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Add Developer Guide for Python users (#1512)
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* fix style for python

* add pip build doc

* update

* add IDE instructions

* minor
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hkvision committed Jul 13, 2019
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63 changes: 63 additions & 0 deletions docs/docs/DeveloperGuide/python.md
@@ -0,0 +1,63 @@
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](https://github.com/intel-analytics/analytics-zoo):

```bash
git clone https://github.com/intel-analytics/analytics-zoo.git
```

By default, `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](https://pythonwheels.com/) package for pip install, you can run the following script:

```bash
bash analytics-zoo/pyzoo/dev/build.sh linux default
```

**Arguments:**

- 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==2.4.3` is a dependency, you need to add profiles `-Dspark.version=2.4.3 -Dbigdl.artifactId=bigdl-SPARK_2.4 -P spark_2.x` 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:
```bash
pip install analytics-zoo/pyzoo/dist/analytics_zoo-VERSION-py2.py3-none-PLATFORM_x86_64.whl # for Python 2.7
pip3 install analytics-zoo/pyzoo/dist/analytics_zoo-VERSION-py2.py3-none-PLATFORM_x86_64.whl # for Python 3.5 and Python 3.6
```

See [here](../PythonUserGuide/install/#install-from-pip-for-local-usage) for more remarks related to pip install.

See [here](../PythonUserGuide/run/#run-after-pip-install) 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](../ScalaUserGuide/install/#build-with-script-recommended) for more instructions.
- Prepare Spark environment by either setting `SPARK_HOME` as the environment variable or pip install `pyspark`. Note that the Spark version should match the one you build Analytics Zoo on.
- Set BIGDL_CLASSPATH:
```bash
export BIGDL_CLASSPATH=analytics-zoo/dist/lib/analytics-zoo-*-jar-with-dependencies.jar
```

- Prepare BigDL Python environment by either downloading BigDL from [GitHub](https://github.com/intel-analytics/BigDL) or pip install `bigdl`. Note that the BigDL version should match the one you build Analytics Zoo on.
- Add `pyzoo` and `spark-analytics-zoo.conf` to `PYTHONPATH`:
```bash
export PYTHONPATH=analytics-zoo/pyzoo:analytics-zoo/dist/conf/spark-analytics-zoo.conf:$PYTHONPATH
```
If you download BigDL from [GitHub](https://github.com/intel-analytics/BigDL), you also need to add `BigDL/pyspark` to `PYTHONPATH`:
```bash
export PYTHONPATH=BigDL/pyspark:$PYTHONPATH
```
13 changes: 6 additions & 7 deletions docs/docs/PythonUserGuide/install.md
Expand Up @@ -24,34 +24,33 @@ sc = init_nncontext()
```

**Remarks:**

1. We've tested this package with pip 9.0.1. `pip install --upgrade pip` if necessary.
2. Pip install supports __Mac__ and __Linux__ platforms.
3. You need to install Java __>= JDK8__ before running Analytics Zoo, which is required by `pyspark`.
4. `pyspark==2.4.3`, `bigdl==0.8.0` and their dependencies will automatically be installed if they haven't been detected in the current Python environment.

---
## **Install from pip for yarn cluster**

You only need to following these steps on your driver node and we only support yarn-client mode for now.

1) Install [Conda](https://docs.conda.io/projects/conda/en/latest/commands/install.html) and create a conda-env(i.e in the name of "zoo")
1) Install [Conda](https://docs.conda.io/projects/conda/en/latest/commands/install.html) and create a conda-env (i.e in the name of "zoo").

2) Install Analytics-Zoo into the created conda-env
2) Install Analytics-Zoo into the created conda-env.

```
source activate zoo
pip install analytics-zoo
```
3) Download JDK8 and set the environment variable: JAVA_HOME (recommended).

- You can also install JDK via conda without setting the JAVA_HOME manually:
`conda install -c anaconda openjdk=8.0.152`

4) Start python and then execute the following code for verification.

- Create a SparkContext on Yarn
4) Start python and then execute the following code to create a SparkContext on Yarn for verification.

