repo stringlengths 7 54 | path stringlengths 4 223 | func_name stringlengths 1 134 | original_string stringlengths 75 104k | language stringclasses 1
value | code stringlengths 75 104k | code_tokens listlengths 20 28.4k | docstring stringlengths 1 46.3k | docstring_tokens listlengths 1 1.66k | sha stringlengths 40 40 | url stringlengths 87 315 | partition stringclasses 1
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dpkp/kafka-python | kafka/record/default_records.py | DefaultRecordBatchBuilder.estimate_size_in_bytes | def estimate_size_in_bytes(cls, key, value, headers):
""" Get the upper bound estimate on the size of record
"""
return (
cls.HEADER_STRUCT.size + cls.MAX_RECORD_OVERHEAD +
cls.size_of(key, value, headers)
) | python | def estimate_size_in_bytes(cls, key, value, headers):
""" Get the upper bound estimate on the size of record
"""
return (
cls.HEADER_STRUCT.size + cls.MAX_RECORD_OVERHEAD +
cls.size_of(key, value, headers)
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dpkp/kafka-python | kafka/coordinator/heartbeat.py | Heartbeat.time_to_next_heartbeat | def time_to_next_heartbeat(self):
"""Returns seconds (float) remaining before next heartbeat should be sent"""
time_since_last_heartbeat = time.time() - max(self.last_send, self.last_reset)
if self.heartbeat_failed:
delay_to_next_heartbeat = self.config['retry_backoff_ms'] / 1000
... | python | def time_to_next_heartbeat(self):
"""Returns seconds (float) remaining before next heartbeat should be sent"""
time_since_last_heartbeat = time.time() - max(self.last_send, self.last_reset)
if self.heartbeat_failed:
delay_to_next_heartbeat = self.config['retry_backoff_ms'] / 1000
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dpkp/kafka-python | kafka/conn.py | _address_family | def _address_family(address):
"""
Attempt to determine the family of an address (or hostname)
:return: either socket.AF_INET or socket.AF_INET6 or socket.AF_UNSPEC if the address family
could not be determined
"""
if address.startswith('[') and address.endswith(']'):
... | python | def _address_family(address):
"""
Attempt to determine the family of an address (or hostname)
:return: either socket.AF_INET or socket.AF_INET6 or socket.AF_UNSPEC if the address family
could not be determined
"""
if address.startswith('[') and address.endswith(']'):
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dpkp/kafka-python | kafka/conn.py | get_ip_port_afi | def get_ip_port_afi(host_and_port_str):
"""
Parse the IP and port from a string in the format of:
* host_or_ip <- Can be either IPv4 address literal or hostname/fqdn
* host_or_ipv4:port <- Can be either IPv4 address literal or hostname/fqdn
* [host_or_ip] ... | python | def get_ip_port_afi(host_and_port_str):
"""
Parse the IP and port from a string in the format of:
* host_or_ip <- Can be either IPv4 address literal or hostname/fqdn
* host_or_ipv4:port <- Can be either IPv4 address literal or hostname/fqdn
* [host_or_ip] ... | [
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dpkp/kafka-python | kafka/conn.py | collect_hosts | def collect_hosts(hosts, randomize=True):
"""
Collects a comma-separated set of hosts (host:port) and optionally
randomize the returned list.
"""
if isinstance(hosts, six.string_types):
hosts = hosts.strip().split(',')
result = []
afi = socket.AF_INET
for host_port in hosts:
... | python | def collect_hosts(hosts, randomize=True):
"""
Collects a comma-separated set of hosts (host:port) and optionally
randomize the returned list.
"""
if isinstance(hosts, six.string_types):
hosts = hosts.strip().split(',')
result = []
afi = socket.AF_INET
for host_port in hosts:
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dpkp/kafka-python | kafka/conn.py | dns_lookup | def dns_lookup(host, port, afi=socket.AF_UNSPEC):
"""Returns a list of getaddrinfo structs, optionally filtered to an afi (ipv4 / ipv6)"""
# XXX: all DNS functions in Python are blocking. If we really
# want to be non-blocking here, we need to use a 3rd-party
# library like python-adns, or move resoluti... | python | def dns_lookup(host, port, afi=socket.AF_UNSPEC):
"""Returns a list of getaddrinfo structs, optionally filtered to an afi (ipv4 / ipv6)"""
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.connect | def connect(self):
"""Attempt to connect and return ConnectionState"""
if self.state is ConnectionStates.DISCONNECTED and not self.blacked_out():
self.last_attempt = time.time()
next_lookup = self._next_afi_sockaddr()
if not next_lookup:
self.close(Err... | python | def connect(self):
"""Attempt to connect and return ConnectionState"""
if self.state is ConnectionStates.DISCONNECTED and not self.blacked_out():
self.last_attempt = time.time()
next_lookup = self._next_afi_sockaddr()
if not next_lookup:
self.close(Err... | [
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dpkp/kafka-python | kafka/conn.py | BrokerConnection._token_extensions | def _token_extensions(self):
"""
Return a string representation of the OPTIONAL key-value pairs that can be sent with an OAUTHBEARER
initial request.
"""
token_provider = self.config['sasl_oauth_token_provider']
# Only run if the #extensions() method is implemented by th... | python | def _token_extensions(self):
"""
Return a string representation of the OPTIONAL key-value pairs that can be sent with an OAUTHBEARER
initial request.
"""
token_provider = self.config['sasl_oauth_token_provider']
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.blacked_out | def blacked_out(self):
"""
Return true if we are disconnected from the given node and can't
re-establish a connection yet
"""
if self.state is ConnectionStates.DISCONNECTED:
if time.time() < self.last_attempt + self._reconnect_backoff:
return True
... | python | def blacked_out(self):
"""
Return true if we are disconnected from the given node and can't
re-establish a connection yet
"""
if self.state is ConnectionStates.DISCONNECTED:
if time.time() < self.last_attempt + self._reconnect_backoff:
return True
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.connection_delay | def connection_delay(self):
"""
Return the number of milliseconds to wait, based on the connection
state, before attempting to send data. When disconnected, this respects
the reconnect backoff time. When connecting, returns 0 to allow
non-blocking connect to finish. When connecte... | python | def connection_delay(self):
"""
Return the number of milliseconds to wait, based on the connection
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.connecting | def connecting(self):
"""Returns True if still connecting (this may encompass several
different states, such as SSL handshake, authorization, etc)."""
return self.state in (ConnectionStates.CONNECTING,
ConnectionStates.HANDSHAKE,
Connec... | python | def connecting(self):
"""Returns True if still connecting (this may encompass several
different states, such as SSL handshake, authorization, etc)."""
