Module glean.glean

The main Glean general API.

Expand source code
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.

"""
The main Glean general API.
"""


import atexit
import logging
from pathlib import Path
import shutil
import tempfile
import threading
from typing import Dict, Optional, Set, TYPE_CHECKING


from .config import Configuration
from . import _uniffi
from . import _ffi
from .net import PingUploadWorker
from ._process_dispatcher import ProcessDispatcher
from . import _util


# To avoid cyclical imports, but still make mypy type-checking work.
# See https://mypy.readthedocs.io/en/latest/common_issues.html#import-cycles
if TYPE_CHECKING:
    from .metrics import PingType, RecordedExperiment


log = logging.getLogger("glean")


_ffi.setup_logging()


def _rmtree(path) -> bool:
    """
    A small wrapper around shutil.rmtree to make it runnable on the
    ProcessDispatcher.
    """
    shutil.rmtree(path)
    return True


class OnGleanEventsImpl(_uniffi.OnGleanEvents):
    def __init__(self, glean):
        self.glean = glean

    def initialize_finished(self):
        self.glean._init_finished = True

    def trigger_upload(self):
        PingUploadWorker.process(Glean._testing_mode)

    def start_metrics_ping_scheduler(self):
        pass

    def cancel_uploads(self):
        pass

    def shutdown(self):
        pass


class Glean:
    """
    The main Glean API.

    Before any data collection can take place, the Glean SDK **must** be
    initialized from the application.

    >>> Glean.initialize(
    ...     application_id="my-app",
    ...     application_version="0.0.0",
    ...     upload_enabled=True,
    ...     data_dir=Path.home() / ".glean",
    ... )
    """

    # Whether Glean was initialized
    _initialized: bool = False
    # Set when `initialize()` returns.
    # This allows to detect calls that happen before `Glean.initialize()` was called.
    # Note: The initialization might still be in progress, as it runs in a separate thread.
    _init_finished: bool = False

    # Are we in testing mode?
    _testing_mode: bool = False

    # The Configuration that was passed to `initialize`
    _configuration: Configuration

    # The directory that Glean stores data in
    _data_dir: Path = Path()

    # Whether Glean "owns" the data directory and should destroy it upon reset.
    _destroy_data_dir: bool = False

    # Keep track of this setting before Glean is initialized
    _upload_enabled: bool = True

    # The ping types, so they can be registered prior to Glean initialization,
    # and saved between test runs.
    _ping_type_queue: Set["PingType"] = set()

    # The application id to send in the ping.
    _application_id: str

    # The version of the application sending Glean data.
    _application_version: str

    # The build identifier generated by the CI system.
    _application_build_id: str

    # A thread lock for Glean operations that need to be synchronized
    _thread_lock = threading.RLock()

    # Simple logging API log level
    _simple_log_level: Optional[int] = None

    @classmethod
    def initialize(
        cls,
        application_id: str,
        application_version: str,
        upload_enabled: bool,
        configuration: Optional[Configuration] = None,
        data_dir: Optional[Path] = None,
        application_build_id: Optional[str] = None,
        log_level: Optional[int] = None,
    ) -> None:
        """
        Initialize the Glean SDK.

        This should only be initialized once by the application, and not by
        libraries using the Glean SDK. A message is logged to error and no
        changes are made to the state if initialize is called a more than
        once.

        Args:
            application_id (str): The application id to use when sending pings.
            application_version (str): The version of the application sending
                Glean data. The meaning of this field is application-specific,
                but it is highly recommended to set this to something
                meaningful.
            upload_enabled (bool): Controls whether telemetry is enabled. If
                disabled, all persisted metrics, events and queued pings
                (except first_run_date) are cleared.
            configuration (glean.config.Configuration): (optional) An object with
                global settings.
            data_dir (pathlib.Path): The path to the Glean data directory.
            application_build_id (str): (optional) The build identifier generated
                by the CI system (e.g. "1234/A").
            log_level (int): (optional) The level of log messages that Glean
                will emit. One of the constants in the Python `logging` module:
                `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`. If you need a
                specialized logging configuration, such as to redirecting,
                filtering or reformatting, you should use the Python `logging`
                module's API directly, but that will not affect logging any of
                Glean's networking operations which happen in a subprocess.
                Details in the "Debugging Python applications with the Glean
                SDK" chapter in the docs.
        """
        if log_level is not None:
            cls._simple_log_level = log_level
            logging.basicConfig(level=log_level)

        with cls._thread_lock:
            if cls.is_initialized():
                return

            atexit.register(Glean._reset)

            if configuration is None:
                configuration = Configuration()

            if data_dir is None:
                raise TypeError("data_dir must be provided")
            cls._data_dir = data_dir
            cls._destroy_data_dir = False

            cls._configuration = configuration
            cls._application_id = application_id

            if application_version is None:
                cls._application_version = "Unknown"
            else:
                cls._application_version = application_version

            if application_build_id is None:
                cls._application_build_id = "Unknown"
            else:
                cls._application_build_id = application_build_id

