# Dogma Data
**Dogma Data** is a Python package built for fast and efficient parsing of FASTA files, optimized for high-performance computing. It leverages multi-threading to fully utilize all available system threads, enabling parallel processing. Additionally, the package supports exporting parsed data to the HDF5 file format for easy storage and access.
## Installation
To install Dogma Data, you can use **pip**:
```bash
pip install dogma-data
```
## Usage
```python
import dogma_data
vocab = {
'a': 0,
'g': 1,
'c': 2,
't': 3,
...
}
mapping = dogma_data.FastaMapping(vocab, vocab['a'])
(tokens, sequences, (taxons)) = dogma_data.parse_fasta('input_path.fa', dogma_data.HeaderType.TaxonId, mapping)
header_info = {"taxons": taxons}
dogma_data.export_hdf5(
'output_path.h5',
dogma_data.Splitter(
train_prop=0.95,
val_prop=0.025,
test_prop=0.025,
length=len(sequences) - 1,
),
tokens,
sequences,
header_info,
mapping
)
```
## Requirements
- Python 3.10
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Contact
For any questions, feel free to reach out:
- **Marcel Rød** - roed@stanford.edu
- **Miha Krajnc** - miha.krajnc@cs.stanford.edu
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"description": "# Dogma Data\n\n**Dogma Data** is a Python package built for fast and efficient parsing of FASTA files, optimized for high-performance computing. It leverages multi-threading to fully utilize all available system threads, enabling parallel processing. Additionally, the package supports exporting parsed data to the HDF5 file format for easy storage and access.\n\n## Installation\n\nTo install Dogma Data, you can use **pip**:\n\n```bash\npip install dogma-data\n```\n\n## Usage\n```python\nimport dogma_data\n\nvocab = {\n 'a': 0,\n 'g': 1,\n 'c': 2,\n 't': 3,\n ...\n}\n\nmapping = dogma_data.FastaMapping(vocab, vocab['a'])\n(tokens, sequences, (taxons)) = dogma_data.parse_fasta('input_path.fa', dogma_data.HeaderType.TaxonId, mapping)\n\nheader_info = {\"taxons\": taxons}\n\ndogma_data.export_hdf5(\n 'output_path.h5',\n dogma_data.Splitter(\n train_prop=0.95,\n val_prop=0.025,\n test_prop=0.025,\n length=len(sequences) - 1,\n ),\n tokens,\n sequences,\n header_info,\n mapping\n)\n```\n\n## Requirements\n- Python 3.10\n \n## License\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Contact\nFor any questions, feel free to reach out:\n- **Marcel R\u00f8d** - roed@stanford.edu\n- **Miha Krajnc** - miha.krajnc@cs.stanford.edu\n",
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