The command line interface for GPAS
Project description
GPAS CLI
The command line and Python API client for the GPAS mycobacterial platform. Enables secure sample upload with client-side human read removal and retrieval of analytical outputs.
Install
Installing Miniconda
If a conda package manager is already installed, skip to Installing the GPAS CLI, otherwise:
Linux
- In a terminal console, install Miniconda, following instructions and accepting default options:
curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh bash Miniconda3-latest-Linux-x86_64.sh
MacOS
The GPAS CLI requires an x86_64
conda installation. If your Mac has an Apple processor, you must disable or delete any existing arm64
conda installations before continuing.
- If your Mac has an Apple processor, using Terminal, firstly run:
arch -x86_64 zsh
- Install Miniconda using Terminal, following instructions and accepting default options:
curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh bash Miniconda3-latest-MacOSX-x86_64.sh
Installing or updating the GPAS CLI
-
If using a Mac with an Apple processor, using Terminal, firstly run:
arch -x86_64 zsh
-
Perform the installation/upgrade:
conda create --yes -n gpas -c conda-forge -c bioconda hostile conda activate gpas pip install gpas
-
Test:
gpas --version
Usage
Ensure that the conda environment is active:
conda activate gpas
Help
Run gpas --help
for an overview of CLI subcommands. For help with a specific subcommand, use e.g. gpas auth --help
Authentication (gpas auth
)
The first time you use the CLI, you will need to authenticate by running gpas auth
and entering your username and password. This token will be used automatically for subsequent commands.
gpas auth
Enter your username: bede.constantinides@ndm.ox.ac.uk
Enter your password: ***************
Uploading samples (gpas upload
)
Performs metadata validation and client-side removal of human reads in each of your samples before uploading sequences to the GPAS platform.
gpas upload tests/data/illumina.csv
This generates a mapping CSV (e.g. a5w2e8.mapping.csv
) linking your local sample names with their randomly generated remote identifiers (GUIDs). Keep this file safe as it's useful for linking results later.
Downloading output files (gpas download
)
Download output files associated with an uploaded batch of samples, given a mapping CSV generated during upload, or one or more comma-separated sample GUIDs. When a mapping CSV is used, files are prefixed with the sample names provided at upload, otherwise files are prefixed with the sample GUID.
# Download the main report for sample 3bf7d6f9-c883-4273-adc0-93bb96a499f6
gpas download 3bf7d6f9-c883-4273-adc0-93bb96a499f6
# Download the main reports for all samples in a5w2e8.mapping.csv
gpas download a5w2e8.mapping.csv
# Download the main and speciation reports for samples in a5w2e8.mapping.csv
gpas download a5w2e8.mapping.csv --filenames main_report.json,speciation_report.json
# Save downloaded files to a specific directory
gpas download a5w2e8.mapping.csv --out-dir results
Support
For technical support, please open an issue or contact support@gpas.global
Development
Development install
git clone https://github.com/GlobalPathogenAnalysisService/cli.git
cd cli
conda env create -f environment-dev.yml
pip install --editable .
Updating
git pull origin main
gpas --version
Using a local development server
export GPAS_HOST="localhost:8000"
export GPAS_PROTOCOL="http"
To unset:
unset GPAS_HOST
unset GPAS_PROTOCOL
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file gpas-0.15.0.tar.gz
.
File metadata
- Download URL: gpas-0.15.0.tar.gz
- Upload date:
- Size: 17.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.31.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b3bcd3cb5e522b037aeb8fb5072ec79b063a672853eef8e0437b25ff767cba06 |
|
MD5 | 6b47404cc40a1c0703d4766f5aa5bab7 |
|
BLAKE2b-256 | 9c9c69aa2df7d9a28f40b2afc5a2498a89a44f37a354837d069ec6f0a263cc2a |
File details
Details for the file gpas-0.15.0-py3-none-any.whl
.
File metadata
- Download URL: gpas-0.15.0-py3-none-any.whl
- Upload date:
- Size: 14.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.31.0
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 98e365a426d9f16d966229127a141482eac7d023db81516afd1b10201b85178b |
|
MD5 | f4bedebb6845b8be63b0d016ba26fb87 |
|
BLAKE2b-256 | 6147babc48cfbaeaa80a2e75b7a3f0b963dfdac88278e85689b59d595c7f5826 |