Highlighter Documentation

Getting Started

How to get started with the Highlighter Python SDK

This guide will help you install and configure the Highlighter Python SDK

Steps

Install the Highlighter SDK

Linux|Mac

python -m venv venv
source venv/bin/activate
pip install -U pip
pip install highlighter-sdk

Windows

python -m venv venv
venv\Scripts\activate.bat
venv\Scripts\python.exe -m pip install -U pip
venv\Scripts\python.exe -m pip install highlighter-sdk

NixOS

nix-shell
# Then follow the normal Linux setup

Setup Highlighter API Credentials

See Highlighter API Credentials

Using the CLI

Use hl --help to list the individual commands. Use hl COMMAND --help for help on specific commands. Some commands are nested so, hl COMMAND SUB_COMMAND --help may be required.

The CLI supports headless management of many system resources, allowing you to list and delete entities like Cases, Experiments, and Workflows directly from the terminal. See CLI Resource Management for details.

Below is how to download an data-file using the cli.

Note: on Windows replace / with \

# Replace 12345 with a DataFile ID from your Highlighter account
# -o will save the resulting DataFile to your cwd
hl data-file read -i 12345 -o .

Network Discovery and Data Sources

The Highlighter SDK includes powerful tools for discovering devices on your network and managing data sources:

  • Network Discovery: Use hl datasource discover to find cameras and devices via mDNS/Bonjour

    • Discover all cameras on your network: hl datasource discover list
    • Find a camera by MAC address: hl datasource discover find --mac XX:XX:XX:XX:XX:XX
    • Batch lookup multiple devices: hl datasource discover batch --file macs.txt

  • Data Source Management: Use hl datasource to create, update, and manage data sources in Highlighter Cloud

    • List data sources: hl datasource list
    • Create a data source: hl datasource create --name "Camera-1" --source-uri "rtsp://..."
    • Import/export data sources: hl datasource import --file cameras.json --create-missing

For detailed information, see:

Using the Python API

See Download And Write Datasets

What's next

See Scaffolding new Highlighter agents