<commit_before>import os
import re

from setuptools import find_packages, setup

this_dir = os.path.abspath(os.path.dirname(__file__))

with open(os.path.join(this_dir, "README.md"), encoding="utf-8") as f:
    long_description = f.read()


with open("megnet/__init__.py", encoding="utf-8") as fd:
    try:
        lines = ""
        for item in fd.readlines():
            item = item
            lines += item + "\n"
    except Exception as exc:
        raise Exception(f"Caught exception {exc}")


version = re.search('__version__ = "(.*)"', lines).group(1)


setup(
    name="megnet",
    version=version,
    description="MatErials Graph Networks for machine learning of molecules and crystals.",
    long_description=long_description,
    long_description_content_type="text/markdown",
    author="<NAME>",
    author_email="<EMAIL>",
    download_url="https://github.com/materialsvirtuallab/megnet",
    license="BSD",
    install_requires=["numpy", "scikit-learn", "pymatgen>=2019.10.4", "monty"],
    extras_require={
        "model_saving": ["h5py"],
        "molecules": ["openbabel", "rdkit"],
        "tensorflow": ["tensorflow>=2.1"],
        "tensorflow with gpu": ["tensorflow-gpu>=2.1"],
    },
    packages=find_packages(),
    package_data={
        "megnet": ["*.json", "*.md"],
    },
    include_package_data=True,
    keywords=["materials", "science", "machine", "learning", "deep", "graph", "networks", "neural"],
    classifiers=[<commit_msg>Add tqdm to setup.py<commit_after>import os
import re

from setuptools import find_packages, setup

this_dir = os.path.abspath(os.path.dirname(__file__))

with open(os.path.join(this_dir, "README.md"), encoding="utf-8") as f:
    long_description = f.read()


with open("megnet/__init__.py", encoding="utf-8") as fd:
    try:
        lines = ""
        for item in fd.readlines():
            item = item
            lines += item + "\n"
    except Exception as exc:
        raise Exception(f"Caught exception {exc}")


version = re.search('__version__ = "(.*)"', lines).group(1)


setup(
    name="megnet",
    version=version,
    description="MatErials Graph Networks for machine learning of molecules and crystals.",
    long_description=long_description,
    long_description_content_type="text/markdown",
    author="<NAME>",
    author_email="<EMAIL>",
    download_url="https://github.com/materialsvirtuallab/megnet",
    license="BSD",
    install_requires=["numpy", "scikit-learn", "pymatgen>=2019.10.4", "monty", "tqdm"],
    extras_require={
        "model_saving": ["h5py"],
        "molecules": ["openbabel", "rdkit"],
        "tensorflow": ["tensorflow>=2.1"],
        "tensorflow with gpu": ["tensorflow-gpu>=2.1"],
    },
    packages=find_packages(),
    package_data={
        "megnet": ["*.json", "*.md"],
    },
    include_package_data=True,
    keywords=["materials", "science", "machine", "learning", "deep", "graph", "networks", "neural"],
    classifiers=[
{'fraction_non_alphanumeric': 0.1702271956595456, 'fraction_numerical': 0.01017293997965412, 'mean_word_length': 3.56656346749226, 'pattern_counts': {'":': 10, '<': 7, '<?xml version=': 0, '>': 13, 'https://': 2, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2153392', 'n_tokens_mistral': 991, 'n_tokens_neox': 946, 'n_words': 195}