def test_asbool(self):
# ensure the value is properly cast
eq_(asbool("True"), True)
eq_(asbool("true"), True)
eq_(asbool("1"), True)
eq_(asbool("False"), False)
eq_(asbool("false"), False)
eq_(asbool(None), False)
eq_(asbool(""), False)
eq_(asbool(True), True)
eq_(asbool(False), False)
def update_patched_modules():
modules_to_patch = os.environ.get("DATADOG_PATCH_MODULES")
if not modules_to_patch:
return
modules = parse_tags_str(modules_to_patch)
for module, should_patch in modules.items():
EXTRA_PATCHED_MODULES[module] = asbool(should_patch)
def __attrs_post_init__(self):
r = self._recorder = recorder.Recorder(
max_events={
# Allow to store up to 10 threads for 60 seconds at 100 Hz
stack.StackSampleEvent:
10 * 60 * 100,
stack.StackExceptionSampleEvent:
10 * 60 * 100,
# This can generate one event every 0.1s if 100% are taken — though we take 5% by default.
# = (60 seconds / 0.1 seconds)
memory.MemorySampleEvent:
int(60 / 0.1),
# (default buffer size / interval) * export interval
memalloc.MemoryAllocSampleEvent:
int((memalloc.MemoryCollector._DEFAULT_MAX_EVENTS /
memalloc.MemoryCollector._DEFAULT_INTERVAL) * 60),
# Do not limit the heap sample size as the number of events is relative to allocated memory anyway
memalloc.MemoryHeapSampleEvent:
None,
},
default_max_events=int(
os.environ.get("DD_PROFILING_MAX_EVENTS",
recorder.Recorder._DEFAULT_MAX_EVENTS)),
)
if formats.asbool(os.environ.get("DD_PROFILING_MEMALLOC", "true")):
mem_collector = memalloc.MemoryCollector(r)
else:
mem_collector = memory.MemoryCollector(r)
self._collectors = [
stack.StackCollector(r, tracer=self.tracer),
mem_collector,
threading.LockCollector(r, tracer=self.tracer),
]
exporters = self._build_default_exporters(self.tracer, self.url,
self.tags, self.service,
self.env, self.version)
if exporters:
self._scheduler = scheduler.Scheduler(
recorder=r,
exporters=exporters,
before_flush=self._collectors_snapshot)
def __attrs_post_init__(self):
r = recorder.Recorder(
max_events={
# Allow to store up to 10 threads for 60 seconds at 100 Hz
stack.StackSampleEvent:
10 * 60 * 100,
stack.StackExceptionSampleEvent:
10 * 60 * 100,
# This can generate one event every 0.1s if 100% are taken — though we take 5% by default.
# = (60 seconds / 0.1 seconds)
memory.MemorySampleEvent:
int(60 / 0.1),
# (default buffer size / interval) * export interval
memalloc.MemoryAllocSampleEvent:
int((64 / 0.5) * 60),
},
default_max_events=int(
os.environ.get("DD_PROFILING_MAX_EVENTS",
recorder.Recorder._DEFAULT_MAX_EVENTS)),
)
if formats.asbool(os.environ.get("DD_PROFILING_MEMALLOC", "false")):
mem_collector = memalloc.MemoryCollector(r)
else:
mem_collector = memory.MemoryCollector(r)
self._collectors = [
stack.StackCollector(r, tracer=self.tracer),
mem_collector,
exceptions.UncaughtExceptionCollector(r),
threading.LockCollector(r),
]
exporters = self._build_default_exporters(self.service, self.env,
self.version)
if exporters:
self._scheduler = scheduler.Scheduler(recorder=r,
exporters=exporters)
enabled = os.environ.get("DATADOG_TRACE_ENABLED")
hostname = os.environ.get("DATADOG_TRACE_AGENT_HOSTNAME")
port = os.environ.get("DATADOG_TRACE_AGENT_PORT")
priority_sampling = os.environ.get("DATADOG_PRIORITY_SAMPLING")
opts = {}
if enabled and enabled.lower() == "false":
opts["enabled"] = False
patch = False
if hostname:
opts["hostname"] = hostname
if port:
opts["port"] = int(port)
if priority_sampling:
opts["priority_sampling"] = asbool(priority_sampling)
if opts:
tracer.configure(**opts)
if not hasattr(sys, 'argv'):
sys.argv = ['']
if patch:
update_patched_modules()
from ddtrace import patch_all; patch_all(**EXTRA_PATCHED_MODULES) # noqa
debug = os.environ.get("DATADOG_TRACE_DEBUG")
if debug and debug.lower() == "true":
tracer.debug_logging = True
class _ProfilerInstance(service.Service):
"""A instance of the profiler.
