# Mappy-rs
[](https://github.com/Adoni5/mappy-rs/actions/workflows/CI.yml)
[](https://github.com/Adoni5/mappy-rs/actions/workflows/check.yml)
A multi-threaded minimap2 aligner for python. Built for [readfish](https://github.com/LooseLab/readfish/) compatibility.
Heavily leaning on and inspired by Joeseph Guhlin's minimap2-rs [repository](https://github.com/jguhlin/minimap2-rs). They also have a more heavily featured python client, which also provides multithreaded alignment. This client provides a more simple streaming interface for use in pipelines.
`pip install mappy-rs`
## Developers
Start with some Docs on Py03 - https://pyo3.rs/latest/
If you wish to contribute, have a look at [CONTRIBUTING.md](.github/CONTRIBUTING.md)
In order to build an importable module:
```bash
python -m venv .env
source -m .env/bin/activate
pip install ".[tests]"
```
To run the tests:
```bash
# Python
pytest
# Rust
cargo t --no-default-features
```
Then in your python shell of choice:
```python
import mappy_rs
aligner = mappy_rs.Aligner("resources/test/test.mmi")
```
The current iteration of `mappy-rs` serves as a drop in for `mappy`, implementing all the same methods. However if this is the use case, you may well be better off using `mappy`, as the extra level of Rust between your python and C++ may well add slightly slower performance.
### Multithreading
In order to use multi threading, one must first enable it.
```python
import mappy_rs
aligner = mappy_rs.Aligner("resources/test/test.mmi")
# Use 10 threads
aligner.enable_threading(10)
```
Enabling threading makes the `map_batch` method available.
This method requires a list or iterable of dictionaries, which can have any number of keys and depth, but **must** contain the key `seq` with a string value in the top-level dictionary.
Currently, the maximum batch size to be iterated in one call is 20000.
For example:
```python
import mappy_rs
aligner = mappy_rs.Aligner("resources/test/test.mmi")
aligner.enable_threading(10)
seqs = [
{"seq": "ACGTAGCATCGAGACTACGA", "Other_random_key": "banter"},
{"seq": "ACGTAGCATCGAGACTACGA", "Other_random_key": "banter"},
]
for (mapping, data) in aligner.map_batch(seqs):
print(list(mapping))
print(data)
```
### Benchmarks
A simple benchmark against classic mappy, and mappy_rs with incrementing numbers of threads, run on a 2018 Macbook.
#### __Device__
| Property | Value |
|------------------------------|----------------------------|
| Model Name | MacBook Pro |
| Model Identifier | MacBookPro15,2 |
| Processor Name | Quad-Core Intel Core i7 |
| Processor Speed | 2.7 GHz |
| Number of Processors | 1 |
| Total Number of Cores | 4 |
| L2 Cache (per Core) | 256 KB |
| L3 Cache | 8 MB |
| Hyper-Threading Technology | Enabled |
| Memory | 16 GB |
#### __Results__
Name (time in s) | Min | Max | Mean | StdDev | Median | IQR | Outliers | OPS | Rounds | Iterations
------------------------------|---------------|----------------|---------------|--------------|---------------|--------------|--------------|---------------|---------------|------------
test_benchmark_multi[5] | 26.8900 (1.0) | 30.0969 (1.0) | 28.0622 (1.0) | 1.2614 (1.0) | 27.9017 (1.0) | 1.6081 (1.35)| 1;0 | 0.0356 (1.0) | 5 | 1
