npysearch
npysearch implements an efficient BLAST-like sequence comparison algorithm, written in C++11 and using native Python datatypes and bindings. npysearch is light-weight, fast, and dependency-free. The code base of npysearch is adapted from nsearch.
Installation
from pypi
pip install npysearch
from conda-forge
Installing from the conda-forge channel can be achieved by adding conda-forge to your channes with:
conda config --add channels conda-forge
conda config --set channel_priority strict
You can skip the above step if conda-forge channel has been added already.
Once the conda-forge channel has been enabled, npysearch can be installed with:
conda install npysearch
from github
# Clone repository from github
git clone https://github.com/tamminenlab/npysearch.git
# Install package using pip
pip install ./npysearch
Examples
# Import npysearch package
import npysearch as npy
# Read query file into a dictionary
query = npy.read_fasta("npysearch/data/query.fasta")
# Read database file into a dictionary
database = npy.read_fasta("npysearch/data/db.fasta")
# BLAST the query against the database
results_dna = npy.blast(query, database)
# BLAST protein sequence file against itself using filenames as blast function arguments
results_prot = npy.blast(query = "npysearch/data/prot.fasta",
database = "npysearch/data/prot.fasta",
alphabet = "protein")
Caveats
- The
blastfunction automatically detects whether the query and database arguments were passed as string paths to fasta files or as dictionaries of sequences. Both of them need not be input as the same type. - Use
help(npy)(assuming you've imported npysearch as npy) to get a list of the functions included and their docstrings. For docstrings of specific functions, for example blast, usehelp(npy.blast)
Metadata
Release files for npysearch 1.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| npysearch-1.3.1.tar.gz | 38.0 kB | Without provenance | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| npysearch-1.3.1-cp310-cp310-win_amd64.whl | CPython 3.10 | CPython 3.10 | Windows x86-64 | Details |
| npysearch-1.3.1-cp310-cp310-manylinux_2_24_x86_64.whl | CPython 3.10 | CPython 3.10 | Linux glibc 2.24+ x86-64 | Details |
| npysearch-1.3.1-cp39-cp39-win_amd64.whl | CPython 3.9 | CPython 3.9 | Windows x86-64 | Details |
| npysearch-1.3.1-cp38-cp38-macosx_11_0_arm64.whl | CPython 3.8 | CPython 3.8 | macOS 11.0+ ARM64 | Details |
Total release size: 627.2 kB
Release files / npysearch-1.3.1.tar.gz
| Download URL | npysearch-1.3.1.tar.gz |
|---|---|
| Size | 38.0 kB |
| Tags | Source |
|
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.10
|
Release files / npysearch-1.3.1-cp310-cp310-win_amd64.whl
| Download URL | npysearch-1.3.1-cp310-cp310-win_amd64.whl |
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| Size | 137.4 kB |
| Tags | CPython 3.10 Windows x86-64 |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.10
|
Release files / npysearch-1.3.1-cp310-cp310-manylinux_2_24_x86_64.whl
| Download URL | npysearch-1.3.1-cp310-cp310-manylinux_2_24_x86_64.whl |
|---|---|
| Size | 153.1 kB |
| Tags | CPython 3.10 Linux glibc 2.24+ x86-64 |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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No |
| Uploaded via |
twine/4.0.1 CPython/3.9.10
|
Release files / npysearch-1.3.1-cp39-cp39-win_amd64.whl
| Download URL | npysearch-1.3.1-cp39-cp39-win_amd64.whl |
|---|---|
| Size | 137.4 kB |
| Tags | CPython 3.9 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.10
|
Release files / npysearch-1.3.1-cp38-cp38-macosx_11_0_arm64.whl
| Download URL | npysearch-1.3.1-cp38-cp38-macosx_11_0_arm64.whl |
|---|---|
| Size | 161.3 kB |
| Tags | CPython 3.8 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.10
|
Security for npysearch 1.3.1
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