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A parser to convert WAFS IWXXM SIGWX XML files into GeoJSON FeatureCollections.

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The maintainers of this project have marked this project as archived. No new releases are expected.

Project description

sigwx-parser

A Python parser for converting WAFS IWXXM SIGWX XML files into GeoJSON, WKT, or WKB feature collections.

SIGWX (Significant Weather) charts are issued by the World Area Forecast System (WAFS) and contain information about meteorological hazards for aviation — things like icing, turbulence, jet streams, and tropical cyclones. This library parses the IWXXM XML format of those files and outputs structured geometry data in your choice of format.

Installation

pip install sigwx-parser

Usage

from sigwx_parser import SigwxParser

# From a file
parser = SigwxParser(file_path="sigwx_output.xml")

# From a raw XML string
parser = SigwxParser(file_path=None, xml_content=xml_string)

forecasts = parser.parse()

The output_format parameter controls the geometry representation. It defaults to "geojson", but "wkt" and "wkb" are also supported:

forecasts = parser.parse(output_format="geojson")  # default
forecasts = parser.parse(output_format="wkt")
forecasts = parser.parse(output_format="wkb")

The top-level key of the feature collection in each result dict matches the chosen format.


GeoJSON output (output_format="geojson")

[
    {
        "valid_time": "2024-02-22T12:00:00Z",
        "issue_time": "2024-02-21T18:00:00Z",
        "geojson": {
            "type": "FeatureCollection",
            "features": [
                {
                    "type": "Feature",
                    "geometry": {
                        "type": "Polygon",
                        "coordinates": [ [ [lon, lat], ... ] ]
                    },
                    "properties": {
                        "feature_id": "uuid.12345...",
                        "phenomenon": "AIRFRAME_ICING",
                        "upper_fl": "240",
                        "lower_fl": "100"
                    }
                }
            ]
        }
    }
]

WKT output (output_format="wkt")

[
    {
        "valid_time": "2024-02-22T12:00:00Z",
        "issue_time": "2024-02-21T18:00:00Z",
        "wkt": {
            "features": [
                {
                    "geometry": "POLYGON ((lon lat, lon lat, ...))",
                    "properties": {
                        "feature_id": "uuid.12345...",
                        "phenomenon": "AIRFRAME_ICING",
                        "upper_fl": "240",
                        "lower_fl": "100"
                    }
                }
            ]
        }
    }
]

WKB output (output_format="wkb")

[
    {
        "valid_time": "2024-02-22T12:00:00Z",
        "issue_time": "2024-02-21T18:00:00Z",
        "wkb": {
            "features": [
                {
                    "geometry": "0103000000...",
                    "properties": {
                        "feature_id": "uuid.12345...",
                        "phenomenon": "AIRFRAME_ICING",
                        "upper_fl": "240",
                        "lower_fl": "100"
                    }
                }
            ]
        }
    }
]

WKB geometries are returned as hex-encoded strings so they remain JSON-serializable. To get raw bytes for direct database insertion:

raw_bytes = bytes.fromhex(feature["geometry"])

Most databases (PostGIS, SpatiaLite, etc.) also accept the hex string directly via their ST_GeomFromWKB / GeomFromWKB functions, so in practice you often don't need to convert.


Excluding feature types

You can skip specific phenomenon types by passing an exclude set to parse():

forecasts = parser.parse(exclude={"CLOUD", "RADIATION"})

Valid values for exclude:

Value Description
AIRFRAME_ICING Airframe icing areas
CLOUD Significant cloud (e.g. CB, TCU)
JETSTREAM Jet stream axes
TROPOPAUSE Tropopause height
TURBULENCE Turbulence areas
RADIATION Radiation hazards
TROPICAL_CYCLONE Tropical cyclone positions
VOLCANO Volcanic ash areas

Notes

  • Polygon winding order is corrected automatically using Shapely.
  • Geometries that cross the antimeridian are split correctly using the antimeridian library.
  • Namespaces are stripped from the XML before parsing, so the XPath queries stay clean.

Dependencies

License

MIT

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