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aws/aws-xray-sdk-python | aws_xray_sdk/ext/util.py | calculate_segment_name | def calculate_segment_name(host_name, recorder):
"""
Returns the segment name based on recorder configuration and
input host name. This is a helper generally used in web framework
middleware where a host name is available from incoming request's headers.
"""
if recorder.dynamic_naming:
r... | python | def calculate_segment_name(host_name, recorder):
"""
Returns the segment name based on recorder configuration and
input host name. This is a helper generally used in web framework
middleware where a host name is available from incoming request's headers.
"""
if recorder.dynamic_naming:
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/util.py | prepare_response_header | def prepare_response_header(origin_header, segment):
"""
Prepare a trace header to be inserted into response
based on original header and the request segment.
"""
if origin_header and origin_header.sampled == '?':
new_header = TraceHeader(root=segment.trace_id,
... | python | def prepare_response_header(origin_header, segment):
"""
Prepare a trace header to be inserted into response
based on original header and the request segment.
"""
if origin_header and origin_header.sampled == '?':
new_header = TraceHeader(root=segment.trace_id,
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/util.py | to_snake_case | def to_snake_case(name):
"""
Convert the input string to snake-cased string.
"""
s1 = first_cap_re.sub(r'\1_\2', name)
# handle acronym words
return all_cap_re.sub(r'\1_\2', s1).lower() | python | def to_snake_case(name):
"""
Convert the input string to snake-cased string.
"""
s1 = first_cap_re.sub(r'\1_\2', name)
# handle acronym words
return all_cap_re.sub(r'\1_\2', s1).lower() | [
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/botocore/patch.py | patch | def patch():
"""
Patch botocore client so it generates subsegments
when calling AWS services.
"""
if hasattr(botocore.client, '_xray_enabled'):
return
setattr(botocore.client, '_xray_enabled', True)
wrapt.wrap_function_wrapper(
'botocore.client',
'BaseClient._make_ap... | python | def patch():
"""
Patch botocore client so it generates subsegments
when calling AWS services.
"""
if hasattr(botocore.client, '_xray_enabled'):
return
setattr(botocore.client, '_xray_enabled', True)
wrapt.wrap_function_wrapper(
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.configure | def configure(self, sampling=None, plugins=None,
context_missing=None, sampling_rules=None,
daemon_address=None, service=None,
context=None, emitter=None, streaming=None,
dynamic_naming=None, streaming_threshold=None,
max_trace_ba... | python | def configure(self, sampling=None, plugins=None,
context_missing=None, sampling_rules=None,
daemon_address=None, service=None,
context=None, emitter=None, streaming=None,
dynamic_naming=None, streaming_threshold=None,
max_trace_ba... | [
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Configure needs to run before patching thrid party libraries
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:param bool sampling: If sampling is enabled, every time the recorder
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.begin_segment | def begin_segment(self, name=None, traceid=None,
parent_id=None, sampling=None):
"""
Begin a segment on the current thread and return it. The recorder
only keeps one segment at a time. Create the second one without
closing existing one will overwrite it.
:p... | python | def begin_segment(self, name=None, traceid=None,
parent_id=None, sampling=None):
"""
Begin a segment on the current thread and return it. The recorder
only keeps one segment at a time. Create the second one without
closing existing one will overwrite it.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.end_segment | def end_segment(self, end_time=None):
"""
End the current segment and send it to X-Ray daemon
if it is ready to send. Ready means segment and
all its subsegments are closed.
:param float end_time: segment compeletion in unix epoch in seconds.
"""
self.context.end... | python | def end_segment(self, end_time=None):
"""
End the current segment and send it to X-Ray daemon
if it is ready to send. Ready means segment and
all its subsegments are closed.
:param float end_time: segment compeletion in unix epoch in seconds.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.current_segment | def current_segment(self):
"""
Return the currently active segment. In a multithreading environment,
this will make sure the segment returned is the one created by the
same thread.
"""
entity = self.get_trace_entity()
if self._is_subsegment(entity):
re... | python | def current_segment(self):
"""
Return the currently active segment. In a multithreading environment,
this will make sure the segment returned is the one created by the
same thread.
"""
entity = self.get_trace_entity()
if self._is_subsegment(entity):
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.begin_subsegment | def begin_subsegment(self, name, namespace='local'):
"""
Begin a new subsegment.
If there is open subsegment, the newly created subsegment will be the
child of latest opened subsegment.
If not, it will be the child of the current open segment.
:param str name: the name o... | python | def begin_subsegment(self, name, namespace='local'):
"""
Begin a new subsegment.
