json-logging

Python logging library to emit JSON log that can be easily indexed and searchable by logging infrastructure such as ELK, EFK

If you're using Cloud Foundry, it worth to check out the library SAP/cf-python-logging-support which I'm also original author.

Content

Features
Usage
2.1 Non-web application log
2.2 Web application log
2.3 Get current correlation-id
2.4 Log extra properties
2.5 Root logger
2.6 Custom log formatter
Configuration
Python References
Framework support plugin development
FAQ & Troubleshooting
References

1. Features

Emit JSON logs (format detail)
Auto extract correlation-id for distributed tracing [1]
Lightweight, no dependencies, minimal configuration needed (1 LoC to get it working)
Fully compatible with Python logging module. Support both Python 2.7.x and 3.x
Support HTTP request instrumentation. Built in support for Flask, Sanic, Quart, Connexion. Extensible to support other web frameworks. PR welcome 😃 .
Support inject arbitrary extra properties to JSON log message.

2. Usage

Install by running this command:

pip install json-logging

By default log will be emitted in normal format to ease the local development. To enable it on production set either json_logging.ENABLE_JSON_LOGGING or ENABLE_JSON_LOGGING environment variable to true.

To configure, call json_logging.init(framework_name). Once configured library will try to configure all loggers (existing and newly created) to emit log in JSON format.
See following use cases for more detail.

TODO: update guide on how to use ELK stack to view log

2.1 Non-web application log

This mode don't support correlation-id.

import json_logging, logging, sys

# log is initialized without a web framework name
json_logging.ENABLE_JSON_LOGGING = True
json_logging.init()

logger = logging.getLogger("test-logger")
logger.setLevel(logging.DEBUG)
logger.addHandler(logging.StreamHandler(sys.stdout))

logger.info("test logging statement")

2.2 Web application log

Flask

import datetime, logging, sys, json_logging, flask

app = flask.Flask(__name__)
json_logging.ENABLE_JSON_LOGGING = True
json_logging.init(framework_name='flask')
json_logging.init_request_instrument(app)

# init the logger as usual
logger = logging.getLogger("test-logger")
logger.setLevel(logging.DEBUG)
logger.addHandler(logging.StreamHandler(sys.stdout))

@app.route('/')
def home():
    logger.info("test log statement")
    return "Hello world : " + str(datetime.datetime.now())

if __name__ == "__main__":
    app.run(host='0.0.0.0', port=int(5000), use_reloader=False)

Sanic

import logging, sys, json_logging, sanic

app = sanic.Sanic()
json_logging.ENABLE_JSON_LOGGING = True
json_logging.init(framework_name='sanic')
json_logging.init_request_instrument(app)

# init the logger as usual
logger = logging.getLogger("sanic-integration-test-app")
logger.setLevel(logging.DEBUG)
logger.addHandler(logging.StreamHandler(sys.stdout))

@app.route("/")
async def home(request):
    logger.info("test log statement")
    return sanic.response.text("hello world")

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=8000)

Quart

import asyncio, logging, sys, json_logging, quart

app = quart.Quart(__name__)
json_logging.ENABLE_JSON_LOGGING = True
json_logging.init(framework_name='quart')
json_logging.init_request_instrument(app)

# init the logger as usual
logger = logging.getLogger("test logger")
logger.setLevel(logging.DEBUG)
logger.addHandler(logging.StreamHandler(sys.stdout))

@app.route('/')
async def home():
    logger.info("test log statement")
    logger.info("test log statement", extra={'props': {"extra_property": 'extra_value'}})
    return "Hello world"

if __name__ == "__main__":
    loop = asyncio.get_event_loop()
    app.run(host='0.0.0.0', port=int(5000), use_reloader=False, loop=loop)

Connexion

import datetime, logging, sys, json_logging, connexion

app = connexion.FlaskApp(__name__)
json_logging.ENABLE_JSON_LOGGING = True
json_logging.init(framework_name='connexion', specification_dir='openapi/')
json_logging.init_request_instrument(app)

app.add_api('api.yaml')

# init the logger as usual
logger = logging.getLogger("test-logger")
logger.setLevel(logging.DEBUG)
logger.addHandler(logging.StreamHandler(sys.stdout))

if __name__ == "__main__":
    app.run()

2.3 Get current correlation-id

Current request correlation-id can be retrieved and pass to downstream services call as follow:

correlation_id = json_logging.get_correlation_id()
# use correlation id for downstream service calls here

In request context, if one is not present, a new one might be generated depends on CREATE_CORRELATION_ID_IF_NOT_EXISTS setting value.