test_benchmark_multi[4] | 28.5573 (1.06)| 43.4543 (1.44) | 32.3371 (1.15)| 6.2815 (4.98)| 29.7480 (1.07)| 5.2148 (4.37)| 1;1 | 0.0309 (0.87) | 5 | 1
test_benchmark_multi[3] | 31.6497 (1.18)| 36.9986 (1.23) | 33.5103 (1.19)| 2.0542 (1.63)| 32.8415 (1.18)| 1.9576 (1.64)| 1;0 | 0.0298 (0.84) | 5 | 1
test_benchmark_multi[2] | 43.2616 (1.61)| 86.3859 (2.87) | 53.8572 (1.92)| 18.3339 (14.53)| 45.9328 (1.65)| 14.6382 (12.26)| 1;1 | 0.0186 (0.52) | 5 | 1
test_classic_mappy[mappy_al] | 78.5566 (2.92)| 82.8876 (2.75) | 79.6177 (2.84)| 1.8343 (1.45)| 78.8350 (2.83)| 1.1938 (1.0) | 1;1 | 0.0126 (0.35) | 5 | 1
test_classic_mappy[mappy_al_rs]| 83.7239 (3.11)| 87.9675 (2.92) | 85.4424 (3.04)| 1.6806 (1.33)| 85.6335 (3.07)| 2.3310 (1.95)| 2;0 | 0.0117 (0.33) | 5 | 1
test_benchmark_multi[1] | 84.8418 (3.16)| 94.0907 (3.13) | 86.7404 (3.09)| 4.1096 (3.26)| 84.8749 (3.04)| 2.4310 (2.04)| 1;1 | 0.0115 (0.32) | 5 | 1
# Changelog
## 0.0.6
- Lowered backoff time for `map_batch` to 50 milliseconds, with 6 attempts. Each attempt will double the previous back off time.
- Improved error handling for `map_batch`, now will raise a `RuntimeError` if the backoff time is exceeded. Also prevented logging `Internal error returning data, the receiver iterator has finished. sending on a disconnected channel 2870` to stderr excessively.
- Added tests for mapping more than 50000 reads, using `back_off=True` and `back_off=False`
Raw data
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"description": "# Mappy-rs\n[](https://github.com/Adoni5/mappy-rs/actions/workflows/CI.yml)\n[](https://github.com/Adoni5/mappy-rs/actions/workflows/check.yml)\n\n\n\n\nA multi-threaded minimap2 aligner for python. Built for [readfish](https://github.com/LooseLab/readfish/) compatibility.\n\nHeavily leaning on and inspired by Joeseph Guhlin's minimap2-rs [repository](https://github.com/jguhlin/minimap2-rs). They also have a more heavily featured python client, which also provides multithreaded alignment. This client provides a more simple streaming interface for use in pipelines.\n\n`pip install mappy-rs`\n\n## Developers\nStart with some Docs on Py03 - https://pyo3.rs/latest/\n\nIf you wish to contribute, have a look at [CONTRIBUTING.md](.github/CONTRIBUTING.md)\n\nIn order to build an importable module:\n\n```bash\npython -m venv .env\nsource -m .env/bin/activate\npip install \".[tests]\"\n```\n\n\nTo run the tests:\n\n```bash\n#\u00a0Python\npytest\n\n# Rust\ncargo t --no-default-features\n```\n\nThen in your python shell of choice:\n\n```python\nimport mappy_rs\naligner = mappy_rs.Aligner(\"resources/test/test.mmi\")\n```\n\nThe current iteration of `mappy-rs` serves as a drop in for `mappy`, implementing all the same methods. However if this is the use case, you may well be better off using `mappy`, as the extra level of Rust between your python and C++ may well add slightly slower performance.\n\n### Multithreading\nIn order to use multi threading, one must first enable it.\n\n```python\nimport mappy_rs\naligner = mappy_rs.Aligner(\"resources/test/test.mmi\")\n# Use 10 threads\naligner.enable_threading(10)\n```\n\nEnabling threading makes the `map_batch` method available.