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add dockerfile (#1817)
* add dockerfile * add execute script * add docs * optimize docs * optimize dockerfile * optimize docs * optimize dockerfile * update code & update README * doc build error * update docs * update code
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docs/developer/how_to_build_image.rst
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81
docs/developer/how_to_build_image.rst
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.. _docker_image:
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==================
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Build Docker Image
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==================
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Dockerfile
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==========
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There is a **Dockerfile** file in the root directory of the project from which you can build the docker image. There are two build methods in Dockerfile to choose from.
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When executing the build command, use the ``--build-arg`` parameter to control the image version. The ``--build-arg`` parameter defaults to ``yes``, which builds the ``stable`` version of the qlib image.
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1.For the ``stable`` version, use ``pip install pyqlib`` to build the qlib image.
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.. code-block:: bash
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docker build --build-arg IS_STABLE=yes -t <image name> -f ./Dockerfile .
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.. code-block:: bash
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docker build -t <image name> -f ./Dockerfile .
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2. For the ``nightly`` version, use current source code to build the qlib image.
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.. code-block:: bash
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docker build --build-arg IS_STABLE=no -t <image name> -f ./Dockerfile .
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Auto build of qlib images
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=========================
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1. There is a **build_docker_image.sh** file in the root directory of your project, which can be used to automatically build docker images and upload them to your docker hub repository(Optional, configuration required).
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.. code-block:: bash
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sh build_docker_image.sh
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>>> Do you want to build the nightly version of the qlib image? (default is stable) (yes/no):
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>>> Is it uploaded to docker hub? (default is no) (yes/no):
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2. If you want to upload the built image to your docker hub repository, you need to edit your **build_docker_image.sh** file first, fill in ``docker_user`` in the file, and then execute this file.
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How to use qlib images
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======================
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1. Start a new Docker container
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.. code-block:: bash
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docker run -it --name <container name> -v <Mounted local directory>:/app <image name>
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2. At this point you are in the docker environment and can run the qlib scripts. An example:
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.. code-block:: bash
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>>> python scripts/get_data.py qlib_data --name qlib_data_simple --target_dir ~/.qlib/qlib_data/cn_data --interval 1d --region cn
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>>> python qlib/workflow/cli.py examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml
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3. Exit the container
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.. code-block:: bash
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>>> exit
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4. Restart the container
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.. code-block:: bash
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docker start -i -a <container name>
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5. Stop the container
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.. code-block:: bash
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docker stop -i -a <container name>
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6. Delete the container
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.. code-block:: bash
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docker rm <container name>
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7. For more information on using docker see the `docker documentation <https://docs.docker.com/reference/cli/docker/>`_.
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