# Copyright 2020 Cognite AS
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
The ``util`` package contains miscellaneous functions and classes that can some times be useful while developing
extractors.
"""
import logging
import random
from functools import partial, wraps
from threading import Thread
from time import time
from typing import Any, Callable, Dict, Generator, Iterable, List, Optional, Tuple, Type, TypeVar, Union
from decorator import decorator
from cognite.client import CogniteClient
from cognite.client.data_classes import Asset, ExtractionPipelineRun, TimeSeries
from cognite.client.exceptions import CogniteAPIError, CogniteException, CogniteFileUploadError, CogniteNotFoundError
from cognite.extractorutils.threading import CancellationToken
def _ensure(endpoint: Any, items: Iterable[Any]) -> None:
try:
external_ids = [ts.external_id for ts in items]
# Not doing anything with the result, only want to make sure they exist. This will throw an exception if not.
endpoint.retrieve_multiple(external_ids=external_ids)
except CogniteNotFoundError as e:
# Create the missing time series
external_ids = [obj["externalId"] for obj in e.not_found]
create_these = [ts for ts in items if ts.external_id in external_ids]
endpoint.create(create_these)
[docs]
def ensure_time_series(cdf_client: CogniteClient, time_series: Iterable[TimeSeries]) -> None:
"""
Ensure that all the given time series exists in CDF.
Searches through the tenant after the external IDs of the time series given, and creates those that are missing.
Args:
cdf_client: Tenant to create time series in
time_series: Time series to create
"""
_ensure(cdf_client.time_series, time_series)
[docs]
def ensure_assets(cdf_client: CogniteClient, assets: Iterable[Asset]) -> None:
"""
Ensure that all the given assets exists in CDF.
Searches through the tenant after the external IDs of the assets given, and creates those that are missing.
Args:
cdf_client: Tenant to create assets in
assets: Assets to create
"""
_ensure(cdf_client.assets, assets)
[docs]
class EitherId:
"""
Class representing an ID in CDF, which can either be an external or internal ID. An EitherId can only hold one ID
type, not both.
Args:
id: Internal ID
external_id: external ID. It can be `external_id` or `externalId`
Raises:
TypeError: If none of both of id types are set.
"""
def __init__(self, **kwargs: Union[int, str, None]):
internal_id = kwargs.get("id")
external_id = kwargs.get("externalId") or kwargs.get("external_id")
if internal_id is None and external_id is None:
raise TypeError("Either id or external_id must be set")
if internal_id is not None and external_id is not None:
raise TypeError("Only one of id and external_id can be set")
if internal_id is not None and not isinstance(internal_id, int):
raise TypeError("Internal IDs must be integers")
if external_id is not None and not isinstance(external_id, str):
raise TypeError("External IDs must be strings")
self.internal_id: Optional[int] = internal_id
self.external_id: Optional[str] = external_id
[docs]
def type(self) -> str:
"""
Get the type of the ID
Returns:
'id' if the EitherId represents an internal ID, 'externalId' if the EitherId represents an external ID
"""
return "id" if self.internal_id is not None else "externalId"
[docs]
def content(self) -> Union[int, str]:
"""
Get the value of the ID
Returns:
The ID
"""
return self.internal_id or self.external_id # type: ignore # checked to be not None in init
def __eq__(self, other: Any) -> bool:
"""
Compare with another object. Only returns true if other is an EitherId with the same type and content
Args:
other: Another object
Returns:
True if the other object is equal to this
"""
if not isinstance(other, EitherId):
return False
return self.internal_id == other.internal_id and self.external_id == other.external_id
def __hash__(self) -> int:
"""
Returns a hash of the internal or external ID
Returns:
Hash code of ID
"""
return hash((self.internal_id, self.external_id))
def __str__(self) -> str:
"""
Get a string representation of the EitherId on the format "type: content".
Returns:
A string rep of the EitherId
"""
return "{}: {}".format(self.type(), self.content())
def __repr__(self) -> str:
"""
Get a string representation of the EitherId on the format "type: content".
Returns:
A string rep of the EitherId
"""
return self.__str__()
_T1 = TypeVar("_T1")
[docs]
def throttled_loop(target_time: int, cancellation_token: CancellationToken) -> Generator[None, None, None]:
"""
A loop generator that automatically sleeps until each iteration has taken the desired amount of time. Useful for
when you want to avoid overloading a source system with requests.
Example:
This example will throttle printing to only print every 10th second:
.. code-block:: python
for _ in throttled_loop(10, stop_event):
print("Hello every 10 seconds!")
Args:
target_time: How long (in seconds) an iteration should take om total
cancellation_token: An Event object that will act as the stop event. When set, the loop will stop.