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.close | def close(self, error=None):
"""Close socket and fail all in-flight-requests.
Arguments:
error (Exception, optional): pending in-flight-requests
will be failed with this exception.
Default: kafka.errors.KafkaConnectionError.
"""
if self.state ... | python | def close(self, error=None):
"""Close socket and fail all in-flight-requests.
Arguments:
error (Exception, optional): pending in-flight-requests
will be failed with this exception.
Default: kafka.errors.KafkaConnectionError.
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.send | def send(self, request, blocking=True):
"""Queue request for async network send, return Future()"""
future = Future()
if self.connecting():
return future.failure(Errors.NodeNotReadyError(str(self)))
elif not self.connected():
return future.failure(Errors.KafkaConn... | python | def send(self, request, blocking=True):
"""Queue request for async network send, return Future()"""
future = Future()
if self.connecting():
return future.failure(Errors.NodeNotReadyError(str(self)))
elif not self.connected():
return future.failure(Errors.KafkaConn... | [
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.send_pending_requests | def send_pending_requests(self):
"""Can block on network if request is larger than send_buffer_bytes"""
try:
with self._lock:
if not self._can_send_recv():
return Errors.NodeNotReadyError(str(self))
# In the future we might manage an intern... | python | def send_pending_requests(self):
"""Can block on network if request is larger than send_buffer_bytes"""
try:
with self._lock:
if not self._can_send_recv():
return Errors.NodeNotReadyError(str(self))
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.recv | def recv(self):
"""Non-blocking network receive.
Return list of (response, future) tuples
"""
responses = self._recv()
if not responses and self.requests_timed_out():
log.warning('%s timed out after %s ms. Closing connection.',
self, self.conf... | python | def recv(self):
"""Non-blocking network receive.
Return list of (response, future) tuples
"""
responses = self._recv()
if not responses and self.requests_timed_out():
log.warning('%s timed out after %s ms. Closing connection.',
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dpkp/kafka-python | kafka/conn.py | BrokerConnection._recv | def _recv(self):
"""Take all available bytes from socket, return list of any responses from parser"""
recvd = []
self._lock.acquire()
if not self._can_send_recv():
log.warning('%s cannot recv: socket not connected', self)
self._lock.release()
return ()... | python | def _recv(self):
"""Take all available bytes from socket, return list of any responses from parser"""
recvd = []
self._lock.acquire()
if not self._can_send_recv():
log.warning('%s cannot recv: socket not connected', self)
self._lock.release()
return ()... | [
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dpkp/kafka-python | kafka/conn.py | BrokerConnection.check_version | def check_version(self, timeout=2, strict=False, topics=[]):
"""Attempt to guess the broker version.
Note: This is a blocking call.
Returns: version tuple, i.e. (0, 10), (0, 9), (0, 8, 2), ...
"""
timeout_at = time.time() + timeout
log.info('Probing node %s broker versi... | python | def check_version(self, timeout=2, strict=False, topics=[]):
"""Attempt to guess the broker version.
Note: This is a blocking call.
Returns: version tuple, i.e. (0, 10), (0, 9), (0, 8, 2), ...
"""
timeout_at = time.time() + timeout
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dpkp/kafka-python | kafka/producer/sender.py | Sender.run | def run(self):
"""The main run loop for the sender thread."""
log.debug("Starting Kafka producer I/O thread.")
# main loop, runs until close is called
while self._running:
try:
self.run_once()
except Exception:
log.exception("Uncau... | python | def run(self):
"""The main run loop for the sender thread."""
log.debug("Starting Kafka producer I/O thread.")
# main loop, runs until close is called
while self._running:
try:
self.run_once()
except Exception:
log.exception("Uncau... | [
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dpkp/kafka-python | kafka/producer/sender.py | Sender.run_once | def run_once(self):
"""Run a single iteration of sending."""
while self._topics_to_add:
self._client.add_topic(self._topics_to_add.pop())
# get the list of partitions with data ready to send
result = self._accumulator.ready(self._metadata)
ready_nodes, next_ready_che... | python | def run_once(self):
"""Run a single iteration of sending."""
while self._topics_to_add:
self._client.add_topic(self._topics_to_add.pop())
# get the list of partitions with data ready to send
result = self._accumulator.ready(self._metadata)
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dpkp/kafka-python | kafka/producer/sender.py | Sender.initiate_close | def initiate_close(self):
"""Start closing the sender (won't complete until all data is sent)."""
self._running = False
self._accumulator.close()
self.wakeup() | python | def initiate_close(self):
"""Start closing the sender (won't complete until all data is sent)."""
self._running = False
self._accumulator.close()
self.wakeup() | [
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dpkp/kafka-python | kafka/producer/sender.py | Sender._handle_produce_response | def _handle_produce_response(self, node_id, send_time, batches, response):
"""Handle a produce response."""
# if we have a response, parse it
log.debug('Parsing produce response: %r', response)
if response:
batches_by_partition = dict([(batch.topic_partition, batch)
... | python | def _handle_produce_response(self, node_id, send_time, batches, response):
"""Handle a produce response."""
# if we have a response, parse it
log.debug('Parsing produce response: %r', response)
if response:
batches_by_partition = dict([(batch.topic_partition, batch)
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dpkp/kafka-python | kafka/producer/sender.py | Sender._complete_batch | def _complete_batch(self, batch, error, base_offset, timestamp_ms=None):
"""Complete or retry the given batch of records.
Arguments:
batch (RecordBatch): The record batch
error (Exception): The error (or None if none)
base_offset (int): The base offset assigned to th... | python | def _complete_batch(self, batch, error, base_offset, timestamp_ms=None):
"""Complete or retry the given batch of records.
