partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
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train | HDFSNameNode._set_metric | Set a metric | hdfs_namenode/datadog_checks/hdfs_namenode/hdfs_namenode.py | def _set_metric(self, metric_name, metric_type, value, tags=None):
"""
Set a metric
"""
if metric_type == self.GAUGE:
self.gauge(metric_name, value, tags=tags)
else:
self.log.error('Metric type "{}" unknown'.format(metric_type)) | def _set_metric(self, metric_name, metric_type, value, tags=None):
"""
Set a metric
"""
if metric_type == self.GAUGE:
self.gauge(metric_name, value, tags=tags)
else:
self.log.error('Metric type "{}" unknown'.format(metric_type)) | [
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train | HDFSNameNode._rest_request_to_json | Query the given URL and return the JSON response | hdfs_namenode/datadog_checks/hdfs_namenode/hdfs_namenode.py | def _rest_request_to_json(self, instance, url, object_path, query_params, tags=None):
"""
Query the given URL and return the JSON response
"""
if object_path:
url = self._join_url_dir(url, object_path)
# Add query_params as arguments
if query_params:
... | def _rest_request_to_json(self, instance, url, object_path, query_params, tags=None):
"""
Query the given URL and return the JSON response
"""
if object_path:
url = self._join_url_dir(url, object_path)
# Add query_params as arguments
if query_params:
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train | HDFSNameNode._join_url_dir | Join a URL with multiple directories | hdfs_namenode/datadog_checks/hdfs_namenode/hdfs_namenode.py | def _join_url_dir(cls, url, *args):
"""
Join a URL with multiple directories
"""
for path in args:
url = url.rstrip('/') + '/'
url = urljoin(url, path.lstrip('/'))
return url | def _join_url_dir(cls, url, *args):
"""
Join a URL with multiple directories
"""
for path in args:
url = url.rstrip('/') + '/'
url = urljoin(url, path.lstrip('/'))
return url | [
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train | _maybe_add_read_preference | Add $readPreference to spec when appropriate. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _maybe_add_read_preference(spec, read_preference):
"""Add $readPreference to spec when appropriate."""
mode = read_preference.mode
tag_sets = read_preference.tag_sets
max_staleness = read_preference.max_staleness
# Only add $readPreference if it's something other than primary to avoid
# prob... | def _maybe_add_read_preference(spec, read_preference):
"""Add $readPreference to spec when appropriate."""
mode = read_preference.mode
tag_sets = read_preference.tag_sets
max_staleness = read_preference.max_staleness
# Only add $readPreference if it's something other than primary to avoid
# prob... | [
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train | _convert_write_result | Convert a legacy write result to write commmand format. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _convert_write_result(operation, command, result):
"""Convert a legacy write result to write commmand format."""
# Based on _merge_legacy from bulk.py
affected = result.get("n", 0)
res = {"ok": 1, "n": affected}
errmsg = result.get("errmsg", result.get("err", ""))
if errmsg:
# The w... | def _convert_write_result(operation, command, result):
"""Convert a legacy write result to write commmand format."""
# Based on _merge_legacy from bulk.py
affected = result.get("n", 0)
res = {"ok": 1, "n": affected}
errmsg = result.get("errmsg", result.get("err", ""))
if errmsg:
# The w... | [
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train | _gen_explain_command | Generate an explain command document. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _gen_explain_command(
coll, spec, projection, skip, limit, batch_size,
options, read_concern):
"""Generate an explain command document."""
cmd = _gen_find_command(
coll, spec, projection, skip, limit, batch_size, options)
if read_concern.level:
return SON([('explain', cmd... | def _gen_explain_command(
coll, spec, projection, skip, limit, batch_size,
options, read_concern):
"""Generate an explain command document."""
cmd = _gen_find_command(
coll, spec, projection, skip, limit, batch_size, options)
if read_concern.level:
return SON([('explain', cmd... | [
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train | _gen_find_command | Generate a find command document. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _gen_find_command(coll, spec, projection, skip, limit, batch_size,
options, read_concern=DEFAULT_READ_CONCERN,
collation=None):
"""Generate a find command document."""
cmd = SON([('find', coll)])
if '$query' in spec:
cmd.update([(_MODIFIERS[key], val) ... | def _gen_find_command(coll, spec, projection, skip, limit, batch_size,
options, read_concern=DEFAULT_READ_CONCERN,
collation=None):
"""Generate a find command document."""
cmd = SON([('find', coll)])
if '$query' in spec:
cmd.update([(_MODIFIERS[key], val) ... | [
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train | _gen_get_more_command | Generate a getMore command document. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _gen_get_more_command(cursor_id, coll, batch_size, max_await_time_ms):
"""Generate a getMore command document."""
cmd = SON([('getMore', cursor_id),
('collection', coll)])
if batch_size:
cmd['batchSize'] = batch_size
if max_await_time_ms is not None:
cmd['maxTimeMS'] =... | def _gen_get_more_command(cursor_id, coll, batch_size, max_await_time_ms):
"""Generate a getMore command document."""
cmd = SON([('getMore', cursor_id),
('collection', coll)])
if batch_size:
cmd['batchSize'] = batch_size
if max_await_time_ms is not None:
cmd['maxTimeMS'] =... | [
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train | __last_error | Data to send to do a lastError. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def __last_error(namespace, args):
"""Data to send to do a lastError.
"""
cmd = SON([("getlasterror", 1)])
cmd.update(args)
splitns = namespace.split('.', 1)
return query(0, splitns[0] + '.$cmd', 0, -1, cmd,
None, DEFAULT_CODEC_OPTIONS) | def __last_error(namespace, args):
"""Data to send to do a lastError.
"""
cmd = SON([("getlasterror", 1)])
cmd.update(args)
splitns = namespace.split('.', 1)
return query(0, splitns[0] + '.$cmd', 0, -1, cmd,
None, DEFAULT_CODEC_OPTIONS) | [
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train | __pack_message | Takes message data and adds a message header based on the operation.
Returns the resultant message string. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def __pack_message(operation, data):
"""Takes message data and adds a message header based on the operation.
Returns the resultant message string.
"""
request_id = _randint()
message = struct.pack("<i", 16 + len(data))
message += struct.pack("<i", request_id)
message += _ZERO_32 # response... | def __pack_message(operation, data):
"""Takes message data and adds a message header based on the operation.