        # FIXME: Require user to pass in build-date
        dt = _uniffi.Datetime(
            year=1970,
            month=1,
            day=1,
            hour=0,
            minute=0,
            second=0,
            nanosecond=0,
            offset_seconds=0,
        )
        client_info = _uniffi.ClientInfoMetrics(
            app_build=cls._application_build_id,
            app_display_version=cls._application_version,
            app_build_date=dt,
            channel=configuration.channel,
            architecture="Unknown",
            os_version="Unknown",
            locale=None,
            device_manufacturer=None,
            device_model=None,
            android_sdk_version=None,
            windows_build_number=None,
        )
        callbacks = OnGleanEventsImpl(cls)
        cfg = _uniffi.InternalConfiguration(
            data_path=str(cls._data_dir),
            application_id=application_id,
            language_binding_name="Python",
            upload_enabled=upload_enabled,
            max_events=configuration.max_events,
            delay_ping_lifetime_io=False,
            use_core_mps=False,
            app_build=cls._application_build_id,
            trim_data_to_registered_pings=False,
            log_level=None,
            rate_limit=None,
            enable_event_timestamps=configuration.enable_event_timestamps,
            experimentation_id=configuration.experimentation_id,
        )

        _uniffi.glean_initialize(cfg, client_info, callbacks)
        cls._initialized = True

    @classmethod
    def _initialize_with_tempdir_for_testing(
        cls,
        application_id: str,
        application_version: str,
        upload_enabled: bool,
        configuration: Optional[Configuration] = None,
        application_build_id: Optional[str] = None,
    ) -> None:
        """
        Initialize Glean to use a temporary data directory. Use for internal
        unit testing only.

        The temporary directory will be destroyed when Glean is initialized
        again or at process shutdown.
        """

        actual_data_dir = Path(tempfile.TemporaryDirectory().name)
        cls.initialize(
            application_id,
            application_version,
            upload_enabled,
            configuration=configuration,
            data_dir=actual_data_dir,
            application_build_id=application_build_id,
        )
        cls._destroy_data_dir = True

    @_util.classproperty
    def configuration(cls) -> Configuration:
        """
        Access the configuration object to change dynamic parameters.
        """
        return cls._configuration

    @classmethod
    def _reset(cls) -> None:
        """
        Resets the Glean singleton.
        """
        # TODO: 1594184 Send the metrics ping
        log.debug("Resetting Glean")

        # Wait for the subprocess to complete.  We only need to do this if
        # we know we are going to be deleting the data directory.
        if cls._destroy_data_dir and cls._data_dir.exists():
            ProcessDispatcher._wait_for_last_process()

        # Destroy the Glean object.
        # Importantly on Windows, this closes the handle to the database so
        # that the data directory can be deleted without a multiple access
        # violation.
        _uniffi.glean_test_destroy_glean(False)

        _uniffi.glean_set_test_mode(False)
        cls._init_finished = False
        cls._initialized = False
        cls._testing_mode = False

        # Remove the atexit handler or it will get called multiple times at
        # exit.
        atexit.unregister(cls._reset)

        if cls._destroy_data_dir and cls._data_dir.exists():
            # This needs to be run in the same one-at-a-time process as the
            # PingUploadWorker to avoid a race condition. This will block the
            # main thread waiting for all pending uploads to complete, but this
            # only happens during testing when the data directory is a
            # temporary directory, so there is no concern about delaying
            # application shutdown here.
            p = ProcessDispatcher.dispatch(_rmtree, (str(cls._data_dir),))
            p.wait()

    @classmethod
    def is_initialized(cls) -> bool:
        """
        Returns True if the Glean SDK has been initialized.
        """
        return cls._initialized

    @classmethod
    def set_upload_enabled(cls, enabled: bool) -> None:
        """
        Enable or disable Glean collection and upload.

        Metric collection is enabled by default.

        When uploading is disabled, metrics aren't recorded at all and no data
        is uploaded.

        When disabling, all pending metrics, events and queued pings are cleared.

        When enabling, the core Glean metrics are recreated.

