Version: 1.0.0 | Published: 24 Jan 2026 | Updated: 110 days ago
Guide: How to access SENSE with Python
Dataset
Summary
Description:
A guide to help you access SENSE from your own computer/pipeline using python.
Difficulty level: **low-medium**
### Requires an understanding of:
- Docker
- Python
- Notebooks
### In this tutorial you will learn how to:
1. Set up your credentials
2.
Identifier:
42842565-f4f4-41b5-8315-0f648b3e7f1e
Access Tier:
Open
Contact Point:
Documentation
Documentation:
A guide to help you access SENSE from your own computer/pipeline using python.
Difficulty level: **low-medium**
### Requires an understanding of:
- Docker
- Python
- Notebooks
### In this tutorial you will learn how to:
1. Set up your credentials
2. Connect to the SENSE data catalog using PyIceberg
3. Explore an organisation and tables
4. Review the schema of a queryable table
5. Load queryable table data into Pandas DataFrames
6. Review the schema of a raw table
7. Load raw table data and then turn it into a file
### Requirements:
- A Sense account
- [**Docker**](https://docs.docker.com/get-docker/)
- [**Docker Compose**](https://docs.docker.com/compose/install/)
- A way to unzip the zip file
### Steps to follow:
1. Download the "sense_python.zip"
2. Unzip the file
3. Follow the README to get the docker compose started and onto the JupyterLab
4. Get you client credentials from the **Client Credentials** section in the **Profile** tab to the left
5. Follow the steps in the JupyterLab
Coverage
Temporal
Date of First Release:
24 January 2026
Provenance
Origin
Collection Situation:
Method of Collection:
Guide
Author 1
Name Organisation:
Author 2
Name Organisation:
SENSE
Access and Governance
Access
Access Rights:
Review link
Data Controller:
SENSE + West of England Mayoral Combined Authority
Data Processor:
Review link
Licence:
OGL v.3
Format and Standards
Language:
en
Format:
- queryable
- svg
- zip
Data Distribution
Data Status:
deprecated