Returns the resultant message string.
"""
request_id = _randint()
message = struct.pack("<i", 16 + len(data))
message += struct.pack("<i", request_id)
message += _ZERO_32 # response... | [
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train | insert | Get an **insert** message. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def insert(collection_name, docs, check_keys,
safe, last_error_args, continue_on_error, opts):
"""Get an **insert** message."""
options = 0
if continue_on_error:
options += 1
data = struct.pack("<i", options)
data += bson._make_c_string(collection_name)
encoded = [bson.BSON.en... | def insert(collection_name, docs, check_keys,
safe, last_error_args, continue_on_error, opts):
"""Get an **insert** message."""
options = 0
if continue_on_error:
options += 1
data = struct.pack("<i", options)
data += bson._make_c_string(collection_name)
encoded = [bson.BSON.en... | [
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train | update | Get an **update** message. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def update(collection_name, upsert, multi,
spec, doc, safe, last_error_args, check_keys, opts):
"""Get an **update** message.
"""
options = 0
if upsert:
options += 1
if multi:
options += 2
data = _ZERO_32
data += bson._make_c_string(collection_name)
data += st... | def update(collection_name, upsert, multi,
spec, doc, safe, last_error_args, check_keys, opts):
"""Get an **update** message.
"""
options = 0
if upsert:
options += 1
if multi:
options += 2
data = _ZERO_32
data += bson._make_c_string(collection_name)
data += st... | [
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train | query | Get a **query** message. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def query(options, collection_name, num_to_skip,
num_to_return, query, field_selector, opts, check_keys=False):
"""Get a **query** message.
"""
data = struct.pack("<I", options)
data += bson._make_c_string(collection_name)
data += struct.pack("<i", num_to_skip)
data += struct.pack("<i"... | def query(options, collection_name, num_to_skip,
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"""Get a **query** message.
"""
data = struct.pack("<I", options)
data += bson._make_c_string(collection_name)
data += struct.pack("<i", num_to_skip)
data += struct.pack("<i"... | [
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train | delete | Get a **delete** message.
`opts` is a CodecOptions. `flags` is a bit vector that may contain
the SingleRemove flag or not:
http://docs.mongodb.org/meta-driver/latest/legacy/mongodb-wire-protocol/#op-delete | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def delete(collection_name, spec, safe,
last_error_args, opts, flags=0):
"""Get a **delete** message.
`opts` is a CodecOptions. `flags` is a bit vector that may contain
the SingleRemove flag or not:
http://docs.mongodb.org/meta-driver/latest/legacy/mongodb-wire-protocol/#op-delete
"""
... | def delete(collection_name, spec, safe,
last_error_args, opts, flags=0):
"""Get a **delete** message.
`opts` is a CodecOptions. `flags` is a bit vector that may contain
the SingleRemove flag or not:
http://docs.mongodb.org/meta-driver/latest/legacy/mongodb-wire-protocol/#op-delete
"""
... | [
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train | kill_cursors | Get a **killCursors** message. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def kill_cursors(cursor_ids):
"""Get a **killCursors** message.
"""
data = _ZERO_32
data += struct.pack("<i", len(cursor_ids))
for cursor_id in cursor_ids:
data += struct.pack("<q", cursor_id)
return __pack_message(2007, data) | def kill_cursors(cursor_ids):
"""Get a **killCursors** message.
"""
data = _ZERO_32
data += struct.pack("<i", len(cursor_ids))
for cursor_id in cursor_ids:
data += struct.pack("<q", cursor_id)
return __pack_message(2007, data) | [
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train | _do_batched_write_command | Execute a batch of insert, update, or delete commands. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _do_batched_write_command(namespace, operation, command,
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train | _Query.as_command | Return a find command document for this query.
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"""Return a find command document for this query.
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"""
if '$explain' in self.spec:
self.name = 'explain'
return _gen_explain_command(
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self.name = 'explain'
return _gen_explain_command(
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train | _Query.get_message | Get a query message, possibly setting the slaveOk bit. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def get_message(self, set_slave_ok, is_mongos, use_cmd=False):
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if set_slave_ok:
# Set the slaveOk bit.
flags = self.flags | 4
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# Set the slaveOk bit.
flags = self.flags | 4
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train | _GetMore.as_command | Return a getMore command document for this query. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def as_command(self):
"""Return a getMore command document for this query."""
return _gen_get_more_command(self.cursor_id, self.coll,
self.ntoreturn,
self.max_await_time_ms), self.db | def as_command(self):
"""Return a getMore command document for this query."""
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train | _GetMore.get_message | Get a getmore message. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def get_message(self, dummy0, dummy1, use_cmd=False):
"""Get a getmore message."""
ns = _UJOIN % (self.db, self.coll)
if use_cmd:
ns = _UJOIN % (self.db, "$cmd")
spec = self.as_command()[0]
return query(0, ns, 0, -1, spec, None, self.codec_options)
... | def get_message(self, dummy0, dummy1, use_cmd=False):
"""Get a getmore message."""
ns = _UJOIN % (self.db, self.coll)
if use_cmd:
ns = _UJOIN % (self.db, "$cmd")
spec = self.as_command()[0]
return query(0, ns, 0, -1, spec, None, self.codec_options)
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train | _BulkWriteContext.legacy_write | A proxy for SocketInfo.legacy_write that handles event publishing. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def legacy_write(self, request_id, msg, max_doc_size, acknowledged, docs):
"""A proxy for SocketInfo.legacy_write that handles event publishing.