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batch (RecordBatch): The record batch
error (Exception): The error (or None if none)
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dpkp/kafka-python | kafka/producer/sender.py | Sender._can_retry | def _can_retry(self, batch, error):
"""
We can retry a send if the error is transient and the number of
attempts taken is fewer than the maximum allowed
"""
return (batch.attempts < self.config['retries']
and getattr(error, 'retriable', False)) | python | def _can_retry(self, batch, error):
"""
We can retry a send if the error is transient and the number of
attempts taken is fewer than the maximum allowed
"""
return (batch.attempts < self.config['retries']
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dpkp/kafka-python | kafka/producer/sender.py | Sender._create_produce_requests | def _create_produce_requests(self, collated):
"""
Transfer the record batches into a list of produce requests on a
per-node basis.
Arguments:
collated: {node_id: [RecordBatch]}
Returns:
dict: {node_id: ProduceRequest} (version depends on api_version)
... | python | def _create_produce_requests(self, collated):
"""
Transfer the record batches into a list of produce requests on a
per-node basis.
Arguments:
collated: {node_id: [RecordBatch]}
Returns:
dict: {node_id: ProduceRequest} (version depends on api_version)
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dpkp/kafka-python | kafka/producer/sender.py | Sender._produce_request | def _produce_request(self, node_id, acks, timeout, batches):
"""Create a produce request from the given record batches.
Returns:
ProduceRequest (version depends on api_version)
"""
produce_records_by_partition = collections.defaultdict(dict)
for batch in batches:
... | python | def _produce_request(self, node_id, acks, timeout, batches):
"""Create a produce request from the given record batches.
Returns:
ProduceRequest (version depends on api_version)
"""
produce_records_by_partition = collections.defaultdict(dict)
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dpkp/kafka-python | kafka/codec.py | snappy_encode | def snappy_encode(payload, xerial_compatible=True, xerial_blocksize=32*1024):
"""Encodes the given data with snappy compression.
If xerial_compatible is set then the stream is encoded in a fashion
compatible with the xerial snappy library.
The block size (xerial_blocksize) controls how frequent the bl... | python | def snappy_encode(payload, xerial_compatible=True, xerial_blocksize=32*1024):
"""Encodes the given data with snappy compression.
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dpkp/kafka-python | kafka/codec.py | lz4f_decode | def lz4f_decode(payload):
"""Decode payload using interoperable LZ4 framing. Requires Kafka >= 0.10"""
# pylint: disable-msg=no-member
ctx = lz4f.createDecompContext()
data = lz4f.decompressFrame(payload, ctx)
lz4f.freeDecompContext(ctx)
# lz4f python module does not expose how much of the payl... | python | def lz4f_decode(payload):
"""Decode payload using interoperable LZ4 framing. Requires Kafka >= 0.10"""
# pylint: disable-msg=no-member
ctx = lz4f.createDecompContext()
data = lz4f.decompressFrame(payload, ctx)
lz4f.freeDecompContext(ctx)
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dpkp/kafka-python | kafka/codec.py | lz4_encode_old_kafka | def lz4_encode_old_kafka(payload):
"""Encode payload for 0.8/0.9 brokers -- requires an incorrect header checksum."""
assert xxhash is not None
data = lz4_encode(payload)
header_size = 7
flg = data[4]
if not isinstance(flg, int):
flg = ord(flg)
content_size_bit = ((flg >> 3) & 1)
... | python | def lz4_encode_old_kafka(payload):
"""Encode payload for 0.8/0.9 brokers -- requires an incorrect header checksum."""
assert xxhash is not None
data = lz4_encode(payload)
header_size = 7
flg = data[4]
if not isinstance(flg, int):
flg = ord(flg)
content_size_bit = ((flg >> 3) & 1)
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.brokers | def brokers(self):
"""Get all BrokerMetadata
Returns:
set: {BrokerMetadata, ...}
"""
return set(self._brokers.values()) or set(self._bootstrap_brokers.values()) | python | def brokers(self):
"""Get all BrokerMetadata
Returns:
set: {BrokerMetadata, ...}
"""
return set(self._brokers.values()) or set(self._bootstrap_brokers.values()) | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.broker_metadata | def broker_metadata(self, broker_id):
"""Get BrokerMetadata
Arguments:
broker_id (int): node_id for a broker to check
Returns:
BrokerMetadata or None if not found
"""
return self._brokers.get(broker_id) or self._bootstrap_brokers.get(broker_id) | python | def broker_metadata(self, broker_id):
"""Get BrokerMetadata
Arguments:
broker_id (int): node_id for a broker to check
Returns:
BrokerMetadata or None if not found
"""
return self._brokers.get(broker_id) or self._bootstrap_brokers.get(broker_id) | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.partitions_for_topic | def partitions_for_topic(self, topic):
"""Return set of all partitions for topic (whether available or not)
Arguments:
topic (str): topic to check for partitions
Returns:
set: {partition (int), ...}
"""
if topic not in self._partitions:
retur... | python | def partitions_for_topic(self, topic):
"""Return set of all partitions for topic (whether available or not)
Arguments:
topic (str): topic to check for partitions
Returns:
set: {partition (int), ...}
"""
if topic not in self._partitions:
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.available_partitions_for_topic | def available_partitions_for_topic(self, topic):
"""Return set of partitions with known leaders
Arguments:
topic (str): topic to check for partitions
Returns:
set: {partition (int), ...}
None if topic not found.
"""
if topic not in self._part... | python | def available_partitions_for_topic(self, topic):
"""Return set of partitions with known leaders
Arguments:
topic (str): topic to check for partitions
Returns:
set: {partition (int), ...}
None if topic not found.
"""
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.leader_for_partition | def leader_for_partition(self, partition):
"""Return node_id of leader, -1 unavailable, None if unknown."""
if partition.topic not in self._partitions:
return None
elif partition.partition not in self._partitions[partition.topic]:
return None
return self._partitio... | python | def leader_for_partition(self, partition):
"""Return node_id of leader, -1 unavailable, None if unknown."""
if partition.topic not in self._partitions:
return None
elif partition.partition not in self._partitions[partition.topic]:
return None
return self._partitio... | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.ttl | def ttl(self):
"""Milliseconds until metadata should be refreshed"""
now = time.time() * 1000
if self._need_update:
ttl = 0
else:
metadata_age = now - self._last_successful_refresh_ms
ttl = self.config['metadata_max_age_ms'] - metadata_age
ret... | python | def ttl(self):
"""Milliseconds until metadata should be refreshed"""
now = time.time() * 1000
if self._need_update:
ttl = 0
else:
metadata_age = now - self._last_successful_refresh_ms
ttl = self.config['metadata_max_age_ms'] - metadata_age
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.request_update | def request_update(self):
"""Flags metadata for update, return Future()
Actual update must be handled separately. This method will only
change the reported ttl()
Returns:
kafka.future.Future (value will be the cluster object after update)
"""
with self._lock... | python | def request_update(self):
"""Flags metadata for update, return Future()
Actual update must be handled separately. This method will only
change the reported ttl()
Returns:
kafka.future.Future (value will be the cluster object after update)
"""
with self._lock... | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.topics | def topics(self, exclude_internal_topics=True):
"""Get set of known topics.
