semvec/pypi-packages huggingface dataset:
logs-ingestion 0.2.5
Package for logging to Azure Logs Ingestion API using decorators and regular logging statements.
License: Apache
Requires Python: <4.0,>=3.10

## Introduction

This logs_ingestion package provides several methods for logging data into Azure Monitor using the Logs Ingestion API.

The following attributes are part of the logging with the coding attribute names between brackets:
- _TimeGenerated_ (time_generated): the datetime the logging entry was created (required) 
- _Message_ (message): the message of the log entry (optional)
- _Duration_ (duration): the duration of the function in case the decorator is used (optional)
- _Status_ (status): the status of the system (optional)
- _RunId_ (run_id): the run ID of the flow that is being processed (required)
- _Tag_ (tag): the tag for grouping log entries (required)

The attribute `TimeGenerated` is automatically set for you. The `RunId` and `Tag` are part of the configuration of the logger you need to create and only need to be set once per logger.


## Usage

You'll need a `logger` to perform the actual logging:
```python
logger: Logger = get_logger(__name__, run_id="42", tag="logger1")
```
With the logger instantiation you'll also set the `RunId` and `Tag` to be used in all logging entries as generated through this logger.

The first method for logging information is by using a decorator in your Python code:
```python
@time_and_log(logger=logger, message="bla", status="timed")
def my_function():
    pass
```
Whenever the `my_function()` is called a log entry is created with when the function end that automatically includes the duration of the function call. This is a convenient way for monitoring the performance of functions and the possible drift in processing times. 
With the `message` and `status` arguments you can add additional details to the message logged.

The second method is by calling the usual logging lines, for example:
```python
from logs_ingestion.logs_record import LogsRecord
logger.warning(message='testing azure logging', record=LogsRecord(
               status="OK",
               duration=1.23))
```
The arguments are:
- `message`, speaks for itself
- `record`, the record(s) to be logged

The `record` argument must be either a `LogsRecord` or a list of `LogsRecord`s.
By using a list, you can simply log a whole batch of log records in one command. The `rund_id` and `tag` from the logger are pushed down to the individual log messages.