Returns:
A generator that will only yield when the target iteration time is met
"""
logger = logging.getLogger(__name__)
while not cancellation_token.is_cancelled:
start_time = time()
yield
iteration_time = time() - start_time
if iteration_time > target_time:
logger.warning("Iteration time longer than target time, will not sleep")
else:
logger.debug(f"Iteration took {iteration_time:.1f} s, sleeping {target_time - iteration_time:.1f} s")
cancellation_token.wait(target_time - iteration_time)
_T2 = TypeVar("_T2")
def _retry_internal(
f: Callable[..., _T2],
cancellation_token: CancellationToken,
exceptions: Union[Tuple[Type[Exception], ...], Dict[Type[Exception], Callable[[Exception], bool]]],
tries: int,
delay: float,
max_delay: Optional[float],
backoff: float,
jitter: Union[float, Tuple[float, float]],
) -> _T2:
logger = logging.getLogger(__name__)
while tries and not cancellation_token.is_cancelled:
try:
return f()
except Exception as e:
if isinstance(exceptions, tuple):
for ex_type in exceptions:
if isinstance(e, ex_type):
break
else:
raise e
else:
for ex_type in exceptions:
if isinstance(e, ex_type) and exceptions[ex_type](e):
break
else:
raise e
tries -= 1
if not tries:
raise e
if logger is not None:
logger.warning("%s, retrying in %.1f seconds...", str(e), delay)
cancellation_token.wait(delay)
delay *= backoff
if isinstance(jitter, tuple):
delay += random.uniform(*jitter)
else:
delay += jitter
if max_delay is not None:
delay = min(delay, max_delay)
return None # type: ignore # unreachable, we will have raised an exception before this
[docs]
def retry(
cancellation_token: Optional[CancellationToken] = None,
exceptions: Union[Tuple[Type[Exception], ...], Dict[Type[Exception], Callable[[Any], bool]]] = (Exception,),
tries: int = 10,
delay: float = 1,
max_delay: Optional[float] = 60,
backoff: float = 2,
jitter: Union[float, Tuple[float, float]] = (0, 2),
) -> Callable[[Callable[..., _T2]], Callable[..., _T2]]:
"""
Returns a retry decorator.
This is adapted from https://github.com/invl/retry
Args:
cancellation_token: a threading token that is waited on.
exceptions: a tuple of exceptions to catch, or a dictionary from exception types to a callback determining
whether to retry the exception or not. The callback will be given the exception object as argument.
default: retry all exceptions.
tries: the maximum number of attempts. default: -1 (infinite).
delay: initial delay between attempts. default: 0.
max_delay: the maximum value of delay. default: None (no limit).
backoff: multiplier applied to delay between attempts. default: 1 (no backoff).
jitter: extra seconds added to delay between attempts. default: 0.
fixed if a number, random if a range tuple (min, max)
logger: logger.warning(fmt, error, delay) will be called on failed attempts.
default: retry.logging_logger. if None, logging is disabled.
"""
@decorator
def retry_decorator(f: Callable[..., _T2], *fargs: Any, **fkwargs: Any) -> _T2:
args = fargs if fargs else []
kwargs = fkwargs if fkwargs else {}
return _retry_internal(
partial(f, *args, **kwargs),
cancellation_token or CancellationToken(),
exceptions,
tries,
delay,
max_delay,
backoff,
jitter,
)
return retry_decorator
[docs]
def requests_exceptions(
status_codes: Optional[List[int]] = None,
) -> Dict[Type[Exception], Callable[[Any], bool]]:
"""
Retry exceptions from using the ``requests`` library. This will retry all connection and HTTP errors matching
the given status codes.
Example:
.. code-block:: python
@retry(exceptions = requests_exceptions())
def my_function() -> None:
...
"""
status_codes = status_codes or [408, 425, 429, 500, 502, 503, 504]
# types ignored, since they are not installed as we don't depend on the package
from requests.exceptions import HTTPError, RequestException
def handle_http_errors(exception: RequestException) -> bool:
if isinstance(exception, HTTPError):
response = exception.response
if response is None:
return True
return response.status_code in status_codes
else:
return True
return {RequestException: handle_http_errors}
[docs]
def httpx_exceptions(
status_codes: Optional[List[int]] = None,
) -> Dict[Type[Exception], Callable[[Any], bool]]:
"""
Retry exceptions from using the ``httpx`` library. This will retry all connection and HTTP errors matching
the given status codes.
Example:
.. code-block:: python
@retry(exceptions = httpx_exceptions())
def my_function() -> None:
...
"""
status_codes = status_codes or [408, 425, 429, 500, 502, 503, 504]
# types ignored, since they are not installed as we don't depend on the package
from httpx import HTTPError, HTTPStatusError
def handle_http_errors(exception: HTTPError) -> bool:
if isinstance(exception, HTTPStatusError):
response = exception.response
if response is None:
return True
return response.status_code in status_codes
else:
return True
return {HTTPError: handle_http_errors}
[docs]
def cognite_exceptions(
status_codes: Optional[List[int]] = None,
) -> Dict[Type[Exception], Callable[[Any], bool]]:
"""
Retry exceptions from using the Cognite SDK. This will retry all connection and HTTP errors matching
the given status codes.
Example:
.. code-block:: python
@retry(exceptions = cognite_exceptions())
def my_function() -> None:
...
"""
status_codes = status_codes or [408, 425, 429, 500, 502, 503, 504]
def handle_cognite_errors(exception: CogniteException) -> bool:
if isinstance(exception, (CogniteAPIError, CogniteFileUploadError)):
return exception.code in status_codes
return True
return {CogniteException: handle_cognite_errors}