        Args:
            enabled (bool): When True, enable metric collection.
        """
        # Changing upload enabled always happens asynchronous.
        # That way it follows what a user expect when calling it inbetween other calls:
        # It executes in the right order.
        #
        # Because the dispatch queue is halted until Glean is fully initialized
        # we can safely enqueue here and it will execute after initialization.
        _uniffi.glean_set_upload_enabled(enabled)

    @classmethod
    def set_experiment_active(
        cls, experiment_id: str, branch: str, extra: Optional[Dict[str, str]] = None
    ) -> None:
        """
        Indicate that an experiment is running. Glean will then add an
        experiment annotation to the environment which is sent with pings. This
        information is not persisted between runs.

        Args:
            experiment_id (str): The id of the active experiment (maximum 100
                bytes)
            branch (str): The experiment branch (maximum 100 bytes)
            extra (dict of str -> str): Optional metadata to output with the
                ping
        """
        map = {} if extra is None else extra
        _uniffi.glean_set_experiment_active(experiment_id, branch, map)

    @classmethod
    def set_experiment_inactive(cls, experiment_id: str) -> None:
        """
        Indicate that the experiment is no longer running.

        Args:
            experiment_id (str): The id of the experiment to deactivate.
        """
        _uniffi.glean_set_experiment_inactive(experiment_id)

    @classmethod
    def test_is_experiment_active(cls, experiment_id: str) -> bool:
        """
        Tests whether an experiment is active, for testing purposes only.

        Args:
            experiment_id (str): The id of the experiment to look for.

        Returns:
            is_active (bool): If the experiement is active and reported in
                pings.
        """
        return _uniffi.glean_test_get_experiment_data(experiment_id) is not None

    @classmethod
    def test_get_experiment_data(cls, experiment_id: str) -> "RecordedExperiment":
        """
        Returns the stored data for the requested active experiment, for testing purposes only.

        Args:
            experiment_id (str): The id of the experiment to look for.

        Returns:
            experiment_data (RecordedExperiment): The data associated with
                the experiment.
        """
        data = _uniffi.glean_test_get_experiment_data(experiment_id)
        if data is not None:
            return data
        else:
            raise RuntimeError("Experiment data is not set")

    @classmethod
    def set_experimentation_id(cls, experimentation_id: str):
        """
        Dynamically set the experimentation identifier, as opposed to setting it through
        the configuration during initialization.

        Args:
            experimentation_id (str): The string experimentation identifier to set
        """
        _uniffi.glean_set_experimentation_id(experimentation_id)

    @classmethod
    def test_get_experimentation_id(cls) -> str:
        """
        Returns the stored experimentation id, for testing purposes only.

        Returns:
            experimentation_id (str): The experimentation id set by the client.
        """
        experimentation_id = _uniffi.glean_test_get_experimentation_id()
        if experimentation_id is not None:
            return experimentation_id
        else:
            raise RuntimeError("Experimentation id is not set")

    @classmethod
    def handle_client_active(cls):
        """
        Performs the collection/cleanup operations required by becoming active.

        This functions generates a baseline ping with reason `active`
        and then sets the dirty bit.
        This should be called whenever the consuming product becomes active (e.g.
        getting to foreground).
        """
        _uniffi.glean_handle_client_active()

    @classmethod
    def handle_client_inactive(cls):
        """
        Performs the collection/cleanup operations required by becoming inactive.

        This functions generates a baseline and an events ping with reason
        `inactive` and then clears the dirty bit.
        This should be called whenever the consuming product becomes inactive (e.g.
        getting to background).
        """
        _uniffi.glean_handle_client_inactive()

    @classmethod
    def shutdown(cls):
        """
        Shuts down Glean in an orderly fashion.
        """
        _uniffi.glean_shutdown()

        # On top of the Glean shutdown
        # we also wait for the process dispatcher to finish.
        ProcessDispatcher._wait_for_last_process()


__all__ = ["Glean"]

Classes

class Glean

The main Glean API.

Before any data collection can take place, the Glean SDK must be initialized from the application.

>>> Glean.initialize(
...     application_id="my-app",
...     application_version="0.0.0",
...     upload_enabled=True,
...     data_dir=Path.home() / ".glean",
... )
Expand source code
class Glean:
    """
    The main Glean API.

    Before any data collection can take place, the Glean SDK **must** be
    initialized from the application.