Each process must manage its own instance.
"""
# User-supplied values
url = attr.ib(default=None)
service = attr.ib(factory=_get_service_name)
tags = attr.ib(factory=dict)
env = attr.ib(factory=lambda: os.environ.get("DD_ENV"))
version = attr.ib(factory=lambda: os.environ.get("DD_VERSION"))
tracer = attr.ib(default=ddtrace.tracer)
api_key = attr.ib(factory=lambda: os.environ.get("DD_API_KEY"),
type=Optional[str])
agentless = attr.ib(factory=lambda: formats.asbool(
os.environ.get("DD_PROFILING_AGENTLESS", "False")),
type=bool)
_recorder = attr.ib(init=False, default=None)
_collectors = attr.ib(init=False, default=None)
_scheduler = attr.ib(init=False, default=None)
ENDPOINT_TEMPLATE = "https://intake.profile.{}"
def _build_default_exporters(self):
# type: (...) -> List[exporter.Exporter]
_OUTPUT_PPROF = os.environ.get("DD_PROFILING_OUTPUT_PPROF")
if _OUTPUT_PPROF:
return [
file.PprofFileExporter(_OUTPUT_PPROF),
]
if self.url is not None:
endpoint = self.url
elif self.agentless:
LOG.warning(
"Agentless uploading is currently for internal usage only and not officially supported. "
"You should not enable it unless somebody at Datadog instructed you to do so."
)
endpoint = self.ENDPOINT_TEMPLATE.format(
os.environ.get("DD_SITE", "datadoghq.com"))
else:
if isinstance(self.tracer.writer, writer.AgentWriter):
endpoint = self.tracer.writer.agent_url
else:
endpoint = agent.get_trace_url()
if self.agentless:
endpoint_path = "/v1/input"
else:
# Agent mode
# path is relative because it is appended
# to the agent base path.
endpoint_path = "profiling/v1/input"
return [
http.PprofHTTPExporter(
service=self.service,
env=self.env,
tags=self.tags,
version=self.version,
api_key=self.api_key,
endpoint=endpoint,
endpoint_path=endpoint_path,
),
]
def __attrs_post_init__(self):
r = self._recorder = recorder.Recorder(
max_events={
# Allow to store up to 10 threads for 60 seconds at 100 Hz
stack.StackSampleEvent:
10 * 60 * 100,
stack.StackExceptionSampleEvent:
10 * 60 * 100,
# (default buffer size / interval) * export interval
memalloc.MemoryAllocSampleEvent:
int((memalloc.MemoryCollector._DEFAULT_MAX_EVENTS /
memalloc.MemoryCollector._DEFAULT_INTERVAL) * 60),
# Do not limit the heap sample size as the number of events is relative to allocated memory anyway
memalloc.MemoryHeapSampleEvent:
None,
},
default_max_events=int(
os.environ.get("DD_PROFILING_MAX_EVENTS",
recorder.Recorder._DEFAULT_MAX_EVENTS)),
)
self._collectors = [
stack.StackCollector(r, tracer=self.tracer),
memalloc.MemoryCollector(r),
threading.LockCollector(r, tracer=self.tracer),
]
exporters = self._build_default_exporters()
if exporters:
self._scheduler = scheduler.Scheduler(
recorder=r,
exporters=exporters,
before_flush=self._collectors_snapshot)
def _collectors_snapshot(self):
for c in self._collectors:
try:
snapshot = c.snapshot()
if snapshot:
for events in snapshot:
self._recorder.push_events(events)
except Exception:
LOG.error("Error while snapshoting collector %r",
c,
exc_info=True)
def copy(self):
return self.__class__(service=self.service,
env=self.env,
version=self.version,
tracer=self.tracer,
tags=self.tags)
def _start_service(self): # type: ignore[override]
# type: (...) -> None
"""Start the profiler."""
collectors = []
for col in self._collectors:
try:
col.start()
except collector.CollectorUnavailable:
LOG.debug("Collector %r is unavailable, disabling", col)
except Exception:
LOG.error("Failed to start collector %r, disabling.",
col,
exc_info=True)
else:
collectors.append(col)
self._collectors = collectors
if self._scheduler is not None:
self._scheduler.start()
def _stop_service( # type: ignore[override]
self,
flush=True # type: bool
):
# type: (...) -> None
"""Stop the profiler.