If there is open subsegment, the newly created subsegment will be the
child of latest opened subsegment.
If not, it will be the child of the current open segment.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.end_subsegment | def end_subsegment(self, end_time=None):
"""
End the current active subsegment. If this is the last one open
under its parent segment, the entire segment will be sent.
:param float end_time: subsegment compeletion in unix epoch in seconds.
"""
if not self.context.end_sub... | python | def end_subsegment(self, end_time=None):
"""
End the current active subsegment. If this is the last one open
under its parent segment, the entire segment will be sent.
:param float end_time: subsegment compeletion in unix epoch in seconds.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.put_annotation | def put_annotation(self, key, value):
"""
Annotate current active trace entity with a key-value pair.
Annotations will be indexed for later search query.
:param str key: annotation key
:param object value: annotation value. Any type other than
string/number/bool will... | python | def put_annotation(self, key, value):
"""
Annotate current active trace entity with a key-value pair.
Annotations will be indexed for later search query.
:param str key: annotation key
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.put_metadata | def put_metadata(self, key, value, namespace='default'):
"""
Add metadata to the current active trace entity.
Metadata is not indexed but can be later retrieved
by BatchGetTraces API.
:param str namespace: optional. Default namespace is `default`.
It must be a string... | python | def put_metadata(self, key, value, namespace='default'):
"""
Add metadata to the current active trace entity.
Metadata is not indexed but can be later retrieved
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder.stream_subsegments | def stream_subsegments(self):
"""
Stream all closed subsegments to the daemon
and remove reference to the parent segment.
No-op for a not sampled segment.
"""
segment = self.current_segment()
if self.streaming.is_eligible(segment):
self.streaming.stre... | python | def stream_subsegments(self):
"""
Stream all closed subsegments to the daemon
and remove reference to the parent segment.
No-op for a not sampled segment.
"""
segment = self.current_segment()
if self.streaming.is_eligible(segment):
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aws/aws-xray-sdk-python | aws_xray_sdk/core/recorder.py | AWSXRayRecorder._send_segment | def _send_segment(self):
"""
Send the current segment to X-Ray daemon if it is present and
sampled, then clean up context storage.
The emitter will handle failures.
"""
segment = self.current_segment()
if not segment:
return
if segment.sample... | python | def _send_segment(self):
"""
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aws/aws-xray-sdk-python | aws_xray_sdk/core/sampling/local/sampling_rule.py | SamplingRule.applies | def applies(self, host, method, path):
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/django/apps.py | XRayConfig.ready | def ready(self):
"""
Configure global XRay recorder based on django settings
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because of base command and reload command.
So this function must be idempotent
"""
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Configure global XRay recorder based on django settings
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aws/aws-xray-sdk-python | aws_xray_sdk/core/sampling/sampler.py | DefaultSampler.start | def start(self):
"""
Start rule poller and target poller once X-Ray daemon address
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"""
if not global_sdk_config.sdk_enabled():
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self._rule_poller.start()... | python | def start(self):
"""
Start rule poller and target poller once X-Ray daemon address
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/pynamodb/patch.py | patch | def patch():
"""Patch PynamoDB so it generates subsegements when calling DynamoDB."""
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setattr(botocore.vendored.requests.sessions, '_xray_enabled', True)
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"""Patch PynamoDB so it generates subsegements when calling DynamoDB."""
import pynamodb
if hasattr(botocore.vendored.requests.sessions, '_xray_enabled'):
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aws/aws-xray-sdk-python | aws_xray_sdk/core/context.py | Context.end_segment | def end_segment(self, end_time=None):
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End the current active segment.
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"""
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End the current active segment.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/context.py | Context.put_subsegment | def put_subsegment(self, subsegment):
"""
Store the subsegment created by ``xray_recorder`` to the context.
If you put a new subsegment while there is already an open subsegment,
the new subsegment becomes the child of the existing subsegment.
"""
entity = self.get_trace_... | python | def put_subsegment(self, subsegment):
"""
Store the subsegment created by ``xray_recorder`` to the context.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/context.py | Context.end_subsegment | def end_subsegment(self, end_time=None):
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End the current active segment. Return False if there is no
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:param int end_time: epoch in seconds. If not specified the current
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End the current active segment. Return False if there is no
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aws/aws-xray-sdk-python | aws_xray_sdk/core/context.py | Context.handle_context_missing | def handle_context_missing(self):
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aws/aws-xray-sdk-python | aws_xray_sdk/core/lambda_launcher.py | check_in_lambda | def check_in_lambda():
"""
Return None if SDK is not loaded in AWS Lambda worker.
