A data analysis and visualization software
Project description
PyNanoLab is an all-in-one GUI software for Nanopore data analysis and visualization, expecially for nanopore analysis.
You can get tutorials from the PyNanoLab website.
Installition
In the version 3.X, binary installer (*.exe) is not provided anymore owing to the complex workflow and lost feature and performance.
We recommend you use the pip install to obtain all the advanced features.
System Required
Firstly, you should have already installed the python or conda virtual environment in your system.
Miniconda is recommended. And you should add the conda to your system environment variable.
In windows, you also need to install a terminal. git-windows or windows-terminal is recommended.
1. Create a new python virtual environment
PyNanoLab depend on th PySide6 to create its GUI. And it's not compatible with the other PyQt package. So we highly recommend to install pynanolab to a new python virtual environment.
use following command in a terminal:
conda create -n pnl python=3.11.8 #
source activate
conda activate pnl # activate the pnl environment.
conda install numpy # optional, install the numpy-MKL to speed up the software.
Then, you should install Pytorch on this environment (Any version, you should select a version, GPU verison is more better).
For example:
# CPU 版本
pip install torch torchvision torchaudio
# 或者自行安装GPU版本
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
! warning: at windows, you should install hdbscan by manually compiling. For example using conda
conda install hdbscan -c conda-forge
If using pip, you should have c/c++ compiler on your system.
Now, you have created a new python virtual environment and activated it. The name is pnl, and you can change the name to anything you want, and the python version is specified to >=3.11. (We recommend >=3.13.x)
2. Install the pynanolab by pip
Then, you can directly install as general python packages.
# online install
pip install pynanolab
Use the above command, the pynanolab will be installed automaticly. And a entry fille will be created in the Scripts folder of the "pnl" virtual environment. In windows is named "pynanolab.exe" and "pynanolab" in Linux and MacOSX.
Then, you can directily conduct the following command to open it in a terminal with pnl virtual environment activated.
pynanolab
If you want to create a shortcut or a desktop entry. Use the following command:
pnl-shortcut
3. Upgrade pynanolab
If you use the pip installtion. You can upgrade the packages manually using the following command:
pip install --upgrade pynanolab
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pynanolab-3.1.0-cp313-cp313-win_amd64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp313-cp313-win_amd64.whl
- Upload date:
- Size: 63.8 MB
- Tags: CPython 3.13, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
985de25b6daaec753934918101eaac707868a6b78a840603ef1ec3b5bfa95a81
|
|
| MD5 |
a12fb28c7ff1608320188837bf1ebc50
|
|
| BLAKE2b-256 |
a52dd7ca6c4938e69e2a5c25e72aa95e6e3aacbf942330689d8833fe4b656865
|
File details
Details for the file pynanolab-3.1.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
- Upload date:
- Size: 66.7 MB
- Tags: CPython 3.13, manylinux: glibc 2.17+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
24647d81896bbdcf845bf78655f5596deffb40dbdfebc0a28acdc95259e3bab0
|
|
| MD5 |
477e5207ab3e031f4e76a980c27bf59c
|
|
| BLAKE2b-256 |
e26fafd0a7b2651aa801e30041121b356f3db56a8994a2495bd98596e798e18f
|
File details
Details for the file pynanolab-3.1.0-cp313-cp313-macosx_11_0_arm64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp313-cp313-macosx_11_0_arm64.whl
- Upload date:
- Size: 64.5 MB
- Tags: CPython 3.13, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8f71500a3f09aae3236b740ae86553a8c70cbfe2bd3b426adbb4793dca76adc0
|
|
| MD5 |
ea7961482116d3ae740eddf27c5dc73b
|
|
| BLAKE2b-256 |
c480e5497322043b7d916c93929d191b2da1ba77ec0772f70001d0ded8617bd1
|
File details