Arguments:
exclude_internal_topics (bool): Whether records from internal topics
(such as offsets) should be exposed to the consumer. If set to
True the only way to receive records fro... | python | def topics(self, exclude_internal_topics=True):
"""Get set of known topics.
Arguments:
exclude_internal_topics (bool): Whether records from internal topics
(such as offsets) should be exposed to the consumer. If set to
True the only way to receive records fro... | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.failed_update | def failed_update(self, exception):
"""Update cluster state given a failed MetadataRequest."""
f = None
with self._lock:
if self._future:
f = self._future
self._future = None
if f:
f.failure(exception)
self._last_refresh_ms ... | python | def failed_update(self, exception):
"""Update cluster state given a failed MetadataRequest."""
f = None
with self._lock:
if self._future:
f = self._future
self._future = None
if f:
f.failure(exception)
self._last_refresh_ms ... | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.update_metadata | def update_metadata(self, metadata):
"""Update cluster state given a MetadataResponse.
Arguments:
metadata (MetadataResponse): broker response to a metadata request
Returns: None
"""
# In the common case where we ask for a single topic and get back an
# erro... | python | def update_metadata(self, metadata):
"""Update cluster state given a MetadataResponse.
Arguments:
metadata (MetadataResponse): broker response to a metadata request
Returns: None
"""
# In the common case where we ask for a single topic and get back an
# erro... | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.add_group_coordinator | def add_group_coordinator(self, group, response):
"""Update with metadata for a group coordinator
Arguments:
group (str): name of group from GroupCoordinatorRequest
response (GroupCoordinatorResponse): broker response
Returns:
bool: True if metadata is updat... | python | def add_group_coordinator(self, group, response):
"""Update with metadata for a group coordinator
Arguments:
group (str): name of group from GroupCoordinatorRequest
response (GroupCoordinatorResponse): broker response
Returns:
bool: True if metadata is updat... | [
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dpkp/kafka-python | kafka/cluster.py | ClusterMetadata.with_partitions | def with_partitions(self, partitions_to_add):
"""Returns a copy of cluster metadata with partitions added"""
new_metadata = ClusterMetadata(**self.config)
new_metadata._brokers = copy.deepcopy(self._brokers)
new_metadata._partitions = copy.deepcopy(self._partitions)
new_metadata.... | python | def with_partitions(self, partitions_to_add):
"""Returns a copy of cluster metadata with partitions added"""
new_metadata = ClusterMetadata(**self.config)
new_metadata._brokers = copy.deepcopy(self._brokers)
new_metadata._partitions = copy.deepcopy(self._partitions)
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.assign | def assign(self, partitions):
"""Manually assign a list of TopicPartitions to this consumer.
Arguments:
partitions (list of TopicPartition): Assignment for this instance.
Raises:
IllegalStateError: If consumer has already called
:meth:`~kafka.KafkaConsumer.s... | python | def assign(self, partitions):
"""Manually assign a list of TopicPartitions to this consumer.
Arguments:
partitions (list of TopicPartition): Assignment for this instance.
Raises:
IllegalStateError: If consumer has already called
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.close | def close(self, autocommit=True):
"""Close the consumer, waiting indefinitely for any needed cleanup.
Keyword Arguments:
autocommit (bool): If auto-commit is configured for this consumer,
this optional flag causes the consumer to attempt to commit any
pending... | python | def close(self, autocommit=True):
"""Close the consumer, waiting indefinitely for any needed cleanup.
Keyword Arguments:
autocommit (bool): If auto-commit is configured for this consumer,
this optional flag causes the consumer to attempt to commit any
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.commit_async | def commit_async(self, offsets=None, callback=None):
"""Commit offsets to kafka asynchronously, optionally firing callback.
This commits offsets only to Kafka. The offsets committed using this API
will be used on the first fetch after every rebalance and also on
startup. As such, if you... | python | def commit_async(self, offsets=None, callback=None):
"""Commit offsets to kafka asynchronously, optionally firing callback.
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.commit | def commit(self, offsets=None):
"""Commit offsets to kafka, blocking until success or error.
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"""Commit offsets to kafka, blocking until success or error.
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.committed | def committed(self, partition):
"""Get the last committed offset for the given partition.
This offset will be used as the position for the consumer
in the event of a failure.
This call may block to do a remote call if the partition in question
isn't assigned to this consumer or... | python | def committed(self, partition):
"""Get the last committed offset for the given partition.
This offset will be used as the position for the consumer
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.topics | def topics(self):
"""Get all topics the user is authorized to view.
Returns:
set: topics
"""
cluster = self._client.cluster
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future = cluster.request_update()
self._client.... | python | def topics(self):
"""Get all topics the user is authorized to view.
Returns:
set: topics
"""
cluster = self._client.cluster
if self._client._metadata_refresh_in_progress and self._client._topics:
future = cluster.request_update()
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.poll | def poll(self, timeout_ms=0, max_records=None):
"""Fetch data from assigned topics / partitions.
Records are fetched and returned in batches by topic-partition.
On each poll, consumer will try to use the last consumed offset as the
starting offset and fetch sequentially. The last consum... | python | def poll(self, timeout_ms=0, max_records=None):
"""Fetch data from assigned topics / partitions.
Records are fetched and returned in batches by topic-partition.
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer._poll_once | def _poll_once(self, timeout_ms, max_records):
"""Do one round of polling. In addition to checking for new data, this does
any needed heart-beating, auto-commits, and offset updates.
Arguments:
timeout_ms (int): The maximum time in milliseconds to block.
Returns:
... | python | def _poll_once(self, timeout_ms, max_records):
"""Do one round of polling. In addition to checking for new data, this does
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Arguments:
timeout_ms (int): The maximum time in milliseconds to block.