:param flush: Flush a last profile.
"""
if self._scheduler is not None:
self._scheduler.stop()
# Wait for the export to be over: export might need collectors (e.g., for snapshot) so we can't stop
# collectors before the possibly running flush is finished.
self._scheduler.join()
if flush:
# Do not stop the collectors before flushing, they might be needed (snapshot)
self._scheduler.flush()
for col in reversed(self._collectors):
try:
col.stop()
except service.ServiceStatusError:
# It's possible some collector failed to start, ignore failure to stop
pass
for col in reversed(self._collectors):
col.join()
import mariadb
from ddtrace import Pin
from ddtrace import config
from ddtrace.contrib.dbapi import TracedConnection
from ddtrace.ext import db
from ddtrace.ext import net
from ddtrace.utils.formats import asbool
from ddtrace.utils.formats import get_env
from ddtrace.utils.wrappers import unwrap
from ddtrace.vendor import wrapt
config._add(
"mariadb",
dict(
trace_fetch_methods=asbool(
get_env("mariadb", "trace_fetch_methods", default=False)),
_default_service="mariadb",
),
)
def patch():
if getattr(mariadb, "_datadog_patch", False):
return
setattr(mariadb, "_datadog_patch", True)
wrapt.wrap_function_wrapper("mariadb", "connect", _connect)
def unpatch():
if getattr(mariadb, "_datadog_patch", False):
setattr(mariadb, "_datadog_patch", False)
"""
Bootstrapping code that is run when using the `ddtrace-run` Python entrypoint
Add all monkey-patching that needs to run by default here
"""
import os
import imp
import sys
import logging
from ddtrace.utils.formats import asbool, get_env
from ddtrace.internal.logger import get_logger
from ddtrace import constants
logs_injection = asbool(get_env('logs', 'injection'))
DD_LOG_FORMAT = '%(asctime)s %(levelname)s [%(name)s] [%(filename)s:%(lineno)d] {}- %(message)s'.format(
'[dd.trace_id=%(dd.trace_id)s dd.span_id=%(dd.span_id)s] ' if logs_injection else ''
)
if logs_injection:
# immediately patch logging if trace id injected
from ddtrace import patch
patch(logging=True)
debug = os.environ.get('DATADOG_TRACE_DEBUG')
# Set here a default logging format for basicConfig
# DEV: Once basicConfig is called here, future calls to it cannot be used to
# change the formatter since it applies the formatter to the root handler only
# upon initializing it the first time.
"""
import logging
import wrapt
from ddtrace import Pin
from ddtrace.ext import AppTypes, sql
from ddtrace.settings import config
from ddtrace.utils.formats import asbool, get_env
log = logging.getLogger(__name__)
config._add(
'dbapi2',
dict(trace_fetch_methods=asbool(
get_env('dbapi2', 'trace_fetch_methods', 'false')), ))
class TracedCursor(wrapt.ObjectProxy):
""" TracedCursor wraps a psql cursor and traces it's queries. """
def __init__(self, cursor, pin):
super(TracedCursor, self).__init__(cursor)
pin.onto(self)
name = pin.app or 'sql'
self._self_datadog_name = '{}.query'.format(name)
self._self_last_execute_operation = None
def _trace_method(self, method, name, resource, extra_tags, *args,
**kwargs):
"""
Internal function to trace the call to the underlying cursor method
log = get_logger(__name__)
config._add(
"django",
dict(
_default_service="django",
cache_service_name=get_env("django", "cache_service_name") or "django",
database_service_name_prefix=get_env("django",
"database_service_name_prefix",
default=""),
database_service_name=get_env("django",
"database_service_name",
default=""),
distributed_tracing_enabled=True,
instrument_middleware=asbool(
get_env("django", "instrument_middleware", default=True)),
instrument_databases=True,
instrument_caches=True,
analytics_enabled=
None, # None allows the value to be overridden by the global config
analytics_sample_rate=None,
trace_query_string=None, # Default to global config
include_user_name=True,
use_handler_resource_format=asbool(
get_env("django", "use_handler_resource_format", default=False)),
use_legacy_resource_format=asbool(
get_env("django", "use_legacy_resource_format", default=False)),
),
)
propagator = HTTPPropagator()
from ddtrace.utils.formats import asbool # noqa
from ddtrace.utils.formats import get_env
from ddtrace.utils.formats import parse_tags_str
if config.logs_injection:
# immediately patch logging if trace id injected
from ddtrace import patch
patch(logging=True)
