dxf2geo 0.1.4

Convert CAD DXF data into geospatial formats and visualisations using GeoPandas/Pyogrio.

dxf2geo

[!WARNING]
This package is in the early stages of development and should not be installed unless you are one of the developers.

dxf2geo is a small Python package for converting CAD .dxf files into geospatial formats such as Shapefiles and GeoPackages, and for producing interactive visualisations of the extracted geometry.

It is designed to automate the process of extracting geometry by type (point, line, polygon, etc.), filtering or cleaning the results, and inspecting the output spatially.

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Table of contents

• Installation
• Features
• Example usage
• Filtering options
• License

Installation

dxf2geo uses the GDAL Python bindings (osgeo.*). On supported platforms, pip install dxf2geo will pull a compatible GDAL wheel from PyPI.

pip install dxf2geo

If your platform does not have a prebuilt GDAL wheel, install GDAL from your system/package manager first (or via Conda), then install dxf2geo:

sudo apt install gdal-bin libgdal-dev
pip install dxf2geo

Before usage, it may be worth verifying your installation to ensure that GDAL is installed:

python -c "from osgeo import gdal, ogr; print('GDAL', gdal.VersionInfo(), 'DXF driver:', bool(ogr.GetDriverByName('DXF')))"

If the installation has worked, you should see something like GDAL ##### DXF driver: True.

Features

• Converts DXF files to common vector formats (e.g. Shapefile, GeoPackage),
• Supports geometry filtering by type (e.g., LINESTRING, POLYGON),
• Skips invalid geometries,
• Visualises output geometries in an interactive Plotly-based HTML map,
• Filters out short, axis-aligned DXF gridding lines (optional cleanup step).

Example usage

Below is an example of using the functionality of this package on a CAD file example.dxf. This creates a set of shapefiles for of the types of geometry in a new output/ directory.

# Imports
from dxf2geo.extract import extract_geometries
from dxf2geo.visualise import (
    load_geometries,
    plot_geometries,
)
from pathlib import Path

# Define paths
input_dxf = Path("./example.dxf").expanduser()
output_dir = Path("output")

# Process CAD file
extract_geometries(input_dxf, output_dir)

# Produce `plotly` html figure
gdf = load_geometries(output_dir)
plot_geometries(gdf, output_dir / "geometry_preview.html")

Following this, we would have an output folder that looks like:

output/
├── point/
│   └── point.shp
├── linestring/
│   └── linestring.shp
├── polygon/
│   └── polygon.shp
...
└── export.log

Layer filtering

At present we can filter CAD layers based on a number of different criteria.

Layer name (exact, case-insensitive)

FilterOptions(
    include_layers=("roads", "buildings"),
    exclude_layers=("defpoints", "tmp"),
)

Layer name (regular expressions)

We can also filter layers using regular expressions (applied to the CAD layer name).

FilterOptions(
    # Include any "roads" or "road" layer (case-insensitive), and any layer starting with "bldg_"
    include_layer_patterns=(r"(?i)^roads?$", r"^bldg_.*"),
    # Exclude layers named "defpoints" (any case) or prefixed with "tmp_"
    exclude_layer_patterns=(r"(?i)^defpoints$", r"^tmp_"),
)

Geometry size/structure

# Drop empty geometries and zero-area/length features
FilterOptions(drop_empty=True, drop_zero_geom=True)

# Minimum polygon area
FilterOptions(min_area=5.0)

# Minimum line length
FilterOptions(min_length=10.0)

Spatial bounding box

# (minx, miny, maxx, maxy)
FilterOptions(bbox=(430000.0, 420000.0, 435000.0, 425000.0))

Attribute-value exclusions (exact match)

# Exclude features where fields have disallowed values
FilterOptions(exclude_field_values={
    "EntityType": {"TEXT", "MTEXT"},
    "Linetype": {"HIDDEN"},
})

Geometry type selection (at extraction call)

extract_geometries(
    dxf_path,
    output_root,
    geometry_types=("POINT", "LINESTRING", "POLYGON", "MULTILINESTRING", "MULTIPOLYGON"),
    filter_options=FilterOptions(...),
)

License

dxf2geo is distributed under the terms of the MIT license.

Funding

This package is being developed as part of work on the EPSRC Digital Health Hub for Antimicrobial Resistance (EP/X031276/1).