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How to use conda_install method in pandera

Best Python code snippet using pandera_python

runtimes.py

Source:runtimes.py

1import os2import hashlib3CONDA_DEFAULT_LIST = ["tblib", 4                      "numpy", 5                      "pytest", 6                      "Click", 7                      "numba", 8                      "boto3", 9                      "PyYAML", 10                      'six',11                      "cython", 'future']12PIP_DEFAULT_LIST = ['glob2', 'boto', 'certifi']13PIP_DEFAULT_UPGRADE_LIST = ['cloudpickle', 'enum34']14CONDA_ML_SET = ['scipy', 'pillow', 'cvxopt', 'scikit-learn']15PIP_ML_SET = ['cvxpy', 'redis']16CONDA_OPT_SET = ['scipy', 'cvxopt', ('mosek', 'mosek')]17PIP_OPT_SET = ['cvxpy' ]18RUNTIMES = {'minimal' : {'pythonvers' : ["2.7", "3.5", "3.6"],  19                         'packages' : { 20                             'conda_install' : CONDA_DEFAULT_LIST, 21                             'pip_install' : PIP_DEFAULT_LIST, 22                             'pip_upgrade' : PIP_DEFAULT_UPGRADE_LIST}},23            'ml' : {'pythonvers' :  ["2.7", "3.5", "3.6"],24                    'packages' : {25                        'conda_install' : CONDA_DEFAULT_LIST + CONDA_ML_SET, 26                        'pip_install' : PIP_DEFAULT_LIST + PIP_ML_SET, 27                        'pip_upgrade' : PIP_DEFAULT_UPGRADE_LIST }},28            'default' : {'pythonvers' : ["2.7", "3.5", "3.6"], 29                         'packages' : {30                             'conda_install' : CONDA_DEFAULT_LIST + CONDA_ML_SET, 31                             'pip_install' : PIP_DEFAULT_LIST + PIP_ML_SET, 32                             'pip_upgrade' : PIP_DEFAULT_UPGRADE_LIST}}, 33            'opt' : {'pythonvers' : ["2.7"], 34                         'packages' : {35                             'conda_install' : CONDA_DEFAULT_LIST + CONDA_OPT_SET, 36                             'pip_install' : PIP_DEFAULT_LIST + PIP_OPT_SET, 37                             'pip_upgrade' : PIP_DEFAULT_UPGRADE_LIST }}38}39CONDA_TEST_STRS = {'numpy' : "__import__('numpy')", 40                   'pytest' : "__import__('pytest')", 41                   "numba" : "__import__('numba')", 42                   "boto3" : "__import__('boto3')", 43                   "PyYAML" : "__import__('yaml')", 44                   "boto" : "__import__('boto')", 45                   "scipy" : "__import__('scipy')", 46                   "pillow" : "__import__('PIL.Image')", 47                   "cvxopt" : "__import__('cvxopt')", 48                   "scikit-image" : "__import__('skimage')", 49                   "scikit-learn" : "__import__('sklearn')"}50PIP_TEST_STRS = {"glob2" : "__import__('glob2')", 51                 "cvxpy" : "__import__('cvxpy')", 52                 "redis" : "__import__('redis')", 53                 "certifi": "__import__('certifi')"}54S3_BUCKET = "s3://ericmjonas-public"55S3URL_STAGING_BASE = S3_BUCKET + "/pywren.runtime.staging"56S3URL_BASE = S3_BUCKET + "/pywren.runtime"57def get_staged_runtime_url(runtime_name, runtime_python_version):58    s3url = "{}/pywren_runtime-{}-{}".format(S3URL_STAGING_BASE, 59                                             runtime_python_version, runtime_name)60    return s3url + ".tar.gz", s3url + ".meta.json"61def get_runtime_url_from_staging(staging_url):62    s3_url_base, s3_filename = os.path.split(staging_url)63    release_url = "{}/{}".format(S3URL_BASE, s3_filename)64    return release_url65def hash_s3_key(s):66    """67    MD5-hash the contents of an S3 key to enable good partitioning.68    used for sharding the runtimes69    """70    DIGEST_LEN = 671    m = hashlib.md5()72    m.update(s.encode('ascii'))73    digest = m.hexdigest()74    return "{}-{}".format(digest[:DIGEST_LEN], s)75def get_s3_shard(key, shard_num):76    return "{}.{:04d}".format(key, shard_num)77def split_s3_url(s3_url):78    if s3_url[:5] != "s3://":79        raise ValueError("URL {} is not valid".format(s3_url))80    splits = s3_url[5:].split("/")81    bucket_name = splits[0]82    key = "/".join(splits[1:])...