``` python

from zoo import init_spark_on_yarn

sc = init_spark_on_yarn(
Expand Down
9 changes: 4 additions & 5 deletions docs/docs/PythonUserGuide/run.md
Expand Up @@ -49,14 +49,14 @@ export BIGDL_JARS=...
export BIGDL_PACKAGES=...
```

## **Run on yarn after pip install
---
## **Run on yarn after pip install**

You should use `init_spark_on_yarn` rather than `init_nncontext()` here to create a SparkContext on Yarn.

Start python and then execute the following code:
Caveat: You should use `init_spark_on_yarn` rather than `init_nncontext()` here.
- Create a SparkContext on Yarn

``` python

from zoo import init_spark_on_yarn

sc = init_spark_on_yarn(
Expand All @@ -68,7 +68,6 @@ sc = init_spark_on_yarn(
driver_memory="2g",
driver_cores=4,
extra_executor_memory_for_ray="10g")

```

---
Expand Down
2 changes: 2 additions & 0 deletions docs/mkdocs.yml
Expand Up @@ -25,6 +25,8 @@ pages:
- Install: ScalaUserGuide/install.md
- Run: ScalaUserGuide/run.md
- Examples: ScalaUserGuide/examples.md
- Developer Guide:
- For Python Developers: DeveloperGuide/python.md
- Programming Guide:
- Pipeline APIs:
- DataFrame and ML Pipeline: ProgrammingGuide/nnframes.md
Expand Down
35 changes: 35 additions & 0 deletions pyzoo/dev/build.sh
@@ -0,0 +1,35 @@
#!/usr/bin/env bash

#
# Copyright 2018 Analytics Zoo Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

set -e
RUN_SCRIPT_DIR=$(cd $(dirname $0) ; pwd)
echo $RUN_SCRIPT_DIR

if (( $# < 2)); then
echo "Usage: build.sh platform version mvn_parameters"
echo "Usage example: bash release.sh linux default"
echo "Usage example: bash release.sh linux 0.6.0.dev0"
echo "If needed, you can also add other profiles such as: -Dspark.version=2.4.3 -Dbigdl.artifactId=bigdl-SPARK_2.4 -P spark_2.x"
exit -1
fi

platform=$1
version=$2
profiles=${*:3}

bash ${RUN_SCRIPT_DIR}/release.sh ${platform} ${version} false ${profiles}
7 changes: 3 additions & 4 deletions pyzoo/dev/release/release.sh → pyzoo/dev/release.sh
Expand Up @@ -19,15 +19,15 @@
set -e
RUN_SCRIPT_DIR=$(cd $(dirname $0) ; pwd)
echo $RUN_SCRIPT_DIR
export ANALYTICS_ZOO_HOME="$(cd ${RUN_SCRIPT_DIR}/../../../; pwd)"
export ANALYTICS_ZOO_HOME="$(cd ${RUN_SCRIPT_DIR}/../../; pwd)"
echo $ANALYTICS_ZOO_HOME
ANALYTICS_ZOO_PYTHON_DIR="$(cd ${RUN_SCRIPT_DIR}/../../../pyzoo; pwd)"
ANALYTICS_ZOO_PYTHON_DIR="$(cd ${RUN_SCRIPT_DIR}/../../pyzoo; pwd)"
echo $ANALYTICS_ZOO_PYTHON_DIR

if (( $# < 3)); then
echo "Usage: release.sh platform version upload mvn_parameters"
echo "Usage example: bash release.sh linux default true"
echo "Usage example: bash release.sh linux 0.6.0.dev0 true -Dspark.version=2.4.3 -Dbigdl.artifactId=bigdl-SPARK_2.4 -P spark_2.x"
echo "Usage example: bash release.sh linux 0.6.0.dev0 true"
echo "If needed, you can also add other profiles such as: -Dspark.version=2.4.3 -Dbigdl.artifactId=bigdl-SPARK_2.4 -P spark_2.x"
exit -1
fi
Expand Down Expand Up @@ -92,4 +92,3 @@ if [ ${upload} == true ]; then
echo "Command for uploading to pypi: $upload_command"
$upload_command
fi

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