"""
if self.publish:
duration = datetime.datetime.now() - self.start_time
cmd = self._start(request_id, docs)
start... | def legacy_write(self, request_id, msg, max_doc_size, acknowledged, docs):
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if self.publish:
duration = datetime.datetime.now() - self.start_time
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train | _BulkWriteContext.write_command | A proxy for SocketInfo.write_command that handles event publishing. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def write_command(self, request_id, msg, docs):
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if self.publish:
duration = datetime.datetime.now() - self.start_time
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train | _BulkWriteContext._start | Publish a CommandStartedEvent. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _start(self, request_id, docs):
"""Publish a CommandStartedEvent."""
cmd = self.command.copy()
cmd[self.field] = docs
self.listeners.publish_command_start(
cmd, self.db_name,
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return cmd | def _start(self, request_id, docs):
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cmd, self.db_name,
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train | _BulkWriteContext._succeed | Publish a CommandSucceededEvent. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _succeed(self, request_id, reply, duration):
"""Publish a CommandSucceededEvent."""
self.listeners.publish_command_success(
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request_id, self.sock_info.address, self.op_id) | def _succeed(self, request_id, reply, duration):
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train | _BulkWriteContext._fail | Publish a CommandFailedEvent. | tokumx/datadog_checks/tokumx/vendor/pymongo/message.py | def _fail(self, request_id, failure, duration):
"""Publish a CommandFailedEvent."""
self.listeners.publish_command_failure(
duration, failure, self.name,
request_id, self.sock_info.address, self.op_id) | def _fail(self, request_id, failure, duration):
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train | _machine_bytes | Get the machine portion of an ObjectId. | tokumx/datadog_checks/tokumx/vendor/bson/objectid.py | def _machine_bytes():
"""Get the machine portion of an ObjectId.
"""
machine_hash = hashlib.md5()
if PY3:
# gethostname() returns a unicode string in python 3.x
# while update() requires a byte string.
machine_hash.update(socket.gethostname().encode())
else:
# Calling... | def _machine_bytes():
"""Get the machine portion of an ObjectId.
"""
machine_hash = hashlib.md5()
if PY3:
# gethostname() returns a unicode string in python 3.x
# while update() requires a byte string.
machine_hash.update(socket.gethostname().encode())
else:
# Calling... | [
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train | ObjectId.from_datetime | Create a dummy ObjectId instance with a specific generation time.
This method is useful for doing range queries on a field
containing :class:`ObjectId` instances.
.. warning::
It is not safe to insert a document containing an ObjectId
generated using this method. This met... | tokumx/datadog_checks/tokumx/vendor/bson/objectid.py | def from_datetime(cls, generation_time):
"""Create a dummy ObjectId instance with a specific generation time.
This method is useful for doing range queries on a field
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.. warning::
It is not safe to insert a document containing an Objec... | def from_datetime(cls, generation_time):
"""Create a dummy ObjectId instance with a specific generation time.
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train | ObjectId.is_valid | Checks if a `oid` string is valid or not.
:Parameters:
- `oid`: the object id to validate
.. versionadded:: 2.3 | tokumx/datadog_checks/tokumx/vendor/bson/objectid.py | def is_valid(cls, oid):
"""Checks if a `oid` string is valid or not.
:Parameters:
- `oid`: the object id to validate
.. versionadded:: 2.3
"""
if not oid:
return False
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ObjectId(oid)
return True
except (InvalidI... | def is_valid(cls, oid):
"""Checks if a `oid` string is valid or not.
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.. versionadded:: 2.3
"""
if not oid:
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train | ObjectId.__generate | Generate a new value for this ObjectId. | tokumx/datadog_checks/tokumx/vendor/bson/objectid.py | def __generate(self):
"""Generate a new value for this ObjectId.
"""
# 4 bytes current time
oid = struct.pack(">i", int(time.time()))
# 3 bytes machine
oid += ObjectId._machine_bytes
# 2 bytes pid
oid += struct.pack(">H", os.getpid() % 0xFFFF)
... | def __generate(self):
"""Generate a new value for this ObjectId.
"""
# 4 bytes current time
oid = struct.pack(">i", int(time.time()))
# 3 bytes machine
oid += ObjectId._machine_bytes
# 2 bytes pid
oid += struct.pack(">H", os.getpid() % 0xFFFF)
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train | ObjectId.__validate | Validate and use the given id for this ObjectId.
Raises TypeError if id is not an instance of
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in python 3), ObjectId) and InvalidId if it is not a
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:Parameters:
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"""Validate and use the given id for this ObjectId.
Raises TypeError if id is not an instance of
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in python 3), ObjectId) and InvalidId if it is not a
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"""Validate and use the given id for this ObjectId.
Raises TypeError if id is not an instance of
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train | SparkCheck._get_master_address | Get the master address from the instance configuration | spark/datadog_checks/spark/spark.py | def _get_master_address(self, instance):
"""
Get the master address from the instance configuration
"""
master_address = instance.get(MASTER_ADDRESS)
if master_address is None:
master_address = instance.get(DEPRECATED_MASTER_ADDRESS)
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Get the master address from the instance configuration
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master_address = instance.get(MASTER_ADDRESS)
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master_address = instance.get(DEPRECATED_MASTER_ADDRESS)
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train | SparkCheck._get_request_url | Get the request address, build with proxy if necessary | spark/datadog_checks/spark/spark.py | def _get_request_url(self, instance, url):
"""
Get the request address, build with proxy if necessary
"""
parsed = urlparse(url)
_url = url
if not (parsed.netloc and parsed.scheme) and is_affirmative(instance.get('spark_proxy_enabled', False)):
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"""
Get the request address, build with proxy if necessary
"""
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_url = url
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train | SparkCheck._get_running_apps | Determine what mode was specified | spark/datadog_checks/spark/spark.py | def _get_running_apps(self, instance, requests_config):
"""
Determine what mode was specified
"""
tags = instance.get('tags', [])
if tags is None:
tags = []
master_address = self._get_master_address(instance)
# Get the cluster name from the instance co... | def _get_running_apps(self, instance, requests_config):
"""
Determine what mode was specified
"""
tags = instance.get('tags', [])
if tags is None:
tags = []
master_address = self._get_master_address(instance)
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train | SparkCheck._standalone_init | Return a dictionary of {app_id: (app_name, tracking_url)} for the running Spark applications | spark/datadog_checks/spark/spark.py | def _standalone_init(self, spark_master_address, pre_20_mode, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for the running Spark applications
"""
metrics_json = self._rest_request_to_json(
spark_master_address, SPARK_MASTER_STATE_PATH,... | def _standalone_init(self, spark_master_address, pre_20_mode, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for the running Spark applications
"""
metrics_json = self._rest_request_to_json(
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train | SparkCheck._mesos_init | Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications. | spark/datadog_checks/spark/spark.py | def _mesos_init(self, instance, master_address, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications.
"""
running_apps = {}
metrics_json = self._rest_request_to_json(
master_address, MESOS_MASTER_APP_PAT... | def _mesos_init(self, instance, master_address, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications.
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train | SparkCheck._yarn_init | Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications. | spark/datadog_checks/spark/spark.py | def _yarn_init(self, rm_address, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications.
