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Easily pick a place to store data for your python package.

Project description

PyStow

Build status PyPI - Python Version License Documentation Status DOI

👜 Easily pick a place to store data for your python code.

🚀 Getting Started

Get a directory for your application.

import pystow

# Get a directory (as a pathlib.Path) for ~/.data/pykeen
pykeen_directory = pystow.join('pykeen')

# Get a subdirectory (as a pathlib.Path) for ~/.data/pykeen/experiments
pykeen_experiments_directory = pystow.join('pykeen', 'experiments')

# You can go as deep as you want
pykeen_deep_directory = pystow.join('pykeen', 'experiments', 'a', 'b', 'c')

Get a file path for your application by adding the name keyword argument. This is made explicit so PyStow knows which parent directories to automatically create.

import pystow

# Get a directory (as a pathlib.Path) for ~/.data/indra/database.tsv
indra_database_path = pystow.join('indra', 'database', name='database.tsv')

Ensure a file from the internet is available in your application's directory:

import pystow

url = 'https://raw.githubusercontent.com/pykeen/pykeen/master/src/pykeen/datasets/nations/test.txt'
path = pystow.ensure('pykeen', 'datasets', 'nations', url=url)

Ensure a tabular data file from the internet and load it for usage (requires pip install pandas):

import pystow
import pandas as pd

url = 'https://raw.githubusercontent.com/pykeen/pykeen/master/src/pykeen/datasets/nations/test.txt'
df: pd.DataFrame = pystow.ensure_csv('pykeen', 'datasets', 'nations', url=url)

Ensure a RDF file from the internet and load it for usage (requires pip install rdflib)

import pystow
import rdflib

url = 'https://ftp.expasy.org/databases/rhea/rdf/rhea.rdf.gz'
rdf_graph: rdflib.Graph = pystow.ensure_rdf('rhea', url=url)

Also see pystow.ensure_excel(), pystow.ensure_rdf(), pystow.ensure_zip_df(), and pystow.ensure_tar_df().

⚙️️ Configuration

By default, data is stored in the $HOME/.data directory. By default, the <app> app will create the $HOME/.data/<app> folder.

If you want to use an alternate folder name to .data inside the home directory, you can set the PYSTOW_NAME environment variable. For example, if you set PYSTOW_NAME=mydata, then the following code for the pykeen app will create the $HOME/mydata/pykeen/ directory:

import os
import pystow

# Only for demonstration purposes. You should set environment
# variables either with your .bashrc or in the command line REPL.
os.environ['PYSTOW_NAME'] = 'mydata'

# Get a directory (as a pathlib.Path) for ~/mydata/pykeen
pykeen_directory = pystow.join('pykeen')

If you want to specify a completely custom directory that isn't relative to your home directory, you can set the PYSTOW_HOME environment variable. For example, if you set PYSTOW_HOME=/usr/local/, then the following code for the pykeen app will create the /usr/local/pykeen/ directory:

import os
import pystow

# Only for demonstration purposes. You should set environment
# variables either with your .bashrc or in the command line REPL.
os.environ['PYSTOW_HOME'] = '/usr/local/'

# Get a directory (as a pathlib.Path) for /usr/local/pykeen
pykeen_directory = pystow.join('pykeen')

Note: if you set PYSTOW_HOME, then PYSTOW_NAME is disregarded.

🚀 Installation

The most recent release can be installed from PyPI with:

$ pip install pystow

The most recent code and data can be installed directly from GitHub with:

$ pip install git+https://github.com/cthoyt/pystow.git

To install in development mode, use the following:

$ git clone git+https://github.com/cthoyt/pystow.git
$ cd pystow
$ pip install -e .

⚖️ License

The code in this package is licensed under the MIT License.

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