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... | [
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.position | def position(self, partition):
"""Get the offset of the next record that will be fetched
Arguments:
partition (TopicPartition): Partition to check
Returns:
int: Offset
"""
if not isinstance(partition, TopicPartition):
raise TypeError('partiti... | python | def position(self, partition):
"""Get the offset of the next record that will be fetched
Arguments:
partition (TopicPartition): Partition to check
Returns:
int: Offset
"""
if not isinstance(partition, TopicPartition):
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.highwater | def highwater(self, partition):
"""Last known highwater offset for a partition.
A highwater offset is the offset that will be assigned to the next
message that is produced. It may be useful for calculating lag, by
comparing with the reported position. Note that both position and
... | python | def highwater(self, partition):
"""Last known highwater offset for a partition.
A highwater offset is the offset that will be assigned to the next
message that is produced. It may be useful for calculating lag, by
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.pause | def pause(self, *partitions):
"""Suspend fetching from the requested partitions.
Future calls to :meth:`~kafka.KafkaConsumer.poll` will not return any
records from these partitions until they have been resumed using
:meth:`~kafka.KafkaConsumer.resume`.
Note: This method does no... | python | def pause(self, *partitions):
"""Suspend fetching from the requested partitions.
Future calls to :meth:`~kafka.KafkaConsumer.poll` will not return any
records from these partitions until they have been resumed using
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.seek | def seek(self, partition, offset):
"""Manually specify the fetch offset for a TopicPartition.
Overrides the fetch offsets that the consumer will use on the next
:meth:`~kafka.KafkaConsumer.poll`. If this API is invoked for the same
partition more than once, the latest offset will be use... | python | def seek(self, partition, offset):
"""Manually specify the fetch offset for a TopicPartition.
Overrides the fetch offsets that the consumer will use on the next
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.seek_to_beginning | def seek_to_beginning(self, *partitions):
"""Seek to the oldest available offset for partitions.
Arguments:
*partitions: Optionally provide specific TopicPartitions, otherwise
default to all assigned partitions.
Raises:
AssertionError: If any partition i... | python | def seek_to_beginning(self, *partitions):
"""Seek to the oldest available offset for partitions.
Arguments:
*partitions: Optionally provide specific TopicPartitions, otherwise
default to all assigned partitions.
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.seek_to_end | def seek_to_end(self, *partitions):
"""Seek to the most recent available offset for partitions.
Arguments:
*partitions: Optionally provide specific TopicPartitions, otherwise
default to all assigned partitions.
Raises:
AssertionError: If any partition is... | python | def seek_to_end(self, *partitions):
"""Seek to the most recent available offset for partitions.
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.subscribe | def subscribe(self, topics=(), pattern=None, listener=None):
"""Subscribe to a list of topics, or a topic regex pattern.
Partitions will be dynamically assigned via a group coordinator.
Topic subscriptions are not incremental: this list will replace the
current assignment (if there is o... | python | def subscribe(self, topics=(), pattern=None, listener=None):
"""Subscribe to a list of topics, or a topic regex pattern.
Partitions will be dynamically assigned via a group coordinator.
Topic subscriptions are not incremental: this list will replace the
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.unsubscribe | def unsubscribe(self):
"""Unsubscribe from all topics and clear all assigned partitions."""
self._subscription.unsubscribe()
self._coordinator.close()
self._client.cluster.need_all_topic_metadata = False
self._client.set_topics([])
log.debug("Unsubscribed all topics or pa... | python | def unsubscribe(self):
"""Unsubscribe from all topics and clear all assigned partitions."""
self._subscription.unsubscribe()
self._coordinator.close()
self._client.cluster.need_all_topic_metadata = False
self._client.set_topics([])
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.offsets_for_times | def offsets_for_times(self, timestamps):
"""Look up the offsets for the given partitions by timestamp. The
returned offset for each partition is the earliest offset whose
timestamp is greater than or equal to the given timestamp in the
corresponding partition.
This is a blocking... | python | def offsets_for_times(self, timestamps):
"""Look up the offsets for the given partitions by timestamp. The
returned offset for each partition is the earliest offset whose
timestamp is greater than or equal to the given timestamp in the
corresponding partition.
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.beginning_offsets | def beginning_offsets(self, partitions):
"""Get the first offset for the given partitions.
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partitions.
Note:
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Arguments:
... | python | def beginning_offsets(self, partitions):
"""Get the first offset for the given partitions.
This method does not change the current consumer position of the
partitions.
Note:
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... | [
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer.end_offsets | def end_offsets(self, partitions):
"""Get the last offset for the given partitions. The last offset of a
partition is the offset of the upcoming message, i.e. the offset of the
last available message + 1.
This method does not change the current consumer position of the
partition... | python | def end_offsets(self, partitions):
"""Get the last offset for the given partitions. The last offset of a
partition is the offset of the upcoming message, i.e. the offset of the
last available message + 1.
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer._use_consumer_group | def _use_consumer_group(self):
"""Return True iff this consumer can/should join a broker-coordinated group."""
if self.config['api_version'] < (0, 9):
return False
elif self.config['group_id'] is None:
return False
elif not self._subscription.partitions_auto_assig... | python | def _use_consumer_group(self):
"""Return True iff this consumer can/should join a broker-coordinated group."""
if self.config['api_version'] < (0, 9):
return False
elif self.config['group_id'] is None:
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dpkp/kafka-python | kafka/consumer/group.py | KafkaConsumer._update_fetch_positions | def _update_fetch_positions(self, partitions):
"""Set the fetch position to the committed position (if there is one)
or reset it using the offset reset policy the user has configured.
Arguments:
partitions (List[TopicPartition]): The partitions that need
updating fet... | python | def _update_fetch_positions(self, partitions):
"""Set the fetch position to the committed position (if there is one)
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partitions (List[TopicPartition]): The partitions that need
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dpkp/kafka-python | kafka/metrics/dict_reporter.py | DictReporter.snapshot | def snapshot(self):
"""
Return a nested dictionary snapshot of all metrics and their
values at this time. Example:
{
'category': {
'metric1_name': 42.0,
'metric2_name': 'foo'
}
}
"""
return dict((category, di... | python | def snapshot(self):
"""
Return a nested dictionary snapshot of all metrics and their
values at this time. Example:
{
'category': {
'metric1_name': 42.0,
'metric2_name': 'foo'
}
}
"""
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dpkp/kafka-python | kafka/metrics/dict_reporter.py | DictReporter.get_category | def get_category(self, metric):
"""
Return a string category for the metric.
