pinlog 0.3.2

PinLog is a powerful driver and library integrated several logging systems.

PinLog

PinLog is a powerful driver and library integrated several logging systems. It is divided into smallest independent service units and easy to use.

Installation

PinLog can be installed with pip :

$ python -m pip install pinlog

Get Start

Step 1 - Import pinlog

>>> from pinlog import helper
>>> from pinlog.log import Log
>>> from pinlog.helper import Logger, Console, Logstash, Filters

Step 2 - Add @Logger above the class

>>> @Logger(Log.Console, Log.Logstash)
>>> class MyClass():
...     def __init__(self):
... 
... 

Step 3 - Use pin(str) function to mark an excution timestamp

Define key or unique name to pin(str) function

>>> mc = MyClass()
>>> mc.pin('marker1')

Step 4 - Use latency(str1, str2) function to find out timing in milliseconds from point to point

From below example, to find timing of execution process from 'marker1' to 'marker2' by calling latency('marker1', 'marker2')

>>> time.sleep(3)
>>> mc.pin('marker2')
>>> print("--- %.8f milliseconds execution ---" % (mc.latency('marker1', 'marker2')))
--- 3001.61195 milliseconds execution ---

Step 5 - Use @Filters(...) along with trace(str1, data) function

With placing @Filters(...) above the class and filling some attributes names you need, trace(str1, data) function will format data then return only attributes you declared. In additional the return value will be add latency attribute in milliseconds as well.

>>> @Logger(Log.Console, Log.Logstash)
>>> @Filters('attribute1', 'attribute2', 'attribute3', 'attribute4')
>>> class MyClass():
...     def __init__(self):
... 
... data = {...}
... output = mc.trace('marker1', data)

Step 6 - Finally, use unpin(str) function to reset timestamp

>>> mc.unpin('marker1')
>>> mc.unpin('marker2')

Moreover, Excution process times is able to traced from anywhere no matter other functions, other classes, not even other applications as below examples

Tracing over 2 applications

Below examples show how to trace times across 2 applications. By creating the first application, class1.py and the second application, class2.py

Declaring Class1() in class1.py :

from pinlog import helper
from pinlog.log import Log
from pinlog.helper import Logger, Console, Logstash, Filters
import time

@Logger(Log.Console, Log.Logstash)
@Filters('username', 'firstname', 'middlename', 'lastname')
class Class1():
    
    def __init__(self):
        pass

    def function1(self, str):
        pass


c1 = Class1()
c1.pin('marker1')
time.sleep(3)
c1.pin('marker2')

Declaring Class2() in class2.py :

from pinlog import helper
from pinlog.log import Log
from pinlog.helper import Logger, Console, Logstash, Filters

@Logger(Log.Console, Log.Logstash)
class Class2():

    def __init__(self):
        pass

    def function2(self, str):
        pass

c2 = Class2()
data = {
    'username': 'admin',
    'password': '1qazxsw2',
    'firstname': 'Tom',
    'lastname': 'Cruise',
    'role': 'Administrator',
    'birthdate': 'July 3, 1962',
    'department': 'Cruise/Wagner Productions'
}
output1 = c2.trace('marker1', data)
print('Output 1 : ', output1)
output2 = c2.trace('marker2', data)
print('Output 2 : ', output2)

Output :

Output 1 : {'username': 'admin', 'firstname': 'Tom', 'middlename': None, 'lastname': 'Cruise', 'latency': 13845.938920974731}
Output 2 : {'username': 'admin', 'firstname': 'Tom', 'middlename': None, 'lastname': 'Cruise', 'latency': 10844.847202301025}