Python logger formatter json

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Json Formatter for the standard python logger

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madzak/python-json-logger

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README.md

This library is provided to allow standard python logging to output log data as json objects. With JSON we can make our logs more readable by machines and we can stop writing custom parsers for syslog type records.

Hi, I see this package is quiet alive and I am sorry for ignoring it so long. I will be stepping up my maintenance of this package so please allow me a week to get things back in order (and most likely a new minor version) and I’ll post and update here once I am caught up.

pip install python-json-logger 

Integrating with Python’s logging framework

Json outputs are provided by the JsonFormatter logging formatter. You can add the custom formatter like below:

Please note: version 0.1.0 has changed the import structure, please update to the following example for proper importing

import logging from pythonjsonlogger import jsonlogger logger = logging.getLogger() logHandler = logging.StreamHandler() formatter = jsonlogger.JsonFormatter() logHandler.setFormatter(formatter) logger.addHandler(logHandler)

The fmt parser can also be overidden if you want to have required fields that differ from the default of just message .

These two invocations are equivalent:

class CustomJsonFormatter(jsonlogger.JsonFormatter): def parse(self): return self._fmt.split(';') formatter = CustomJsonFormatter('one;two') # is equivalent to: formatter = jsonlogger.JsonFormatter('%(one)s %(two)s')

You can also add extra fields to your json output by specifying a dict in place of message, as well as by specifying an extra=<> argument.

Contents of these dictionaries will be added at the root level of the entry and may override basic fields.

You can also use the add_fields method to add to or generally normalize the set of default set of fields, it is called for every log event. For example, to unify default fields with those provided by structlog you could do something like this:

class CustomJsonFormatter(jsonlogger.JsonFormatter): def add_fields(self, log_record, record, message_dict): super(CustomJsonFormatter, self).add_fields(log_record, record, message_dict) if not log_record.get('timestamp'): # this doesn't use record.created, so it is slightly off now = datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%S.%fZ') log_record['timestamp'] = now if log_record.get('level'): log_record['level'] = log_record['level'].upper() else: log_record['level'] = record.levelname formatter = CustomJsonFormatter('%(timestamp)s %(level)s %(name)s %(message)s')

Items added to the log record will be included in every log message, no matter what the format requires.

Adding custom object serialization

For custom handling of object serialization you can specify default json object translator or provide a custom encoder

def json_translate(obj): if isinstance(obj, MyClass): return "special": obj.special> formatter = jsonlogger.JsonFormatter(json_default=json_translate, json_encoder=json.JSONEncoder) logHandler.setFormatter(formatter) logger.info("special": "value", "run": 12>) logger.info("classic message", extra="special": "value", "run": 12>)

To use the module with a config file using the fileConfig function, use the class pythonjsonlogger.jsonlogger.JsonFormatter . Here is a sample config file.

[loggers] keys = root,custom [logger_root] handlers = [logger_custom] level = INFO handlers = custom qualname = custom [handlers] keys = custom [handler_custom] class = StreamHandler level = INFO formatter = json args = (sys.stdout,) [formatters] keys = json [formatter_json] format = %(message)s class = pythonjsonlogger.jsonlogger.JsonFormatter

Sample JSON with a full formatter (basically the log message from the unit test). Every log message will appear on 1 line like a typical logger.

< "threadName": "MainThread", "name": "root", "thread": 140735202359648, "created": 1336281068.506248, "process": 41937, "processName": "MainProcess", "relativeCreated": 9.100914001464844, "module": "tests", "funcName": "testFormatKeys", "levelno": 20, "msecs": 506.24799728393555, "pathname": "tests/tests.py", "lineno": 60, "asctime": ["12-05-05 22:11:08,506248"], "message": "testing logging format", "filename": "tests.py", "levelname": "INFO", "special": "value", "run": 12 >

Источник

Overview

This library is provided to allow standard python logging to output log data as json objects. With JSON we can make our logs more readable by machines and we can stop writing custom parsers for syslog type records.

News

Hi, I see this package is quiet alive and I am sorry for ignoring it so long. I will be stepping up my maintenance of this package so please allow me a week to get things back in order (and most likely a new minor version) and I’ll post and update here once I am caught up.

Installing

pip install python-json-logger 

Usage

Integrating with Python’s logging framework

Json outputs are provided by the JsonFormatter logging formatter. You can add the custom formatter like below:

Please note: version 0.1.0 has changed the import structure, please update to the following example for proper importing

The fmt parser can also be overidden if you want to have required fields that differ from the default of just message .