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metric's group and tags.
Examples:
prefix = 'foo', group = 'bar', tags = {'a': 1, 'b': 2}
returns: 'foo.bar.a=1,b=2'
... | python | def get_category(self, metric):
"""
Return a string category for the metric.
The category is made up of this reporter's prefix and the
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Examples:
prefix = 'foo', group = 'bar', tags = {'a': 1, 'b': 2}
returns: 'foo.bar.a=1,b=2'
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.maybe_connect | def maybe_connect(self, node_id, wakeup=True):
"""Queues a node for asynchronous connection during the next .poll()"""
if self._can_connect(node_id):
self._connecting.add(node_id)
# Wakeup signal is useful in case another thread is
# blocked waiting for incoming netwo... | python | def maybe_connect(self, node_id, wakeup=True):
"""Queues a node for asynchronous connection during the next .poll()"""
if self._can_connect(node_id):
self._connecting.add(node_id)
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dpkp/kafka-python | kafka/client_async.py | KafkaClient._maybe_connect | def _maybe_connect(self, node_id):
"""Idempotent non-blocking connection attempt to the given node id."""
with self._lock:
conn = self._conns.get(node_id)
if conn is None:
broker = self.cluster.broker_metadata(node_id)
assert broker, 'Broker id %s... | python | def _maybe_connect(self, node_id):
"""Idempotent non-blocking connection attempt to the given node id."""
with self._lock:
conn = self._conns.get(node_id)
if conn is None:
broker = self.cluster.broker_metadata(node_id)
assert broker, 'Broker id %s... | [
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.ready | def ready(self, node_id, metadata_priority=True):
"""Check whether a node is connected and ok to send more requests.
Arguments:
node_id (int): the id of the node to check
metadata_priority (bool): Mark node as not-ready if a metadata
refresh is required. Default:... | python | def ready(self, node_id, metadata_priority=True):
"""Check whether a node is connected and ok to send more requests.
Arguments:
node_id (int): the id of the node to check
metadata_priority (bool): Mark node as not-ready if a metadata
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.connected | def connected(self, node_id):
"""Return True iff the node_id is connected."""
conn = self._conns.get(node_id)
if conn is None:
return False
return conn.connected() | python | def connected(self, node_id):
"""Return True iff the node_id is connected."""
conn = self._conns.get(node_id)
if conn is None:
return False
return conn.connected() | [
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.close | def close(self, node_id=None):
"""Close one or all broker connections.
Arguments:
node_id (int, optional): the id of the node to close
"""
with self._lock:
if node_id is None:
self._close()
conns = list(self._conns.values())
... | python | def close(self, node_id=None):
"""Close one or all broker connections.
Arguments:
node_id (int, optional): the id of the node to close
"""
with self._lock:
if node_id is None:
self._close()
conns = list(self._conns.values())
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.is_disconnected | def is_disconnected(self, node_id):
"""Check whether the node connection has been disconnected or failed.
A disconnected node has either been closed or has failed. Connection
failures are usually transient and can be resumed in the next ready()
call, but there are cases where transient ... | python | def is_disconnected(self, node_id):
"""Check whether the node connection has been disconnected or failed.
A disconnected node has either been closed or has failed. Connection
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.connection_delay | def connection_delay(self, node_id):
"""
Return the number of milliseconds to wait, based on the connection
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the reconnect backoff time. When connecting, returns 0 to allow
non-blocking connect to finish. When... | python | def connection_delay(self, node_id):
"""
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.is_ready | def is_ready(self, node_id, metadata_priority=True):
"""Check whether a node is ready to send more requests.
In addition to connection-level checks, this method also is used to
block additional requests from being sent during a metadata refresh.
Arguments:
node_id (int): id... | python | def is_ready(self, node_id, metadata_priority=True):
"""Check whether a node is ready to send more requests.
In addition to connection-level checks, this method also is used to
block additional requests from being sent during a metadata refresh.
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.send | def send(self, node_id, request, wakeup=True):
"""Send a request to a specific node. Bytes are placed on an
internal per-connection send-queue. Actual network I/O will be
triggered in a subsequent call to .poll()
Arguments:
node_id (int): destination node
request... | python | def send(self, node_id, request, wakeup=True):
"""Send a request to a specific node. Bytes are placed on an
internal per-connection send-queue. Actual network I/O will be
triggered in a subsequent call to .poll()
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node_id (int): destination node
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.poll | def poll(self, timeout_ms=None, future=None):
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timeout_ms (int, optional): maximum amount of time to wait (... | python | def poll(self, timeout_ms=None, future=None):
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.in_flight_request_count | def in_flight_request_count(self, node_id=None):
"""Get the number of in-flight requests for a node or all nodes.
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node_id (int, optional): a specific node to check. If unspecified,
return the total for all nodes
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int: pending in-flight... | python | def in_flight_request_count(self, node_id=None):
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node_id (int, optional): a specific node to check. If unspecified,
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.least_loaded_node | def least_loaded_node(self):
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in-flight-requests. If no such node is found, a node will be chosen
randomly from disconnected nodes that are not "blacked ... | python | def least_loaded_node(self):
"""Choose the node with fewest outstanding requests, with fallbacks.
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.set_topics | def set_topics(self, topics):
"""Set specific topics to track for metadata.
Arguments:
topics (list of str): topics to check for metadata
Returns:
Future: resolves after metadata request/response
"""
if set(topics).difference(self._topics):
f... | python | def set_topics(self, topics):
"""Set specific topics to track for metadata.
Arguments:
topics (list of str): topics to check for metadata
Returns:
Future: resolves after metadata request/response
"""
if set(topics).difference(self._topics):
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.add_topic | def add_topic(self, topic):
"""Add a topic to the list of topics tracked via metadata.
Arguments:
topic (str): topic to track
Returns:
Future: resolves after metadata request/response
"""
if topic in self._topics:
return Future().success(set(... | python | def add_topic(self, topic):
"""Add a topic to the list of topics tracked via metadata.
Arguments:
topic (str): topic to track
Returns:
Future: resolves after metadata request/response
"""
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dpkp/kafka-python | kafka/client_async.py | KafkaClient._maybe_refresh_metadata | def _maybe_refresh_metadata(self, wakeup=False):
"""Send a metadata request if needed.
