should be running at port ``8000`` on your Docker host.
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Go to http://localhost:8000/ on a web browser to access the web UI.
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Go to http://localhost:8000/pipelines/dashboard/ to view the run status of the importer and improver pipelines.
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Optionally, you can set ``NGINX_PORT`` environment variable in your shell or in the `.env` file
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to run on a different port than 8000.
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.. tip::
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Set ``STAGING`` to ``False`` in production to disable the staging environment warning.
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Execute a Command
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^^^^^^^^^^^^^^^^^
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You can execute a one of ``manage.py`` commands through the Docker command line
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interface, for example::
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docker compose run vulnerablecode ./manage.py import --list
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.. note::
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Refer to the :ref:`command_line_interface` section for the full list of commands.
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Alternatively, you can connect to the Docker container ``bash`` and run commands
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from there::
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docker compose run vulnerablecode bash
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./manage.py import --list
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Set ``STAGING=False`` in ``.env`` file to disable the staging environment warning.
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.. _local_development_installation:
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Local development installation
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------------------------------
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development**.
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Run Pipelines
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^^^^^^^^^^^^^
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For local testing, you can use the ``manage.py`` commands to run importer and improver pipelines.
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To list the available importer pipelines::
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./manage.py import --list
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To run an importer pipeline::
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./manage.py import curl_importer_v2
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To list the available improver pipelines::
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./manage.py improve --list
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To run an improver pipeline::
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./manage.py improve compute_package_risk_v2
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.. note::
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Running a pipeline using a `manage.py` command will not display it on the ``Pipeline Dashboard``. Instead, all logs will be printed directly to the CLI.
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.. tip::
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Refer to the :ref:`command_line_interface` section for the complete list of commands.
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