Scripting

Why doing it?

There are several reasons to learn and use scripts for your research:

1. Apply your work in several contexts, by automatizing a task
2. Make your work reproducible
3. Customize SPPAS solutions

Among the very long list of programming languages, Python is one of the most popular in the world, with strong peer support and helpful documentation. Python offers a wide range of libraries that can be used across various applications, including machine learning, statistics, data analysis, etc.

Python's simple syntax, combined with its large set of libraries, is helping us to do more with fewer efforts.

https://www.python.org

Scripting with Python

It is assumed that a version of Python is installed and configured. It is also assumed that the Python IDLE is ready-to-use. For more details about Python.

Scripting with SPPAS

Adding "sppas" to the Python path

SPPAS implementation is available into the "sppas" directory of the package. For any script using it, we've to tell Python where to find it! This can be done with the following lines:

     import os
     import sys
     # If there's a SPPAS environment variable
     SPPAS = os.getenv("SPPAS")
     if SPPAS is None:
         SPPAS = "path/to/your/SPPAS-package"
     sys.path.append(SPPAS)
     import sppas
     

Scripting for beginners

import sppas.src.anndata

API documentation

• Developer Documentation
• Code Style Guide
• Code Architecture
• Releases and Changelog

SPPAS configuration, and install of its dependencies

import sppas.config

import sppas.preinstall

Data management: annotated data, images and videos

import sppas.src.anndata

import sppas.src.imgdata

import sppas.src.videodata

Data structures and utilities

import sppas.src.structs

import sppas.src.utils

Data files and linguistic resources

import sppas.src.wkps

import sppas.src.resources

Annotations & analysis

import sppas.src.analysis

import sppas.src.annotations

Licenses and Credits

SPPAS is distributed under the GNU Affero General Public License v3 or later.

Source code: SourceForge (full code and history) · GitHub mirror (last release only)

Related components

• AudiooPy – AGPL v3 – (homepage · source)
• ClammingPy – AGPL v3 – (homepage · source)
• WhakerPy – AGPL v3 – (homepage · source)
• Whakerexa – AGPL v3 – (homepage · source)
• WhakerKit – AGPL v3 – (homepage · source)