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"""
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Return None if SDK is not loaded in AWS Lambda worker.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/lambda_launcher.py | LambdaContext._refresh_context | def _refresh_context(self):
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aws/aws-xray-sdk-python | aws_xray_sdk/core/lambda_launcher.py | LambdaContext._initialize_context | def _initialize_context(self, trace_header):
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aws/aws-xray-sdk-python | aws_xray_sdk/sdk_config.py | SDKConfig.set_sdk_enabled | def set_sdk_enabled(cls, value):
"""
Modifies the enabled flag if the "AWS_XRAY_SDK_ENABLED" environment variable is not set,
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Modifies the enabled flag if the "AWS_XRAY_SDK_ENABLED" environment variable is not set,
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/psycopg2/patch.py | _xray_register_type_fix | def _xray_register_type_fix(wrapped, instance, args, kwargs):
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return wrapped... | python | def _xray_register_type_fix(wrapped, instance, args, kwargs):
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aws/aws-xray-sdk-python | aws_xray_sdk/core/models/trace_header.py | TraceHeader.from_header_str | def from_header_str(cls, header):
"""
Create a TraceHeader object from a tracing header string
extracted from a http request headers.
"""
if not header:
return cls()
try:
params = header.strip().split(HEADER_DELIMITER)
header_dict = {}... | python | def from_header_str(cls, header):
"""
Create a TraceHeader object from a tracing header string
extracted from a http request headers.
"""
if not header:
return cls()
try:
params = header.strip().split(HEADER_DELIMITER)
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aws/aws-xray-sdk-python | aws_xray_sdk/core/models/trace_header.py | TraceHeader.to_header_str | def to_header_str(self):
"""
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aws/aws-xray-sdk-python | aws_xray_sdk/core/models/default_dynamic_naming.py | DefaultDynamicNaming.get_name | def get_name(self, host_name):
"""
Returns the segment name based on the input host name.
"""
if wildcard_match(self._pattern, host_name):
return host_name
else:
return self._fallback | python | def get_name(self, host_name):
"""
Returns the segment name based on the input host name.
"""
if wildcard_match(self._pattern, host_name):
return host_name
else:
return self._fallback | [
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aws/aws-xray-sdk-python | aws_xray_sdk/core/emitters/udp_emitter.py | UDPEmitter.set_daemon_address | def set_daemon_address(self, address):
"""
Set up UDP ip and port from the raw daemon address
string using ``DaemonConfig`` class utlities.
"""
if address:
daemon_config = DaemonConfig(address)
self._ip, self._port = daemon_config.udp_ip, daemon_config.udp... | python | def set_daemon_address(self, address):
"""
Set up UDP ip and port from the raw daemon address
string using ``DaemonConfig`` class utlities.
"""
if address:
daemon_config = DaemonConfig(address)
self._ip, self._port = daemon_config.udp_ip, daemon_config.udp... | [
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/aiobotocore/patch.py | patch | def patch():
"""
Patch aiobotocore client so it generates subsegments
when calling AWS services.
"""
if hasattr(aiobotocore.client, '_xray_enabled'):
return
setattr(aiobotocore.client, '_xray_enabled', True)
wrapt.wrap_function_wrapper(
'aiobotocore.client',
'AioBase... | python | def patch():
"""
Patch aiobotocore client so it generates subsegments
when calling AWS services.
"""
if hasattr(aiobotocore.client, '_xray_enabled'):
return
setattr(aiobotocore.client, '_xray_enabled', True)
wrapt.wrap_function_wrapper(
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aws/aws-xray-sdk-python | aws_xray_sdk/core/streaming/default_streaming.py | DefaultStreaming.is_eligible | def is_eligible(self, segment):
"""
A segment is eligible to have its children subsegments streamed
if it is sampled and it breaches streaming threshold.
"""
if not segment or not segment.sampled:
return False
return segment.get_total_subsegments_size() > sel... | python | def is_eligible(self, segment):
"""
A segment is eligible to have its children subsegments streamed
if it is sampled and it breaches streaming threshold.
"""
if not segment or not segment.sampled:
return False
return segment.get_total_subsegments_size() > sel... | [
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aws/aws-xray-sdk-python | aws_xray_sdk/core/streaming/default_streaming.py | DefaultStreaming.stream | def stream(self, entity, callback):
"""
Stream out all eligible children of the input entity.
:param entity: The target entity to be streamed.
:param callback: The function that takes the node and
actually send it out.
"""
with self._lock:
self._s... | python | def stream(self, entity, callback):
"""
Stream out all eligible children of the input entity.
:param entity: The target entity to be streamed.
