spark-instrumented-optimizer/python/setup.py
Shuai Lin bd9a4a5ac3
[SPARK-18652][PYTHON] Include the example data and third-party licenses in pyspark package.
## What changes were proposed in this pull request?

Since we already include the python examples in the pyspark package, we should include the example data with it as well.

We should also include the third-party licences since we distribute their jars with the pyspark package.

## How was this patch tested?

Manually tested with python2.7 and python3.4
```sh
$ ./build/mvn -DskipTests -Phive -Phive-thriftserver -Pyarn -Pmesos clean package
$ cd python
$ python setup.py sdist
$ pip install  dist/pyspark-2.1.0.dev0.tar.gz

$ ls -1 /usr/local/lib/python2.7/dist-packages/pyspark/data/
graphx
mllib
streaming

$ du -sh /usr/local/lib/python2.7/dist-packages/pyspark/data/
600K    /usr/local/lib/python2.7/dist-packages/pyspark/data/

$ ls -1  /usr/local/lib/python2.7/dist-packages/pyspark/licenses/|head -5
LICENSE-AnchorJS.txt
LICENSE-DPark.txt
LICENSE-Mockito.txt
LICENSE-SnapTree.txt
LICENSE-antlr.txt
```

Author: Shuai Lin <linshuai2012@gmail.com>

Closes #16082 from lins05/include-data-in-pyspark-dist.
2016-12-07 06:09:27 +08:00

