This page gives some general instructions and tips to build and develop Analytics Zoo for Python developers.
You are very welcome to add customized functionalities to Analytics Zoo to meet your own demands. You are also highly encouraged to contribute to Analytics Zoo for extra features so that other community users would get benefits as well.
Download Analytics Zoo Source Code
Analytics Zoo source code is available at GitHub:
git clone https://github.com/intel-analytics/analytics-zoo.git
git clone will download the development version of Analytics Zoo. If you want a release version, you can use the command
git checkout to change the specified version.
Build whl package for pip install
If you have modified some Python code and want to newly generate the whl package for pip install, you can run the following script:
bash analytics-zoo/pyzoo/dev/build.sh linux default
- The first argument is the platform to build for. Either 'linux' or 'mac'.
- The second argument is the analytics-zoo version to build for. 'default' means the default version for the current branch. You can also specify a different version if you wish, e.g., '0.6.0.dev1'.
- You can also add other profiles to build the package, especially Spark and BigDL versions.
For example, under the situation that
pyspark==2.4.3is a dependency, you need to add profiles
-Dspark.version=2.4.3 -Dbigdl.artifactId=bigdl-SPARK_2.4 -P spark_2.4+to build Analytics Zoo for Spark 2.4.3.
After running the above command, you will find a
whl file under the folder
analytics-zoo/pyzoo/dist/. You can then directly pip install it to your local Python environment:
pip install analytics-zoo/pyzoo/dist/analytics_zoo-VERSION-py2.py3-none-PLATFORM_x86_64.whl
See here for more remarks related to pip install.
See here for more instructions to run analytics-zoo after pip install.
Run in IDE
You need to do the following preparations before starting the Integrated Development Environment (IDE) to successfully run an Analytics Zoo Python program in the IDE:
- Build Analytics Zoo. See here for more instructions.
- Prepare Spark environment by either setting
SPARK_HOMEas the environment variable or pip install
pyspark. Note that the Spark version should match the one you build Analytics Zoo on.
- Set BIGDL_CLASSPATH:
- Prepare BigDL Python environment by either downloading BigDL from GitHub or pip install
bigdl. Note that the BigDL version should match the one you build Analytics Zoo on.
If you download BigDL from GitHub, you also need to add