"""
running_apps = self._yarn_get_running_spark_apps(rm_address, requests_config, tags)
# Report success after gathering all met... | def _yarn_init(self, rm_address, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications.
"""
running_apps = self._yarn_get_running_spark_apps(rm_address, requests_config, tags)
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train | SparkCheck._get_standalone_app_url | Return the application URL from the app info page on the Spark master.
Due to a bug, we need to parse the HTML manually because we cannot
fetch JSON data from HTTP interface. | spark/datadog_checks/spark/spark.py | def _get_standalone_app_url(self, app_id, spark_master_address, requests_config, tags):
"""
Return the application URL from the app info page on the Spark master.
Due to a bug, we need to parse the HTML manually because we cannot
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"""
a... | def _get_standalone_app_url(self, app_id, spark_master_address, requests_config, tags):
"""
Return the application URL from the app info page on the Spark master.
Due to a bug, we need to parse the HTML manually because we cannot
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train | SparkCheck._yarn_get_running_spark_apps | Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications.
The `app_id` returned is that of the YARN application. This will eventually be mapped into
a Spark application ID. | spark/datadog_checks/spark/spark.py | def _yarn_get_running_spark_apps(self, rm_address, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications.
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... | def _yarn_get_running_spark_apps(self, rm_address, requests_config, tags):
"""
Return a dictionary of {app_id: (app_name, tracking_url)} for running Spark applications.
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train | SparkCheck._get_spark_app_ids | Traverses the Spark application master in YARN to get a Spark application ID.
Return a dictionary of {app_id: (app_name, tracking_url)} for Spark applications | spark/datadog_checks/spark/spark.py | def _get_spark_app_ids(self, running_apps, requests_config, tags):
"""
Traverses the Spark application master in YARN to get a Spark application ID.
Return a dictionary of {app_id: (app_name, tracking_url)} for Spark applications
"""
spark_apps = {}
for app_id, (app_name... | def _get_spark_app_ids(self, running_apps, requests_config, tags):
"""
Traverses the Spark application master in YARN to get a Spark application ID.
Return a dictionary of {app_id: (app_name, tracking_url)} for Spark applications
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spark_apps = {}
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train | SparkCheck._spark_job_metrics | Get metrics for each Spark job. | spark/datadog_checks/spark/spark.py | def _spark_job_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each Spark job.
"""
for app_id, (app_name, tracking_url) in iteritems(running_apps):
base_url = self._get_request_url(instance, tracking_url)
response = self._re... | def _spark_job_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each Spark job.
"""
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train | SparkCheck._spark_executor_metrics | Get metrics for each Spark executor. | spark/datadog_checks/spark/spark.py | def _spark_executor_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each Spark executor.
"""
for app_id, (app_name, tracking_url) in iteritems(running_apps):
base_url = self._get_request_url(instance, tracking_url)
response ... | def _spark_executor_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each Spark executor.
"""
for app_id, (app_name, tracking_url) in iteritems(running_apps):
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train | SparkCheck._spark_rdd_metrics | Get metrics for each Spark RDD. | spark/datadog_checks/spark/spark.py | def _spark_rdd_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each Spark RDD.
"""
for app_id, (app_name, tracking_url) in iteritems(running_apps):
base_url = self._get_request_url(instance, tracking_url)
response = self._re... | def _spark_rdd_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each Spark RDD.
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train | SparkCheck._spark_streaming_statistics_metrics | Get metrics for each application streaming statistics. | spark/datadog_checks/spark/spark.py | def _spark_streaming_statistics_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each application streaming statistics.
"""
for app_id, (app_name, tracking_url) in iteritems(running_apps):
try:
base_url = self._get_request... | def _spark_streaming_statistics_metrics(self, instance, running_apps, addl_tags, requests_config):
"""
Get metrics for each application streaming statistics.
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for app_id, (app_name, tracking_url) in iteritems(running_apps):
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train | SparkCheck._set_metric | Set a metric | spark/datadog_checks/spark/spark.py | def _set_metric(self, metric_name, metric_type, value, tags=None):
"""
Set a metric
"""
if tags is None:
tags = []
if metric_type == GAUGE:
self.gauge(metric_name, value, tags=tags)
elif metric_type == COUNT:
self.count(metric_name, val... | def _set_metric(self, metric_name, metric_type, value, tags=None):
"""
Set a metric
"""
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tags = []
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self.gauge(metric_name, value, tags=tags)
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train | SparkCheck._rest_request | Query the given URL and return the response | spark/datadog_checks/spark/spark.py | def _rest_request(self, url, object_path, service_name, requests_config, tags, *args, **kwargs):
"""
Query the given URL and return the response
"""
service_check_tags = ['url:%s' % self._get_url_base(url)] + tags
if object_path:
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"""
Query the given URL and return the response
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train | SparkCheck._rest_request_to_json | Query the given URL and return the JSON response | spark/datadog_checks/spark/spark.py | def _rest_request_to_json(self, address, object_path, service_name, requests_config, tags, *args, **kwargs):
"""
Query the given URL and return the JSON response
"""
response = self._rest_request(address, object_path, service_name, requests_config, tags, *args, **kwargs)
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"""
Query the given URL and return the JSON response
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response = self._rest_request(address, object_path, service_name, requests_config, tags, *args, **kwargs)
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train | SparkCheck._get_url_base | Return the base of a URL | spark/datadog_checks/spark/spark.py | def _get_url_base(cls, url):
"""
Return the base of a URL
"""
s = urlsplit(url)
return urlunsplit([s.scheme, s.netloc, '', '', '']) | def _get_url_base(cls, url):
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Return the base of a URL
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return urlunsplit([s.scheme, s.netloc, '', '', '']) | [
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train | parse_capacity_tags | This parses tags from a dn designator. They look like this:
topology/pod-1/node-101/sys/phys-[eth1/6]/CDeqptMacsectxpkts5min | cisco_aci/datadog_checks/cisco_aci/helpers.py | def parse_capacity_tags(dn):
"""
This parses tags from a dn designator. They look like this:
topology/pod-1/node-101/sys/phys-[eth1/6]/CDeqptMacsectxpkts5min
"""
tags = []
pod = get_pod_from_dn(dn)