    >>> Glean.initialize(
    ...     application_id="my-app",
    ...     application_version="0.0.0",
    ...     upload_enabled=True,
    ...     data_dir=Path.home() / ".glean",
    ... )
    """

    # Whether Glean was initialized
    _initialized: bool = False
    # Set when `initialize()` returns.
    # This allows to detect calls that happen before `Glean.initialize()` was called.
    # Note: The initialization might still be in progress, as it runs in a separate thread.
    _init_finished: bool = False

    # Are we in testing mode?
    _testing_mode: bool = False

    # The Configuration that was passed to `initialize`
    _configuration: Configuration

    # The directory that Glean stores data in
    _data_dir: Path = Path()

    # Whether Glean "owns" the data directory and should destroy it upon reset.
    _destroy_data_dir: bool = False

    # Keep track of this setting before Glean is initialized
    _upload_enabled: bool = True

    # The ping types, so they can be registered prior to Glean initialization,
    # and saved between test runs.
    _ping_type_queue: Set["PingType"] = set()

    # The application id to send in the ping.
    _application_id: str

    # The version of the application sending Glean data.
    _application_version: str

    # The build identifier generated by the CI system.
    _application_build_id: str

    # A thread lock for Glean operations that need to be synchronized
    _thread_lock = threading.RLock()

    # Simple logging API log level
    _simple_log_level: Optional[int] = None

    @classmethod
    def initialize(
        cls,
        application_id: str,
        application_version: str,
        upload_enabled: bool,
        configuration: Optional[Configuration] = None,
        data_dir: Optional[Path] = None,
        application_build_id: Optional[str] = None,
        log_level: Optional[int] = None,
    ) -> None:
        """
        Initialize the Glean SDK.

        This should only be initialized once by the application, and not by
        libraries using the Glean SDK. A message is logged to error and no
        changes are made to the state if initialize is called a more than
        once.

        Args:
            application_id (str): The application id to use when sending pings.
            application_version (str): The version of the application sending
                Glean data. The meaning of this field is application-specific,
                but it is highly recommended to set this to something
                meaningful.
            upload_enabled (bool): Controls whether telemetry is enabled. If
                disabled, all persisted metrics, events and queued pings
                (except first_run_date) are cleared.
            configuration (glean.config.Configuration): (optional) An object with
                global settings.
            data_dir (pathlib.Path): The path to the Glean data directory.
            application_build_id (str): (optional) The build identifier generated
                by the CI system (e.g. "1234/A").
            log_level (int): (optional) The level of log messages that Glean
                will emit. One of the constants in the Python `logging` module:
                `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`. If you need a
                specialized logging configuration, such as to redirecting,
                filtering or reformatting, you should use the Python `logging`
                module's API directly, but that will not affect logging any of
                Glean's networking operations which happen in a subprocess.
                Details in the "Debugging Python applications with the Glean
                SDK" chapter in the docs.
        """
        if log_level is not None:
            cls._simple_log_level = log_level
            logging.basicConfig(level=log_level)

        with cls._thread_lock:
            if cls.is_initialized():
                return

            atexit.register(Glean._reset)

            if configuration is None:
                configuration = Configuration()

            if data_dir is None:
                raise TypeError("data_dir must be provided")
            cls._data_dir = data_dir
            cls._destroy_data_dir = False

            cls._configuration = configuration
            cls._application_id = application_id

            if application_version is None:
                cls._application_version = "Unknown"
            else:
                cls._application_version = application_version

            if application_build_id is None:
                cls._application_build_id = "Unknown"
            else:
                cls._application_build_id = application_build_id

        # FIXME: Require user to pass in build-date
        dt = _uniffi.Datetime(
            year=1970,
            month=1,
            day=1,
            hour=0,
            minute=0,
            second=0,
            nanosecond=0,
            offset_seconds=0,
        )
        client_info = _uniffi.ClientInfoMetrics(
            app_build=cls._application_build_id,
            app_display_version=cls._application_version,
            app_build_date=dt,
            channel=configuration.channel,
            architecture="Unknown",
            os_version="Unknown",
            locale=None,
            device_manufacturer=None,
            device_model=None,
            android_sdk_version=None,
            windows_build_number=None,
        )
        callbacks = OnGleanEventsImpl(cls)
        cfg = _uniffi.InternalConfiguration(
            data_path=str(cls._data_dir),
            application_id=application_id,
            language_binding_name="Python",
            upload_enabled=upload_enabled,
            max_events=configuration.max_events,
            delay_ping_lifetime_io=False,
            use_core_mps=False,
            app_build=cls._application_build_id,
            trim_data_to_registered_pings=False,
            log_level=None,
            rate_limit=None,
            enable_event_timestamps=configuration.enable_event_timestamps,
            experimentation_id=configuration.experimentation_id,
        )

        _uniffi.glean_initialize(cfg, client_info, callbacks)
        cls._initialized = True

    @classmethod
    def _initialize_with_tempdir_for_testing(
        cls,
        application_id: str,
        application_version: str,
        upload_enabled: bool,
        configuration: Optional[Configuration] = None,
        application_build_id: Optional[str] = None,
    ) -> None:
        """
        Initialize Glean to use a temporary data directory. Use for internal
        unit testing only.