2.4 Log extra properties

Extra property can be added to logging statement as follow:

logger.info("test log statement", extra = {'props' : {'extra_property' : 'extra_value'}})

2.5 Root logger

If you want to use root logger as main logger to emit log. Made sure you call config_root_logger() after initialize root logger (by logging.basicConfig() or logging.getLogger('root')) [2]

logging.basicConfig()
json_logging.config_root_logger()

2.6 Custom log formatter

Customer JSON log formatter can be passed to init method. see example for more detail: https://github.com/thangbn/json-logging-python/blob/master/example/custom_log_format.py

3. Configuration

logging library can be configured by setting the value in json_logging, all configuration must be placed before json_logging.init method call

Name	Description	Default value
ENABLE_JSON_LOGGING	Whether to enable JSON logging mode.Can be set as an environment variable, enable when set to to either one in following list (case-insensitive) ['true', '1', 'y', 'yes']	false
ENABLE_JSON_LOGGING_DEBUG	Whether to enable debug logging for this library for development purpose.	true
CORRELATION_ID_HEADERS	List of HTTP headers that will be used to look for correlation-id value. HTTP headers will be searched one by one according to list order	['X-Correlation-ID','X-Request-ID']
EMPTY_VALUE	Default value when a logging record property is None	'-'
CORRELATION_ID_GENERATOR	function to generate unique correlation-id	uuid.uuid1
JSON_SERIALIZER	function to encode object to JSON	json.dumps
COMPONENT_ID	Uniquely identifies the software component that has processed the current request	EMPTY_VALUE
COMPONENT_NAME	A human-friendly name representing the software component	EMPTY_VALUE
COMPONENT_INSTANCE_INDEX	Instance's index of horizontally scaled service	0
CREATE_CORRELATION_ID_IF_NOT_EXISTS	Whether to generate a new correlation-id in case one is not present	True

4. Python References

TODO: update Python API docs on Github page

5. Framework support plugin development

To add support for a new web framework, you need to extend following classes in framework_base and register support using json_logging.register_framework_support method:

Class	Description	Mandatory
RequestAdapter	Helper class help to extract logging-relevant information from HTTP request object	no
ResponseAdapter	Helper class help to extract logging-relevant information from HTTP response object	yes
FrameworkConfigurator	Class to perform logging configuration for given framework as needed	no
AppRequestInstrumentationConfigurator	Class to perform request instrumentation logging configuration	no

Take a look at json_logging/base_framework.py, json_logging.flask and json_logging.sanic packages for reference implementations.

6. FAQ & Troubleshooting

I configured everything, but no logs are printed out?
- Forgot to add handlers to your logger?
- Check whether logger is disabled.
Same log statement is printed out multiple times.
- Check whether the same handler is added to both parent and child loggers [2]
- If you using flask, by default option use_reloader is set to True which will start 2 instances of web application. change it to False to disable this behaviour [3]
Can not install Sanic on Windows?

you can install Sanic on windows by running these commands:

git clone --branch 0.7.0 https://github.com/channelcat/sanic.git
set SANIC_NO_UVLOOP=true
set SANIC_NO_UJSON=true
pip3 install .

7. References

[0] Full logging format references

2 types of logging statement will be emitted by this library:

Application log: normal logging statement e.g.:

{
	"type": "log",
	"written_at": "2017-12-23T16:55:37.280Z",
	"written_ts": 1514048137280721000,
	"component_id": "1d930c0xd-19-s3213",
	"component_name": "ny-component_name",
	"component_instance": 0,
	"logger": "test logger",
	"thread": "MainThread",
	"level": "INFO",
	"line_no": 22,
	"filename": "/path/to/foo.py"
	"exc_info": "Traceback (most recent call last): \n  File "<stdin>", line 1, in <module>\n ValueError: There is something wrong with your input",
	"correlation_id": "1975a02e-e802-11e7-8971-28b2bd90b19a",
	"extra_property": "extra_value",
	"msg": "This is a message"
}

Request log: request instrumentation logging statement which recorded request information such as response time, request size, etc.

