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## Benchmarks
Below is a comparison between the default Python MIME parser and
`flanker.mime` in Time, Memory, and Function calls as well as other
benchmarks relating to Flanker performance.
### Test Specification:
* 2x Intel Core i7-3520M CPU @ 2.90GHz
* 2 GB RAM
* Results were averaged over 50 runs
#### Time
Full Message:
| File Size | `email.parser` (seconds) | `flanker.mime` (seconds) | Speedup |
| --------- | ------------------------ | ------------------------ | ------- |
| 11 MB | 0.601 | 0.073 | 8x |
| 1.8 MB | 0.113 | 0.011 | 10x |
| 16 KB | 0.001 | 0.003 | 0.33x |
Headers Only:
| File Size | `email.parser` (seconds) | `flanker.mime` (seconds) | Speedup |
| --------- | ------------------------ | ------------------------ | ------- |
| 11 MB | 0.601 | 0.029 | 20x |
| 1.8 MB | 0.113 | 0.009 | 12x |
| 16 KB | 0.001 | 0.002 | 0.5x |
#### Peak Memory Usage (including interpreter)
Full Message:
| File Size | `email.parser` (MB) | `flanker.mime` (MB) | Memory Difference |
| --------- | ------------------- | ------------------- | ----------------- |
| 11 MB | 59.51 | 46.27 | 0.77x |
| 1.8 MB | 30.55 | 28.52 | 0.93x |
| 16 KB | 28.45 | 28.51 | 0x |
Headers Only:
| File Size | `email.parser` (MB) | `flanker.mime` (MB) | Memory Difference |
| --------- | ------------------- | ------------------- | ----------------- |
| 11 MB | 59.51 | 28.07 | 0.47x |
| 1.8 MB | 30.55 | 28.52 | 0.93x |
| 16 KB | 28.45 | 28.52 | 0x |
#### Function Calls
Full Message:
| File Size | `email.parser` (#) | `flanker.mime` (#) | Speedup |
| --------- | ------------------ | ------------------ | ------- |
| 11 MB | 914,741 | 2,011 | 454x |
| 1.8 MB | 195,062 | 11,046 | 17x |
| 16 KB | 3,216 | 3,5842 | -1.1x |
Headers Only:
| File Size | `email.parser` (#) | `flanker.mime` (#) | Speedup |
| --------- | ------------------ | ------------------ | ------- |
| 11 MB | 914,741 | 1,253 | 730x |
| 1.8 MB | 195,062 | 9,741 | 20x |
| 16 KB | 3,216 | 2,476 | 1.2x |
#### Pinned Regex
Even though `master` does not use a pinned version of regex, we strongly recommend
due to the 6x speedup compared to the latest version on PyPi (as of 4/15/14). It may
not be an issue for someone that handles many small files, but is an issue for large
files.
| File Size | `regex.1.20110315` (seconds) | `regex 2014.04.10` (seconds) | Speedup |
| --------- | ---------------------------- | ---------------------------- | ------- |
| [11 MB](https://github.com/mailgun/flanker/blob/master/tests/fixtures/messages/big.eml) | 0.0720 | 0.4652 | 6x |
|
