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setup.py
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setup.py
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# SPDX-License-Identifier: MIT
# Copyright (c) 2019 Intel Corporation
import os
import sys
import ast
import site
import pathlib
from io import open
import importlib.util
from setuptools import find_packages, setup
# See https://github.com/pypa/pip/issues/7953
site.ENABLE_USER_SITE = "--user" in sys.argv[1:]
class InstallException(Exception):
pass
if sys.version_info.major != 3 and sys.version_info.minor < 7:
raise InstallException("dffml is incompatible with Python version < 3.7!")
with open(pathlib.Path("dffml", "version.py"), "r") as f:
for line in f:
if line.startswith("VERSION"):
VERSION = ast.literal_eval(line.strip().split("=")[-1].strip())
break
# Load file by path
spec = importlib.util.spec_from_file_location(
"plugins", os.path.join(os.path.dirname(__file__), "dffml", "plugins.py")
)
plugins = importlib.util.module_from_spec(spec)
spec.loader.exec_module(plugins)
with open("README.md", "r", encoding="utf-8") as f:
README = f.read()
REQUIREMENTS_DEV_TXT_PATH = pathlib.Path("requirements-dev.txt")
if REQUIREMENTS_DEV_TXT_PATH.is_file():
DEV_REQUIRES = list(
map(
lambda i: i.strip(),
REQUIREMENTS_DEV_TXT_PATH.read_text().split("\n"),
)
)
setup(
name="dffml",
version=VERSION,
description="Data Flow Facilitator for Machine Learning",
long_description=README,
long_description_content_type="text/markdown",
author="John Andersen",
author_email="[email protected]",
maintainer="John Andersen",
maintainer_email="[email protected]",
url="https://github.com/intel/dffml",
license="MIT",
keywords=[""],
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"License :: OSI Approved :: MIT License",
"Natural Language :: English",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3 :: Only",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: Implementation :: CPython",
"Programming Language :: Python :: Implementation :: PyPy",
],
packages=find_packages(),
include_package_data=True,
zip_safe=False,
# Temporary until we split consoletest into it's own package
install_requires=["httptest>=0.0.17"],
extras_require={
"dev": DEV_REQUIRES,
**plugins.PACKAGE_NAMES_BY_PLUGIN_INSTALLABLE,
},
entry_points={
"console_scripts": ["dffml = dffml.cli.cli:CLI.main"],
"dffml.source": [
"csv = dffml.source.csv:CSVSource",
"json = dffml.source.json:JSONSource",
"memory = dffml.source.memory:MemorySource",
"idx1 = dffml.source.idx1:IDX1Source",
"idx3 = dffml.source.idx3:IDX3Source",
"db = dffml.source.db:DbSource",
"ini = dffml.source.ini:INISource",
"dfpreprocess = dffml.source.dfpreprocess:DataFlowPreprocessSource",
"op = dffml.source.op:OpSource",
"df = dffml.source.df:DataFlowSource",
"dir = dffml.source.dir:DirectorySource",
"dataframe = dffml.source.dataframe:DataFrameSource",
"iris.training = dffml.source.dataset.iris:iris_training.source",
],
"dffml.port": ["json = dffml.port.json:JSON"],
"dffml.service.cli": ["dev = dffml.service.dev:Develop"],
"dffml.configloader": [
"json = dffml.configloader.json:JSONConfigLoader"
],
# Data Flow
"dffml.operation": [
# Output
"group_by = dffml.operation.output:GroupBy",
"get_single = dffml.operation.output:GetSingle",
"get_multi = dffml.operation.output:GetMulti",
"associate = dffml.operation.output:Associate",
"associate_definition = dffml.operation.output:AssociateDefinition",
# Mapping
"dffml.mapping.extract = dffml.operation.mapping:mapping_extract_value",
"dffml.mapping.create = dffml.operation.mapping:create_mapping",
# Dataflow
"dffml.dataflow.run = dffml.operation.dataflow:run_dataflow",
# Model
"dffml.model.predict = dffml.operation.model:model_predict",
# io
"AcceptUserInput = dffml.operation.io:AcceptUserInput",
"print_output = dffml.operation.io:print_output",
# preprocess
"literal_eval = dffml.operation.preprocess:literal_eval",
# math
"multiply = dffml.operation.math:multiply",
# Database
"db_query_create_table = dffml.operation.db:db_query_create_table",
"db_query_insert = dffml.operation.db:db_query_insert",
"db_query_update = dffml.operation.db:db_query_update",
"db_query_remove = dffml.operation.db:db_query_remove",
"db_query_insert_or_update = dffml.operation.db:db_query_insert_or_update",
"db_query_lookup = dffml.operation.db:db_query_lookup",
# Archive
"make_zip_archive = dffml.operation.archive:make_zip_archive",
"extract_zip_archive = dffml.operation.archive:extract_zip_archive",
"make_tar_archive = dffml.operation.archive:make_tar_archive",
"extract_tar_archive = dffml.operation.archive:extract_tar_archive",
# Compression
"gz_compress = dffml.operation.compression:gz_compress",
"gz_decompress = dffml.operation.compression:gz_decompress",
"bz2_compress = dffml.operation.compression:bz2_compress",
"bz2_decompress = dffml.operation.compression:bz2_decompress",
"xz_compress = dffml.operation.compression:xz_compress",
"xz_decompress = dffml.operation.compression:xz_decompress",
# Source
"convert_list_to_records = dffml.operation.source:convert_list_to_records",
"convert_records_to_list = dffml.operation.source:convert_records_to_list",
],
"dffml.kvstore": ["memory = dffml.df.memory:MemoryKeyValueStore"],
"dffml.input.network": ["memory = dffml.df.memory:MemoryInputNetwork"],
"dffml.operation.network": [
"memory = dffml.df.memory:MemoryOperationNetwork"
],
"dffml.redundancy.checker": [
"memory = dffml.df.memory:MemoryRedundancyChecker"
],
"dffml.lock.network": ["memory = dffml.df.memory:MemoryLockNetwork"],
"dffml.operation.implementation.network": [
"memory = dffml.df.memory:MemoryOperationImplementationNetwork"
],
"dffml.orchestrator": ["memory = dffml.df.memory:MemoryOrchestrator"],
# Databases
"dffml.db": ["sqlite = dffml.db.sqlite:SqliteDatabase"],
# Models
"dffml.model": ["slr = dffml.model.slr:SLRModel"],
# Secrets
"dffml.secret": ["ini = dffml.secret.ini:INISecret"],
# Accuracy
"dffml.accuracy": [
"mse = dffml.accuracy.mse:MeanSquaredErrorAccuracy",
"clf = dffml.accuracy.clf:ClassificationAccuracy",
],
# Tuner
"dffml.tuner": [
"parameter_grid = dffml.tuner.parameter_grid:ParameterGrid",
],
},
)