These two invocations are equivalent:

  You can also add extra fields to your json output by specifying a dict in place of message, as well as by specifying an extra=<> argument.

Contents of these dictionaries will be added at the root level of the entry and may override basic fields.

You can also use the add_fields method to add to or generally normalize the set of default set of fields, it is called for every log event. For example, to unify default fields with those provided by structlog you could do something like this:

 Items added to the log record will be included in every log message, no matter what the format requires.

Adding custom object serialization

For custom handling of object serialization you can specify default json object translator or provide a custom encoder

To use the module with a config file using the fileConfig function, use the class pythonjsonlogger.jsonlogger.JsonFormatter . Here is a sample config file.

Sample JSON with a full formatter (basically the log message from the unit test). Every log message will appear on 1 line like a typical logger.

Источник

JSON-log-formatter 0.5.2

The library helps you to store logs in JSON format. Why is it important? Well, it facilitates integration with Logstash.

The log file will contain the following log record (inline).

            If you use a log collection and analysis system, you might need to include the built-in log record attributes with VerboseJSONFormatter .

JSON libraries

You can use ujson or simplejson instead of built-in json library.

Note, ujson doesn’t support dumps(default=f) argument: if it can’t serialize an attribute, it might fail with TypeError or skip an attribute.

Django integration

Here is an example of how the JSON formatter can be used with Django.

Let’s try to log something.

Custom formatter

You will likely need a custom log formatter. For instance, you want to log a user ID, an IP address and time as django.utils.timezone.now() . To do so you should override JSONFormatter.json_record() .

Let’s say you want datetime to be serialized as timestamp. You can use ujson (which does it by default) and disable ISO8601 date mutation.

Tests

 pip install -r requirements.txt tox

Источник

jsonformatter — for python log json

jsonformatter is a formatter for python output json log, e.g. output LogStash needed log.

Easily custom(add/replace) LogRecord attribute, e.g. in Flask web project, add username attribute to LogRecord for auto output username.

Python 2.7 and python 3 are supported from version 0.2.X, if you are using a version lower than 0.2.X, Only python 3 is supported.

Installation

jsonformatter is available on PyPI. Use pip to install:

$ pip install jsonformatter

$ git clone https://github.com/MyColorfulDays/jsonformatter.git $ 
Basic Usage
Case 1. Initial root logger like logging.basicConfig
$ cat logger_config.ini python code:
Case 1. Mix extra to output


Attribute name
Format
Description




args
You shouldn’t need to format this yourself.
The tuple of arguments merged into msg to produce message, or a dict whose values are used for the merge (when there is only one argument, and it is a dictionary).


asctime
%(asctime)s
Human-readable time when the LogRecord was created. By default this is of the form ‘2003-07-08 16:49:45,896’ (the numbers after the comma are millisecond portion of the time).


created
%(created)f
Time when the LogRecord was created (as returned by time.time()).


exc_info
You shouldn’t need to format this yourself.
Exception tuple (à la sys.exc_info) or, if no exception has occurred, None.


filename
%(filename)s
Filename portion of pathname.


funcName
%(funcName)s
Name of function containing the logging call.


levelname
%(levelname)s
Text logging level for the message ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL').


levelno
%(levelno)s
Numeric logging level for the message (DEBUG, INFO, WARNING, ERROR, CRITICAL).


lineno
%(lineno)d
Source line number where the logging call was issued (if available).


message
%(message)s
The logged message, computed as msg % args. This is set when Formatter.format() is invoked.


module
%(module)s
Module (name portion of filename).


msecs
%(msecs)d
Millisecond portion of the time when the LogRecord was created.


msg
You shouldn’t need to format this yourself.
The format string passed in the original logging call. Merged with args to produce message, or an arbitrary object (see Using arbitrary objects as messages).


name
%(name)s
Name of the logger used to log the call.


pathname
%(pathname)s
Full pathname of the source file where the logging call was issued (if available).


process
%(process)d
Process ID (if available).


processName
%(processName)s
Process name (if available).


relativeCreated
%(relativeCreated)d
Time in milliseconds when the LogRecord was created, relative to the time the logging module was loaded.


stack_info
You shouldn’t need to format this yourself.
Stack frame information (where available) from the bottom of the stack in the current thread, up to and including the stack frame of the logging call which resulted in the creation of this record.


thread
%(thread)d
Thread ID (if available).


threadName
%(threadName)s
Thread name (if available).



Подробности проекта
Ссылки проекта
Статистика
Метаданные
Лицензия: BSD License (BSD License)
Требует: Python >=2.7
Источник