Returns:
int: milliseconds until next refresh
"""
ttl = self.cluster.ttl()
wait_for_in_progress_ms = self.config['request_timeout_ms'] if self._metadata_refresh_in_progress else 0
... | python | def _maybe_refresh_metadata(self, wakeup=False):
"""Send a metadata request if needed.
Returns:
int: milliseconds until next refresh
"""
ttl = self.cluster.ttl()
wait_for_in_progress_ms = self.config['request_timeout_ms'] if self._metadata_refresh_in_progress else 0
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dpkp/kafka-python | kafka/client_async.py | KafkaClient.check_version | def check_version(self, node_id=None, timeout=2, strict=False):
"""Attempt to guess the version of a Kafka broker.
Note: It is possible that this method blocks longer than the
specified timeout. This can happen if the entire cluster
is down and the client enters a bootstrap back... | python | def check_version(self, node_id=None, timeout=2, strict=False):
"""Attempt to guess the version of a Kafka broker.
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dpkp/kafka-python | kafka/metrics/stats/rate.py | Rate.window_size | def window_size(self, config, now):
# purge old samples before we compute the window size
self._stat.purge_obsolete_samples(config, now)
"""
Here we check the total amount of time elapsed since the oldest
non-obsolete window. This give the total window_size of the batch
... | python | def window_size(self, config, now):
# purge old samples before we compute the window size
self._stat.purge_obsolete_samples(config, now)
"""
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dpkp/kafka-python | kafka/producer/base.py | Producer.send_messages | def send_messages(self, topic, partition, *msg):
"""Helper method to send produce requests.
Note that msg type *must* be encoded to bytes by user. Passing unicode
message will not work, for example you should encode before calling
send_messages via something like `unicode_message.encode... | python | def send_messages(self, topic, partition, *msg):
"""Helper method to send produce requests.
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dpkp/kafka-python | kafka/producer/base.py | Producer.stop | def stop(self, timeout=None):
"""
Stop the producer (async mode). Blocks until async thread completes.
"""
if timeout is not None:
log.warning('timeout argument to stop() is deprecated - '
'it will be removed in future release')
if not self.as... | python | def stop(self, timeout=None):
"""
Stop the producer (async mode). Blocks until async thread completes.
"""
if timeout is not None:
log.warning('timeout argument to stop() is deprecated - '
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dpkp/kafka-python | kafka/record/legacy_records.py | LegacyRecordBatchBuilder.append | def append(self, offset, timestamp, key, value, headers=None):
""" Append message to batch.
"""
assert not headers, "Headers not supported in v0/v1"
# Check types
if type(offset) != int:
raise TypeError(offset)
if self._magic == 0:
timestamp = self... | python | def append(self, offset, timestamp, key, value, headers=None):
""" Append message to batch.
"""
assert not headers, "Headers not supported in v0/v1"
# Check types
if type(offset) != int:
raise TypeError(offset)
if self._magic == 0:
timestamp = self... | [
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dpkp/kafka-python | kafka/record/legacy_records.py | LegacyRecordBatchBuilder._encode_msg | def _encode_msg(self, start_pos, offset, timestamp, key, value,
attributes=0):
""" Encode msg data into the `msg_buffer`, which should be allocated
to at least the size of this message.
"""
magic = self._magic
buf = self._buffer
pos = start_pos
... | python | def _encode_msg(self, start_pos, offset, timestamp, key, value,
attributes=0):
""" Encode msg data into the `msg_buffer`, which should be allocated
to at least the size of this message.
"""
magic = self._magic
buf = self._buffer
pos = start_pos
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dpkp/kafka-python | kafka/record/legacy_records.py | LegacyRecordBatchBuilder.size_in_bytes | def size_in_bytes(self, offset, timestamp, key, value, headers=None):
""" Actual size of message to add
"""
assert not headers, "Headers not supported in v0/v1"
magic = self._magic
return self.LOG_OVERHEAD + self.record_size(magic, key, value) | python | def size_in_bytes(self, offset, timestamp, key, value, headers=None):
""" Actual size of message to add
"""
assert not headers, "Headers not supported in v0/v1"
magic = self._magic
return self.LOG_OVERHEAD + self.record_size(magic, key, value) | [
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dpkp/kafka-python | kafka/record/legacy_records.py | LegacyRecordBatchBuilder.estimate_size_in_bytes | def estimate_size_in_bytes(cls, magic, compression_type, key, value):
""" Upper bound estimate of record size.
"""
assert magic in [0, 1], "Not supported magic"
# In case of compression we may need another overhead for inner msg
if compression_type:
return (
... | python | def estimate_size_in_bytes(cls, magic, compression_type, key, value):
""" Upper bound estimate of record size.
"""
assert magic in [0, 1], "Not supported magic"
# In case of compression we may need another overhead for inner msg
if compression_type:
return (
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dpkp/kafka-python | kafka/producer/buffer.py | SimpleBufferPool.allocate | def allocate(self, size, max_time_to_block_ms):
"""
Allocate a buffer of the given size. This method blocks if there is not
enough memory and the buffer pool is configured with blocking mode.
Arguments:
size (int): The buffer size to allocate in bytes [ignored]
m... | python | def allocate(self, size, max_time_to_block_ms):
"""
Allocate a buffer of the given size. This method blocks if there is not
enough memory and the buffer pool is configured with blocking mode.
Arguments:
size (int): The buffer size to allocate in bytes [ignored]
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dpkp/kafka-python | kafka/producer/buffer.py | SimpleBufferPool.deallocate | def deallocate(self, buf):
"""
Return buffers to the pool. If they are of the poolable size add them
to the free list, otherwise just mark the memory as free.
Arguments:
buffer_ (io.BytesIO): The buffer to return
"""
with self._lock:
# BytesIO.tru... | python | def deallocate(self, buf):
"""
Return buffers to the pool. If they are of the poolable size add them
to the free list, otherwise just mark the memory as free.