noxfile.py

Source:noxfile.py

...3nox.options.sessions = "black", "lint", "mypy"4ADSODIR = ".adso_test"5py_version = ["3.9", "3.8", "3.7"]6def install_this(session):7    session.conda_install("mamba")8    if session.python:9        with open(f"{session.virtualenv.location}/conda-meta/pinned", "w") as f:10            f.write(f"python={session.python}.*")11    session.run(12        "mamba",13        "env",14        "update",15        "--file",16        "environment.yml",17        "--prefix",18        f"{session.virtualenv.location}",19    )20    session.install(".")21@nox.session()22def black(session):23    args = session.posargs or locations24    session.install("black")25    session.run("black", "--exclude", "src/vendor/*", *args)26@nox.session()27def lint(session):28    args = session.posargs or locations29    session.install(30        "flake8",31        "flake8-annotations",32        "flake8-bandit",33        "flake8-black",34        "flake8-bugbear",35        "flake8-docstrings",36        "flake8-import-order",37        "darglint",38    )39    session.run("flake8", *args)40@nox.session(venv_backend="conda")41def mypy(session):42    args = session.posargs or locations43    install_this(session)44    session.conda_install("mypy")45    session.run("python", "-m", "pip", "install", "types-requests")46    session.run("mypy", *args)47@nox.session(python=py_version, venv_backend="conda")48def xdoctest(session):49    args = session.posargs or ["all"]50    install_this(session)51    session.conda_install("xdoctest")52    session.run("python", "-m", "xdoctest", "adso", *args)53@nox.session(venv_backend="conda")54def cov(session):55    install_this(session)56    session.conda_install("coverage", "pytest", "pytest-cov")57    session.run("rm", "-rf", ADSODIR, external=True)58    session.run("rm", "-rf", ".test", external=True)59    session.run(60        "pytest",61        "--cov-config",62        ".coveragerc",63        "--cov-report",64        "html:coverage",65        "--cov-report",66        "term",67        "--cov",68        "adso",69        "-v",70        "--durations=0",71        env={"ADSODIR": ADSODIR},72    )73@nox.session(venv_backend="conda")74def coverage(session):75    install_this(session)76    session.conda_install("coverage", "codecov", "pytest-cov")77    session.run("rm", "-rf", ADSODIR, external=True)78    session.run("rm", "-rf", ".test", external=True)79    session.run(80        "pytest",81        "--cov-config",82        ".coveragerc",83        "--cov",84        "adso",85        env={"ADSODIR": ADSODIR},86    )87    session.run("coverage", "xml", "--fail-under=0")88    session.run("codecov", *session.posargs)89@nox.session(python=py_version, venv_backend="conda")90def test(session):91    install_this(session)92    session.conda_install("pytest")93    session.run("rm", "-rf", ADSODIR, external=True)94    session.run("rm", "-rf", ".test", external=True)95    session.run("pytest", env={"ADSODIR": ADSODIR})96@nox.session(python=py_version)97def pip_test(session):98    session.install("pytest")99    session.install(".")100    session.run("rm", "-rf", ADSODIR, external=True)101    session.run("rm", "-rf", ".test", external=True)102    session.run(103        "pytest",104        "--ignore=tests/test_06_LDAGS.py",105        "--ignore=tests/test_09_TM.py",106        "--ignore=tests/test_10_hSBM.py",107        "--ignore=tests/test_12_UMAP_HDBSCAN.py",108        env={"ADSODIR": ADSODIR},109    )110@nox.session(venv_backend="conda")111def docs(session):112    install_this(session)113    session.conda_install("sphinx", "sphinx-autodoc-typehints", "sphinx-gallery")114    session.run("sphinx-build", "-b", "html", "docs/_source", "docs")115    session.run("sphinx-build", "-M", "latexpdf", "docs/_source", "docs/_latex")...

pythoninstall.py

Source:pythoninstall.py

1import sys2import importlib3import importlib.util4import argparse5parser = argparse.ArgumentParser()6parser.add_argument("--gpu", help="install nvidia gpu support", action="store_true", default=False)7args, unknown = parser.parse_known_args()89if importlib.util.find_spec("conda") is None:10    print("Error: A Conda environment is required to install the required packages.", file=sys.stderr)11    exit()1213import conda.cli.python_api as Conda1415# datasets(+huggingface_hub) required by hugging face hub16# scipy required by torchvision: Caltech ImageNet SBD SVHN datasets and Inception v3 GoogLeNet models17# pandas required by the dataset tutorial: https://pytorch.org/tutorials/beginner/data_loading_tutorial.html18# matplotlib-base required by torchstudio renderers19# python-graphviz required by torchstudio graph20# paramiko required for ssh connections21# pysoundfile required on windows by torchaudio: https://pytorch.org/audio/stable/backend.html#soundfile-backend22if sys.platform.startswith('win'):23    if args.gpu:24        conda_install="pytorch torchvision torchaudio cudatoolkit=11.3 datasets scipy pandas matplotlib-base python-graphviz paramiko pysoundfile"25    else:26        conda_install="pytorch torchvision torchaudio cpuonly datasets scipy pandas matplotlib-base python-graphviz paramiko pysoundfile"27elif sys.platform.startswith('darwin'):28    # force a pytorch/mkl version, because pytorch 1.10.2+ depends on mkl 2022 which is incompatible with Rosetta 2 in M1 macs, and update cffi 1.15.0-py39hc55c11b_1 to 1.15.0-py39he338e87_0+ to avoid paramiko error29    conda_install="pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 mkl==2021.4.0 datasets scipy pandas matplotlib-base python-graphviz paramiko cffi"30elif sys.platform.startswith('linux'):31    if args.gpu:32        conda_install="pytorch torchvision torchaudio cudatoolkit=11.3 datasets scipy pandas matplotlib-base python-graphviz paramiko"33    else:34        conda_install="pytorch torchvision torchaudio cpuonly datasets scipy pandas matplotlib-base python-graphviz paramiko"35else:36    print("Error: Unsupported platform.", file=sys.stderr)37    print("Windows, macOS or Linux is required.", file=sys.stderr)38    exit()3940print("Downloading and installing PyTorch and additional packages:")41print(conda_install)42print("")4344# channels: pytorch for pytorch torchvision torchaudio, nvidia for cudatoolkit=11.1 on Linux, huggingface for datasets(+huggingface_hub), conda-forge for everything else except anaconda for python-graphviz45conda_install+=" -c pytorch -c nvidia -c huggingface -c conda-forge -c anaconda"4647# https://stackoverflow.com/questions/41767340/using-conda-install-within-a-python-script
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