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pipservices4observability 0.0.5
Observability Components for Python
This module is a part of the Pip.Services polyglot microservices toolkit.
The Observability module contains observability component definitions that can be used to build applications and services.
The module contains the following packages:
Count - performance counters
Log - basic logging components that provide console and composite logging, as well as an interface for developing custom loggers
Trace - tracing components
Quick links:
Logging
API Reference
Change Log
Get Help
Contribute
Use
Install the Python package as
pip install pip_services4_observability
Example how to use Logging and Performance counters.
Here we are going to use CompositeLogger and CompositeCounters components.
They will pass through calls to loggers and counters that are set in references.
class MyComponent(IConfigurable, IReferenceable):
__logger = CompositeLogger()
__counters = CompositeCounters()
def configure(self, config):
self.__logger.configure(config)
def set_references(self, references):
self.__logger.set_references(references)
self.__counters.set_references(references)
def my_method(self, context, param1):
try:
self.__logger.trace(context, "Executed method mycomponent.mymethod")
self.__counters.increment("mycomponent.mymethod.exec_count", 1)
timing = self.__counters.begin_timing("mycomponent.mymethod.exec_time")
# ...
timing.end_timing()
except Exception as ex:
self.__logger.error(context, ex, "Failed to execute mycomponent.mymethod")
self.__counters.increment("mycomponent.mymethod.error_count", 1)
Develop
For development you shall install the following prerequisites:
Python 3.7+
Visual Studio Code or another IDE of your choice
Docker
Install dependencies:
pip install -r requirements.txt
Run automated tests:
python test.py
Generate API documentation:
./docgen.ps1
Before committing changes run dockerized build and test as:
./build.ps1
./test.ps1
./clear.ps1
Contacts
The initial implementation is done by Sergey Seroukhov. Pip.Services team is looking for volunteers to
take ownership over Python implementation in the project.
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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