This repo is a public collection of Fused User Defined Functions (UDFs).
Fused is the glue layer that interfaces data platforms and data tools via a managed serverless API. With Fused, you can write, share, or discover UDFs which are the building blocks of serverless geospatial operations. UDFs are Python functions that turn into live HTTP endpoints that load their output into any tools that can call an API.
The Fused Python SDK is available at PyPI. Use the standard Python installation tools. UDFs this repo expect the most recent version.
pip install fused
This snippet shows how to import a UDF from a Python environment and their modules from a public GitHub URL. The URL must be of a directory that contains a UDF generated with Fused. This example shows how to import a UDF.
import fused
common = fused.core.load_udf_from_github('https://github.com/fusedio/udfs/tree/main/public/common/')
import geopandas as gpd
gdf = gpd.read_file('https://www2.census.gov/geo/tiger/TIGER_RD18/STATE/11_DISTRICT_OF_COLUMBIA/11/tl_rd22_11_bg.zip')
gdf2 = common.utils.geo_buffer(gdf, 10)
print(gdf2)
This repository is structured to facilitate easy access of UDFs and their supporting files. Each UDF, like Sample_UDF
, is contained within its own subdirectory within the public
directory - along with its documentation, code, metadata, and utility function code.
Each UDF can be thought of as a standalone Python package.
├── README.md
└── public
└── Sample_UDF
├── README.MD
├── Sample_UDF.py
├── meta.json
└── utils.py
Files relevant to each UDF are:
README.md
Provides details of the UDF's purpose and how it works.Sample_UDF.py
This eponymous Python file contains the UDF's business logic as a Python function decorated with@fused.udf
.meta.json
This file contains metadata needed to render the UDF in the Fused explorer and for the UDF to run correctly.utils.py
This Python file contains helper functions the UDF (optionally) imports and references.
- Save UDF
import fused
@fused.udf
def my_udf(bbox=None):
import pandas as pd
return pd.DataFrame({'Hello': ['from Fused']})
# Run locally
print(fused.run(my_udf))
# Save locally
my_udf.to_directory('my_udf')
# or for zip file: my_udf.to_file('my_udf.zip')
# Save remotely to Fused
my_udf.to_fused('my_udf')
"Save locally" generates the UDF folder on your local system, which you'll use in the following step.
- Open a PR
Clone this repo to your local system and add the UDF folder under public
or community
. Create a PR on this repo.
Build any scale workflows with the Fused Python SDK and Workbench webapp, and integrate them into your stack with the Fused Hosted API.
Fused documentation is in docs.fused.io.
All UDF contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.