        The temporary directory will be destroyed when Glean is initialized
        again or at process shutdown.
        """

        actual_data_dir = Path(tempfile.TemporaryDirectory().name)
        cls.initialize(
            application_id,
            application_version,
            upload_enabled,
            configuration=configuration,
            data_dir=actual_data_dir,
            application_build_id=application_build_id,
        )
        cls._destroy_data_dir = True

    @_util.classproperty
    def configuration(cls) -> Configuration:
        """
        Access the configuration object to change dynamic parameters.
        """
        return cls._configuration

    @classmethod
    def _reset(cls) -> None:
        """
        Resets the Glean singleton.
        """
        # TODO: 1594184 Send the metrics ping
        log.debug("Resetting Glean")

        # Wait for the subprocess to complete.  We only need to do this if
        # we know we are going to be deleting the data directory.
        if cls._destroy_data_dir and cls._data_dir.exists():
            ProcessDispatcher._wait_for_last_process()

        # Destroy the Glean object.
        # Importantly on Windows, this closes the handle to the database so
        # that the data directory can be deleted without a multiple access
        # violation.
        _uniffi.glean_test_destroy_glean(False)

        _uniffi.glean_set_test_mode(False)
        cls._init_finished = False
        cls._initialized = False
        cls._testing_mode = False

        # Remove the atexit handler or it will get called multiple times at
        # exit.
        atexit.unregister(cls._reset)

        if cls._destroy_data_dir and cls._data_dir.exists():
            # This needs to be run in the same one-at-a-time process as the
            # PingUploadWorker to avoid a race condition. This will block the
            # main thread waiting for all pending uploads to complete, but this
            # only happens during testing when the data directory is a
            # temporary directory, so there is no concern about delaying
            # application shutdown here.
            p = ProcessDispatcher.dispatch(_rmtree, (str(cls._data_dir),))
            p.wait()

    @classmethod
    def is_initialized(cls) -> bool:
        """
        Returns True if the Glean SDK has been initialized.
        """
        return cls._initialized

    @classmethod
    def set_upload_enabled(cls, enabled: bool) -> None:
        """
        Enable or disable Glean collection and upload.

        Metric collection is enabled by default.

        When uploading is disabled, metrics aren't recorded at all and no data
        is uploaded.

        When disabling, all pending metrics, events and queued pings are cleared.

        When enabling, the core Glean metrics are recreated.

        Args:
            enabled (bool): When True, enable metric collection.
        """
        # Changing upload enabled always happens asynchronous.
        # That way it follows what a user expect when calling it inbetween other calls:
        # It executes in the right order.
        #
        # Because the dispatch queue is halted until Glean is fully initialized
        # we can safely enqueue here and it will execute after initialization.
        _uniffi.glean_set_upload_enabled(enabled)

    @classmethod
    def set_experiment_active(
        cls, experiment_id: str, branch: str, extra: Optional[Dict[str, str]] = None
    ) -> None:
        """
        Indicate that an experiment is running. Glean will then add an
        experiment annotation to the environment which is sent with pings. This
        information is not persisted between runs.

        Args:
            experiment_id (str): The id of the active experiment (maximum 100
                bytes)
            branch (str): The experiment branch (maximum 100 bytes)
            extra (dict of str -> str): Optional metadata to output with the
                ping
        """
        map = {} if extra is None else extra
        _uniffi.glean_set_experiment_active(experiment_id, branch, map)

    @classmethod
    def set_experiment_inactive(cls, experiment_id: str) -> None:
        """
        Indicate that the experiment is no longer running.

        Args:
            experiment_id (str): The id of the experiment to deactivate.
        """
        _uniffi.glean_set_experiment_inactive(experiment_id)

    @classmethod
    def test_is_experiment_active(cls, experiment_id: str) -> bool:
        """
        Tests whether an experiment is active, for testing purposes only.

        Args:
            experiment_id (str): The id of the experiment to look for.

        Returns:
            is_active (bool): If the experiement is active and reported in
                pings.
        """
        return _uniffi.glean_test_get_experiment_data(experiment_id) is not None

    @classmethod
    def test_get_experiment_data(cls, experiment_id: str) -> "RecordedExperiment":
        """
        Returns the stored data for the requested active experiment, for testing purposes only.

        Args:
            experiment_id (str): The id of the experiment to look for.

