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325 lines (263 loc) · 10.2 KB
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import os
import random
import shutil
import string
import tarfile
import io
import unittest
import warnings
from itertools import product
from pathlib import Path
from unittest.mock import Mock
from typing import Any, Callable, Dict, List, Iterator, Tuple
from tenacity import (
retry,
stop_after_attempt,
wait_exponential,
retry_if_exception_type,
retry_if_exception,
)
import requests
from requests.exceptions import ChunkedEncodingError
from aistore.sdk import Client, Object
from aistore.sdk.const import UTF_ENCODING
from aistore.sdk.obj.content_iterator import ContentIterProvider
from aistore.sdk.response_handler import ResponseHandler
from aistore.sdk.types import BucketModel
from aistore.sdk.errors import AISError
from tests.const import KB
from tests.integration.sdk import DEFAULT_TEST_CLIENT
# pylint: disable=too-few-public-methods
class BadContentStream(io.BytesIO):
"""
Simulates a stream that fails intermittently with a specified error after a set number of reads.
Args:
data (bytes): The data to be streamed.
fail_on_read (int): The number of reads after which the error is raised.
error (Exception): The error instance to raise after `fail_on_read` reads.
"""
def __init__(self, data: bytes, fail_on_read: int, error: Exception):
super().__init__(data)
self.read_count = 0
self.fail_on_read = fail_on_read
self.error = error
def read(self, size: int = -1) -> bytes:
"""Overrides `BytesIO.read` to raise an error after a specific number of reads."""
self.read_count += 1
if self.read_count == self.fail_on_read:
raise self.error
return super().read(size)
# pylint: disable=too-few-public-methods
class BadContentIterProvider(ContentIterProvider):
"""
Simulates a ContentIterProvider that creates a bad iterator that streams data
in chunks and intermittently raises errors via a `BadContentStream`.
Args:
data (bytes): The data to be streamed in chunks.
fail_on_read (int): The number of reads after which an error will be raised.
chunk_size (int): The size of each chunk to be read from the data.
error (Exception): The error instance to raise after `fail_on_read` reads.
"""
def __init__(
self,
data: bytes,
fail_on_read: int,
chunk_size: int,
error: Exception = ChunkedEncodingError("Simulated ChunkedEncodingError"),
):
super().__init__(client=Mock(), chunk_size=chunk_size)
self.data = data
self.fail_on_read = fail_on_read
self.error = error
self.read_position = 0
def create_iter(self, offset: int = 0) -> Iterator[bytes]:
"""Streams data using `BadContentStream`, starting from `offset`."""
stream = BadContentStream(
self.data[offset:], fail_on_read=self.fail_on_read, error=self.error
)
self.read_position = offset
def iterator():
while self.read_position < len(self.data):
chunk = stream.read(self._chunk_size)
self.read_position += len(chunk)
yield chunk
return iterator()
# pylint: disable=unused-variable
def random_string(length: int = 10) -> str:
return "".join(random.choices(string.ascii_lowercase, k=length))
def string_to_dict(input_string: str) -> Dict:
pairs = input_string.split(", ")
result_dict = {
key_value.split("=")[0]: key_value.split("=")[1] for key_value in pairs
}
return result_dict
# pylint: disable=unused-variable
def create_and_put_object(
client: Client,
bck: BucketModel,
obj_name: str,
obj_size: int = 0,
) -> Tuple["Object", bytes]:
obj_size = obj_size if obj_size else random.randrange(10, 20)
content = random_string(obj_size).encode(UTF_ENCODING)
obj = client.bucket(bck.name, provider=bck.provider).object(obj_name)
obj.get_writer().put_content(content)
return obj, content
def cleanup_local(path: str):
try:
shutil.rmtree(path)
except FileNotFoundError:
pass
def cases(*args):
def decorator(func):
def wrapper(self, *inner_args, **kwargs):
for arg in args:
with self.subTest(arg=arg):
func(self, arg, *inner_args, **kwargs)
return wrapper
return decorator
def case_matrix(*args_list):
def decorator(func):
def wrapper(self, *inner_args, **kwargs):
for args in product(*args_list):
with self.subTest(args=args):
func(self, *args, *inner_args, **kwargs)
return wrapper
return decorator
def create_archive(archive_name, content_dict):
directory = os.path.dirname(archive_name)
if not os.path.exists(directory):
os.makedirs(directory)
with tarfile.open(archive_name, "w") as tar:
for file_name, file_content in content_dict.items():
info = tarfile.TarInfo(name=file_name)
info.size = len(file_content)