if pod:
tags.append("fabric_pod_id:{}".format(pod))
node = get_node_from_dn(dn)
... | def parse_capacity_tags(dn):
"""
This parses tags from a dn designator. They look like this:
topology/pod-1/node-101/sys/phys-[eth1/6]/CDeqptMacsectxpkts5min
"""
tags = []
pod = get_pod_from_dn(dn)
if pod:
tags.append("fabric_pod_id:{}".format(pod))
node = get_node_from_dn(dn)
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train | get_event_tags_from_dn | This grabs the event tags from the dn designator. They look like this:
uni/tn-DataDog/ap-DtDg-AP1-EcommerceApp/epg-DtDg-Ecomm/HDl2IngrPktsAg1h | cisco_aci/datadog_checks/cisco_aci/helpers.py | def get_event_tags_from_dn(dn):
"""
This grabs the event tags from the dn designator. They look like this:
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"""
tags = []
node = get_node_from_dn(dn)
if node:
tags.append("node:" + node)
app = get_app_from_dn(... | def get_event_tags_from_dn(dn):
"""
This grabs the event tags from the dn designator. They look like this:
uni/tn-DataDog/ap-DtDg-AP1-EcommerceApp/epg-DtDg-Ecomm/HDl2IngrPktsAg1h
"""
tags = []
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tags.append("node:" + node)
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train | get_hostname_from_dn | This parses the hostname from a dn designator. They look like this:
topology/pod-1/node-101/sys/phys-[eth1/6]/CDeqptMacsectxpkts5min | cisco_aci/datadog_checks/cisco_aci/helpers.py | def get_hostname_from_dn(dn):
"""
This parses the hostname from a dn designator. They look like this:
topology/pod-1/node-101/sys/phys-[eth1/6]/CDeqptMacsectxpkts5min
"""
pod = get_pod_from_dn(dn)
node = get_node_from_dn(dn)
if pod and node:
return "pod-{}-node-{}".format(pod, node)
... | def get_hostname_from_dn(dn):
"""
This parses the hostname from a dn designator. They look like this:
topology/pod-1/node-101/sys/phys-[eth1/6]/CDeqptMacsectxpkts5min
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pod = get_pod_from_dn(dn)
node = get_node_from_dn(dn)
if pod and node:
return "pod-{}-node-{}".format(pod, node)
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train | get_attributes | the json objects look like this:
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"attributes": {
...
}
}
It always has the attributes nested below the object type
This helper provides a way of getting at the attributes | cisco_aci/datadog_checks/cisco_aci/helpers.py | def get_attributes(obj):
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...
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train | check_metric_can_be_zero | When a counter is reset, don't send a zero because it will look bad on the graphs
This checks if the zero makes sense or not | cisco_aci/datadog_checks/cisco_aci/helpers.py | def check_metric_can_be_zero(metric_name, metric_value, json_attributes):
"""
When a counter is reset, don't send a zero because it will look bad on the graphs
This checks if the zero makes sense or not
"""
if "last" in metric_name.lower():
return True
if not metric_value:
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"""
When a counter is reset, don't send a zero because it will look bad on the graphs
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if "last" in metric_name.lower():
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train | create | Create scaffolding for a new integration. | datadog_checks_dev/datadog_checks/dev/tooling/commands/create.py | def create(ctx, name, integration_type, location, non_interactive, quiet, dry_run):
"""Create scaffolding for a new integration."""
repo_choice = ctx.obj['repo_choice']
root = resolve_path(location) if location else get_root()
path_sep = os.path.sep
integration_dir = os.path.join(root, normalize_pa... | def create(ctx, name, integration_type, location, non_interactive, quiet, dry_run):
"""Create scaffolding for a new integration."""
repo_choice = ctx.obj['repo_choice']
root = resolve_path(location) if location else get_root()
path_sep = os.path.sep
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train | freeze | Freezes any mutable object including dictionaries and lists for hashing.
Accepts nested dictionaries. | datadog_checks_base/datadog_checks/base/utils/containers.py | def freeze(o):
"""
Freezes any mutable object including dictionaries and lists for hashing.
Accepts nested dictionaries.
"""
if isinstance(o, (tuple, list)):
return tuple(sorted(freeze(e) for e in o))
if isinstance(o, dict):
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Freezes any mutable object including dictionaries and lists for hashing.
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train | _decimal_to_128 | Converts a decimal.Decimal to BID (high bits, low bits).
:Parameters:
- `value`: An instance of decimal.Decimal | tokumx/datadog_checks/tokumx/vendor/bson/decimal128.py | def _decimal_to_128(value):
"""Converts a decimal.Decimal to BID (high bits, low bits).
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- `value`: An instance of decimal.Decimal
"""
with decimal.localcontext(_DEC128_CTX) as ctx:
value = ctx.create_decimal(value)
if value.is_infinite():
return _NINF if value.is... | def _decimal_to_128(value):
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- `value`: An instance of decimal.Decimal
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with decimal.localcontext(_DEC128_CTX) as ctx:
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train | Decimal128.to_decimal | Returns an instance of :class:`decimal.Decimal` for this
:class:`Decimal128`. | tokumx/datadog_checks/tokumx/vendor/bson/decimal128.py | def to_decimal(self):
"""Returns an instance of :class:`decimal.Decimal` for this
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"""
high = self.__high
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sign = 1 if (high & _SIGN) else 0
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sign = 1 if (high & _SIGN) else 0
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train | Decimal128.from_bid | Create an instance of :class:`Decimal128` from Binary Integer
Decimal string.
:Parameters:
- `value`: 16 byte string (128-bit IEEE 754-2008 decimal floating
point in Binary Integer Decimal (BID) format). | tokumx/datadog_checks/tokumx/vendor/bson/decimal128.py | def from_bid(cls, value):
"""Create an instance of :class:`Decimal128` from Binary Integer
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- `value`: 16 byte string (128-bit IEEE 754-2008 decimal floating
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train | IBMMQConfig._compile_tag_re | Compile regex strings from queue_tag_re option and return list of compiled regex/tag pairs | ibm_mq/datadog_checks/ibm_mq/config.py | def _compile_tag_re(self):
"""
Compile regex strings from queue_tag_re option and return list of compiled regex/tag pairs
"""
queue_tag_list = []
for regex_str, tags in iteritems(self._queue_tag_re):
try:
queue_tag_list.append([re.compile(regex_str), [... | def _compile_tag_re(self):
"""
Compile regex strings from queue_tag_re option and return list of compiled regex/tag pairs
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queue_tag_list = []
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train | _get_server_type | Determine the server type from an ismaster response. | tokumx/datadog_checks/tokumx/vendor/pymongo/ismaster.py | def _get_server_type(doc):
"""Determine the server type from an ismaster response."""
if not doc.get('ok'):
return SERVER_TYPE.Unknown
if doc.get('isreplicaset'):
return SERVER_TYPE.RSGhost
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return SERVER_TYPE.RSOther
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"""Determine the server type from an ismaster response."""