        Returns:
            experiment_data (RecordedExperiment): The data associated with
                the experiment.
        """
        data = _uniffi.glean_test_get_experiment_data(experiment_id)
        if data is not None:
            return data
        else:
            raise RuntimeError("Experiment data is not set")

    @classmethod
    def set_experimentation_id(cls, experimentation_id: str):
        """
        Dynamically set the experimentation identifier, as opposed to setting it through
        the configuration during initialization.

        Args:
            experimentation_id (str): The string experimentation identifier to set
        """
        _uniffi.glean_set_experimentation_id(experimentation_id)

    @classmethod
    def test_get_experimentation_id(cls) -> str:
        """
        Returns the stored experimentation id, for testing purposes only.

        Returns:
            experimentation_id (str): The experimentation id set by the client.
        """
        experimentation_id = _uniffi.glean_test_get_experimentation_id()
        if experimentation_id is not None:
            return experimentation_id
        else:
            raise RuntimeError("Experimentation id is not set")

    @classmethod
    def handle_client_active(cls):
        """
        Performs the collection/cleanup operations required by becoming active.

        This functions generates a baseline ping with reason `active`
        and then sets the dirty bit.
        This should be called whenever the consuming product becomes active (e.g.
        getting to foreground).
        """
        _uniffi.glean_handle_client_active()

    @classmethod
    def handle_client_inactive(cls):
        """
        Performs the collection/cleanup operations required by becoming inactive.

        This functions generates a baseline and an events ping with reason
        `inactive` and then clears the dirty bit.
        This should be called whenever the consuming product becomes inactive (e.g.
        getting to background).
        """
        _uniffi.glean_handle_client_inactive()

    @classmethod
    def shutdown(cls):
        """
        Shuts down Glean in an orderly fashion.
        """
        _uniffi.glean_shutdown()

        # On top of the Glean shutdown
        # we also wait for the process dispatcher to finish.
        ProcessDispatcher._wait_for_last_process()

Static methods

def handle_client_active()

Performs the collection/cleanup operations required by becoming active.

This functions generates a baseline ping with reason active and then sets the dirty bit. This should be called whenever the consuming product becomes active (e.g. getting to foreground).

Expand source code
@classmethod
def handle_client_active(cls):
    """
    Performs the collection/cleanup operations required by becoming active.

    This functions generates a baseline ping with reason `active`
    and then sets the dirty bit.
    This should be called whenever the consuming product becomes active (e.g.
    getting to foreground).
    """
    _uniffi.glean_handle_client_active()
def handle_client_inactive()

Performs the collection/cleanup operations required by becoming inactive.

This functions generates a baseline and an events ping with reason inactive and then clears the dirty bit. This should be called whenever the consuming product becomes inactive (e.g. getting to background).

Expand source code
@classmethod
def handle_client_inactive(cls):
    """
    Performs the collection/cleanup operations required by becoming inactive.

    This functions generates a baseline and an events ping with reason
    `inactive` and then clears the dirty bit.
    This should be called whenever the consuming product becomes inactive (e.g.
    getting to background).
    """
    _uniffi.glean_handle_client_inactive()
def initialize(application_id: str, application_version: str, upload_enabled: bool, configuration: Optional[Configuration] = None, data_dir: Optional[pathlib.Path] = None, application_build_id: Optional[str] = None, log_level: Optional[int] = None) ‑> None

Initialize the Glean SDK.

This should only be initialized once by the application, and not by libraries using the Glean SDK. A message is logged to error and no changes are made to the state if initialize is called a more than once.

Args

application_id : str
The application id to use when sending pings.
application_version : str
The version of the application sending Glean data. The meaning of this field is application-specific, but it is highly recommended to set this to something meaningful.
upload_enabled : bool
Controls whether telemetry is enabled. If disabled, all persisted metrics, events and queued pings (except first_run_date) are cleared.
configuration : Configuration
(optional) An object with global settings.
data_dir : pathlib.Path
The path to the Glean data directory.
application_build_id : str
(optional) The build identifier generated by the CI system (e.g. "1234/A").
log_level : int
(optional) The level of log messages that Glean will emit. One of the constants in the Python logging module: DEBUG, INFO, WARNING, ERROR, CRITICAL. If you need a specialized logging configuration, such as to redirecting, filtering or reformatting, you should use the Python logging module's API directly, but that will not affect logging any of Glean's networking operations which happen in a subprocess. Details in the "Debugging Python applications with the Glean SDK" chapter in the docs.
Expand source code
@classmethod
def initialize(
    cls,
    application_id: str,
    application_version: str,
    upload_enabled: bool,
    configuration: Optional[Configuration] = None,
    data_dir: Optional[Path] = None,
    application_build_id: Optional[str] = None,
    log_level: Optional[int] = None,
) -> None:
    """
    Initialize the Glean SDK.

