最近需要使用 RQAlpha 进行国内的量化分析工作，并对 RQAlpha 进行了容器化处理，
方便使用 docker 和ks进行容器化管理
1.基于 jupyter/minimal-notebook jupyter的官方镜像，默认使用 python 3
2.使用Anaconda的mini-conda进行环境管理，可以自由切换python27和python3运行环境
3.使用pip安装了其他非conda管理的包内容
pip install bs4 cx-Oracle docopt future hdfs pyecharts PyMySQL raven typing lxml
4.使用编译方式安装了TA-lib,暂时为32bit版本，安装了国内流行的tushare
pip install tushare TA-lib
5.将matplotlib.pyplot自动导入，同时配合安装了国内流行的pyechart
6.安装了HDFS，cx-Oracle，PyMySQL等常用的数据连接包
可以在以下位置找到
https://github.com/limccn/rqalpha/tree/master/docker
完整的 Docker file内容
# Copyright (c) Jupyter Development Team. # Distributed under the terms of the Modified BSD License. FROM jupyter/minimal-notebook LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>" USER root # libav-tools for matplotlib anim RUN apt-get update && \ apt-get install -y --no-install-recommends libav-tools && \ apt-get clean && \ rm -rf /var/lib/apt/lists/* # Install TA-lib RUN wget https://jaist.dl.sourceforge.net/project/ta-lib/ta-lib/0.4.0/ta-lib-0.4.0-src.tar.gz && \ tar xf ta-lib-0.4.0-src.tar.gz && rm ta-lib-0.4.0-src.tar.gz && \ cd ta-lib && \ ./configure --prefix=/usr &&\ make && make install && \ rm -rf /home/$NB_USER/ta-lib USER $NB_UID # Install Python 3 packages # Remove pyqt and qt pulled in for matplotlib since we're only ever going to # use notebook-friendly backends in these images RUN conda install --quiet --yes \ 'nomkl' \ 'ipywidgets=7.1*' \ 'pandas=0.19*' \ 'numexpr=2.6*' \ 'matplotlib=2.0*' \ 'scipy=0.19*' \ 'seaborn=0.7*' \ 'scikit-learn=0.18*' \ 'scikit-image=0.12*' \ 'sympy=1.0*' \ 'cython=0.25*' \ 'patsy=0.4*' \ 'statsmodels=0.8*' \ 'cloudpickle=0.2*' \ 'dill=0.2*' \ 'numba=0.31*' \ 'bokeh=0.12*' \ 'sqlalchemy=1.1*' \ 'hdf5=1.8.17' \ 'h5py=2.6*' \ 'vincent=0.4.*' \ 'beautifulsoup4=4.5.*' \ 'protobuf=3.*' \ 'bcolz' \ 'xlrd' && \ conda remove --quiet --yes --force qt pyqt && \ conda clean -tipsy && \ # Install RQAlpha pip install -i https://pypi.tuna.tsinghua.edu.cn/simple rqalpha && \ rm -rf /home/$NB_USER/.rqalpha/bundle/ && \ rqalpha update_bundle && \ # Install RQAlpha libs pip install bs4 cx-Oracle docopt future hdfs pyecharts PyMySQL raven typing lxml && \ pip install tushare TA-lib && \ rm -rf /home/$NB_USER/.cache/pip/ && \ # Activate ipywidgets extension in the environment that runs the notebook server jupyter nbextension enable --py widgetsnbextension --sys-prefix && \ # Also activate ipywidgets extension for JupyterLab jupyter labextension install @jupyter-widgets/jupyterlab-manager@^0.33.1 && \ npm cache clean && \ rm -rf $CONDA_DIR/share/jupyter/lab/staging && \ rm -rf /home/$NB_USER/.cache/yarn && \ rm -rf /home/$NB_USER/.node-gyp && \ fix-permissions $CONDA_DIR && \ fix-permissions /home/$NB_USER # Install facets which does not have a pip or conda package at the moment RUN cd /tmp && \ git clone https://github.com/PAIR-code/facets.git && \ cd facets && \ jupyter nbextension install facets-dist/ --sys-prefix && \ rm -rf facets && \ fix-permissions $CONDA_DIR && \ fix-permissions /home/$NB_USER # Import matplotlib the first time to build the font cache. ENV XDG_CACHE_HOME /home/$NB_USER/.cache/ RUN MPLBACKEND=Agg python -c "import matplotlib.pyplot" && \ fix-permissions /home/$NB_USER USER $NB_UID
以上所述就是小编给大家介绍的《RQAlpha Docker容器化Dockerfile》，希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持！
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