chore: remove Logger deprecated code

Author: heitorlessa

aws_lambda_powertools/logging/__init__.py

@@ -1,6 +1,6 @@
 """Logging utility
 """
 from ..helper.models import MetricUnit
-from .logger import Logger, log_metric, logger_inject_lambda_context, logger_setup
+from .logger import Logger
 
-__all__ = ["logger_setup", "logger_inject_lambda_context", "log_metric", "MetricUnit", "Logger"]
+__all__ = ["MetricUnit", "Logger"]

aws_lambda_powertools/logging/logger.py

@@ -1,16 +1,14 @@
 import copy
 import functools
-import itertools
 import json
 import logging
 import os
 import random
 import sys
-import warnings
 from distutils.util import strtobool
 from typing import Any, Callable, Dict, Union
 
-from ..helper.models import MetricUnit, build_lambda_context_model, build_metric_unit_from_str
+from ..helper.models import build_lambda_context_model
 from .exceptions import InvalidLoggerSamplingRateError
 
 logger = logging.getLogger(__name__)
@@ -114,44 +112,6 @@ def format(self, record):  # noqa: A003
         return json_record
 
 
-def logger_setup(
-    service: str = None, level: str = None, sampling_rate: float = 0.0, legacy: bool = False, **kwargs
-) -> DeprecationWarning:
-    """DEPRECATED
-
-    This will be removed when GA - Use `aws_lambda_powertools.logging.logger.Logger` instead
-
-    Example
-    -------
-        **Logger class - Same UX**
-
-        from aws_lambda_powertools import Logger
-        logger = Logger(service="payment") # same env var still applies
-
-    """
-    raise DeprecationWarning("Use Logger instead - This method will be removed when GA")
-
-
-def logger_inject_lambda_context(
-    lambda_handler: Callable[[Dict, Any], Any] = None, log_event: bool = False
-) -> DeprecationWarning:
-    """DEPRECATED
-
-    This will be removed when GA - Use `aws_lambda_powertools.logging.logger.Logger` instead
-
-    Example
-    -------
-        **Logger class - Same UX**
-
-        from aws_lambda_powertools import Logger
-        logger = Logger(service="payment") # same env var still applies
-        @logger.inject_lambda_context
-        def handler(evt, ctx):
-            pass
-    """
-    raise DeprecationWarning("Use Logger instead - This method will be removed when GA")
-
-
 def _is_cold_start() -> bool:
     """Verifies whether is cold start
 
@@ -170,113 +130,6 @@ def _is_cold_start() -> bool:
     return cold_start
 
 
-def log_metric(
-    name: str, namespace: str, unit: MetricUnit, value: float = 0, service: str = "service_undefined", **dimensions,
-):
-    """Logs a custom metric in a statsD-esque format to stdout.
-
-    **This will be removed when GA - Use `aws_lambda_powertools.metrics.metrics.Metrics` instead**
-
-    Creating Custom Metrics synchronously impact on performance/execution time.
-    Instead, log_metric prints a metric to CloudWatch Logs.
-    That allows us to pick them up asynchronously via another Lambda function and create them as a metric.
-
-    NOTE: It takes up to 9 dimensions by default, and Metric units are conveniently available via MetricUnit Enum.
-    If service is not passed as arg or via env var, "service_undefined" will be used as dimension instead.
-
-    **Output in CloudWatch Logs**: `MONITORING|<metric_value>|<metric_unit>|<metric_name>|<namespace>|<dimensions>`
-
-    Serverless Application Repository App that creates custom metric from this log output:
-    https://serverlessrepo.aws.amazon.com/applications/arn:aws:serverlessrepo:us-east-1:374852340823:applications~async-custom-metrics
-
-    Environment variables
-    ---------------------
-    POWERTOOLS_SERVICE_NAME: str
-        service name
-
-    Parameters
-    ----------
-    name : str
-        metric name, by default None
-    namespace : str
-        metric namespace (e.g. application name), by default None
-    unit : MetricUnit, by default MetricUnit.Count
-        metric unit enum value (e.g. MetricUnit.Seconds), by default None\n
-        API Info: https://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/API_MetricDatum.html
-    value : float, optional
-        metric value, by default 0
-    service : str, optional
-        service name used as dimension, by default "service_undefined"
-    dimensions: dict, optional
-        keyword arguments as additional dimensions (e.g. `customer=customerId`)
-
-    Example
-    -------
-    **Log metric to count number of successful payments; define service via env var**
-
-        $ export POWERTOOLS_SERVICE_NAME="payment"
-        from aws_lambda_powertools.logging import MetricUnit, log_metric
-        log_metric(
-            name="SuccessfulPayments",
-            unit=MetricUnit.Count,
-            value=1,
-            namespace="DemoApp"
-        )
-
-    **Log metric to count number of successful payments per campaign & customer**
-
-        from aws_lambda_powertools.logging import MetricUnit, log_metric
-        log_metric(
-            name="SuccessfulPayments",
-            service="payment",
-            unit=MetricUnit.Count,
-            value=1,
-            namespace="DemoApp",
-            campaign=campaign_id,
-            customer=customer_id
-        )
-    """
-
-    warnings.warn(message="This method will be removed in GA; use Metrics instead", category=DeprecationWarning)
-    logger.debug(f"Building new custom metric. Name: {name}, Unit: {unit}, Value: {value}, Dimensions: {dimensions}")
-    service = os.getenv("POWERTOOLS_SERVICE_NAME") or service
-    dimensions = __build_dimensions(**dimensions)
-    unit = build_metric_unit_from_str(unit)
-
-    metric = f"MONITORING|{value}|{unit.name}|{name}|{namespace}|service={service}"
-    if dimensions:
-        metric = f"MONITORING|{value}|{unit.name}|{name}|{namespace}|service={service},{dimensions}"
-
-    print(metric)
-
-
-def __build_dimensions(**dimensions) -> str:
-    """Builds correct format for custom metric dimensions from kwargs
-
-    Parameters
-    ----------
-    dimensions: dict, optional
-        additional dimensions
-
-    Returns
-    -------
-    str
-        Dimensions in the form of "key=value,key2=value2"
-    """
-    MAX_DIMENSIONS = 10
-    dimension = ""
-
-    # CloudWatch accepts a max of 10 dimensions per metric
-    # We include service name as a dimension
-    # so we take up to 9 values as additional dimensions
-    # before we convert everything to a string of key=value
-    dimensions_partition = dict(itertools.islice(dimensions.items(), MAX_DIMENSIONS))
-    dimensions_list = [dimension + "=" + value for dimension, value in dimensions_partition.items() if value]
-    dimension = ",".join(dimensions_list)
-
-    return dimension
-
-
 class Logger(logging.Logger):
     """Creates and setups a logger to format statements in JSON.
 