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return SERVER_TYPE.Unknown
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return SERVER_TYPE.RSGhost
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train | IsMaster.all_hosts | List of hosts, passives, and arbiters known to this server. | tokumx/datadog_checks/tokumx/vendor/pymongo/ismaster.py | def all_hosts(self):
"""List of hosts, passives, and arbiters known to this server."""
return set(imap(common.clean_node, itertools.chain(
self._doc.get('hosts', []),
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train | GitlabRunnerCheck._create_gitlab_runner_prometheus_instance | Set up the gitlab_runner instance so it can be used in OpenMetricsBaseCheck | gitlab_runner/datadog_checks/gitlab_runner/gitlab_runner.py | def _create_gitlab_runner_prometheus_instance(self, instance, init_config):
"""
Set up the gitlab_runner instance so it can be used in OpenMetricsBaseCheck
"""
# Mapping from Prometheus metrics names to Datadog ones
# For now it's a 1:1 mapping
allowed_metrics = init_conf... | def _create_gitlab_runner_prometheus_instance(self, instance, init_config):
"""
Set up the gitlab_runner instance so it can be used in OpenMetricsBaseCheck
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# Mapping from Prometheus metrics names to Datadog ones
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train | HDFSDataNode._get_jmx_data | Get namenode beans data from JMX endpoint | hdfs_datanode/datadog_checks/hdfs_datanode/hdfs_datanode.py | def _get_jmx_data(self, instance, jmx_address, tags):
"""
Get namenode beans data from JMX endpoint
"""
response = self._rest_request_to_json(
instance, jmx_address, self.JMX_PATH, {'qry': self.HDFS_DATANODE_BEAN_NAME}, tags=tags
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beans = response.get('beans'... | def _get_jmx_data(self, instance, jmx_address, tags):
"""
Get namenode beans data from JMX endpoint
"""
response = self._rest_request_to_json(
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beans = response.get('beans'... | [
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train | HDFSDataNode._hdfs_datanode_metrics | Process HDFS Datanode metrics from given beans | hdfs_datanode/datadog_checks/hdfs_datanode/hdfs_datanode.py | def _hdfs_datanode_metrics(self, beans, tags):
"""
Process HDFS Datanode metrics from given beans
"""
# Only get the first bean
bean = next(iter(beans))
bean_name = bean.get('name')
self.log.debug("Bean name retrieved: {}".format(bean_name))
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"""
Process HDFS Datanode metrics from given beans
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# Only get the first bean
bean = next(iter(beans))
bean_name = bean.get('name')
self.log.debug("Bean name retrieved: {}".format(bean_name))
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train | requirements | Write the `requirements-agent-release.txt` file at the root of the repo
listing all the Agent-based integrations pinned at the version they currently
have in HEAD. | datadog_checks_dev/datadog_checks/dev/tooling/commands/agent/requirements.py | def requirements(ctx):
"""Write the `requirements-agent-release.txt` file at the root of the repo
listing all the Agent-based integrations pinned at the version they currently
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"""
echo_info('Freezing check releases')
checks = get_valid_checks()
checks.remove('datadog_checks_dev... | def requirements(ctx):
"""Write the `requirements-agent-release.txt` file at the root of the repo
listing all the Agent-based integrations pinned at the version they currently
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"""
echo_info('Freezing check releases')
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train | Nginx._nest_payload | Nest a payload in a dict under the keys contained in `keys` | nginx/datadog_checks/nginx/nginx.py | def _nest_payload(self, keys, payload):
"""
Nest a payload in a dict under the keys contained in `keys`
"""
if len(keys) == 0:
return payload
return {keys[0]: self._nest_payload(keys[1:], payload)} | def _nest_payload(self, keys, payload):
"""
Nest a payload in a dict under the keys contained in `keys`
"""
if len(keys) == 0:
return payload
return {keys[0]: self._nest_payload(keys[1:], payload)} | [
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train | Nginx._flatten_json | Recursively flattens the nginx json object. Returns the following: [(metric_name, value, tags)] | nginx/datadog_checks/nginx/nginx.py | def _flatten_json(cls, metric_base, val, tags):
"""
Recursively flattens the nginx json object. Returns the following: [(metric_name, value, tags)]
"""
output = []
if isinstance(val, dict):
# Pull out the server as a tag instead of trying to read as a metric
... | def _flatten_json(cls, metric_base, val, tags):
"""
Recursively flattens the nginx json object. Returns the following: [(metric_name, value, tags)]
"""
output = []
if isinstance(val, dict):
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train | get_agent_tags | Return a list of tags from integrations-core representing an Agent release,
sorted by more recent first. | datadog_checks_dev/datadog_checks/dev/tooling/commands/agent/common.py | def get_agent_tags(since, to):
"""
Return a list of tags from integrations-core representing an Agent release,
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"""
agent_tags = sorted(parse_version_info(t) for t in git_tag_list(r'^\d+\.\d+\.\d+$'))
# default value for `to` is the latest tag
if to:
to =... | def get_agent_tags(since, to):
"""
Return a list of tags from integrations-core representing an Agent release,
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"""
agent_tags = sorted(parse_version_info(t) for t in git_tag_list(r'^\d+\.\d+\.\d+$'))
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train | run | Run commands in the proper repo. | datadog_checks_dev/datadog_checks/dev/tooling/commands/run.py | def run(ctx, args):
"""Run commands in the proper repo."""
if not args:
click.echo(ctx.get_help())
return
with chdir(get_root()):
result = run_command(args)
ctx.exit(result.code) | def run(ctx, args):
"""Run commands in the proper repo."""
if not args:
click.echo(ctx.get_help())
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train | TeamCityCheck._normalize_server_url | Check if the server URL starts with a HTTP or HTTPS scheme, fall back to http if not present | teamcity/datadog_checks/teamcity/teamcity.py | def _normalize_server_url(self, server):
"""
Check if the server URL starts with a HTTP or HTTPS scheme, fall back to http if not present
"""
server = server if server.startswith(("http://", "https://")) else "http://{}".format(server)
return server | def _normalize_server_url(self, server):
"""
Check if the server URL starts with a HTTP or HTTPS scheme, fall back to http if not present
"""
server = server if server.startswith(("http://", "https://")) else "http://{}".format(server)
return server | [
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train | ESCheck._get_es_version | Get the running version of elasticsearch. | elastic/datadog_checks/elastic/elastic.py | def _get_es_version(self, config):
"""
Get the running version of elasticsearch.
