sparv 5.3.1

Språkbanken's analysis platform

Sparv – Språkbanken's Analysis Platform

Sparv 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 [e-mail].

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 3.10 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

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

Sparv 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. If you happen to clone the repository before installing Git Large File Storage you will have to run git lfs fetch in order to update the corpus and annotation files.

Install the dependencies, including the dev dependencies. We recommend that you first set up a virtual environment:

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 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).