Getting Started
===============

This guide walks through a complete GeoSmith workflow using synthetic data. The focus stays on structure and intent, not file formats.

We begin with a simple set of points and polygons represented in pandas.

.. code-block:: python

   import pandas as pd
   import numpy as np

   points = pd.DataFrame(
       {
           "x": np.random.uniform(0, 100, size=50),
           "y": np.random.uniform(0, 100, size=50),
           "value": np.random.normal(10, 2, size=50),
       }
   )

   polygons = pd.DataFrame(
       {
           "xmin": [0, 50],
           "ymin": [0, 50],
           "xmax": [50, 100],
           "ymax": [50, 100],
           "region": ["A", "B"],
       }
   )

GeoSmith tasks convert these inputs into spatial objects at the boundary.

.. code-block:: python

   from geosmith.workflows import make_features

   features = make_features(
       points=points,
       polygons=polygons,
       operation="point_in_polygon"
   )

The result is a table of spatial features aligned to the original points.

.. code-block:: python

   print(features.head())

This is the GeoSmith loop. Objects represent space. Primitives compute geometry. Tasks express intent. Workflows handle I O and integration.