slurpit_sdk
Python SDK for interfacing with Slurp'it, enabling easy data retrieval from your network with minimal code. On top of that we added Pandas support and an easy way to export to CSV.
Summary
| Latest Version | Unknown |
|---|---|
| License | Unknown |
| CI Status | Failing |
| Stars | 2 |
| Forks | 3 |
| Open Issues | 0 |
| Last Commit | 2026-07-31 |
| Downloads | 0 |
| Last Indexed | 2026-08-11 05:07 |
Tags
Installation
nimble install slurpit_sdk
choosenim install slurpit_sdk
git clone https://gitlab.com/slurpit.io/slurpit_sdk
OS Compatibility
| Platform | Linux | macOS | Windows | FreeBSD | OpenBSD | NetBSD | Android | iOS | WASM | Embedded |
|---|---|---|---|---|---|---|---|---|---|---|
| slurpit_sdk | ✓ | ✓ | ✓ | - | - | - | - | - | - | - |
Source
| Repository | https://gitlab.com/slurpit.io/slurpit_sdk |
|---|---|
| Homepage | https://gitlab.com/slurpit.io/slurpit_sdk |
| Registry Source | gitlab |
README
Slurpit SDK
The Slurpit SDK is a Python package for interacting with the Slurpit API, enabling developers to easily manage devices and planning resources. It is designed for simplicity and flexibility, offering methods for listing devices, retrieving planning data, and exporting information to CSV format.
Installation
Install the SDK:
pip install slurpit_sdk
To run the examples, install dependencies using Poetry (recommended):
poetry install
Alternatively, use pip:
pip install -r requirements.txt
To build from source:
cd src
python setup.py install
Quick Start
To quickly test the examples, copy .env.example to .env (includes default sandbox credentials):
# From the examples/ folder run:
cp .env.example .env
Working with Devices
Retrieve and print the hostnames of all devices:
devices = api.device.get_devices()
for device in devices:
print(device.hostname)
Exporting Data to CSV
To export planning data to a CSV file:
plannings_csvdata = api.planning.get_plannings(export_csv=True)
result = api.device.save_csv_bytes(plannings_csvdata, "csv/plannings.csv")
Exporting Data as Pandas DataFrame
To export planning data as a pandas dataframe
plannings_df = api.planning.get_plannings(export_df=True)
Pagination
Handle large sets of devices with pagination:
devices = api.device.get_devices(offset=100, limit=1000)
for device in devices:
print(device.hostname)