:param callback: The function that takes the node and
actually send it out.
"""
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/sqlalchemy/util/decorators.py | parse_bind | def parse_bind(bind):
"""Parses a connection string and creates SQL trace metadata"""
if isinstance(bind, Connection):
engine = bind.engine
else:
engine = bind
m = re.match(r"Engine\((.*?)\)", str(engine))
if m is not None:
u = urlparse(m.group(1))
# Add Scheme to use... | python | def parse_bind(bind):
"""Parses a connection string and creates SQL trace metadata"""
if isinstance(bind, Connection):
engine = bind.engine
else:
engine = bind
m = re.match(r"Engine\((.*?)\)", str(engine))
if m is not None:
u = urlparse(m.group(1))
# Add Scheme to use... | [
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aws/aws-xray-sdk-python | aws_xray_sdk/core/models/subsegment.py | Subsegment.add_subsegment | def add_subsegment(self, subsegment):
"""
Add input subsegment as a child subsegment and increment
reference counter and total subsegments counter of the
parent segment.
"""
super(Subsegment, self).add_subsegment(subsegment)
self.parent_segment.increment() | python | def add_subsegment(self, subsegment):
"""
Add input subsegment as a child subsegment and increment
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"""
super(Subsegment, self).add_subsegment(subsegment)
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aws/aws-xray-sdk-python | aws_xray_sdk/core/models/subsegment.py | Subsegment.remove_subsegment | def remove_subsegment(self, subsegment):
"""
Remove input subsegment from child subsegemnts and
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:param Subsegment: subsegment to remove.
"""
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"""
Remove input subsegment from child subsegemnts and
decrement parent segment total subsegments count.
:param Subsegment: subsegment to remove.
"""
super(Subsegment, self).remove_subsegment(subsegment)
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aws/aws-xray-sdk-python | aws_xray_sdk/core/models/subsegment.py | Subsegment.close | def close(self, end_time=None):
"""
Close the trace entity by setting `end_time`
and flip the in progress flag to False. Also decrement
parent segment's ref counter by 1.
:param int end_time: Epoch in seconds. If not specified
current time will be used.
"""
... | python | def close(self, end_time=None):
"""
Close the trace entity by setting `end_time`
and flip the in progress flag to False. Also decrement
parent segment's ref counter by 1.
:param int end_time: Epoch in seconds. If not specified
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aws/aws-xray-sdk-python | aws_xray_sdk/core/sampling/connector.py | ServiceConnector.fetch_sampling_rules | def fetch_sampling_rules(self):
"""
Use X-Ray botocore client to get the centralized sampling rules
from X-Ray service. The call is proxied and signed by X-Ray Daemon.
"""
new_rules = []
resp = self._xray_client.get_sampling_rules()
records = resp['SamplingRuleRe... | python | def fetch_sampling_rules(self):
"""
Use X-Ray botocore client to get the centralized sampling rules
from X-Ray service. The call is proxied and signed by X-Ray Daemon.
"""
new_rules = []
resp = self._xray_client.get_sampling_rules()
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aws/aws-xray-sdk-python | aws_xray_sdk/core/sampling/connector.py | ServiceConnector.setup_xray_client | def setup_xray_client(self, ip, port, client):
"""
Setup the xray client based on ip and port.
If a preset client is specified, ip and port
will be ignored.
"""
if not client:
client = self._create_xray_client(ip, port)
self._xray_client = client | python | def setup_xray_client(self, ip, port, client):
"""
Setup the xray client based on ip and port.
If a preset client is specified, ip and port
will be ignored.
"""
if not client:
client = self._create_xray_client(ip, port)
self._xray_client = client | [
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aws/aws-xray-sdk-python | aws_xray_sdk/core/sampling/connector.py | ServiceConnector._dt_to_epoch | def _dt_to_epoch(self, dt):
"""
Convert a offset-aware datetime to POSIX time.
"""
if PY2:
# The input datetime is from botocore unmarshalling and it is
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# to 01/01/1970 using the same tzinfo give... | python | def _dt_to_epoch(self, dt):
"""
Convert a offset-aware datetime to POSIX time.
"""
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aws/aws-xray-sdk-python | aws_xray_sdk/core/utils/stacktrace.py | get_stacktrace | def get_stacktrace(limit=None):
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Get a full stacktrace for the current state of execution.
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If there is an active exception, include the stacktrace information from
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"""
Get a full stacktrace for the current state of execution.
