LOGS is a scientific data management system (SDMS) software allowing for automated data collection, visualization, and organization. Within its internal organizational concepts, it allows you to enrich your experimental data with metadata. LOGS allows you to adapt many of its organization structures, which enables your data management to follow your internal workflows.

LOGS-Py is a Python package interacting with the LOGS web API to enable you to extract and push data to LOGS and generally to interact with the LOGS backend in a programmatic way. The main motivation behind the design of the library is to keep this interaction as pythonic as possible. The communication with the API remains mainly in the background, while the user of the library handles native Python objects. Thereby, the user is still able to interact with nearly all LOGS functionalities and entities.

Thus, this library firstly targets lab and data scientist, allowing them to freely interact with experimental data and its metadata without any pre-knowledge of Web technologies and communication. Secondly, it facilitates power-users to implement highly specific workflow automations and 3rd-party software integrations with LOGS and other lab software.


The LOGS-Py package can be easily installed using pip.

For this, open the terminal and do:

pip install logs-py


Please find below the overview of LOGS-Py documentation.

Main Classes

Helper Classes

Indices and tables