python/setup.py

#!/usr/bin/env python3

#
# 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.

import importlib.util
import glob
import os
import sys
import ctypes
from setuptools import setup
from setuptools.command.install import install
from shutil import copyfile, copytree, rmtree

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)
try:
    spec = importlib.util.spec_from_file_location("install", "pyspark/install.py")
    install_module = importlib.util.module_from_spec(spec)
    spec.loader.exec_module(install_module)
except IOError:
    print(
        "Failed to load the installing module (pyspark/install.py) which had to be "
        "packaged together.",
        file=sys.stderr,
    )
    sys.exit(-1)
VERSION = __version__  # noqa
# 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")
USER_SCRIPTS_PATH = os.path.join(SPARK_HOME, "sbin")
DATA_PATH = os.path.join(SPARK_HOME, "data")
LICENSES_PATH = os.path.join(SPARK_HOME, "licenses")

SCRIPTS_TARGET = os.path.join(TEMP_PATH, "bin")
USER_SCRIPTS_TARGET = os.path.join(TEMP_PATH, "sbin")
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 hasattr(os, "symlink") and (
        (not hasattr(ctypes, "windll"))  # Non-Windows
        or (
            # In some Windows, `os.symlink` works but only for admins.
            hasattr(ctypes.windll, "shell32")
            and hasattr(ctypes.windll.shell32, "IsUserAnAdmin")
            and bool(ctypes.windll.shell32.IsUserAnAdmin())
        )
    )


if in_spark:
    # Construct links for setup
    try:
        os.mkdir(TEMP_PATH)
    except BaseException:
        print(
            "Temp path for symlink to parent already exists {0}".format(TEMP_PATH), file=sys.stderr
        )
        sys.exit(-1)

# If you are changing the versions here, please also change ./python/pyspark/sql/pandas/utils.py
# For Arrow, you should also check ./pom.xml and ensure there are no breaking changes in the
# binary format protocol with the Java version, see ARROW_HOME/format/* for specifications.
# Also don't forget to update python/docs/source/getting_started/install.rst.
_minimum_pandas_version = "1.0.5"
_minimum_pyarrow_version = "1.0.0"
_minimum_grpc_version = "1.48.1"
_minimum_googleapis_common_protos_version = "1.56.4"


class InstallCommand(install):
    # TODO(SPARK-32837) leverage pip's custom options

    def run(self):
        install.run(self)

        # Make sure the destination is always clean.
        spark_dist = os.path.join(self.install_lib, "pyspark", "spark-distribution")
        rmtree(spark_dist, ignore_errors=True)

        if ("PYSPARK_HADOOP_VERSION" in os.environ) or ("PYSPARK_HIVE_VERSION" in os.environ):
            # Note that PYSPARK_VERSION environment is just a testing purpose.
            # PYSPARK_HIVE_VERSION environment variable is also internal for now in case
            # we support another version of Hive in the future.
            spark_version, hadoop_version, hive_version = install_module.checked_versions(
                os.environ.get("PYSPARK_VERSION", VERSION).lower(),
                os.environ.get("PYSPARK_HADOOP_VERSION", install_module.DEFAULT_HADOOP).lower(),
                os.environ.get("PYSPARK_HIVE_VERSION", install_module.DEFAULT_HIVE).lower(),
            )

            if "PYSPARK_VERSION" not in os.environ and (
                (install_module.DEFAULT_HADOOP, install_module.DEFAULT_HIVE)
                == (hadoop_version, hive_version)
            ):
                # Do not download and install if they are same as default.
                return

            install_module.install_spark(
                dest=spark_dist,
                spark_version=spark_version,
                hadoop_version=hadoop_version,
                hive_version=hive_version,
            )


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(USER_SCRIPTS_PATH, USER_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(USER_SCRIPTS_PATH, USER_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)
        sys.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")

    with open("README.md") as f:
        long_description = f.read()

    setup(
        name="pyspark",
        version=VERSION,
        description="Apache Spark Python API",
        long_description=long_description,
        long_description_content_type="text/markdown",
        author="Spark Developers",
        author_email="dev@spark.apache.org",
        url="https://github.com/apache/spark/tree/master/python",
        packages=[
            "pyspark",
            "pyspark.cloudpickle",
            "pyspark.mllib",
            "pyspark.mllib.linalg",
            "pyspark.mllib.stat",
            "pyspark.ml",
            "pyspark.ml.linalg",
            "pyspark.ml.param",
            "pyspark.ml.torch",
            "pyspark.sql",
            "pyspark.sql.avro",
            "pyspark.sql.connect",
            "pyspark.sql.connect.proto",
            "pyspark.sql.pandas",
            "pyspark.sql.protobuf",
            "pyspark.sql.streaming",
            "pyspark.streaming",
            "pyspark.bin",
            "pyspark.sbin",
            "pyspark.jars",
            "pyspark.pandas",
            "pyspark.pandas.data_type_ops",
            "pyspark.pandas.indexes",
            "pyspark.pandas.missing",
            "pyspark.pandas.plot",
            "pyspark.pandas.spark",
            "pyspark.pandas.typedef",
            "pyspark.pandas.usage_logging",
            "pyspark.python.pyspark",
            "pyspark.python.lib",
            "pyspark.data",
            "pyspark.licenses",
            "pyspark.resource",
            "pyspark.errors",
            "pyspark.errors.exceptions",
            "pyspark.examples.src.main.python",
        ],
        include_package_data=True,
        package_dir={
            "pyspark.jars": "deps/jars",
            "pyspark.bin": "deps/bin",
            "pyspark.sbin": "deps/sbin",
            "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.sbin": [
                "spark-config.sh",
                "spark-daemon.sh",
                "start-history-server.sh",
                "stop-history-server.sh",
            ],
            "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",
        # Don't forget to update python/docs/source/getting_started/install.rst
        # if you're updating the versions or dependencies.
        install_requires=["py4j==0.10.9.7"],
        extras_require={
            "ml": ["numpy>=1.15"],
            "mllib": ["numpy>=1.15"],
            "sql": [
                "pandas>=%s" % _minimum_pandas_version,
                "pyarrow>=%s" % _minimum_pyarrow_version,
                "numpy>=1.15",
            ],
            "pandas_on_spark": [
                "pandas>=%s" % _minimum_pandas_version,
                "pyarrow>=%s" % _minimum_pyarrow_version,
                "numpy>=1.15",
            ],
            "connect": [
                "pandas>=%s" % _minimum_pandas_version,
                "pyarrow>=%s" % _minimum_pyarrow_version,
                "grpcio>=%s" % _minimum_grpc_version,
                "grpcio-status>=%s" % _minimum_grpc_version,
                "googleapis-common-protos>=%s" % _minimum_googleapis_common_protos_version,
                "numpy>=1.15",
            ],
        },
        python_requires=">=3.7",
        classifiers=[
            "Development Status :: 5 - Production/Stable",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Programming Language :: Python :: 3.9",
            "Programming Language :: Python :: 3.10",
            "Programming Language :: Python :: 3.11",
            "Programming Language :: Python :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy",
            "Typing :: Typed",
        ],
        cmdclass={
            "install": InstallCommand,
        },
    )
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, "sbin"))
            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, "sbin"))
            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)