"""
try:
data = self._get_data(config.url, config, send_sc=False)
# pre-release versions of elasticearch are suffixed with -rcX etc..
# peel that off so that the map below... | def _get_es_version(self, config):
"""
Get the running version of elasticsearch.
"""
try:
data = self._get_data(config.url, config, send_sc=False)
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train | ESCheck._join_url | overrides `urlparse.urljoin` since it removes base url path
https://docs.python.org/2/library/urlparse.html#urlparse.urljoin | elastic/datadog_checks/elastic/elastic.py | def _join_url(self, base, url, admin_forwarder=False):
"""
overrides `urlparse.urljoin` since it removes base url path
https://docs.python.org/2/library/urlparse.html#urlparse.urljoin
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if admin_forwarder:
return base + url
else:
return urljoin(b... | def _join_url(self, base, url, admin_forwarder=False):
"""
overrides `urlparse.urljoin` since it removes base url path
https://docs.python.org/2/library/urlparse.html#urlparse.urljoin
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if admin_forwarder:
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train | ESCheck._get_urls | Compute the URLs we need to hit depending on the running ES version | elastic/datadog_checks/elastic/elastic.py | def _get_urls(self, version, cluster_stats):
"""
Compute the URLs we need to hit depending on the running ES version
"""
pshard_stats_url = "/_stats"
health_url = "/_cluster/health"
if version >= [0, 90, 10]:
pending_tasks_url = "/_cluster/pending_tasks"
... | def _get_urls(self, version, cluster_stats):
"""
Compute the URLs we need to hit depending on the running ES version
"""
pshard_stats_url = "/_stats"
health_url = "/_cluster/health"
if version >= [0, 90, 10]:
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train | ESCheck._get_data | Hit a given URL and return the parsed json | elastic/datadog_checks/elastic/elastic.py | def _get_data(self, url, config, send_sc=True):
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train | Limiter.reset | Resets state and uid set. To be called asap to free memory | datadog_checks_base/datadog_checks/base/utils/limiter.py | def reset(self):
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Fetch highwater offsets for each topic/partition from Kafka cluster.
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train | KafkaCheck._get_zk_path_children | Fetch child nodes for a given Zookeeper path. | kafka_consumer/datadog_checks/kafka_consumer/kafka_consumer.py | def _get_zk_path_children(self, zk_conn, zk_path, name_for_error):
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train | KafkaCheck._get_zk_consumer_offsets | Fetch Consumer Group offsets from Zookeeper.
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Fetch Consumer Group offsets from Zookeeper.
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train | KafkaCheck._get_kafka_consumer_offsets | retrieve consumer offsets via the new consumer api. Offsets in this version are stored directly
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train | KafkaCheck._validate_explicit_consumer_groups | Validate any explicitly specified consumer groups.
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val = {'consumer_group': {'topic': [0, 1]}} | kafka_consumer/datadog_checks/kafka_consumer/kafka_consumer.py | def _validate_explicit_consumer_groups(cls, val):
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val = {'consumer_group': {'topic': [0, 1]}}
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train | KafkaCheck._send_event | Emit an event to the Datadog Event Stream. | kafka_consumer/datadog_checks/kafka_consumer/kafka_consumer.py | def _send_event(self, title, text, tags, event_type, aggregation_key, severity='info'):
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train | display_package_changes | Print packages that've been added, removed or changed | datadog_checks_dev/datadog_checks/dev/tooling/commands/dep.py | def display_package_changes(pre_packages, post_packages, indent=''):
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Print packages that've been added, removed or changed
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# use package name to determine what's changed
pre_package_names = {p.name: p for p in pre_packages}
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train | resolve | Resolve transient dependencies for any number of checks.
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train | pin | Pin a dependency for all checks that require it. This can
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train | freeze | Combine all dependencies for the Agent's static environment. | datadog_checks_dev/datadog_checks/dev/tooling/commands/dep.py | def freeze():
"""Combine all dependencies for the Agent's static environment."""
echo_waiting('Verifying collected packages...')
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echo_failure(error)
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train | reload_env | Restart an Agent to detect environment changes. | datadog_checks_dev/datadog_checks/dev/tooling/commands/env/reload.py | def reload_env(check, env):
"""Restart an Agent to detect environment changes."""
envs = get_configured_envs(check)
if not envs:
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echo_failure('No active environments found for `{}`.'.format(check))
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train | GitlabCheck._create_gitlab_prometheus_instance | Set up the gitlab instance so it can be used in OpenMetricsBaseCheck | gitlab/datadog_checks/gitlab/gitlab.py | def _create_gitlab_prometheus_instance(self, instance, init_config):
"""
Set up the gitlab instance so it can be used in OpenMetricsBaseCheck
"""
# Mapping from Prometheus metrics names to Datadog ones
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Set up the gitlab instance so it can be used in OpenMetricsBaseCheck
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train | PrometheusScraper._submit_gauge | Submit a metric as a gauge, additional tags provided will be added to
the ones from the label provided via the metrics object.
`custom_tags` is an array of 'tag:value' that will be added to the
metric when sending the gauge to Datadog. | datadog_checks_base/datadog_checks/base/checks/prometheus/base_check.py | def _submit_gauge(self, metric_name, val, metric, custom_tags=None, hostname=None):
"""
Submit a metric as a gauge, additional tags provided will be added to
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`custom_tags` is an array of 'tag:value' that will be added to the
... | def _submit_gauge(self, metric_name, val, metric, custom_tags=None, hostname=None):
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Submit a metric as a gauge, additional tags provided will be added to
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`custom_tags` is an array of 'tag:value' that will be added to the
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train | _validate_tag_sets | Validate tag sets for a MongoReplicaSetClient. | tokumx/datadog_checks/tokumx/vendor/pymongo/read_preferences.py | def _validate_tag_sets(tag_sets):
"""Validate tag sets for a MongoReplicaSetClient.