228 lines
9.3 KiB
Python

#!/usr/bin/env python
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You 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.
from __future__ import print_function
import glob
import os
import sys
from setuptools import setup, find_packages
from shutil import copyfile, copytree, rmtree
if sys.version_info < (2, 7):
print("Python versions prior to 2.7 are not supported for pip installed PySpark.",
file=sys.stderr)
exit(-1)
try:
exec(open('pyspark/version.py').read())
except IOError:
print("Failed to load PySpark version file for packaging. You must be in Spark's python dir.",
file=sys.stderr)
sys.exit(-1)
VERSION = __version__
# A temporary path so we can access above the Python project root and fetch scripts and jars we need
TEMP_PATH = "deps"
SPARK_HOME = os.path.abspath("../")
# Provide guidance about how to use setup.py
incorrect_invocation_message = """
If you are installing pyspark from spark source, you must first build Spark and
run sdist.
To build Spark with maven you can run:
./build/mvn -DskipTests clean package
Building the source dist is done in the Python directory:
cd python
python setup.py sdist
pip install dist/*.tar.gz"""
# Figure out where the jars are we need to package with PySpark.
JARS_PATH = glob.glob(os.path.join(SPARK_HOME, "assembly/target/scala-*/jars/"))
if len(JARS_PATH) == 1:
JARS_PATH = JARS_PATH[0]
elif (os.path.isfile("../RELEASE") and len(glob.glob("../jars/spark*core*.jar")) == 1):
# Release mode puts the jars in a jars directory
JARS_PATH = os.path.join(SPARK_HOME, "jars")
elif len(JARS_PATH) > 1:
print("Assembly jars exist for multiple scalas ({0}), please cleanup assembly/target".format(
JARS_PATH), file=sys.stderr)
sys.exit(-1)
elif len(JARS_PATH) == 0 and not os.path.exists(TEMP_PATH):
print(incorrect_invocation_message, file=sys.stderr)
sys.exit(-1)
EXAMPLES_PATH = os.path.join(SPARK_HOME, "examples/src/main/python")
SCRIPTS_PATH = os.path.join(SPARK_HOME, "bin")
DATA_PATH = os.path.join(SPARK_HOME, "data")
LICENSES_PATH = os.path.join(SPARK_HOME, "licenses")
SCRIPTS_TARGET = os.path.join(TEMP_PATH, "bin")
JARS_TARGET = os.path.join(TEMP_PATH, "jars")
EXAMPLES_TARGET = os.path.join(TEMP_PATH, "examples")
DATA_TARGET = os.path.join(TEMP_PATH, "data")
LICENSES_TARGET = os.path.join(TEMP_PATH, "licenses")
# Check and see if we are under the spark path in which case we need to build the symlink farm.
# This is important because we only want to build the symlink farm while under Spark otherwise we
# want to use the symlink farm. And if the symlink farm exists under while under Spark (e.g. a
# partially built sdist) we should error and have the user sort it out.
in_spark = (os.path.isfile("../core/src/main/scala/org/apache/spark/SparkContext.scala") or
(os.path.isfile("../RELEASE") and len(glob.glob("../jars/spark*core*.jar")) == 1))
def _supports_symlinks():
"""Check if the system supports symlinks (e.g. *nix) or not."""
return getattr(os, "symlink", None) is not None
if (in_spark):
# Construct links for setup
try:
os.mkdir(TEMP_PATH)
except:
print("Temp path for symlink to parent already exists {0}".format(TEMP_PATH),
file=sys.stderr)
exit(-1)
try:
# We copy the shell script to be under pyspark/python/pyspark so that the launcher scripts
# find it where expected. The rest of the files aren't copied because they are accessed
# using Python imports instead which will be resolved correctly.
try:
os.makedirs("pyspark/python/pyspark")
except OSError:
# Don't worry if the directory already exists.
pass
copyfile("pyspark/shell.py", "pyspark/python/pyspark/shell.py")
if (in_spark):
# Construct the symlink farm - this is necessary since we can't refer to the path above the
# package root and we need to copy the jars and scripts which are up above the python root.
if _supports_symlinks():
os.symlink(JARS_PATH, JARS_TARGET)
os.symlink(SCRIPTS_PATH, SCRIPTS_TARGET)
os.symlink(EXAMPLES_PATH, EXAMPLES_TARGET)
os.symlink(DATA_PATH, DATA_TARGET)
os.symlink(LICENSES_PATH, LICENSES_TARGET)
else:
# For windows fall back to the slower copytree
copytree(JARS_PATH, JARS_TARGET)
copytree(SCRIPTS_PATH, SCRIPTS_TARGET)
copytree(EXAMPLES_PATH, EXAMPLES_TARGET)
copytree(DATA_PATH, DATA_TARGET)
copytree(LICENSES_PATH, LICENSES_TARGET)
else:
# If we are not inside of SPARK_HOME verify we have the required symlink farm
if not os.path.exists(JARS_TARGET):
print("To build packaging must be in the python directory under the SPARK_HOME.",
file=sys.stderr)
if not os.path.isdir(SCRIPTS_TARGET):
print(incorrect_invocation_message, file=sys.stderr)
exit(-1)
# Scripts directive requires a list of each script path and does not take wild cards.
script_names = os.listdir(SCRIPTS_TARGET)
scripts = list(map(lambda script: os.path.join(SCRIPTS_TARGET, script), script_names))
# We add find_spark_home.py to the bin directory we install so that pip installed PySpark
# will search for SPARK_HOME with Python.
scripts.append("pyspark/find_spark_home.py")
# Parse the README markdown file into rst for PyPI
long_description = "!!!!! missing pandoc do not upload to PyPI !!!!"
try:
import pypandoc
long_description = pypandoc.convert('README.md', 'rst')
except ImportError:
print("Could not import pypandoc - required to package PySpark", file=sys.stderr)
setup(
name='pyspark',
version=VERSION,
description='Apache Spark Python API',
long_description=long_description,
author='Spark Developers',
author_email='dev@spark.apache.org',
url='https://github.com/apache/spark/tree/master/python',
packages=['pyspark',
'pyspark.mllib',
'pyspark.ml',
'pyspark.sql',
'pyspark.streaming',
'pyspark.bin',
'pyspark.jars',
'pyspark.python.pyspark',
'pyspark.python.lib',
'pyspark.data',
'pyspark.licenses',
'pyspark.examples.src.main.python'],
include_package_data=True,
package_dir={
'pyspark.jars': 'deps/jars',
'pyspark.bin': 'deps/bin',
'pyspark.python.lib': 'lib',
'pyspark.data': 'deps/data',
'pyspark.licenses': 'deps/licenses',
'pyspark.examples.src.main.python': 'deps/examples',
},
package_data={
'pyspark.jars': ['*.jar'],
'pyspark.bin': ['*'],
'pyspark.python.lib': ['*.zip'],
'pyspark.data': ['*.txt', '*.data'],
'pyspark.licenses': ['*.txt'],
'pyspark.examples.src.main.python': ['*.py', '*/*.py']},
scripts=scripts,
license='http://www.apache.org/licenses/LICENSE-2.0',
install_requires=['py4j==0.10.4'],
setup_requires=['pypandoc'],
extras_require={
'ml': ['numpy>=1.7'],
'mllib': ['numpy>=1.7'],
'sql': ['pandas']
},
classifiers=[
'Development Status :: 5 - Production/Stable',
'License :: OSI Approved :: Apache Software License',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: Implementation :: CPython',
'Programming Language :: Python :: Implementation :: PyPy']
)
finally:
# We only cleanup the symlink farm if we were in Spark, otherwise we are installing rather than
# packaging.
if (in_spark):
# Depending on cleaning up the symlink farm or copied version
if _supports_symlinks():
os.remove(os.path.join(TEMP_PATH, "jars"))
os.remove(os.path.join(TEMP_PATH, "bin"))
os.remove(os.path.join(TEMP_PATH, "examples"))
os.remove(os.path.join(TEMP_PATH, "data"))
os.remove(os.path.join(TEMP_PATH, "licenses"))
else:
rmtree(os.path.join(TEMP_PATH, "jars"))
rmtree(os.path.join(TEMP_PATH, "bin"))
rmtree(os.path.join(TEMP_PATH, "examples"))
rmtree(os.path.join(TEMP_PATH, "data"))
rmtree(os.path.join(TEMP_PATH, "licenses"))
os.rmdir(TEMP_PATH)