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https://github.com/ashutoshvarma/tslogs

ThrottleStop logs parsers and visualizer
https://github.com/ashutoshvarma/tslogs

cpu-monitoring cpu-temperature gpu-monitoring log-parser log-visualization parse plot visualizer

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ThrottleStop logs parsers and visualizer

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# `tslogs` [![Stars](https://img.shields.io/github/stars/ashutoshvarma/tslogs.svg?style=social&maxAge=3600&label=Star)](https://github.com/ashutoshvarma/tslogs/stargazers)
*A Python parser and visualizer for ThrottleStop logs.*

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## 🚩 Table of Contents

- [Overview](#%EF%B8%8F-overview)
- [What is ThrottleStop ?](#-what-is-throttlestop-)
- [Why would you like to parse ThrottleStop Logs ?](#why-would-you-like-to-parse-throttlestop-logs-)
- [Enable Logging in ThrottleStop](#%EF%B8%8F-enable-logging-in-throttlestop)
- [Installing](#-installing)
- [Usage](#-usage)
- [License](#-license)

## πŸ—ΊοΈ Overview

tslogs is a Python library to parse, browse, export and visualize
[ThrottleStop](https://www.techpowerup.com/download/techpowerup-throttlestop/) log files.

#### πŸ“– What is ThrottleStop ?
> [ThrottleStop](https://www.techpowerup.com/download/techpowerup-throttlestop/)
is a small application designed to monitor for
and correct the three main types of CPU throttling that are
being used on many laptop computers.

Official Thread - [here](http://forum.notebookreview.com/threads/the-throttlestop-guide.531329/)

Comprehensive Guide - [here](https://www.ultrabookreview.com/31385-the-throttlestop-guide/)

#### Why would you like to parse ThrottleStop Logs ?
TODO

#### 🏳️ Enable Logging in ThrottleStop


Select the `Log File` checkbox
Click on `Options` button and Select the Folder where you want logs to be saved.











## πŸ”§ Installing

Installing with `pip` is the easiest:
```console
# pip install tslogs # if you have the admin rights
$ pip install tslogs --user # install it in a user-site directory
```

Finally, a development version can be installed from GitHub
using `setuptools` & `pip`
```console
$ git clone https://github.com/ashutoshvarma/tslogs
$ cd tslogs
# pip install .
```

## πŸ’‘ Usage
### 1. `tslogs` - CLI tool
```console
$ tslogs --help
usage: tslogs [-h] [--json | --plot ] [--dates START END] [--interval INTERVAL] [--smooth SMOOTH] [--output FILE] [--indent VALUE] [--quiet]
[--version]
paths paths

positional arguments:
paths One or more paths to log dir or log files.

optional arguments:
-h, --help show this help message and exit
--json, -j dump all parsed log data.
--plot, -p Plot given the logs attributes (default: None). Allowed values are {multi, c0, clock_mod, chip_mod, battery_mw,
cpu_temp, gpu_mhz, gpu_temp, vid, power}
--quiet, -q Run in silent mode
--version, -v show program's version number and exit

Filter:
--dates, -d START END
Datetime range to filter (in ISO format, yyyy-mm-dd HH:MM:SS)

Plot Options:
--interval, -I INTERVAL
Plot data frequency in seconds (default: 60)
--smooth, -S SMOOTH Span interval for smoothing the graph, if data frequency is very high using increasing this with 'interval' can
yield smooth graph (default: 2)

Output:
--output, -o FILE Output file path, default is '-' (stdout)
--indent VALUE indent value for json output, default is 4
```
- #### a.) Print the summary
![tslogs-summary](docs/_static/summary.jpg)

- #### b.) Plot Graphs
This will plot `cpu_temp`, `multi` (clock speed in GHz),
`power` (in W) and `c0` from logs between time 16:00 to 16:15 in `2020-07-28.txt`
```console
tslogs .\tests\logs\2020-07-28.txt -p cpu_temp multi power --smooth 2 --interval 1 -d "2020-07-28 16:00:00" "2020-07-28 16:15:00"
```
![tslogs-plot](docs/_static/plot.jpg)

### 2. `tslogs` - Python Module
TODO

See `parse_logs()` and `LogLine` in `parse.py`. For more references
see the CLI implementation in `cli.py`

## πŸ“œ License

This library is provided under the open-source
[MIT license](https://choosealicense.com/licenses/mit/).