tar.addfile(tarinfo=info, fileobj=io.BytesIO(file_content))
def create_random_tarballs(
num_files: int, num_extensions: int, min_shard_size: int, dest_dir: Path
):
def generate_files(
num_files: int, num_extensions: int, dest_dir: Path
) -> Tuple[List[Path], List[str]]:
files_list = []
filenames_list = []
extension_list = [random_string(3) for _ in range(num_extensions)]
for _ in range(num_files):
filename = random_string(10)
filenames_list.append(filename)
for ext in extension_list:
file_path = dest_dir.joinpath(f"{filename}.{ext}")
with open(file_path, "wb") as file:
file.write(os.urandom((random.randint(KB, 10 * KB))))
files_list.append(file_path)
return files_list, extension_list
def create_tarballs(
min_shard_size: int, dest_dir: Path, files_list: List[Path]
) -> int:
num_input_shards = 0
current_size = 0
current_tarball = dest_dir.joinpath(f"input-shard-{num_input_shards}.tar")
total_size = 0
file_count = 0
tarball_info = []
random.shuffle(files_list)
for file in files_list:
file_size = file.stat().st_size
if current_size > min_shard_size:
tarball_info.append(
f"{current_tarball.name}\t{current_size}\t{file_count}"
)
num_input_shards += 1
current_tarball = dest_dir.joinpath(
f"input-shard-{num_input_shards}.tar"
)
current_size = 0
file_count = 0
with tarfile.open(current_tarball, "a") as tar:
tar.add(file, arcname=file.name)
current_size += file_size
file_count += 1
total_size += file_size
file.unlink()
tarball_info.append(f"{current_tarball.name}\t{current_size}\t{file_count}")
return num_input_shards
file_list, extension_list = generate_files(num_files, num_extensions, dest_dir)
num_input_shards = create_tarballs(min_shard_size, dest_dir, file_list)
filename_list = list(map(lambda filepath: filepath.stem, file_list))
return filename_list, extension_list, num_input_shards
def create_api_error_response(req_url: str, status: int, msg: str) -> requests.Response:
"""
Given test details, manually generate a requests.Response object
Args:
req_url (str): Original request url
status (str): Response HTTP status code
msg (str): Response text content
Returns: requests.Response containing the given details
"""
req = requests.PreparedRequest()
req.url = req_url
response = requests.Response()
response.status_code = status
# pylint: disable=protected-access
response._content = msg.encode("utf-8")
response.request = req
return response
def has_targets(n: int = 2) -> bool:
"""Check if the cluster has at least two targets before running tests."""
try:
return len(DEFAULT_TEST_CLIENT.cluster().get_info().tmap) >= n
except Exception:
return False # Assume failure means insufficient targets or unreachable cluster (AuthN)
def handler_parse_and_assert(
test: unittest.TestCase,
handler: "ResponseHandler",
error_type: Any,
test_case: Tuple[str, Any, int],
):
"""
Utility function for different response handler tests to pass their handler class type, expected parsed error,
and test parameters and assert the proper error is created.
Args:
test: TestCase using this function.
handler: Type of ResponseHandler class.
error_type: Expected error type created by the handler's parser.
test_case: Parameters to test.
"""
err_msg, expected_err, err_status = test_case
test_url = "http://test-url"
response = create_api_error_response(test_url, err_status, err_msg)
err = handler.parse_error(response)
test.assertIsInstance(err, error_type)
test.assertIsInstance(err, expected_err)
test.assertEqual(err_status, err.status_code)
test.assertEqual(err_msg, err.message)
test.assertEqual(test_url, err.req_url)
test.assertEqual(response.request, err.req)
@retry(
stop=stop_after_attempt(5),
wait=wait_exponential(multiplier=0.4, max=6),
retry=retry_if_exception_type(AssertionError),
reraise=True,
)
def assert_with_retries(
assertion_fn: Callable[..., None], *args: Any, **kwargs: Any
) -> None:
assertion_fn(*args, **kwargs)
def _warn_on_busy_retry(retry_state):
exc = retry_state.outcome.exception()
warnings.warn(
f"ErrBusy (409) encountered, retrying (attempt {retry_state.attempt_number}/5).",
RuntimeWarning,
)
@retry(
stop=stop_after_attempt(5),
wait=wait_exponential(multiplier=0.4, max=6),
retry=retry_if_exception(
lambda e: isinstance(e, AISError) and e.status_code == 409
),
before_sleep=_warn_on_busy_retry,
reraise=True,
)
def call_with_busy_retry(fn: Callable[..., Any], *args: Any, **kwargs: Any) -> Any:
"""Retry API calls that might fail with ErrBusy (409) due to concurrent requests."""
return fn(*args, **kwargs)
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