All Projects → spraakbanken → sparv-pipeline

spraakbanken / sparv-pipeline

Licence: MIT license
Språkbanken's text analysis tool

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Språkbanken's Sparv Pipeline

The Sparv Pipeline is a text analysis tool run from the command line. The documentation can be found here: https://spraakbanken.gu.se/sparv.

Check the changelog to see what's new!

Sparv is developed by Språkbanken. The source code is available under the MIT license.

If you have any questions, problems or suggestions please contact [email protected].

Prerequisites

  • A Unix-like environment (e.g. Linux, OS X or Windows Subsystem for Linux) Note: Most of Sparv's features should work in a Windows environment as well, but since we don't do any testing on Windows we cannot guarantee anything.
  • Python 3.6.1 or newer

Installation

Sparv is available on PyPI and can be installed using pip or pipx. We recommend using pipx, which will install Sparv in an isolated environment while still making it available to be run from anywhere.

python3 -m pip install --user pipx
python3 -m pipx ensurepath
pipx install sparv-pipeline

Now you should be ready to run the Sparv command! Try it by typing sparv --help.

The Sparv Pipeline can be used together with several plugins and third-party software. Please check the Sparv user manual for more details!

Running tests

If you want to run the tests you will need to clone this project from GitHub since the test data is not distributed with pip.

Before cloning the repository with git make sure you have Git Large File Storage installed (apt install git-lfs). Some files will not be downloaded correctly otherwise.

We recommend that you set up a virtual environment and install the dependencies (including the dev dependencies) listed in setup.py:

python3 -m venv venv
source venv/bin/activate
pip install -e .[dev]

Now with the virtual environment activated you can run pytest from the sparv-pipeline directory. You can run particular tests using the provided markers (e.g. pytest -m swe to run the Swedish tests only) or via substring matching (e.g. pytest -k "not slow" to skip the slow tests).

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].