Arguments:
buffer_ (io.BytesIO): The buffer to return
"""
with self._lock:
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dpkp/kafka-python | kafka/protocol/message.py | MessageSet.decode | def decode(cls, data, bytes_to_read=None):
"""Compressed messages should pass in bytes_to_read (via message size)
otherwise, we decode from data as Int32
"""
if isinstance(data, bytes):
data = io.BytesIO(data)
if bytes_to_read is None:
bytes_to_read = Int3... | python | def decode(cls, data, bytes_to_read=None):
"""Compressed messages should pass in bytes_to_read (via message size)
otherwise, we decode from data as Int32
"""
if isinstance(data, bytes):
data = io.BytesIO(data)
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dpkp/kafka-python | kafka/record/util.py | encode_varint | def encode_varint(value, write):
""" Encode an integer to a varint presentation. See
https://developers.google.com/protocol-buffers/docs/encoding?csw=1#varints
on how those can be produced.
Arguments:
value (int): Value to encode
write (function): Called per byte that needs ... | python | def encode_varint(value, write):
""" Encode an integer to a varint presentation. See
https://developers.google.com/protocol-buffers/docs/encoding?csw=1#varints
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value (int): Value to encode
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dpkp/kafka-python | kafka/record/util.py | size_of_varint | def size_of_varint(value):
""" Number of bytes needed to encode an integer in variable-length format.
"""
value = (value << 1) ^ (value >> 63)
if value <= 0x7f:
return 1
if value <= 0x3fff:
return 2
if value <= 0x1fffff:
return 3
if value <= 0xfffffff:
return ... | python | def size_of_varint(value):
""" Number of bytes needed to encode an integer in variable-length format.
"""
value = (value << 1) ^ (value >> 63)
if value <= 0x7f:
return 1
if value <= 0x3fff:
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dpkp/kafka-python | kafka/record/util.py | decode_varint | def decode_varint(buffer, pos=0):
""" Decode an integer from a varint presentation. See
https://developers.google.com/protocol-buffers/docs/encoding?csw=1#varints
on how those can be produced.
Arguments:
buffer (bytearry): buffer to read from.
pos (int): optional position to... | python | def decode_varint(buffer, pos=0):
""" Decode an integer from a varint presentation. See
https://developers.google.com/protocol-buffers/docs/encoding?csw=1#varints
on how those can be produced.
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dpkp/kafka-python | kafka/protocol/parser.py | KafkaProtocol.send_request | def send_request(self, request, correlation_id=None):
"""Encode and queue a kafka api request for sending.
Arguments:
request (object): An un-encoded kafka request.
correlation_id (int, optional): Optionally specify an ID to
correlate requests with responses. If ... | python | def send_request(self, request, correlation_id=None):
"""Encode and queue a kafka api request for sending.
Arguments:
request (object): An un-encoded kafka request.
correlation_id (int, optional): Optionally specify an ID to
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dpkp/kafka-python | kafka/protocol/parser.py | KafkaProtocol.send_bytes | def send_bytes(self):
"""Retrieve all pending bytes to send on the network"""
data = b''.join(self.bytes_to_send)
self.bytes_to_send = []
return data | python | def send_bytes(self):
"""Retrieve all pending bytes to send on the network"""
data = b''.join(self.bytes_to_send)
self.bytes_to_send = []
return data | [
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dpkp/kafka-python | kafka/protocol/parser.py | KafkaProtocol.receive_bytes | def receive_bytes(self, data):
"""Process bytes received from the network.
Arguments:
data (bytes): any length bytes received from a network connection
to a kafka broker.
Returns:
responses (list of (correlation_id, response)): any/all completed
... | python | def receive_bytes(self, data):
"""Process bytes received from the network.
Arguments:
data (bytes): any length bytes received from a network connection
to a kafka broker.
Returns:
responses (list of (correlation_id, response)): any/all completed
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dpkp/kafka-python | kafka/client.py | SimpleClient._get_conn | def _get_conn(self, host, port, afi):
"""Get or create a connection to a broker using host and port"""
host_key = (host, port)
if host_key not in self._conns:
self._conns[host_key] = BrokerConnection(
host, port, afi,
request_timeout_ms=self.timeout * ... | python | def _get_conn(self, host, port, afi):
"""Get or create a connection to a broker using host and port"""
host_key = (host, port)
if host_key not in self._conns:
self._conns[host_key] = BrokerConnection(
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dpkp/kafka-python | kafka/client.py | SimpleClient._get_leader_for_partition | def _get_leader_for_partition(self, topic, partition):
"""
Returns the leader for a partition or None if the partition exists
but has no leader.
Raises:
UnknownTopicOrPartitionError: If the topic or partition is not part
of the metadata.
LeaderNot... | python | def _get_leader_for_partition(self, topic, partition):
"""
Returns the leader for a partition or None if the partition exists
but has no leader.
Raises:
UnknownTopicOrPartitionError: If the topic or partition is not part
of the metadata.
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dpkp/kafka-python | kafka/client.py | SimpleClient._get_coordinator_for_group | def _get_coordinator_for_group(self, group):
"""
Returns the coordinator broker for a consumer group.
GroupCoordinatorNotAvailableError will be raised if the coordinator
does not currently exist for the group.
GroupLoadInProgressError is raised if the coordinator is available
... | python | def _get_coordinator_for_group(self, group):
"""
Returns the coordinator broker for a consumer group.
GroupCoordinatorNotAvailableError will be raised if the coordinator
does not currently exist for the group.
GroupLoadInProgressError is raised if the coordinator is available
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dpkp/kafka-python | kafka/client.py | SimpleClient._send_broker_unaware_request | def _send_broker_unaware_request(self, payloads, encoder_fn, decoder_fn):
"""
Attempt to send a broker-agnostic request to one of the available
brokers. Keep trying until you succeed.
"""
hosts = set()
for broker in self.brokers.values():
host, port, afi = get... | python | def _send_broker_unaware_request(self, payloads, encoder_fn, decoder_fn):
"""
Attempt to send a broker-agnostic request to one of the available
brokers. Keep trying until you succeed.
"""
hosts = set()
for broker in self.brokers.values():
host, port, afi = get... | [
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dpkp/kafka-python | kafka/client.py | SimpleClient._send_broker_aware_request | def _send_broker_aware_request(self, payloads, encoder_fn, decoder_fn):
"""
Group a list of request payloads by topic+partition and send them to
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functions
Arguments:
payloads: list of object-like enti... | python | def _send_broker_aware_request(self, payloads, encoder_fn, decoder_fn):
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Group a list of request payloads by topic+partition and send them to
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