    This should only be initialized once by the application, and not by
    libraries using the Glean SDK. A message is logged to error and no
    changes are made to the state if initialize is called a more than
    once.

    Args:
        application_id (str): The application id to use when sending pings.
        application_version (str): The version of the application sending
            Glean data. The meaning of this field is application-specific,
            but it is highly recommended to set this to something
            meaningful.
        upload_enabled (bool): Controls whether telemetry is enabled. If
            disabled, all persisted metrics, events and queued pings
            (except first_run_date) are cleared.
        configuration (glean.config.Configuration): (optional) An object with
            global settings.
        data_dir (pathlib.Path): The path to the Glean data directory.
        application_build_id (str): (optional) The build identifier generated
            by the CI system (e.g. "1234/A").
        log_level (int): (optional) The level of log messages that Glean
            will emit. One of the constants in the Python `logging` module:
            `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`. If you need a
            specialized logging configuration, such as to redirecting,
            filtering or reformatting, you should use the Python `logging`
            module's API directly, but that will not affect logging any of
            Glean's networking operations which happen in a subprocess.
            Details in the "Debugging Python applications with the Glean
            SDK" chapter in the docs.
    """
    if log_level is not None:
        cls._simple_log_level = log_level
        logging.basicConfig(level=log_level)

    with cls._thread_lock:
        if cls.is_initialized():
            return

        atexit.register(Glean._reset)

        if configuration is None:
            configuration = Configuration()

        if data_dir is None:
            raise TypeError("data_dir must be provided")
        cls._data_dir = data_dir
        cls._destroy_data_dir = False

        cls._configuration = configuration
        cls._application_id = application_id

        if application_version is None:
            cls._application_version = "Unknown"
        else:
            cls._application_version = application_version

        if application_build_id is None:
            cls._application_build_id = "Unknown"
        else:
            cls._application_build_id = application_build_id

    # FIXME: Require user to pass in build-date
    dt = _uniffi.Datetime(
        year=1970,
        month=1,
        day=1,
        hour=0,
        minute=0,
        second=0,
        nanosecond=0,
        offset_seconds=0,
    )
    client_info = _uniffi.ClientInfoMetrics(
        app_build=cls._application_build_id,
        app_display_version=cls._application_version,
        app_build_date=dt,
        channel=configuration.channel,
        architecture="Unknown",
        os_version="Unknown",
        locale=None,
        device_manufacturer=None,
        device_model=None,
        android_sdk_version=None,
        windows_build_number=None,
    )
    callbacks = OnGleanEventsImpl(cls)
    cfg = _uniffi.InternalConfiguration(
        data_path=str(cls._data_dir),
        application_id=application_id,
        language_binding_name="Python",
        upload_enabled=upload_enabled,
        max_events=configuration.max_events,
        delay_ping_lifetime_io=False,
        use_core_mps=False,
        app_build=cls._application_build_id,
        trim_data_to_registered_pings=False,
        log_level=None,
        rate_limit=None,
        enable_event_timestamps=configuration.enable_event_timestamps,
        experimentation_id=configuration.experimentation_id,
    )

    _uniffi.glean_initialize(cfg, client_info, callbacks)
    cls._initialized = True
def is_initialized() ‑> bool

Returns True if the Glean SDK has been initialized.

Expand source code
@classmethod
def is_initialized(cls) -> bool:
    """
    Returns True if the Glean SDK has been initialized.
    """
    return cls._initialized
def set_experiment_active(experiment_id: str, branch: str, extra: Optional[Dict[str, str]] = None) ‑> None

Indicate that an experiment is running. Glean will then add an experiment annotation to the environment which is sent with pings. This information is not persisted between runs.

Args

experiment_id : str
The id of the active experiment (maximum 100 bytes)
branch : str
The experiment branch (maximum 100 bytes)

extra (dict of str -> str): Optional metadata to output with the ping

Expand source code
@classmethod
def set_experiment_active(
    cls, experiment_id: str, branch: str, extra: Optional[Dict[str, str]] = None
) -> None:
    """
    Indicate that an experiment is running. Glean will then add an
    experiment annotation to the environment which is sent with pings. This
    information is not persisted between runs.

    Args:
        experiment_id (str): The id of the active experiment (maximum 100
            bytes)
        branch (str): The experiment branch (maximum 100 bytes)
        extra (dict of str -> str): Optional metadata to output with the
            ping
    """
    map = {} if extra is None else extra
    _uniffi.glean_set_experiment_active(experiment_id, branch, map)
def set_experiment_inactive(experiment_id: str) ‑> None

Indicate that the experiment is no longer running.

