mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-27 19:46:52 +08:00
Y.K. Goon
94 lines
2.4 KiB
Docker
94 lines
2.4 KiB
Docker
#
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# Dockerfile for an image with the currently checked out version of catalyst installed. To build:
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#
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# docker build -t quantopian/catalyst .
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#
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# To run the container:
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#
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# docker run -v /path/to/your/notebooks:/projects -v ~/.catalyst:/root/.catalyst -p 8888:8888/tcp --name catalyst -it quantopian/catalyst
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#
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# To access Jupyter when running docker locally (you may need to add NAT rules):
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#
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# https://127.0.0.1
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#
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# Default password is 'jupyter'. To provide another, see:
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# http://jupyter-notebook.readthedocs.org/en/latest/public_server.html#preparing-a-hashed-password
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#
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# Once generated, you can pass the new value via `docker run --env` the first time
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# you start the container.
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#
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# You can also run an algo using the docker exec command. For example:
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#
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# docker exec -it catalyst catalyst run -f /projects/my_algo.py --start 2015-1-1 --end 2016-1-1 /projects/result.pickle
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#
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FROM python:3.5
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#
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# set up environment
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#
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ENV TINI_VERSION v0.10.0
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ADD https://github.com/krallin/tini/releases/download/${TINI_VERSION}/tini /tini
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RUN chmod +x /tini
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ENTRYPOINT ["/tini", "--"]
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ENV PROJECT_DIR=/projects \
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NOTEBOOK_PORT=8888 \
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SSL_CERT_PEM=/root/.jupyter/jupyter.pem \
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SSL_CERT_KEY=/root/.jupyter/jupyter.key \
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PW_HASH="u'sha1:31cb67870a35:1a2321318481f00b0efdf3d1f71af523d3ffc505'" \
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CONFIG_PATH=/root/.jupyter/jupyter_notebook_config.py
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#
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# install TA-Lib and other prerequisites
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#
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RUN mkdir ${PROJECT_DIR} \
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&& apt-get -y update \
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&& apt-get -y install libfreetype6-dev libpng-dev libopenblas-dev liblapack-dev gfortran \
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&& curl -L https://downloads.sourceforge.net/project/ta-lib/ta-lib/0.4.0/ta-lib-0.4.0-src.tar.gz | tar xvz
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#
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# build and install catalyst from source. install TA-Lib after to ensure
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# numpy is available.
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#
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WORKDIR /ta-lib
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RUN pip install 'numpy>=1.11.1,<2.0.0' \
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&& pip install 'scipy>=0.17.1,<1.0.0' \
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&& pip install 'pandas>=0.18.1,<1.0.0' \
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&& ./configure --prefix=/usr \
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&& make \
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&& make install \
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&& pip install TA-Lib \
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&& pip install matplotlib \
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&& pip install jupyter
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#
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# This is then only file we need from source to remain in the
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# image after build and install.
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#
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ADD ./etc/docker_cmd.sh /
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#
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# make port available. /catalyst is made a volume
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# for developer testing.
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#
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EXPOSE ${NOTEBOOK_PORT}
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#
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# build and install the catalyst package into the image
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#
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ADD . /catalyst
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WORKDIR /catalyst
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RUN pip install -e .
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#
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# start the jupyter server
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#
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WORKDIR ${PROJECT_DIR}
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CMD /docker_cmd.sh
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