\nThis method requires a list or iterable of dictionaries, which can have any number of keys and depth, but **must** contain the key `seq` with a string value in the top-level dictionary.\nCurrently, the maximum batch size to be iterated in one call is 20000.\n\nFor example:\n\n```python\nimport mappy_rs\naligner = mappy_rs.Aligner(\"resources/test/test.mmi\")\naligner.enable_threading(10)\nseqs = [\n {\"seq\": \"ACGTAGCATCGAGACTACGA\", \"Other_random_key\": \"banter\"},\n {\"seq\": \"ACGTAGCATCGAGACTACGA\", \"Other_random_key\": \"banter\"},\n]\nfor (mapping, data) in aligner.map_batch(seqs):\n print(list(mapping))\n print(data)\n```\n\n### Benchmarks\n\nA simple benchmark against classic mappy, and mappy_rs with incrementing numbers of threads, run on a 2018 Macbook.\n#### __Device__\n| Property | Value |\n|------------------------------|----------------------------|\n| Model Name | MacBook Pro |\n| Model Identifier | MacBookPro15,2 |\n| Processor Name | Quad-Core Intel Core i7 |\n| Processor Speed | 2.7 GHz |\n| Number of Processors | 1 |\n| Total Number of Cores | 4 |\n| L2 Cache (per Core) | 256 KB |\n| L3 Cache | 8 MB |\n| Hyper-Threading Technology | Enabled |\n| Memory | 16 GB |\n\n#### __Results__\nName (time in s) | Min | Max | Mean | StdDev | Median | IQR | Outliers | OPS | Rounds | Iterations\n------------------------------|---------------|----------------|---------------|--------------|---------------|--------------|--------------|---------------|---------------|------------\ntest_benchmark_multi[5] | 26.8900 (1.0) | 30.0969 (1.0) | 28.0622 (1.0) | 1.2614 (1.0) | 27.9017 (1.0) | 1.6081 (1.35)| 1;0 | 0.0356 (1.0) | 5 | 1\ntest_benchmark_multi[4] | 28.5573 (1.06)| 43.4543 (1.44) | 32.3371 (1.15)| 6.2815 (4.98)| 29.7480 (1.07)| 5.2148 (4.37)| 1;1 | 0.0309 (0.87) | 5 | 1\ntest_benchmark_multi[3] | 31.6497 (1.18)| 36.9986 (1.23) | 33.5103 (1.19)| 2.0542 (1.63)| 32.8415 (1.18)| 1.9576 (1.64)| 1;0 | 0.0298 (0.84) | 5 | 1\ntest_benchmark_multi[2] | 43.2616 (1.61)| 86.3859 (2.87) | 53.8572 (1.92)| 18.3339 (14.53)| 45.9328 (1.65)| 14.6382 (12.26)| 1;1 | 0.0186 (0.52) | 5 | 1\ntest_classic_mappy[mappy_al] | 78.5566 (2.92)| 82.8876 (2.75) | 79.6177 (2.84)| 1.8343 (1.45)| 78.8350 (2.83)| 1.1938 (1.0) | 1;1 | 0.0126 (0.35) | 5 | 1\ntest_classic_mappy[mappy_al_rs]| 83.7239 (3.11)| 87.9675 (2.92) | 85.4424 (3.04)| 1.6806 (1.33)| 85.6335 (3.07)| 2.3310 (1.95)| 2;0 | 0.0117 (0.33) | 5 | 1\ntest_benchmark_multi[1] | 84.8418 (3.16)| 94.0907 (3.13) | 86.7404 (3.09)| 4.1096 (3.26)| 84.8749 (3.04)| 2.4310 (2.04)| 1;1 | 0.0115 (0.32) | 5 | 1\n\n\n# Changelog\n\n## 0.0.6\n- Lowered backoff time for `map_batch` to 50 milliseconds, with 6 attempts. Each attempt will double the previous back off time.\n- Improved error handling for `map_batch`, now will raise a `RuntimeError` if the backoff time is exceeded. Also prevented logging `Internal error returning data, the receiver iterator has finished. sending on a disconnected channel 2870` to stderr excessively.\n- Added tests for mapping more than 50000 reads, using `back_off=True` and `back_off=False`\n\n",
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