{
	"type": "request",
	"written_at": "2017-12-23T16:55:37.280Z",
	"written_ts": 1514048137280721000,
	"component_id": "-",
	"component_name": "-",
	"component_instance": 0,
	"correlation_id": "1975a02e-e802-11e7-8971-28b2bd90b19a",
	"remote_user": "user_a",
	"request": "/index.html",
	"referer": "-",
	"x_forwarded_for": "-",
	"protocol": "HTTP/1.1",
	"method": "GET",
	"remote_ip": "127.0.0.1",
	"request_size_b": 1234,
	"remote_host": "127.0.0.1",
	"remote_port": 50160,
	"request_received_at": "2017-12-23T16:55:37.280Z",
	"response_time_ms": 0,
	"response_status": 200,
	"response_size_b": "122",
	"response_content_type": "text/html; charset=utf-8",
	"response_sent_at": "2017-12-23T16:55:37.280Z"
}

See following tables for detail format explanation:

Common field

Field	Description	Format	Example
written_at	The date when this log message was written.	ISO 8601 YYYY-MM-DDTHH:MM:SS.milliZ	2017-12-23T15:14:02.208Z
written_ts	The timestamp in nano-second precision when this request metric message was written.	long number	1456820553816849408
correlation_id	The timestamp in nano-second precision when this request metric message was written.	string	db2d002e-2702-41ec-66f5-c002a80a3d3f
type	Type of logging. "logs" or "request"	string
component_id	Uniquely identifies the software component that has processed the current request	string	9e6f3ecf-def0-4baf-8fac-9339e61d5645
component_name	A human-friendly name representing the software component	string	my-fancy-component
component_instance	Instance's index of horizontally scaled service	string	0

application logs

Field	Description	Format	Example
msg	The actual message string passed to the logger.	string	This is a log message
level	The log "level" indicating the severity of the log message.	string	INFO
thread	Identifies the execution thread in which this log message has been written.	string	http-nio-4655
logger	The logger name that emits the log message.	string	requests-logger
filename	The file name where an exception originated	string	/path/to/foo.py
exc_info	Traceback information about an exception	string	"Traceback (most recent call last): \n File "", line 1, in \n ValueError: There is something wrong with your input"

request logs:

Field	Description	Format	Example
request	request path that has been processed.	string	/get/api/v2
request_received_at	The date when an incoming request was received by the producer.	ISO 8601 YYYY-MM-DDTHH:MM:SS.milliZ The precision is in milliseconds. The timezone is UTC.	2015-01-24 14:06:05.071Z
response_sent_at	The date when the response to an incoming request was sent to the consumer.	ditto	2015-01-24 14:06:05.071Z
response_time_ms	How many milliseconds it took the producer to prepare the response.	float	43.476
protocol	Which protocol was used to issue a request to a producer. In most cases, this will be HTTP (including a version specifier), but for outgoing requests reported by a producer, it may contain other values. E.g. a database call via JDBC may report, e.g. "JDBC/1.2"	string	HTTP/1.1
method	The corresponding protocol method.	string	GET
remote_ip	IP address of the consumer (might be a proxy, might be the actual client)	string	192.168.0.1
remote_host	host name of the consumer (might be a proxy, might be the actual client)	string	my.happy.host
remote_port	Which TCP port is used by the consumer to establish a connection to the remote producer.	string	1234
remote_user	The username associated with the request	string	user_name
request_size_b	The size in bytes of the requesting entity or "body" (e.g., in case of POST requests).	long	1234
response_size_b	The size in bytes of the response entity	long	1234
response_status	The status code of the response.	long	200
response_content_type	The MIME type associated with the entity of the response if available/specified	long	application/json
referer	For HTTP requests, identifies the address of the webpage (i.e. the URI or IRI) that linked to the resource being requested.	string	/index.html
x_forwarded_for	Comma-separated list of IP addresses, the left-most being the original client, followed by proxy server addresses that forwarded the client request.	string	192.0.2.60,10.12.9.23

[1] What is correlation-id/request id

https://stackoverflow.com/questions/25433258/what-is-the-x-request-id-http-header

[2] Python logging propagate

https://docs.python.org/3/library/logging.html#logging.Logger.propagate https://docs.python.org/2/library/logging.html#logging.Logger.propagate

[3] more on flask use_reloader

http://flask.pocoo.org/docs/0.12/errorhandling/#working-with-debuggers

Development

create file .pypirc

[distutils]
index-servers =
  pypi
  pypitest

[pypi]
repository: https://upload.pypi.org/legacy/
username:
password:

[pypitest]
repository: https://test.pypi.org/legacy/
username=
password=

build

python setup.py bdist_wheel --universal

pypitest

twine upload --repository-url https://test.pypi.org/legacy/ dist/*
pip3 install json_logging --index-url https://test.pypi.org/simple/

pypi

twine upload --repository-url https://upload.pypi.org/legacy/ dist/*
pip3 install json_logging

edcwkim/json-logging-python