exectimeit 0.1.3
Accurate Measurement of Small Execution Times
Requires Python: >=3.8

# Accurate Measurement of Small Execution Times

This library implements a wrapper that can be used to 
accuratly measure small execution times.
This work is an implementation of the method described in this work [[1]](#1).

Measuring execution times, especially for quick applications (< 100 milliseconds), can be quite hard. The traditional method to do it is by simply measuring the system time before and after a function call. This is not very robust and it is even susceptible to systematic and random measurement errors:

1. **Systematic error:** by invoking the measuring instruction, an unknown amount of time is added to the execution time of the target function. This unknown amount depends on the OS, the particular implementation and other uncontrollable factors.

2. **Random error:** the execution time of the target function will vary to a certain degree.

We can minimize the random error by just performing multiple measurements and taking the average of those. However, it is much more challenging to remove the systematic error.

Carlos Moreno and Sebastian Fischmeister presented a novel technique to combat this systematic error. The basic idea is to measure the execution time of an incremental sequential number of function executions. Starting to measure the time of one execution, then two executions and so on. The overall execution time can then be obtained by taking the slope a from the fitted line. The authors also note that this type of measurement is very robust against occasional measurements with large errors.

## Running unit tests

Several unit tests were written to validate some corner cases.
The unit tests were written in [unittest](https://docs.python.org/3/library/unittest.html).
Run the following commands to execute the unit tests.

```bash
python -m unittest
```

## Documentation

This library was documented using the google style docstring, it can be accessed [here](https://mariolpantunes.github.io/knee/).
Run the following commands to produce the documentation for this library.

```bash
pip install pdoc
pdoc --math -d google -o docs exectime \
--logo https://raw.githubusercontent.com/mariolpantunes/exectime/main/media/stopwatch.png \
--favicon https://raw.githubusercontent.com/mariolpantunes/exectime/main/media/stopwatch.png
```

## Instalation

The library can be used by adding this line to the requirement.txt file:
```txt
git+https://github.com/mariolpantunes/exectime@main#egg=exectime
```

## Usage


## References
<a id="1">[1]</a> 
C. Moreno and S. Fischmeister, "Accurate Measurement of Small Execution Times—Getting Around Measurement Errors," in IEEE Embedded Systems Letters, vol. 9, no. 1, pp. 17-20, March 2017, doi: [10.1109/LES.2017.2654160](https://doi.org/10.1109/LES.2017.2654160).

## Authors

* **Mário Antunes** - [mariolpantunes](https://github.com/mariolpantunes)

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

<a href="https://www.flaticon.com/free-icons/time" title="time icons">Time icons created by Freepik - Flaticon</a>

![Python CI](https://github.com/mariolpantunes/exectimeit/workflows/Python%20CI/badge.svg)

MIT License

Copyright (c) 2022 Mário Antunes

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