import shlex import subprocess import time import uuid import pytest from pandas.compat import ( is_ci_environment, is_platform_arm, is_platform_mac, is_platform_windows, ) import pandas.util._test_decorators as td import pandas.io.common as icom from pandas.io.parsers import read_csv @pytest.fixture def compression_to_extension(): return {value: key for key, value in icom.extension_to_compression.items()} @pytest.fixture def tips_file(datapath): """Path to the tips dataset""" return datapath("io", "data", "csv", "tips.csv") @pytest.fixture def jsonl_file(datapath): """Path to a JSONL dataset""" return datapath("io", "parser", "data", "items.jsonl") @pytest.fixture def salaries_table(datapath): """DataFrame with the salaries dataset""" return read_csv(datapath("io", "parser", "data", "salaries.csv"), sep="\t") @pytest.fixture def feather_file(datapath): return datapath("io", "data", "feather", "feather-0_3_1.feather") @pytest.fixture def xml_file(datapath): return datapath("io", "data", "xml", "books.xml") @pytest.fixture def s3so(worker_id): if is_ci_environment(): url = "http://localhost:5000/" else: worker_id = "5" if worker_id == "master" else worker_id.lstrip("gw") url = f"http://127.0.0.1:555{worker_id}/" return {"client_kwargs": {"endpoint_url": url}} @pytest.fixture(scope="function" if is_ci_environment() else "session") def monkeysession(): with pytest.MonkeyPatch.context() as mp: yield mp @pytest.fixture(scope="function" if is_ci_environment() else "session") def s3_base(worker_id, monkeysession): """ Fixture for mocking S3 interaction. Sets up moto server in separate process locally Return url for motoserver/moto CI service """ pytest.importorskip("s3fs") pytest.importorskip("boto3") # temporary workaround as moto fails for botocore >= 1.11 otherwise, # see https://github.com/spulec/moto/issues/1924 & 1952 monkeysession.setenv("AWS_ACCESS_KEY_ID", "foobar_key") monkeysession.setenv("AWS_SECRET_ACCESS_KEY", "foobar_secret") if is_ci_environment(): if is_platform_arm() or is_platform_mac() or is_platform_windows(): # NOT RUN on Windows/macOS/ARM, only Ubuntu # - subprocess in CI can cause timeouts # - GitHub Actions do not support # container services for the above OSs # - CircleCI will probably hit the Docker rate pull limit pytest.skip( "S3 tests do not have a corresponding service in " "Windows, macOS or ARM platforms" ) else: yield "http://localhost:5000" else: requests = pytest.importorskip("requests") pytest.importorskip("moto", minversion="1.3.14") pytest.importorskip("flask") # server mode needs flask too # Launching moto in server mode, i.e., as a separate process # with an S3 endpoint on localhost worker_id = "5" if worker_id == "master" else worker_id.lstrip("gw") endpoint_port = f"555{worker_id}" endpoint_uri = f"http://127.0.0.1:{endpoint_port}/" # pipe to null to avoid logging in terminal with subprocess.Popen( shlex.split(f"moto_server s3 -p {endpoint_port}"), stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, ) as proc: timeout = 5 while timeout > 0: try: # OK to go once server is accepting connections r = requests.get(endpoint_uri) if r.ok: break except Exception: pass timeout -= 0.1 time.sleep(0.1) yield endpoint_uri proc.terminate() @pytest.fixture def s3_resource(s3_base): import boto3 s3 = boto3.resource("s3", endpoint_url=s3_base) return s3 @pytest.fixture def s3_public_bucket(s3_resource): bucket = s3_resource.Bucket(f"pandas-test-{uuid.uuid4()}") bucket.create() yield bucket bucket.objects.delete() bucket.delete() @pytest.fixture def s3_public_bucket_with_data( s3_public_bucket, tips_file, jsonl_file, feather_file, xml_file ): """ The following datasets are loaded. - tips.csv - tips.csv.gz - tips.csv.bz2 - items.jsonl """ test_s3_files = [ ("tips#1.csv", tips_file), ("tips.csv", tips_file), ("tips.csv.gz", tips_file + ".gz"), ("tips.csv.bz2", tips_file + ".bz2"), ("items.jsonl", jsonl_file), ("simple_dataset.feather", feather_file), ("books.xml", xml_file), ] for s3_key, file_name in test_s3_files: with open(file_name, "rb") as f: s3_public_bucket.put_object(Key=s3_key, Body=f) return s3_public_bucket @pytest.fixture def s3_private_bucket(s3_resource): bucket = s3_resource.Bucket(f"cant_get_it-{uuid.uuid4()}") bucket.create(ACL="private") yield bucket bucket.objects.delete() bucket.delete() @pytest.fixture def s3_private_bucket_with_data( s3_private_bucket, tips_file, jsonl_file, feather_file, xml_file ): """ The following datasets are loaded. - tips.csv - tips.csv.gz - tips.csv.bz2 - items.jsonl """ test_s3_files = [ ("tips#1.csv", tips_file), ("tips.csv", tips_file), ("tips.csv.gz", tips_file + ".gz"), ("tips.csv.bz2", tips_file + ".bz2"), ("items.jsonl", jsonl_file), ("simple_dataset.feather", feather_file), ("books.xml", xml_file), ] for s3_key, file_name in test_s3_files: with open(file_name, "rb") as f: s3_private_bucket.put_object(Key=s3_key, Body=f) return s3_private_bucket _compression_formats_params = [ (".no_compress", None), ("", None), (".gz", "gzip"), (".GZ", "gzip"), (".bz2", "bz2"), (".BZ2", "bz2"), (".zip", "zip"), (".ZIP", "zip"), (".xz", "xz"), (".XZ", "xz"), pytest.param((".zst", "zstd"), marks=td.skip_if_no("zstandard")), pytest.param((".ZST", "zstd"), marks=td.skip_if_no("zstandard")), ] @pytest.fixture(params=_compression_formats_params[1:]) def compression_format(request): return request.param @pytest.fixture(params=_compression_formats_params) def compression_ext(request): return request.param[0] @pytest.fixture( params=[ "python", pytest.param("pyarrow", marks=td.skip_if_no("pyarrow")), ] ) def string_storage(request): """ Parametrized fixture for pd.options.mode.string_storage. * 'python' * 'pyarrow' """ return request.param