python-gis-ecosystem-31-export-vector-to-file
Sub-skill of python-gis-ecosystem: 3.1 Export Vector to File (+1).
Best use case
python-gis-ecosystem-31-export-vector-to-file is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of python-gis-ecosystem: 3.1 Export Vector to File (+1).
Teams using python-gis-ecosystem-31-export-vector-to-file should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/31-export-vector-to-file/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How python-gis-ecosystem-31-export-vector-to-file Compares
| Feature / Agent | python-gis-ecosystem-31-export-vector-to-file | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of python-gis-ecosystem: 3.1 Export Vector to File (+1).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 3.1 Export Vector to File (+1)
## 3.1 Export Vector to File
```python
# GeoPackage (preferred)
gdf_utm.to_file("wells_utm.gpkg", driver="GPKG", layer="wells")
# GeoJSON (web interchange, WGS84 expected)
gdf.to_file("wells.geojson", driver="GeoJSON")
# Shapefile (legacy)
gdf.to_file("wells.shp")
```
## 3.2 Export Raster (Rasterio)
```python
import rasterio
from rasterio.transform import from_bounds
profile = {
"driver": "GTiff", "dtype": "float32",
"width": arr.shape[1], "height": arr.shape[0],
"count": 1, "crs": "EPSG:32631",
"transform": from_bounds(x_min, y_min, x_max, y_max,
arr.shape[1], arr.shape[0]),
"compress": "lzw", "nodata": -9999
}
with rasterio.open("output.tif", "w", **profile) as dst:
dst.write(arr.astype("float32"), 1)
```
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