Args

experiment_id : str
The id of the experiment to deactivate.
Expand source code
@classmethod
def set_experiment_inactive(cls, experiment_id: str) -> None:
    """
    Indicate that the experiment is no longer running.

    Args:
        experiment_id (str): The id of the experiment to deactivate.
    """
    _uniffi.glean_set_experiment_inactive(experiment_id)
def set_experimentation_id(experimentation_id: str)

Dynamically set the experimentation identifier, as opposed to setting it through the configuration during initialization.

Args

experimentation_id : str
The string experimentation identifier to set
Expand source code
@classmethod
def set_experimentation_id(cls, experimentation_id: str):
    """
    Dynamically set the experimentation identifier, as opposed to setting it through
    the configuration during initialization.

    Args:
        experimentation_id (str): The string experimentation identifier to set
    """
    _uniffi.glean_set_experimentation_id(experimentation_id)
def set_upload_enabled(enabled: bool) ‑> None

Enable or disable Glean collection and upload.

Metric collection is enabled by default.

When uploading is disabled, metrics aren't recorded at all and no data is uploaded.

When disabling, all pending metrics, events and queued pings are cleared.

When enabling, the core Glean metrics are recreated.

Args

enabled : bool
When True, enable metric collection.
Expand source code
@classmethod
def set_upload_enabled(cls, enabled: bool) -> None:
    """
    Enable or disable Glean collection and upload.

    Metric collection is enabled by default.

    When uploading is disabled, metrics aren't recorded at all and no data
    is uploaded.

    When disabling, all pending metrics, events and queued pings are cleared.

    When enabling, the core Glean metrics are recreated.

    Args:
        enabled (bool): When True, enable metric collection.
    """
    # Changing upload enabled always happens asynchronous.
    # That way it follows what a user expect when calling it inbetween other calls:
    # It executes in the right order.
    #
    # Because the dispatch queue is halted until Glean is fully initialized
    # we can safely enqueue here and it will execute after initialization.
    _uniffi.glean_set_upload_enabled(enabled)
def shutdown()

Shuts down Glean in an orderly fashion.

Expand source code
@classmethod
def shutdown(cls):
    """
    Shuts down Glean in an orderly fashion.
    """
    _uniffi.glean_shutdown()

    # On top of the Glean shutdown
    # we also wait for the process dispatcher to finish.
    ProcessDispatcher._wait_for_last_process()
def test_get_experiment_data(experiment_id: str) ‑> RecordedExperiment

Returns the stored data for the requested active experiment, for testing purposes only.

Args

experiment_id : str
The id of the experiment to look for.

Returns

experiment_data (RecordedExperiment): The data associated with the experiment.

Expand source code
@classmethod
def test_get_experiment_data(cls, experiment_id: str) -> "RecordedExperiment":
    """
    Returns the stored data for the requested active experiment, for testing purposes only.

    Args:
        experiment_id (str): The id of the experiment to look for.

    Returns:
        experiment_data (RecordedExperiment): The data associated with
            the experiment.
    """
    data = _uniffi.glean_test_get_experiment_data(experiment_id)
    if data is not None:
        return data
    else:
        raise RuntimeError("Experiment data is not set")
def test_get_experimentation_id() ‑> str

Returns the stored experimentation id, for testing purposes only.

Returns

experimentation_id (str): The experimentation id set by the client.

Expand source code
@classmethod
def test_get_experimentation_id(cls) -> str:
    """
    Returns the stored experimentation id, for testing purposes only.

    Returns:
        experimentation_id (str): The experimentation id set by the client.
    """
    experimentation_id = _uniffi.glean_test_get_experimentation_id()
    if experimentation_id is not None:
        return experimentation_id
    else:
        raise RuntimeError("Experimentation id is not set")
def test_is_experiment_active(experiment_id: str) ‑> bool

Tests whether an experiment is active, for testing purposes only.

Args

experiment_id : str
The id of the experiment to look for.

Returns

is_active (bool): If the experiement is active and reported in pings.

Expand source code
@classmethod
def test_is_experiment_active(cls, experiment_id: str) -> bool:
    """
    Tests whether an experiment is active, for testing purposes only.

    Args:
        experiment_id (str): The id of the experiment to look for.

    Returns:
        is_active (bool): If the experiement is active and reported in
            pings.
    """
    return _uniffi.glean_test_get_experiment_data(experiment_id) is not None

Instance variables

var configuration

Decorator for creating a property on a class (rather than an instance).

Expand source code
def __get__(self, obj, owner):
    return self.f(owner)