setup.py

# Copyright 2019 The ASReview Authors. All Rights Reserved.
#
# 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.

# based on https://github.com/pypa/sampleproject - MIT License

# Always prefer setuptools over distutils
import re
import subprocess
from io import open
from os import path
from pathlib import Path

from setuptools import Command
from setuptools import find_packages
from setuptools import setup

import versioneer


def get_long_description():
    """Get project description based on README."""
    here = path.abspath(path.dirname(__file__))

    # Get the long description from the README file
    with open(path.join(here, "README.md"), encoding="utf-8") as f:
        long_description = f.read()

    # remove emoji
    long_description = re.sub(r"\:[a-z_]+\:", "", long_description)

    return long_description


DEPS = {
    "sbert": ["sentence_transformers"],
    "doc2vec": ["gensim"],
    "tensorflow": ["tensorflow~=2.0"],
    "dev": ["black", "check-manifest", "flake8", "flake8-isort", "isort"],
    "test": ["coverage", "pytest", "pytest-random-order"],
}
DEPS["all"] = DEPS["sbert"] + DEPS["doc2vec"]
DEPS["all"] += DEPS["tensorflow"]


class CompileAssets(Command):
    """
    Compile and build the frontend assets using npm and webpack.

    Registered as cmdclass in setup() so it can be called with
    ``python setup.py compile_assets``.
    """

    description = "Compile and build the frontend assets"
    user_options = []

    def initialize_options(self):
        """Set default values for options."""

    def finalize_options(self):
        """Set final values for options."""

    def run(self):
        """Run a command to compile and build assets."""

        path_webapp = Path(__file__).parent / "asreview" / "webapp"

        subprocess.check_call(["npm", "install"], cwd=str(path_webapp))
        subprocess.check_call(["npm", "run-script", "build"], cwd=str(path_webapp))


def get_cmdclass():
    cmdclass = versioneer.get_cmdclass()
    cmdclass["compile_assets"] = CompileAssets
    return cmdclass


setup(
    name="asreview",
    version=versioneer.get_version(),
    cmdclass=get_cmdclass(),
    description="ASReview LAB - A tool for AI-assisted systematic reviews",
    long_description=get_long_description(),
    long_description_content_type="text/markdown",
    url="https://github.com/asreview/asreview",
    author="ASReview LAB developers",
    author_email="asreview@uu.nl",
    classifiers=[
        "Development Status :: 5 - Production/Stable",
        "License :: OSI Approved :: Apache Software License",
        "Programming Language :: Python :: 3",
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Programming Language :: Python :: 3.11",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Scientific/Engineering :: Information Analysis",
        "Topic :: Text Processing :: General",
        "Framework :: Flask",
    ],
    keywords=["systematic review", "machine-learning"],
    packages=find_packages(exclude=["contrib", "docs", "tests"]),
    package_data={
        "asreview": [
            "webapp/build/*",
            "webapp/build/static/*/*",
        ]
    },
    python_requires="~=3.8",
    install_requires=[
        "numpy",
        "pandas>=1,<3",
        "scikit-learn",
        "rispy~=0.7.0",
        "xlrd>=1.0.0",
        "setuptools",
        "flask>=2.0",
        "flask_cors",
        "flask-login",
        "flask-mail",
        "openpyxl",
        "jsonschema",
        "filelock",
        "Flask-SQLAlchemy>=3.0.2",
        "requests",
        "tqdm",
        "gevent>=20",
        "datahugger>=0.2",
    ],
    extras_require=DEPS,
    entry_points={
        "console_scripts": [
            "asreview=asreview.__main__:main",
        ],
        "asreview.entry_points": [
            "lab=asreview.entry_points:LABEntryPoint",
            "web_run_model=asreview.entry_points:WebRunModelEntryPoint",
            "simulate=asreview.entry_points:SimulateEntryPoint",
            "algorithms=asreview.entry_points:AlgorithmsEntryPoint",
            "state-inspect=asreview.entry_points:StateInspectEntryPoint",
            "auth-tool=asreview.entry_points:AuthTool",
        ],
        "asreview.readers": [
            ".csv = asreview.io:CSVReader",
            ".tab = asreview.io:CSVReader",
            ".tsv = asreview.io:CSVReader",
            ".ris = asreview.io:RISReader",
            ".txt = asreview.io:RISReader",
            ".xlsx = asreview.io:ExcelReader",
        ],
        "asreview.writers": [
            ".csv = asreview.io:CSVWriter",
            ".tab = asreview.io:TSVWriter",
            ".tsv = asreview.io:TSVWriter",
            ".ris = asreview.io:RISWriter",
            ".txt = asreview.io:RISWriter",
            ".xlsx = asreview.io:ExcelWriter",
        ],
        "asreview.datasets": [
            "benchmark = asreview.datasets:BenchmarkDataGroup",
            "benchmark-nature = asreview.datasets:NaturePublicationDataGroup",
        ],
        "asreview.models.classifiers": [
            "svm = asreview.models.classifiers:SVMClassifier",
            "nb = asreview.models.classifiers:NaiveBayesClassifier",
            "rf = asreview.models.classifiers:RandomForestClassifier",
            "nn-2-layer = asreview.models.classifiers:NN2LayerClassifier",
            "logistic = asreview.models.classifiers:LogisticClassifier",
            "lstm-base = asreview.models.classifiers:LSTMBaseClassifier",
            "lstm-pool = asreview.models.classifiers:LSTMPoolClassifier",
        ],
        "asreview.models.feature_extraction": [
            "doc2vec = asreview.models.feature_extraction:Doc2Vec",
            "embedding-idf = asreview.models.feature_extraction:EmbeddingIdf",
            "embedding-lstm = asreview.models.feature_extraction:EmbeddingLSTM",
            "sbert = asreview.models.feature_extraction:SBERT",
            "tfidf = asreview.models.feature_extraction:Tfidf",
        ],
        "asreview.models.balance": [
            "simple = asreview.models.balance:SimpleBalance",
            "double = asreview.models.balance:DoubleBalance",
            # "triple = asreview.models.balance:TripleBalance",  # Broken, only via API
            "undersample = asreview.models.balance:UndersampleBalance",
        ],
        "asreview.models.query": [
            "max = asreview.models.query.max:MaxQuery",
            "random = asreview.models.query.random:RandomQuery",
            "uncertainty = asreview.models.query.uncertainty:UncertaintyQuery",
            "cluster = asreview.models.query.cluster:ClusterQuery",
            "max_random = asreview.models.query.mixed:MaxRandomQuery",
            "max_uncertainty = asreview.models.query.mixed:MaxUncertaintyQuery",
        ],
    },
    project_urls={
        "Bug Reports": "https://github.com/asreview/asreview/issues",
        "Source": "https://github.com/asreview/asreview/",
    },
)