Developer SDK
pyoso
Access OSO data and analytics directly from Python. The fastest way to integrate OSO data into your existing workflows.
from pyoso import Client client = Client(api_key="your-api-key") df = client.to_pandas(""" SELECT project_name, star_count FROM projects_v1 ORDER BY star_count DESC LIMIT 100 """) print(df.head())
Simple installation
Install pyoso with a single pip command and start querying OSO data in minutes.
terminal
$ pip install pyoso
Collecting pyoso...
Downloading pyoso-1.2.0.tar.gz
Installing collected packages...
Successfully installed pyoso-1.2.0 ✓
Pandas-native
Get results as Pandas DataFrames for seamless integration with your existing Python data workflows.
df.head()
| project_name | stars | contributors | score |
|---|---|---|---|
| ethereum/go-ethereum | 46.2k | 892 | 98.4 |
| rust-lang/rust | 89.1k | 3810 | 97.1 |
| facebook/react | 218k | 1640 | 96.8 |
| vuejs/vue | 206k | 370 | 94.2 |
Full API access
Access the entire OSO platform directly from Python. Programmatically control any aspect of your account.
# Available mart models
›projects_v1
›users_v1
›repos_v1
›events_v1
›metrics_v1
›artifacts_v1
›collections_v1
›funders_v1
Marimo / Jupyter compatible
Works natively in Jupyter and Marimo notebooks for interactive data exploration. Works in runtime environments from CPython to Pyodide.
In [2]:
df.describe()
Out [2]:
| stat | stars |
|---|---|
| count | 4.00 |
| mean | 87,575 |
| std | 75,432 |
| min | 46,200 |
| max | 218,000 |