Details for the file pynanolab-3.1.0-cp313-cp313-macosx_10_13_x86_64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp313-cp313-macosx_10_13_x86_64.whl
- Upload date:
- Size: 65.3 MB
- Tags: CPython 3.13, macOS 10.13+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
efa4361065c118b84db6ceb1d959ef684365f482a3febe579f54fcd7a72be6e3
|
|
| MD5 |
ce5911f2542bed855298845b398adb2f
|
|
| BLAKE2b-256 |
5126210685904f3b9da7ff872756bf3232e623a5a7960385f34385d6f5533ca3
|
File details
Details for the file pynanolab-3.1.0-cp312-cp312-win_amd64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp312-cp312-win_amd64.whl
- Upload date:
- Size: 64.0 MB
- Tags: CPython 3.12, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9cf01abbde694f775ae7b763bca42152df8b88a21efb33ba1c8c733f4cb8e210
|
|
| MD5 |
e1f0fae9dfe9019c871b446e3f05d8b0
|
|
| BLAKE2b-256 |
fed813ab1004aa8eb6329858d642311776eedede7ddba5ab85faea0ca75af0ea
|
File details
Details for the file pynanolab-3.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
- Upload date:
- Size: 67.0 MB
- Tags: CPython 3.12, manylinux: glibc 2.17+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d160e7a2876ac67b0a242ff39ea50bd50eb1d66e9465880927593dbcb150e1ba
|
|
| MD5 |
313fe57f3f749f2ded3b06cf1cb0b3ea
|
|
| BLAKE2b-256 |
8ca4d53a9088005ad2427b1bd91f03797782bc8cf64d0ab8c539123eceaaf707
|
File details
Details for the file pynanolab-3.1.0-cp312-cp312-macosx_11_0_arm64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp312-cp312-macosx_11_0_arm64.whl
- Upload date:
- Size: 64.7 MB
- Tags: CPython 3.12, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
875235220715cbcb9f191b7ccdcdf3b3424a5116c38dcf2ffe1e0c9f1f39e606
|
|
| MD5 |
f76fbef53605787b71bced9fbf4f328c
|
|
| BLAKE2b-256 |
03d8dc9647272f9a2a923fa0a41f5e228518c895ca00a16b662d945fa651142b
|
File details
Details for the file pynanolab-3.1.0-cp312-cp312-macosx_10_13_x86_64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp312-cp312-macosx_10_13_x86_64.whl
- Upload date:
- Size: 65.5 MB
- Tags: CPython 3.12, macOS 10.13+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8118b737cc87bc543dcf6bd6cc3efc54320f21b180de648f208359e8c87487e4
|
|
| MD5 |
46a553f245c5bdbb056aecdaec941e20
|
|
| BLAKE2b-256 |
15ccd78c8fe64db126fd458b373a9ec14e26ae4d641e31f09320a335818a1bfc
|
File details
Details for the file pynanolab-3.1.0-cp311-cp311-win_amd64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp311-cp311-win_amd64.whl
- Upload date:
- Size: 64.3 MB
- Tags: CPython 3.11, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
24f083bc9fd565002003cd8f95d95f4f2f6288580e6dc32303432d543a02e068
|
|
| MD5 |
f65d205afa3e7616d969840ea4530129
|
|
| BLAKE2b-256 |
e48dc816354c4d0cd0581fec88bd2dafb52839cd13a4bec8721c77d758322f72
|
File details
Details for the file pynanolab-3.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
- Upload date:
- Size: 67.8 MB
- Tags: CPython 3.11, manylinux: glibc 2.17+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5c1024af8df83f62e9a16fe082824e92884db7b316cf62273c1ecc9ad688c6e2
|
|
| MD5 |
e8c7cc9f3c2fecc0bf097fe9d67305e7
|
|
| BLAKE2b-256 |
cc4dd6659b9f4d7c366ee271e7b3ff89372c2552c7d1b93e49528624dae82ec5
|
File details
Details for the file pynanolab-3.1.0-cp311-cp311-macosx_11_0_arm64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp311-cp311-macosx_11_0_arm64.whl
- Upload date:
- Size: 66.1 MB
- Tags: CPython 3.11, macOS 11.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f9adeb1ac6fa64704741bc0deebc1afb210137bd503d52a4736f98d386f6deea
|
|
| MD5 |
a2f6480a41891908fe6f1db197f41675
|
|
| BLAKE2b-256 |
d984b2c72ddc2a1102fb26f1014879a34f808fcabe68cd45828593a56522d9c1
|
File details
Details for the file pynanolab-3.1.0-cp311-cp311-macosx_10_9_x86_64.whl.
File metadata
- Download URL: pynanolab-3.1.0-cp311-cp311-macosx_10_9_x86_64.whl
- Upload date:
- Size: 67.1 MB
- Tags: CPython 3.11, macOS 10.9+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
11fe7ca962d6992ff8b443b38bc0d0ab82f7846cf72d53966f85c71fe2903ae0
|
|
| MD5 |
4dd5597ced0713c54a9293c58ec2a8b2
|
|
| BLAKE2b-256 |
e1cc406d67fb90daf65d36bdad524be850fe525934932431ec9f06e13a2a8bf6
|