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aws/aws-xray-sdk-python | aws_xray_sdk/core/sampling/local/sampler.py | LocalSampler.should_trace | def should_trace(self, sampling_req=None):
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"""
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aws/aws-xray-sdk-python | aws_xray_sdk/ext/django/middleware.py | XRayMiddleware.process_exception | def process_exception(self, request, exception):
"""
Add exception information and fault flag to the
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"""
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segment = xray_recorder.current_segment()
se... | python | def process_exception(self, request, exception):
"""
Add exception information and fault flag to the
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segment = xray_recorder.current_segment()
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aws/aws-xray-sdk-python | aws_xray_sdk/core/sampling/local/reservoir.py | Reservoir.take | def take(self):
"""
Returns True if there are segments left within the
current second, otherwise return False.
"""
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"""
Returns True if there are segments left within the
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"""
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now = int(time.time())
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self.used_this_sec = 0
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/__init__.py | get_default_connection | def get_default_connection():
"""Returns the default datastore connection.
Defaults endpoint to helper.get_project_endpoint_from_env() and
credentials to helper.get_credentials_from_env().
Use set_options to override defaults.
"""
tid = id(threading.current_thread())
conn = _conn_holder.get(tid)
if no... | python | def get_default_connection():
"""Returns the default datastore connection.
Defaults endpoint to helper.get_project_endpoint_from_env() and
credentials to helper.get_credentials_from_env().
Use set_options to override defaults.
"""
tid = id(threading.current_thread())
conn = _conn_holder.get(tid)
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GoogleCloudPlatform/google-cloud-datastore | python/demos/todos/todos.py | Todo.get_all | def get_all(cls):
"""Query for all Todo items ordered by creation date.
This method is eventually consistent to avoid the need for an extra index.
"""
req = datastore.RunQueryRequest()
q = req.query
set_kind(q, kind='Todo')
add_property_orders(q, 'created')
resp = datastore.run_query(r... | python | def get_all(cls):
"""Query for all Todo items ordered by creation date.
This method is eventually consistent to avoid the need for an extra index.
"""
req = datastore.RunQueryRequest()
q = req.query
set_kind(q, kind='Todo')
add_property_orders(q, 'created')
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GoogleCloudPlatform/google-cloud-datastore | python/demos/todos/todos.py | Todo.archive | def archive(cls):
"""Delete all Todo items that are done."""
req = datastore.BeginTransactionRequest()
resp = datastore.begin_transaction(req)
tx = resp.transaction
req = datastore.RunQueryRequest()
req.read_options.transaction = tx
q = req.query
set_kind(q, kind='Todo')
add_projecti... | python | def archive(cls):
"""Delete all Todo items that are done."""
req = datastore.BeginTransactionRequest()
resp = datastore.begin_transaction(req)
tx = resp.transaction
req = datastore.RunQueryRequest()
req.read_options.transaction = tx
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GoogleCloudPlatform/google-cloud-datastore | python/demos/todos/todos.py | Todo.save | def save(self):
"""Update or insert a Todo item."""
req = datastore.CommitRequest()
req.mode = datastore.CommitRequest.NON_TRANSACTIONAL
req.mutations.add().upsert.CopyFrom(self.to_proto())
resp = datastore.commit(req)
if not self.id:
self.id = resp.mutation_results[0].key.path[-1].id
... | python | def save(self):
"""Update or insert a Todo item."""
req = datastore.CommitRequest()
req.mode = datastore.CommitRequest.NON_TRANSACTIONAL
req.mutations.add().upsert.CopyFrom(self.to_proto())
resp = datastore.commit(req)
if not self.id:
self.id = resp.mutation_results[0].key.path[-1].id
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/datastore_emulator.py | DatastoreEmulatorFactory.Get | def Get(self, project_id):
"""Returns an existing emulator instance for the provided project_id.
If an emulator instance doesn't yet exist, it creates one.
Args:
project_id: project ID
Returns:
a DatastoreEmulator
"""
if project_id in self._emulators:
return self._emulators[... | python | def Get(self, project_id):
"""Returns an existing emulator instance for the provided project_id.
If an emulator instance doesn't yet exist, it creates one.
Args:
project_id: project ID
Returns:
a DatastoreEmulator
"""
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/datastore_emulator.py | DatastoreEmulatorFactory.Create | def Create(self, project_id, start_options=None, deadline=10):
"""Creates an emulator instance.
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start.
Args:
project_id: project ID
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"""Creates an emulator instance.
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project_id: project ID
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/datastore_emulator.py | DatastoreEmulator._WaitForStartup | def _WaitForStartup(self, deadline):
"""Waits for the emulator to start.
Args:
deadline: deadline in seconds
Returns:
True if the emulator responds within the deadline, False otherwise.