"""
if tag_sets is None:
return tag_sets
if not isinstance(tag_sets, list):
raise TypeError((
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if len(tag_sets) == 0:
raise Va... | def _validate_tag_sets(tag_sets):
"""Validate tag sets for a MongoReplicaSetClient.
"""
if tag_sets is None:
return tag_sets
if not isinstance(tag_sets, list):
raise TypeError((
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if len(tag_sets) == 0:
raise Va... | [
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train | _validate_max_staleness | Validate max_staleness. | tokumx/datadog_checks/tokumx/vendor/pymongo/read_preferences.py | def _validate_max_staleness(max_staleness):
"""Validate max_staleness."""
if max_staleness == -1:
return -1
if not isinstance(max_staleness, integer_types):
raise TypeError(_invalid_max_staleness_msg(max_staleness))
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"""Validate max_staleness."""
if max_staleness == -1:
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if not isinstance(max_staleness, integer_types):
raise TypeError(_invalid_max_staleness_msg(max_staleness))
if max_staleness <= 0:
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train | _ServerMode.document | Read preference as a document. | tokumx/datadog_checks/tokumx/vendor/pymongo/read_preferences.py | def document(self):
"""Read preference as a document.
"""
doc = {'mode': self.__mongos_mode}
if self.__tag_sets not in (None, [{}]):
doc['tags'] = self.__tag_sets
if self.__max_staleness != -1:
doc['maxStalenessSeconds'] = self.__max_staleness
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"""Read preference as a document.
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doc = {'mode': self.__mongos_mode}
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doc['tags'] = self.__tag_sets
if self.__max_staleness != -1:
doc['maxStalenessSeconds'] = self.__max_staleness
retu... | [
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train | config | Validate default configuration files. | datadog_checks_dev/datadog_checks/dev/tooling/commands/validate/config.py | def config(check):
"""Validate default configuration files."""
if check:
checks = [check]
else:
checks = sorted(get_valid_checks())
files_failed = {}
files_warned = {}
num_files = 0
echo_waiting('Validating default configuration files...')
for check in checks:
c... | def config(check):
"""Validate default configuration files."""
if check:
checks = [check]
else:
checks = sorted(get_valid_checks())
files_failed = {}
files_warned = {}
num_files = 0
echo_waiting('Validating default configuration files...')
for check in checks:
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train | IbmMqCheck.queue_manager_stats | Get stats from the queue manager | ibm_mq/datadog_checks/ibm_mq/ibm_mq.py | def queue_manager_stats(self, queue_manager, tags):
"""
Get stats from the queue manager
"""
for mname, pymqi_value in iteritems(metrics.queue_manager_metrics()):
try:
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mname = '{}.queue_manager.{}'.format... | def queue_manager_stats(self, queue_manager, tags):
"""
Get stats from the queue manager
"""
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train | IbmMqCheck.queue_stats | Grab stats from queues | ibm_mq/datadog_checks/ibm_mq/ibm_mq.py | def queue_stats(self, queue, tags):
"""
Grab stats from queues
"""
for mname, pymqi_value in iteritems(metrics.queue_metrics()):
try:
mname = '{}.queue.{}'.format(self.METRIC_PREFIX, mname)
m = queue.inquire(pymqi_value)
self.ga... | def queue_stats(self, queue, tags):
"""
Grab stats from queues
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train | get_version_string | Get the version string for the given check. | datadog_checks_dev/datadog_checks/dev/tooling/utils.py | def get_version_string(check_name):
"""
Get the version string for the given check.
"""
version = VERSION.search(read_version_file(check_name))
if version:
return version.group(1) | def get_version_string(check_name):
"""
Get the version string for the given check.
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train | load_manifest | Load the manifest file into a dictionary | datadog_checks_dev/datadog_checks/dev/tooling/utils.py | def load_manifest(check_name):
"""
Load the manifest file into a dictionary
"""
manifest_path = os.path.join(get_root(), check_name, 'manifest.json')
if file_exists(manifest_path):
return json.loads(read_file(manifest_path))
return {} | def load_manifest(check_name):
"""
Load the manifest file into a dictionary
"""
manifest_path = os.path.join(get_root(), check_name, 'manifest.json')
if file_exists(manifest_path):
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return {} | [
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train | parse_agent_req_file | Returns a dictionary mapping {check-package-name --> pinned_version} from the
given file contents. We can assume lines are in the form:
datadog-active-directory==1.1.1; sys_platform == 'win32' | datadog_checks_dev/datadog_checks/dev/tooling/utils.py | def parse_agent_req_file(contents):
"""
Returns a dictionary mapping {check-package-name --> pinned_version} from the
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datadog-active-directory==1.1.1; sys_platform == 'win32'
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catalog = OrderedDict()
for line in contents.spli... | def parse_agent_req_file(contents):
"""
Returns a dictionary mapping {check-package-name --> pinned_version} from the
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train | MySql._collect_dict | Query status and get a dictionary back.
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query: show status...
field_metric_map: {"Seconds_behind_master": "mysqlSecondsBehindMaster"} | mysql/datadog_checks/mysql/mysql.py | def _collect_dict(self, metric_type, field_metric_map, query, db, tags):
"""
Query status and get a dictionary back.
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query: show status...
field_metric_map: {"Seconds_behind_master": "mysq... | def _collect_dict(self, metric_type, field_metric_map, query, db, tags):
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Query status and get a dictionary back.
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train | MySql._get_pid_file_variable | Get the `pid_file` variable | mysql/datadog_checks/mysql/mysql.py | def _get_pid_file_variable(self, db):
"""
Get the `pid_file` variable
"""
pid_file = None
try:
with closing(db.cursor()) as cursor:
cursor.execute("SHOW VARIABLES LIKE 'pid_file'")
pid_file = cursor.fetchone()[1]
except Exceptio... | def _get_pid_file_variable(self, db):
"""
Get the `pid_file` variable
"""
pid_file = None
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"(",
"\"SHOW VARIABLES LIKE 'pid_file'\"",
")... | ebd41c873cf9f97a8c51bf9459bc6a7536af8acd |
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