As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Configuring Timeouts and Retries

When using object methods which invoke Google Cloud Storage API methods, you have several options for how the library handles timeouts and how it retries transient errors.

Configuring Timeouts

For a number of reasons, methods which invoke API methods may take longer than expected or desired. By default, such methods are applied a default timeout of 60.0 seconds.

The python-storage client uses the timeout mechanics of the underlying requests HTTP library. The connect timeout is the number of seconds to establish a connection to the server. The read timeout is the number of seconds the client will wait for the server to send a response. In most cases, this is the maximum wait time before the server sends the first byte. Please refer to the requests documentation for details.

You may also choose to configure explicit timeouts in your code, using one of three forms:

  • You can specify a single value for the timeout. The timeout value will be applied to both the connect and the read timeouts. E.g.:

bucket = client.get_bucket(BUCKET_NAME, timeout=300.0)  # five minutes

  • You can also pass a two-tuple, (connect_timeout, read_timeout), if you would like to set the values separately. E.g.:

bucket = client.get_bucket(BUCKET_NAME, timeout=(3, 10))

  • You can also pass None as the timeout value: in this case, the library will block indefinitely for a response. E.g.:

bucket = client.get_bucket(BUCKET_NAME, timeout=None)

Note

Depending on the retry strategy, a request may be repeated several times using the same timeout each time.

See also:

Configuring Retries

Note

For more background on retries, see also the GCS Retry Strategies Document

Methods which invoke API methods may fail for a number of reasons, some of which represent “transient” conditions, and thus can be retried automatically. The library tries to provide a sensible default retry policy for each method, base on its semantics:

  • For API requests which are always idempotent, the library uses its DEFAULT_RETRY policy, which retries any API request which returns a “transient” error.

  • For API requests which are idempotent only if the blob has the same “generation”, the library uses its DEFAULT_RETRY_IF_GENERATION_SPECIFIED policy, which retries API requests which returns a “transient” error, but only if the original request includes a generation or ifGenerationMatch header.

  • For API requests which are idempotent only if the bucket or blob has the same “metageneration”, the library uses its DEFAULT_RETRY_IF_METAGENERATION_SPECIFIED policy, which retries API requests which returns a “transient” error, but only if the original request includes an ifMetagenerationMatch header.

  • For API requests which are idempotent only if the bucket or blob has the same “etag”, the library uses its DEFAULT_RETRY_IF_ETAG_IN_JSON policy, which retries API requests which returns a “transient” error, but only if the original request includes an ETAG in its payload.

  • For those API requests which are never idempotent, the library passes retry=None by default, suppressing any retries.

Rather than using one of the default policies, you may choose to configure an explicit policy in your code.

  • You can pass None as a retry policy to disable retries. E.g.:

bucket = client.get_bucket(BUCKET_NAME, retry=None)

  • You can modify the default retry behavior and create a copy of DEFAULT_RETRY by calling it with a with_XXX method. E.g.:

from google.cloud.storage.retry import DEFAULT_RETRY

# Customize retry with a deadline of 500 seconds (default=120 seconds).
modified_retry = DEFAULT_RETRY.with_deadline(500.0)
# Customize retry with an initial wait time of 1.5 (default=1.0).
# Customize retry with a wait time multiplier per iteration of 1.2 (default=2.0).
# Customize retry with a maximum wait time of 45.0 (default=60.0).
modified_retry = modified_retry.with_delay(initial=1.5, multiplier=1.2, maximum=45.0)

  • You can pass an instance of google.api_core.retry.Retry to enable retries; the passed object will define retriable response codes and errors, as well as configuring backoff and retry interval options. E.g.:

from google.api_core import exceptions
from google.api_core.retry import Retry

_MY_RETRIABLE_TYPES = [
   exceptions.TooManyRequests,  # 429
   exceptions.InternalServerError,  # 500
   exceptions.BadGateway,  # 502
   exceptions.ServiceUnavailable,  # 503
]

def is_retryable(exc):
    return isinstance(exc, _MY_RETRIABLE_TYPES)

my_retry_policy = Retry(predicate=is_retryable)
bucket = client.get_bucket(BUCKET_NAME, retry=my_retry_policy)

  • You can pass an instance of google.cloud.storage.retry.ConditionalRetryPolicy, which wraps a RetryPolicy, activating it only if certain conditions are met. This class exists to provide safe defaults for RPC calls that are not technically safe to retry normally (due to potential data duplication or other side-effects) but become safe to retry if a condition such as if_metageneration_match is set. E.g.:

from google.api_core.retry import Retry
from google.cloud.storage.retry import ConditionalRetryPolicy
from google.cloud.storage.retry import is_etag_in_data

def is_retryable(exc):
    ... # as above

my_retry_policy = Retry(predicate=is_retryable)
my_cond_policy = ConditionalRetryPolicy(
    my_retry_policy, conditional_predicate=is_etag_in_data, ["query_params"])
bucket = client.get_bucket(BUCKET_NAME, retry=my_cond_policy)