"""
start = time.time()
sleep = 0.05
def Elapsed():
return time.time() - start
w... | python | def _WaitForStartup(self, deadline):
"""Waits for the emulator to start.
Args:
deadline: deadline in seconds
Returns:
True if the emulator responds within the deadline, False otherwise.
"""
start = time.time()
sleep = 0.05
def Elapsed():
return time.time() - start
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/datastore_emulator.py | DatastoreEmulator.Clear | def Clear(self):
"""Clears all data from the emulator instance.
Returns:
True if the data was successfully cleared, False otherwise.
"""
headers = {'Content-length': '0'}
response, _ = self._http.request('%s/reset' % self._host, method='POST',
headers=head... | python | def Clear(self):
"""Clears all data from the emulator instance.
Returns:
True if the data was successfully cleared, False otherwise.
"""
headers = {'Content-length': '0'}
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/datastore_emulator.py | DatastoreEmulator.Stop | def Stop(self):
"""Stops the emulator instance."""
if not self.__running:
return
logging.info('shutting down the emulator running at %s', self._host)
headers = {'Content-length': '0'}
response, _ = self._http.request('%s/shutdown' % self._host,
method='POST... | python | def Stop(self):
"""Stops the emulator instance."""
if not self.__running:
return
logging.info('shutting down the emulator running at %s', self._host)
headers = {'Content-length': '0'}
response, _ = self._http.request('%s/shutdown' % self._host,
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/connection.py | Datastore._call_method | def _call_method(self, method, req, resp_class):
"""_call_method call the given RPC method over HTTP.
It uses the given protobuf message request as the payload and
returns the deserialized protobuf message response.
Args:
method: RPC method name to be called.
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"""_call_method call the given RPC method over HTTP.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | get_credentials_from_env | def get_credentials_from_env():
"""Get credentials from environment variables.
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- Google APIs Signed JWT credentials based on
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"""Get credentials from environment variables.
Preference of credentials is:
- No credentials if DATASTORE_EMULATOR_HOST is set.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | get_project_endpoint_from_env | def get_project_endpoint_from_env(project_id=None, host=None):
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project_id: The Cloud project, defaults to the environment
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | add_key_path | def add_key_path(key_proto, *path_elements):
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key_proto: datastore.Key proto message.
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"""Add path elements to the given datastore.Key proto message.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | add_properties | def add_properties(entity_proto, property_dict, exclude_from_indexes=None):
"""Add values to the given datastore.Entity proto message.
Args:
entity_proto: datastore.Entity proto message.
property_dict: a dictionary from property name to either a python object or
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"""Add values to the given datastore.Entity proto message.
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entity_proto: datastore.Entity proto message.
property_dict: a dictionary from property name to either a python object or
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | set_property | def set_property(property_map, name, value, exclude_from_indexes=None):
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Args:
property_map: a string->datastore.Value protobuf map.
name: name of the property.
value: python object or datastore.Value.
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"""Set property value in the given datastore.Property proto message.
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property_map: a string->datastore.Value protobuf map.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | set_value | def set_value(value_proto, value, exclude_from_indexes=None):
"""Set the corresponding datastore.Value _value field for the given arg.
Args:
value_proto: datastore.Value proto message.
value: python object or datastore.Value. (unicode value will set a
datastore string value, str value will set a bl... | python | def set_value(value_proto, value, exclude_from_indexes=None):
"""Set the corresponding datastore.Value _value field for the given arg.
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value_proto: datastore.Value proto message.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | get_value | def get_value(value_proto):
"""Gets the python object equivalent for the given value proto.
Args:
value_proto: datastore.Value proto message.
Returns:
the corresponding python object value. timestamps are converted to
datetime, and datastore.Value is returned for blob_key_value.
"""
field = valu... | python | def get_value(value_proto):
"""Gets the python object equivalent for the given value proto.
Args:
value_proto: datastore.Value proto message.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | get_property_dict | def get_property_dict(entity_proto):
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Args:
entity_proto: datastore.Entity proto message.
Usage:
>>> get_property_dict(entity_proto)
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Returns:
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"""Convert datastore.Entity to a dict of property name -> datastore.Value.
Args:
entity_proto: datastore.Entity proto message.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | set_kind | def set_kind(query_proto, kind):
"""Set the kind constraint for the given datastore.Query proto message."""
del query_proto.kind[:]
query_proto.kind.add().name = kind | python | def set_kind(query_proto, kind):
"""Set the kind constraint for the given datastore.Query proto message."""
del query_proto.kind[:]
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | add_property_orders | def add_property_orders(query_proto, *orders):
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Args:
query_proto: datastore.Query proto message.
orders: list of propertype name string, default to ascending
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>>> add_proper... | python | def add_property_orders(query_proto, *orders):
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query_proto: datastore.Query proto message.
orders: list of propertype name string, default to ascending
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | add_projection | def add_projection(query_proto, *projection):
"""Add projection properties to the given datatstore.Query proto message."""
