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A lighweight functional tracer and log enhancer

Project description

PyBreadCrumbs

pybreadcrumbs is a lightweight function tracer and log enhancer for distributed systems written in python.

Inspiration

  • The inspiration for PyBreadCrumbs came to solve the daily trouble that we faced in our organisation in searching and sorting system logs that were generated.
  • It solves this by adding an extra key value pair to the log data which adds tracability to the logs.
  • It also adds an extra key value pair to add simple time taken based profiling as well.
  • It doesn't wish to compete with fully functional tracer or profiler nor it is a replacement for them, It's just there to make your logs more streamlined, readable and tracable.

Getting Started

Prerequisites

A project of course where you want to integrate breadcrumbs.

Installing

  • pybreadcrumbs is available on PyPi.
  • you can use pip to install this using pip install pybreadcrumbs
  • It requires python 3.7 or greater to work.

Configuring

  • import the breadcrumbs configuration at the root python file from where the execution starts.
  • from breadcrumbs.configuration import breadcrumbs_config
  • breadcrumbs_config is a config dictionary with following options.
  • trace_id_prefix : the prefix which will be appended to system generated trace id key.
  • key_prefix : the prefix which will be added to every key of breadcrumbs log_payload.
  • timezone : the timezone string for datetime in log_payload. default value is UTC
  • datetime_format : The datetime formate to be used in log_payload default value is %Y-%m-%d %H:%M:%S.%f
  • additional_keys : Additional keys that you wish to add to the tracable log payload.
  • extraction_fallback_level: this defines the stack trace level that a trace decorator should look for trace_id before creating a new trace id of it's own.

Using

  • Import the decorator add_bowl using.
  • from breadcrumbs.base import add_bowl
  • use the decorator on any function you would like to trace.
  • the fuction in which it is used needs to accept kwargs in function parameters.
  • to enhance other logging calls inside the function fetch the bowl object using
  • breadcrumbs_bowl = kwargs.get("breadcrumbs_bowl")
  • then whenever logging something pass extra=breadcrumbs_bowl.log_payload in your logging call.
  • eg. logger.info("test message that should be tracable", extra=breadcrumbs_bowl.log_payload)
  • you can also add a trace_text to your log_payload by using below method.
  • eg. logger.info("test message that should be tracable", extra=breadcrumbs_bowl.add_trace_text("CodeEventName"))
  • During the function call if you wish to add some meta data to the next logging calls you can store those meta data in the bowl object using add_trace_meta function.
  • eg. breadcrumbs_bowl.add_trace_meta(key1="string_value", key2=45)
  • The next logging calls using bowl object in the same function will log this meta as well.
  • NOTE: meta data is never propogated to next called function, only the trace_id and keys defined by additional_keys

Advanced Usage

  • You can pass key value pairs for keys defined under additional_keys in the decorator itself.
  • this way the functional trace log will contain these key value pairs and these will also be added to all the upcoming breadcrumbs_bowl.log_payload and breadcrumbs_bowl.add_trace_text("tTraceText") calls.
  • You can pass meta data key value pair in the decorator itself so as to insert meta data from the start itself rather then inside the fucntion manually using add_trace_meta.
  • You can pass custom trace_id of your choice by passing trace_id key and it's value in the decorator.
  • Similarily you can pass custom trace_text for the function tracing logs by passing trace_text key and it's value in the decorator.
  • You can pass python expression in place of value for any key in the decorator to extract value dynamically during a function call.
  • To do this you need to use add_bowlv2 decorator instead of add_bowl available under breadcrumbs.base
  • The expression should be a string starting with @ to signify it's dynamic nature.
  • The python expression should be one liner and need to do operation on args or kwargs variable.
  • All the positional argument passed to the underlying function is stored in args which is a tuple.
  • All the keyword arguments passed to the underlying function is stored in kwargs which is a dict.
  • you can use the | operator and add two expression so that if first one fails second one can be used.
  • eg: add_bowlv2(dynamic_key1='@args[0].attribute1["key1"]') or add_bowlv2(dynamic_key1='@kwargs["key1"].attribute1[0]') or a complex one like add_bowlv2(dynamic_key1='@args[0]|kwargs["key1"].attribute1[0]')