# DEV: Once basicConfig is called here, future calls to it cannot be used to
# change the formatter since it applies the formatter to the root handler only
# upon initializing it the first time.
# See https://github.com/python/cpython/blob/112e4afd582515fcdcc0cde5012a4866e5cfda12/Lib/logging/__init__.py#L1550
# Debug mode from the tracer will do a basicConfig so only need to do this otherwise
call_basic_config = asbool(os.environ.get("DD_CALL_BASIC_CONFIG", "true"))
if not debug_mode and call_basic_config:
if config.logs_injection:
logging.basicConfig(format=DD_LOG_FORMAT)
else:
logging.basicConfig()
log = get_logger(__name__)
EXTRA_PATCHED_MODULES = {
"bottle": True,
"django": True,
"falcon": True,
"flask": True,
"pylons": True,
"pyramid": True,
hostname = os.environ.get("DD_AGENT_HOST",
os.environ.get("DATADOG_TRACE_AGENT_HOSTNAME"))
port = os.environ.get("DATADOG_TRACE_AGENT_PORT")
priority_sampling = os.environ.get("DATADOG_PRIORITY_SAMPLING")
opts = {}
if enabled and enabled.lower() == "false":
opts["enabled"] = False
patch = False
if hostname:
opts["hostname"] = hostname
if port:
opts["port"] = int(port)
if priority_sampling:
opts["priority_sampling"] = asbool(priority_sampling)
opts["collect_metrics"] = asbool(get_env("runtime_metrics", "enabled"))
if opts:
tracer.configure(**opts)
if patch:
update_patched_modules()
from ddtrace import patch_all
patch_all(**EXTRA_PATCHED_MODULES)
if "DATADOG_ENV" in os.environ:
tracer.set_tags({constants.ENV_KEY: os.environ["DATADOG_ENV"]})
"""
Bootstrapping code that is run when using the `ddtrace-run` Python entrypoint
Add all monkey-patching that needs to run by default here
"""
import os
import imp
import sys
import logging
from ddtrace.utils.formats import asbool, get_env
logs_injection = asbool(get_env('logs', 'injection'))
DD_LOG_FORMAT = '%(asctime)s %(levelname)s [%(name)s] [%(filename)s:%(lineno)d] {}- %(message)s'.format(
'[dd.trace_id=%(dd.trace_id)s dd.span_id=%(dd.span_id)s] '
if logs_injection else '')
debug = os.environ.get("DATADOG_TRACE_DEBUG")