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proto.property.name = p | python | def add_projection(query_proto, *projection):
"""Add projection properties to the given datatstore.Query proto message."""
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | set_property_filter | def set_property_filter(filter_proto, name, op, value):
"""Set property filter contraint in the given datastore.Filter proto message.
Args:
filter_proto: datastore.Filter proto message
name: property name
op: datastore.PropertyFilter.Operation
value: property value
Returns:
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"""Set property filter contraint in the given datastore.Filter proto message.
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filter_proto: datastore.Filter proto message
name: property name
op: datastore.PropertyFilter.Operation
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | set_composite_filter | def set_composite_filter(filter_proto, op, *filters):
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filter_proto: datastore.Filter proto message
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | micros_to_timestamp | def micros_to_timestamp(micros, timestamp):
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timestamp: a google.protobuf.timestamp.Timestamp to populate.
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micro_remainder ... | python | def micros_to_timestamp(micros, timestamp):
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timestamp: a google.protobuf.timestamp.Timestamp to populate.
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HDI-Project/MLBlocks | mlblocks/mlblock.py | MLBlock._extract_params | def _extract_params(self, kwargs, hyperparameters):
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HDI-Project/MLBlocks | mlblocks/mlpipeline.py | MLPipeline.get_hyperparameters | def get_hyperparameters(self):
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"""
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HDI-Project/MLBlocks | mlblocks/mlpipeline.py | MLPipeline.fit | def fit(self, X=None, y=None, **kwargs):
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HDI-Project/MLBlocks | mlblocks/mlpipeline.py | MLPipeline.predict | def predict(self, X=None, **kwargs):
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HDI-Project/MLBlocks | mlblocks/mlpipeline.py | MLPipeline.to_dict | def to_dict(self):
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HDI-Project/MLBlocks | mlblocks/mlpipeline.py | MLPipeline.save | def save(self, path):
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Args:
path (str): Path to the JSON file to write.
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HDI-Project/MLBlocks | mlblocks/mlpipeline.py | MLPipeline.from_dict | def from_dict(cls, metadata):
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metadata (dict): Dictionary containing the pipeline specification.
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HDI-Project/MLBlocks | mlblocks/mlpipeline.py | MLPipeline.load | def load(cls, path):
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HDI-Project/MLBlocks | mlblocks/primitives.py | add_primitives_path | def add_primitives_path(path):
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pat... | python | def add_primitives_path(path):
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HDI-Project/MLBlocks | mlblocks/primitives.py | get_primitives_paths | def get_primitives_paths():
"""Get the list of folders where the primitives will be looked for.
This list will include the value of any `entry_point` named `jsons_path` published under
the name `mlprimitives`.
An example of such an entry point would be::
entry_points = {
'mlprimit... | python | def get_primitives_paths():
"""Get the list of folders where the primitives will be looked for.
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HDI-Project/MLBlocks | mlblocks/primitives.py | load_primitive | def load_primitive(name):
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All the paths found in PRIMTIVE_PATHS will be scanned to find a JSON file
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_usps | def load_usps():
"""USPs Digits Dataset.
The data of this dataset is a 3d numpy array vector with shape (224, 224, 3)
containing 9298 224x224 RGB photos of handwritten digits, and the target is
a 1d numpy integer array containing the label of the digit represented in
the image.
"""
dataset_... | python | def load_usps():
"""USPs Digits Dataset.
The data of this dataset is a 3d numpy array vector with shape (224, 224, 3)
containing 9298 224x224 RGB photos of handwritten digits, and the target is
a 1d numpy integer array containing the label of the digit represented in
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_handgeometry | def load_handgeometry():
"""Hand Geometry Dataset.
The data of this dataset is a 3d numpy array vector with shape (224, 224, 3)
containing 112 224x224 RGB photos of hands, and the target is a 1d numpy
float array containing the width of the wrist in centimeters.
"""
dataset_path = _load('handge... | python | def load_handgeometry():
"""Hand Geometry Dataset.
The data of this dataset is a 3d numpy array vector with shape (224, 224, 3)
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_personae | def load_personae():
"""Personae Dataset.
The data of this dataset is a 2d numpy array vector containing 145 entries
that include texts written by Dutch users in Twitter, with some additional
information about the author, and the target is a 1d numpy binary integer
array indicating whether the auth... | python | def load_personae():
"""Personae Dataset.