A Code block showing Usage

# initialise_project.py
from breadcrumbs.configuration import breadcrumbs_config

breadcrumbs_config.update({
    "trace_id_prefix": "test-",
    "key_prefix": "log_",
    "timezone": "Asia/Kolkata",
    "additional_keys": {"key1","key2"}
})

# test.py
from breadcrumbs.base import add_bowl, add_bowlv2
import logging

logger = logging.getLogger(__name__)

@add_bowl(key1="value1", meta_key1="meta_value1")
def test_logging(**kwargs):
    breadcrumbs_bowl = kwargs.get("breadcrumbs_bowl")
    # some operational statements here
    test_advanced_logging(a_token="token123")
    logger.info("Requested action completed", extra=breadcrumbs_bowl.add_trace_text("ActionCompleted"))

@add_bowlv2(key1="@kwargs['a_token']", "key2"="value2", trace_text="Advanced Test Called")
def test_advanced_logging(**kwargs):
    breadcrumbs_bowl = kwargs.get("breadcrumbs_bowl")
    try:
        # some operational statements here
        breadcrumbs_bowl.add_trace_meta(meta_key2="meta_value2")
        logger.info(
            "A Major event in test_advanced_logging happened",
            extra=breadcrumbs_bowl.add_trace_text("MajorEvent2Completed")
        )
    except Exception as e:
        logger.exception(e, extra=breadcrumbs_bowl.log_payload)

The log output

{
    "msg": "test_logging initialised",
    "levelname": "INFO",
    "pathname": "/pybreadcrumbs/base.py",
    "lineno": 409,
    "log_trace_text": "pybreadcrumbs.tests.test.test_logging",
    "log_trace_id": "test-d005ef1c-9f31-11ea-bfee-3e41543b0354",
    "log_elapsed_time": 0.0008239746,
    "log_trace_meta": {
        "meta_key1": "meta_value1"
    },
    "log_key1": "value1",
    "log_decorator_init_time": 0.000039684,
    "log_event_datetime": "2020-06-13 14:48:08.096476"
},
{
    "msg": "test_advanced_logging initialised",
    "levelname": "INFO",
    "pathname": "/pybreadcrumbs/base.py",
    "lineno": 409,
    "log_trace_text": "Advanced Test Called",
    "log_trace_id": "test-d005ef1c-9f31-11ea-bfee-3e41543b0354",
    "log_elapsed_time": 0.0012239746,
    "log_trace_meta": {},
    "log_key1": "token123",
    "log_key2": "value2",
    "log_decorator_init_time": 0.000071684,
    "log_event_datetime": "2020-06-13 14:48:08.116476"
},
{
    "msg": "A Major event in test_advanced_logging happened",
    "levelname": "INFO",
    "pathname": "/pybreadcrumbs/tests/test.py",
    "lineno": 36,
    "log_trace_text": "MajorEvent2Completed",
    "log_trace_id": "test-d005ef1c-9f31-11ea-bfee-3e41543b0354",
    "log_elapsed_time": 0.0017239746,
    "log_trace_meta": {
        "meta_key2": "meta_value2"
    },
    "log_key1": "token123",
    "log_key2": "value2",
    "log_event_datetime": "2020-06-13 14:48:08.146476"
},
{
    "msg": "Requested action completed",
    "levelname": "INFO",
    "pathname": "/pybreadcrumbs/tests/test.py",
    "lineno": 12,
    "log_trace_text": "ActionCompleted",
    "log_trace_id": "test-d005ef1c-9f31-11ea-bfee-3e41543b0354",
    "log_elapsed_time": 0.0023239746,
    "log_trace_meta": {
        "meta_key2": "meta_value2"
    },
    "log_key1": "value1",
    "log_event_datetime": "2020-06-13 14:48:08.176476"
},
  • NOTE: the datetime and elapsed time values for representation purpose only, they do not reflect the actual time taken or the actual time on which this code was run.

Running the tests

  • will be added

Built With

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

  • Hitesh Jha

  • See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE file for details

Future enhancements

  • Ensure child actions have a refrence to thier parents action.
  • Ensure correct time taken is calculated when in an async environment.

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