https://github.com/3noch/primitive-profiling-parser

A very primitive parser for very primitive file-based profiling output. Use this when you need to do quick-and-dirty profiling by writing to a file.
https://github.com/3noch/primitive-profiling-parser

Last synced: about 1 year ago
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A very primitive parser for very primitive file-based profiling output. Use this when you need to do quick-and-dirty profiling by writing to a file.

• Host: GitHub
• URL: https://github.com/3noch/primitive-profiling-parser
• Owner: 3noch
• License: mit
• Created: 2015-10-07T14:39:04.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2014-05-22T15:00:58.000Z (about 12 years ago)
• Last Synced: 2025-03-25T07:01:59.004Z (about 1 year ago)
• Language: Haskell
• Size: 141 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
P3 Overview

===========

The **Primitive Profiling Parser** (or *P3*) is a tiny tool to calculate averages from the

file-based output of a hand-rolled profiler.

Here's how it works:

Your profiler must write a file with two columns (separated by a tab character).

The first column must contain some identifer (like a function name) and the second

column must contain a decimal number representing how long the identified entity ran.

When you have such a file, run `p3` like this:

    $ p3 

or like this:

    $ cat  | p3

and you will get the average time spent for each unique entity along with some other information.

Example

-------

Let's say your program keeps appending to a file called `data.txt`. A small cross-section of

`data.txt` could look something like this:

    groupLogsByUser	0.00500

    ApiActivityLogger::sendLogsForUser	2.25004

    ApiActivityLogger::sendLogsForUser	2.24770

    ApiActivityLogger::sendLogsForUserInBatches	4.52228

    SqliteLogGatherer::resolveLogs	0.05343

    ApiActivityLogger::logActivity	4.59713

    getMaxIdFromQueryResult	0.00571

    SqliteQueuedLogGatherer::getQueryResult	1.42582

    SqliteLogGatherer::convertRowToLog	0.00208

    SqliteLogGatherer::convertRowToLog	0.00020

    Total	11.06091

where the first column is some unique name and the second is the time spent for that entity.

Running `p3 data.txt` will give you something like this to `stdout`:

    ID                                                AVERAGE                  COUNT           SUM

    getMaxIdFromQueryResult                           5.687253886010365e-3     x193            =1.0976400000000004

    SqliteQueuedLogGatherer::getQueryResult           1.0012469430051805       x193            =193.24065999999982

    SqliteLogGatherer::convertRowToLog                8.205776706964147e-4     x385583         =316.4008000001357

    SqliteLogGatherer::getLogs                        6.323538906250004        x192            =1214.1194700000008

    groupLogsByUser                                   5.138593749999997e-3     x192            =0.9866099999999995

    ApiActivityLogger::sendLogsForUser                2.2612985937500003       x384            =868.3386600000001

    ApiActivityLogger::sendLogsForUserInBatches       4.543974554973821        x191            =867.8991399999999

    SqliteLogGatherer::resolveLogs                    6.470340314136125e-2     x191            =12.358349999999998

    ApiActivityLogger::logActivity                    4.6310171204188455       x191            =884.5242699999995

    Total                                             10.965333507853408       x191            =2094.378700000001

Building

========

To build, run the following:

    $ cabal build