#!/usr/bin/env python
# -*- coding: utf-8 -*-

# pylint: skip-file

import os
import sys
from pathlib import Path

from pkg_resources import parse_version
from setuptools import find_packages, setup


# We do not want to install tensorflow in the readthedocs environment, where we
# use autodoc_mock_imports instead. Hence we use this flag to decide whether or
# not to append tensorflow and tensorflow_probability to the requirements:
on_readthedocs = os.environ.get("READTHEDOCS", None) == "True"


# Dependencies of GPflow
requirements = [
    "numpy>=1.10.0",
    "scipy>=0.18.0",
    "multipledispatch>=0.6",
    "tabulate",
    "typing_extensions",
]

if sys.version_info < (3, 7):
    # became part of stdlib in python 3.7
    requirements.append("dataclasses")

if not on_readthedocs:
    requirements.append("tensorflow-probability>=0.9")

min_tf_version = "2.1.0"
tf_cpu = "tensorflow"
tf_gpu = "tensorflow-gpu"


# for latest_version() [see https://github.com/GPflow/GPflow/issues/1348]:
def latest_version(package_name):
    import json
    from urllib import request
    import re

    url = f"https://pypi.python.org/pypi/{package_name}/json"
    data = json.load(request.urlopen(url))
    # filter out rc and beta releases and, more generally, any releases that
    # do not contain exclusively numbers and dots.
    versions = [parse_version(v) for v in data["releases"].keys() if re.match("^[0-9.]+$", v)]
    versions.sort()
    return versions[-1]  # return latest version


# Only detect TF if not installed or outdated. If not, do not do not list as
# requirement to avoid installing over e.g. tensorflow-gpu
# To avoid this, rely on importing rather than the package name (like pip).

try:
    # If tf not installed, import raises ImportError
    import tensorflow as tf

    if parse_version(tf.__version__) < parse_version(min_tf_version):
        # TF pre-installed, but below the minimum required version
        raise DeprecationWarning("TensorFlow version below minimum requirement")
except (ImportError, DeprecationWarning):
    # Add TensorFlow to dependencies to trigger installation/update
    if not on_readthedocs:
        # Do not add TF if we are installing GPflow on readthedocs
        requirements.append(tf_cpu)
        gast_requirement = (
            "gast>=0.2.2,<0.3"
            if latest_version("tensorflow") < parse_version("2.2")
            else "gast>=0.3.3"
        )
        requirements.append(gast_requirement)


def read_file(filename):
    with open(filename, encoding="utf-8") as f:
        return f.read().strip()


version = read_file("VERSION")
readme_text = read_file("README.md")

packages = find_packages(".", exclude=["tests"])

setup(
    name="gpflow",
    version=version,
    author="James Hensman, Alex Matthews",
    author_email="james.hensman@gmail.com",
    description="Gaussian process methods in TensorFlow",
    long_description=readme_text,
    long_description_content_type="text/markdown",
    license="Apache License 2.0",
    keywords="machine-learning gaussian-processes kernels tensorflow",
    url="https://www.gpflow.org",
    project_urls={
        "Source on GitHub": "https://github.com/GPflow/GPflow",
        "Documentation": "https://gpflow.readthedocs.io",
    },
    packages=packages,
    include_package_data=True,
    install_requires=requirements,
    extras_require={"Tensorflow with GPU": [tf_gpu], "ImageToTensorBoard": ["matplotlib"]},
    python_requires=">=3.6",
    classifiers=[
        "License :: OSI Approved :: Apache Software License",
        "Natural Language :: English",
        "Operating System :: MacOS :: MacOS X",
        "Operating System :: Microsoft :: Windows",
        "Operating System :: POSIX :: Linux",
        "Programming Language :: Python :: 3.6",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
    ],
)