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_umls | def load_umls():
"""UMLs Dataset.
The data consists of information about a 135 Graph and the relations between
their nodes given as a DataFrame with three columns, source, target and type,
indicating which nodes are related and with which type of link. The target is
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"""UMLs Dataset.
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_dic28 | def load_dic28():
"""DIC28 Dataset from Pajek.
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- changing a single character (e. g., work - word)
- adding ... | python | def load_dic28():
"""DIC28 Dataset from Pajek.
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_amazon | def load_amazon():
"""Amazon product co-purchasing network and ground-truth communities.
Network was collected by crawling Amazon website. It is based on Customers Who Bought
This Item Also Bought feature of the Amazon website. If a product i is frequently
co-purchased with product j, the graph contain... | python | def load_amazon():
"""Amazon product co-purchasing network and ground-truth communities.
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_jester | def load_jester():
"""Ratings from the Jester Online Joke Recommender System.
This dataset consists of over 1.7 million instances of (user_id, item_id, rating)
triples, which is split 50-50 into train and test data.
source: "University of California Berkeley, CA"
sourceURI: "http://eigentaste.berk... | python | def load_jester():
"""Ratings from the Jester Online Joke Recommender System.
This dataset consists of over 1.7 million instances of (user_id, item_id, rating)
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_wikiqa | def load_wikiqa():
"""A Challenge Dataset for Open-Domain Question Answering.
WikiQA dataset is a publicly available set of question and sentence (QS) pairs,
collected and annotated for research on open-domain question answering.
source: "Microsoft"
sourceURI: "https://www.microsoft.com/en-us/rese... | python | def load_wikiqa():
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_newsgroups | def load_newsgroups():
"""20 News Groups Dataset.
The data of this dataset is a 1d numpy array vector containing the texts
from 11314 newsgroups posts, and the target is a 1d numpy integer array
containing the label of one of the 20 topics that they are about.
"""
dataset = datasets.fetch_20new... | python | def load_newsgroups():
"""20 News Groups Dataset.
The data of this dataset is a 1d numpy array vector containing the texts
from 11314 newsgroups posts, and the target is a 1d numpy integer array
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_iris | def load_iris():
"""Iris Dataset."""
dataset = datasets.load_iris()
return Dataset(load_iris.__doc__, dataset.data, dataset.target,
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"""Iris Dataset."""
dataset = datasets.load_iris()
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HDI-Project/MLBlocks | mlblocks/datasets.py | load_boston | def load_boston():
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dataset = datasets.load_boston()
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dataset = datasets.load_boston()
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HDI-Project/MLBlocks | mlblocks/datasets.py | Dataset.get_splits | def get_splits(self, n_splits=1):
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scoutapp/scout_apm_python | src/scout_apm/api/context.py | Context.add | def add(key, value):
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:value: Any json-serializable type.
Example: "1.1.1.1", "free", 100
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"""Adds context to the currently executing request.
:key: Any String identifying the request context.
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:value: Any json-serializable type.
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Example: "1.1.1.1", "free", 100
:returns: nothing. | [
"Adds",
"context",
"to",
"the",
"currently",
"executing",
"request",
"."
] | e5539ee23b8129be9b75d5007c88b6158b51294f | https://github.com/scoutapp/scout_apm_python/blob/e5539ee23b8129be9b75d5007c88b6158b51294f/src/scout_apm/api/context.py#L8-L18 | train |
scoutapp/scout_apm_python | src/scout_apm/core/platform_detection.py | PlatformDetection.libc | def libc(cls):
"""
Alpine linux uses a non glibc version of the standard library, it uses
the stripped down musl instead. The core agent can be built against it,
but which one is running must be detected. Shelling out to `ldd`
appears to be the most reliable way to do this.
... | python | def libc(cls):
"""
Alpine linux uses a non glibc version of the standard library, it uses
the stripped down musl instead. The core agent can be built against it,
but which one is running must be detected. Shelling out to `ldd`
appears to be the most reliable way to do this.
... | [
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"... | Alpine linux uses a non glibc version of the standard library, it uses
the stripped down musl instead. The core agent can be built against it,
but which one is running must be detected. Shelling out to `ldd`
appears to be the most reliable way to do this. | [
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"r... | e5539ee23b8129be9b75d5007c88b6158b51294f | https://github.com/scoutapp/scout_apm_python/blob/e5539ee23b8129be9b75d5007c88b6158b51294f/src/scout_apm/core/platform_detection.py#L45-L62 | train |
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