tests/functional/test_logger.py

@@ -6,7 +6,6 @@
 import pytest
 
 from aws_lambda_powertools import Logger, Tracer
-from aws_lambda_powertools.logging import MetricUnit, log_metric, logger_inject_lambda_context, logger_setup
 from aws_lambda_powertools.logging.exceptions import InvalidLoggerSamplingRateError
 from aws_lambda_powertools.logging.logger import JsonFormatter, set_package_logger
 
@@ -236,68 +235,6 @@ def handler(event, context):
     assert fourth_log["cold_start"] is False
 
 
-def test_log_metric(capsys):
-    # GIVEN a service, unit and value have been provided
-    # WHEN log_metric is called
-    # THEN custom metric line should be match given values
-    log_metric(
-        service="payment", name="test_metric", unit=MetricUnit.Seconds, value=60, namespace="DemoApp",
-    )
-    expected = "MONITORING|60|Seconds|test_metric|DemoApp|service=payment\n"
-    captured = capsys.readouterr()
-
-    assert captured.out == expected
-
-
-def test_log_metric_env_var(monkeypatch, capsys):
-    # GIVEN a service, unit and value have been provided
-    # WHEN log_metric is called
-    # THEN custom metric line should be match given values
-    service_name = "payment"
-    monkeypatch.setenv("POWERTOOLS_SERVICE_NAME", service_name)
-
-    log_metric(name="test_metric", unit=MetricUnit.Seconds, value=60, namespace="DemoApp")
-    expected = "MONITORING|60|Seconds|test_metric|DemoApp|service=payment\n"
-    captured = capsys.readouterr()
-
-    assert captured.out == expected
-
-
-def test_log_metric_multiple_dimensions(capsys):
-    # GIVEN multiple optional dimensions are provided
-    # WHEN log_metric is called
-    # THEN dimensions should appear as dimenion=value
-    log_metric(
-        name="test_metric", unit=MetricUnit.Seconds, value=60, customer="abc", charge_id="123", namespace="DemoApp",
-    )
-    expected = "MONITORING|60|Seconds|test_metric|DemoApp|service=service_undefined,customer=abc,charge_id=123\n"
-    captured = capsys.readouterr()
-
-    assert captured.out == expected
-
-
-@pytest.mark.parametrize(
-    "invalid_input,expected",
-    [
-        ({"unit": "seconds"}, "MONITORING|0|Seconds|test_metric|DemoApp|service=service_undefined\n",),
-        (
-            {"unit": "Seconds", "customer": None, "charge_id": "123", "payment_status": ""},
-            "MONITORING|0|Seconds|test_metric|DemoApp|service=service_undefined,charge_id=123\n",
-        ),
-    ],
-    ids=["metric unit as string lower case", "empty dimension value"],
-)
-def test_log_metric_partially_correct_args(capsys, invalid_input, expected):
-    # GIVEN invalid arguments are provided such as empty dimension values and metric units in strings
-    # WHEN log_metric is called
-    # THEN default values should be used such as "Count" as a unit, invalid dimensions not included
-    # and no exception raised
-    log_metric(name="test_metric", namespace="DemoApp", **invalid_input)
-    captured = capsys.readouterr()
-
-    assert captured.out == expected
-
-
 def test_package_logger(capsys):
 
     set_package_logger()
@@ -315,32 +252,6 @@ def test_package_logger_format(stdout, capsys):
     assert "test" in output["formatter"]
 
 
-@pytest.mark.parametrize(
-    "invalid_input,expected",
-    [({"unit": "Blah"}, ValueError), ({"unit": None}, ValueError), ({}, TypeError)],
-    ids=["invalid metric unit as str", "unit as None", "missing required unit"],
-)
-def test_log_metric_invalid_unit(capsys, invalid_input, expected):
-    # GIVEN invalid units are provided
-    # WHEN log_metric is called
-    # THEN ValueError exception should be raised
-
-    with pytest.raises(expected):
-        log_metric(name="test_metric", namespace="DemoApp", **invalid_input)
-
-
-def test_logger_setup_deprecated():
-    # Should be removed when GA
-    with pytest.raises(DeprecationWarning):
-        logger_setup()
-
-
-def test_logger_inject_lambda_context_deprecated():
-    # Should be removed when GA
-    with pytest.raises(DeprecationWarning):
-        logger_inject_lambda_context()
-
-
 def test_logger_append_duplicated(stdout):
     logger = Logger(stream=stdout, request_id="value")
     logger.structure_logs(append=True, request_id="new_value")