# Set here a default logging format for basicConfig
# DEV: Once basicConfig is called here, future calls to it cannot be used to
# change the formatter since it applies the formatter to the root handler only
# upon initializing it the first time.
# See https://github.com/python/cpython/blob/112e4afd582515fcdcc0cde5012a4866e5cfda12/Lib/logging/__init__.py#L1550
if debug and debug.lower() == "true":
logging.basicConfig(level=logging.DEBUG, format=DD_LOG_FORMAT)
else:
logging.basicConfig(format=DD_LOG_FORMAT)
log = logging.getLogger(__name__)
enabled = os.environ.get("DATADOG_TRACE_ENABLED")
hostname = os.environ.get("DD_AGENT_HOST", os.environ.get("DATADOG_TRACE_AGENT_HOSTNAME"))
port = os.environ.get("DATADOG_TRACE_AGENT_PORT")
priority_sampling = os.environ.get("DATADOG_PRIORITY_SAMPLING")
opts = {}
if enabled and enabled.lower() == "false":
opts["enabled"] = False
patch = False
if hostname:
opts["hostname"] = hostname
if port:
opts["port"] = int(port)
if priority_sampling:
opts["priority_sampling"] = asbool(priority_sampling)
opts["collect_metrics"] = asbool(os.environ.get(METRICS_ENABLED_ENV_VAR, True))
key_intersection = set(_LIGHTSTEP_ENV_VARS.keys()) & set(os.environ.keys())
if key_intersection:
tracer.set_tags({_LIGHTSTEP_ENV_VARS[key]: os.environ[key] for key in key_intersection})
if "DD_TRACE_GLOBAL_TAGS" in os.environ:
add_global_tags(tracer)
if opts:
tracer.configure(**opts)
if patch:
update_patched_modules()
from ddtrace.propagation.http import HTTPPropagator
from ddtrace.utils import get_argument_value
from ddtrace.utils.formats import asbool
from ddtrace.utils.formats import get_env
from ddtrace.utils.wrappers import unwrap as _u
from ddtrace.vendor.wrapt import wrap_function_wrapper as _w
if typing.TYPE_CHECKING:
from ddtrace import Span
from ddtrace.vendor.wrapt import BoundFunctionWrapper
config._add(
"httpx",
{
"distributed_tracing": asbool(get_env("httpx", "distributed_tracing", default=True)),
"split_by_domain": asbool(get_env("httpx", "split_by_domain", default=False)),
},
)
def _url_to_str(url):
# type: (httpx.URL) -> str
"""
Helper to convert the httpx.URL parts from bytes to a str
"""
scheme, host, port, raw_path = url.raw
url = scheme + b"://" + host
if port is not None:
url += b":" + ensure_binary(str(port))
url += raw_path
from .. import trace_utils
from .compat import get_resolver, user_is_authenticated
from . import utils, conf
log = get_logger(__name__)
config._add(
"django",
dict(
_default_service="django",
cache_service_name=get_env("django", "cache_service_name") or "django",
database_service_name_prefix=get_env("django", "database_service_name_prefix", default=""),
database_service_name=get_env("django", "database_service_name", default=""),
distributed_tracing_enabled=True,
instrument_middleware=asbool(get_env("django", "instrument_middleware", default=True)),
instrument_databases=True,
instrument_caches=True,
analytics_enabled=None, # None allows the value to be overridden by the global config
analytics_sample_rate=None,
trace_query_string=None, # Default to global config
include_user_name=True,
use_handler_resource_format=get_env("django", "use_handler_resource_format", default=False),
),
)
propagator = HTTPPropagator()
def patch_conn(django, conn):
def cursor(django, pin, func, instance, args, kwargs):
def main():
parser = argparse.ArgumentParser(
description=USAGE,
prog="ddtrace-run",
usage="ddtrace-run <your usual python command>",
formatter_class=argparse.RawTextHelpFormatter,
)
parser.add_argument("command",
nargs=argparse.REMAINDER,
type=str,
help="Command string to execute.")
parser.add_argument("-d",
"--debug",
help="enable debug mode (disabled by default)",
action="store_true")
parser.add_argument("-i",
"--info",
help="print library info useful for debugging",
action="store_true")
parser.add_argument("-p",
"--profiling",
help="enable profiling (disabled by default)",
action="store_true")
parser.add_argument("-v",
"--version",
action="version",
version="%(prog)s " + ddtrace.__version__)
args = parser.parse_args()
if args.profiling:
os.environ["DD_PROFILING_ENABLED"] = "true"
debug_mode = args.debug or asbool(get_env("trace", "debug", default=False))
if debug_mode:
logging.basicConfig(level=logging.DEBUG)
os.environ["DD_TRACE_DEBUG"] = "true"
if args.info:
# Inline imports for performance.
import pprint
from ddtrace.internal.debug import collect
pprint.pprint(collect(ddtrace.tracer))
sys.exit(0)
root_dir = os.path.dirname(ddtrace.__file__)
log.debug("ddtrace root: %s", root_dir)
bootstrap_dir = os.path.join(root_dir, "bootstrap")
log.debug("ddtrace bootstrap: %s", bootstrap_dir)
_add_bootstrap_to_pythonpath(bootstrap_dir)
log.debug("PYTHONPATH: %s", os.environ["PYTHONPATH"])
log.debug("sys.path: %s", sys.path)
if not args.command:
parser.print_help()
sys.exit(1)
# Find the executable path
executable = spawn.find_executable(args.command[0])
if not executable:
print("ddtrace-run: failed to find executable '%s'.\n" %
args.command[0])
parser.print_usage()
sys.exit(1)
log.debug("program executable: %s", executable)
if os.path.basename(executable) == "uwsgi":
print((
"ddtrace-run has known compatibility issues with uWSGI where the "
"tracer is not started properly in uWSGI workers which can cause "
"broken behavior. It is recommended you remove ddtrace-run and "
"update your uWSGI configuration following "
"https://ddtrace.readthedocs.io/en/stable/advanced_usage.html#uwsgi."
))
try:
# Raises OSError for permissions errors in Python 2
# PermissionError for Python 3
os.execl(executable, executable, *args.command[1:])
except (OSError, PermissionError):
print(
"ddtrace-run: executable '%s' does not have executable permissions.\n"
% executable)
parser.print_usage()
sys.exit(1)
sys.exit(0)
enabled = os.environ.get("DATADOG_TRACE_ENABLED")
hostname = os.environ.get("DATADOG_TRACE_AGENT_HOSTNAME")
port = os.environ.get("DATADOG_TRACE_AGENT_PORT")
priority_sampling = os.environ.get("DATADOG_PRIORITY_SAMPLING")
opts = {}
if enabled and enabled.lower() == "false":
opts["enabled"] = False
patch = False
if hostname:
opts["hostname"] = hostname
if port:
opts["port"] = int(port)
if priority_sampling:
opts["priority_sampling"] = asbool(priority_sampling)
if opts:
tracer.configure(**opts)
if patch:
update_patched_modules()
from ddtrace import patch_all
patch_all(**EXTRA_PATCHED_MODULES) # noqa
debug = os.environ.get("DATADOG_TRACE_DEBUG")
if debug and debug.lower() == "true":
tracer.debug_logging = True
if 'DATADOG_ENV' in os.environ:
tracer.set_tags({"env": os.environ["DATADOG_ENV"]})
EXTRA_PATCHED_MODULES[module] = asbool(should_patch)
try:
from ddtrace import tracer
patch = True
# Respect DATADOG_* environment variables in global tracer configuration
# TODO: these variables are deprecated; use utils method and update our documentation
# correct prefix should be DD_*
enabled = os.environ.get("DATADOG_TRACE_ENABLED")
hostname = os.environ.get("DD_AGENT_HOST", os.environ.get("DATADOG_TRACE_AGENT_HOSTNAME"))
port = os.environ.get("DATADOG_TRACE_AGENT_PORT")
priority_sampling = os.environ.get("DATADOG_PRIORITY_SAMPLING")
profiling = asbool(os.environ.get("DD_PROFILING_ENABLED", False))
if profiling:
import ddtrace.profiling.auto # noqa: F401
opts = {}
if enabled and enabled.lower() == "false":
opts["enabled"] = False
patch = False
if hostname:
opts["hostname"] = hostname
if port:
opts["port"] = int(port)
if priority_sampling:
opts["priority_sampling"] = asbool(priority_sampling)
"""
Bootstrapping code that is run when using the `ddtrace-run` Python entrypoint
Add all monkey-patching that needs to run by default here
"""
import os
import imp
import sys
import logging
from ddtrace.utils.formats import asbool, get_env
from ddtrace.internal.logger import get_logger
from ddtrace import constants
logs_injection = asbool(get_env("logs", "injection"))
DD_LOG_FORMAT = "%(asctime)s %(levelname)s [%(name)s] [%(filename)s:%(lineno)d] {}- %(message)s".format(
"[dd.trace_id=%(dd.trace_id)s dd.span_id=%(dd.span_id)s] "
if logs_injection else "")
if logs_injection:
# immediately patch logging if trace id injected
from ddtrace import patch
patch(logging=True)
debug = os.environ.get("DATADOG_TRACE_DEBUG")
# Set here a default logging format for basicConfig
# DEV: Once basicConfig is called here, future calls to it cannot be used to
# change the formatter since it applies the formatter to the root handler only
