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TaiGeotrans

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CI PyPI version Python 3.11+ Ruff License: MIT

TaiGeotrans provides Taiwan address geocoding via TGOS and WGS84 ↔ TWD97 coordinate conversion, with a Python API and CLI.

  • Convert between WGS84 (EPSG:4326) and TWD97 (EPSG:3826).
  • Geocode Taiwan addresses through TGOS.
  • Process batches and export pandas DataFrames or GeoJSON.
  • Run conversions from the command line.

Region checks use approximate areas covering Taiwan, Penghu, Kinmen, and Matsu; they do not represent administrative boundaries. Output coordinates always use EPSG:4326 and EPSG:3826. Applying EPSG:3826 to areas such as Kinmen can produce negative X coordinates, which are valid projection results.

Installation

For coordinate conversion:

python -m pip install taigeotrans

Install optional features as needed:

python -m pip install "taigeotrans[geocoding]"
python -m pip install "taigeotrans[dataframe]"
python -m pip install "taigeotrans[cli]"

Or install all runtime features:

python -m pip install "taigeotrans[all]"

Python API

from taigeotrans import TaiGeotrans

tg = TaiGeotrans()

# WGS84 -> TWD97
result = tg.transform_lonlat(121.5654, 25.0330)
print(result.twd97_x, result.twd97_y)

# TWD97 -> WGS84
result = tg.transform_twd97(result.twd97_x, result.twd97_y)
print(result.wgs84_lon, result.wgs84_lat)

Address geocoding

Address geocoding requires the geocoding extra and a TGOS AppID/APIKey pair. Obtain these credentials from TGOS and provide them through environment variables:

export TGOS_APP_ID="your-app-id"
export TGOS_API_KEY="your-api-key"

Alternatively, pass them to TaiGeotrans:

tg = TaiGeotrans(
    tgos_app_id="your-app-id",
    tgos_api_key="your-api-key",
)
result = tg.geocode("臺北市中山區松江路469巷4號")
print(result.matched_address, result.twd97_x, result.twd97_y)

The Python API does not automatically load .env. The CLI loads .env from the current working directory; use .env.example as a template. Keep real credentials out of Git.

Batch processing

addresses = ["嘉義縣民雄鄉中樂路55號", "臺北市信義區市府路1號"]
coords = [(120.4278, 23.5521), (121.5654, 25.0330)]

address_results = tg.batch_geocode(addresses, show_progress=False)
coordinate_results = tg.batch_transform_lonlat(coords, show_progress=False)
df = tg.batch_transform_lonlat_to_dataframe(coords, show_progress=False)

Address batches require TGOS credentials and the geocoding extra. DataFrame methods require taigeotrans[dataframe]. Progress bars use tqdm, available with taigeotrans[progress]; batch methods still work without it, but do not display a progress bar.

GeoJSON

coords = [(120.4278, 23.5521), (121.5654, 25.0330)]
results = tg.batch_transform_lonlat(coords, show_progress=False)
geojson = tg.to_geojson(results)
print(geojson["type"])  # FeatureCollection

GeoJSON uses WGS84 coordinates in [lon, lat] order. By default, failed results are skipped; results without WGS84 coordinates are also skipped.

CLI

python -m pip install "taigeotrans[cli]"

taigeotrans transform 121.5654 25.0330
taigeotrans transform 121.5654 25.0330 --format json
taigeotrans geocode "臺北市信義區市府路1號"
taigeotrans batch-geocode addresses.txt -o results.csv
taigeotrans batch-transform coords.csv -o results.csv

Use one address per line in addresses.txt; coords.csv must contain lon,lat columns. Run taigeotrans --help for all commands. Geocoding commands require TGOS credentials.

Results

Single-address geocoding and coordinate conversion return a GeocodeResult containing input values, WGS84/TWD97 coordinates, source, and status. Status values are success, out_of_bounds, invalid, or failed.

Methods Return type
geocode, transform_lonlat, transform_twd97 GeocodeResult
batch_geocode, batch_transform_lonlat list[GeocodeResult]
batch_geocode_to_dataframe, batch_transform_lonlat_to_dataframe pandas.DataFrame
to_geojson GeoJSON FeatureCollection dictionary

Development

python -m pip install -e ".[dev,all]"
python -m pytest
python -m ruff check src tests
python -m ruff format --check src tests
python -m mypy src
python -m build
python -m twine check dist/*

CI tests Python 3.11–3.13. Pushing a TaiGeotrans-v.X.Y.Z tag triggers the release workflow to build distributions, publish to PyPI, and create a GitHub Release. See CONTRIBUTING.md for release prerequisites.

Documentation

License

MIT License. See LICENSE.

Maintenance

See the maintenance guide (Traditional Chinese) for dependency updates, required CI checks, pinned GitHub Actions, and release verification.

Metadata

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