vector2dggs
Python-based CLI tool to index vector files to DGGS in parallel, writing out to Parquet.
This is the vector equivalent of raster2dggs.
Currently this tool supports the following DGGSs:
... and the following geocode systems:
Contributions (especially for other DGGSs), suggestions, bug reports and strongly worded letters are all welcome.
Installation
This tool makes use of optional extras to allow you to install a limited subset of DGGSs.
If you want all possible:
pip install vector2dggs[all]
If you want only a subset, use the pattern pip install vector2dggs[rhp] (for one) or pip install vector2dggs[h3,s2] (for multiple).
A bare pip install vector2dggs will not install any DGGS backends.
PostgreSQL/PostGIS input requires the postgres extra (e.g. pip install vector2dggs[h3,postgres]); it is included in all.
Usage
All commands (h3, rhp, s2, a5, geohash) share the same interface:
vector2dggs <dggs> [OPTIONS] VECTOR_INPUT OUTPUT_DIRECTORY
VECTOR_INPUT may be a local file (anything GDAL can read), a remote URI or GDAL virtual path (e.g. https://…, /vsizip/…), or a PostgreSQL/PostGIS connection URL (with -lyr naming the table). OUTPUT_DIRECTORY is written as an Apache Parquet data store: a directory with one file per partition.
-r/--resolution: the target DGGS resolution. Each output row is one (feature, cell) pair; a cell is included when its centre falls inside the feature, uniformly across all backends.-pr/--parent_res: a coarser resolution used to partition the output (hive directories such ash3_03=…); defaults to a fixed offset below the target resolution.-id/--id_field: the feature identifier carried into the output. Defaults to the input's own internal ID where one exists (a GPKG's FID column, or a DB table's single-column primary key); otherwise falls back to a synthetic index tied to row position in the read order — stable across repeated runs of the same unchanged input, but not portable to a different export/copy of the same data. Rows sharing an id are treated as one feature.-co/--compact: merges complete sets of sibling cells belonging to one feature (grouped by whichever id_field is in play, explicit, auto-detected, or synthetic), to no coarser than the parent resolution. Compacted output expands back to exactly the full-resolution result.--geo: plain Parquet by default;pointorpolygonwrites GeoParquet (v1.1.0) cell geometries instead.--cell-id:string(default) oruint64. DGGS with a native integer cell form (A5, H3, S2) can write cell IDs as unsigned 64-bit integers instead of text — useful where downstream tools take integer cell IDs directly (e.g. DuckDB'sh3extension). Cell IDs are worked in the native form internally regardless of this flag; it only controls the final output rendering. String-only DGGS (rHEALPix, Geohash) reject--cell-id uint64.
The full reference (vector2dggs h3 --help; the other commands differ only in their resolution ranges):
Usage: vector2dggs h3 [OPTIONS] VECTOR_INPUT OUTPUT_DIRECTORY
Ingest a vector dataset and index it to the H3 DGGS.
VECTOR_INPUT is the path to input vector geospatial data. OUTPUT_DIRECTORY
should be a directory, not a file or database table, as it will instead be the
write location for an Apache Parquet data store.
Options:
-v, --verbosity LVL Either CRITICAL, ERROR, WARNING, INFO or DEBUG
[default: INFO]
-r, --resolution [0|1|2|3|4|5|6|7|8|9|10|11|12|13|14|15]
H3 resolution to index [required]
-pr, --parent_res [0|1|2|3|4|5|6|7|8|9|10|11|12|13|14|15]
H3 parent resolution for the output partition.
Defaults to resolution - 6
-id, --id_field TEXT Field to use as an ID; defaults to the input's
own internal ID if it has one (e.g. a GPKG's
FID column, or a DB table's single-column
primary key), otherwise falls back to a
constructed 0...n index on the original
feature order.
-k, --keep_attributes Retain attributes in output. The default is to
create an output that only includes H3 cell ID
and the ID given by the -id field (or the
default index ID).
-ka, --keep_attribute TEXT Retain only this attribute in output; repeat
for multiple. Takes precedence over
-k/--keep_attributes.
-crs, --cut_crs INTEGER Set the coordinate reference system (CRS) used
for cutting large geometries (see
`--cut_threshold`). Defaults to the same CRS
as the input. Should be a valid EPSG code.
-c, --cut_threshold FLOAT Cutting up large geometries into smaller
geometries based on a target area. Units are
assumed to match the input CRS units unless
`--cut_crs` is also given, in which case units
match the units of the supplied CRS. If left
unspecified, the threshold defaults to the
area of a few thousand cells of the target
resolution (a benchmarked balance of
parallelism against per-piece overhead),
converted into the squared units of the
cutting CRS. A threshold of 0 will skip
bisection entirely (effectively ignoring
--cut_crs).
-t, --threads INTEGER RANGE Amount of threads used for operation
[default: (CPU count - 1, capped by available
memory); x>=1]
-cp, --compression TEXT Compression method to use for the output
Parquet files. Options include 'snappy',
'gzip', 'brotli', 'lz4', 'zstd', etc. Use
'none' for no compression. [default: snappy]
-lyr, --layer TEXT Name of the layer or table to read when using
an input that supports layers or tables
-g, --geom_col TEXT Column name to use when using a spatial
database connection as input [default: geom]
--geo [none|point|polygon] Select geometry encoding for the output:
'none' for regular Parquet (no GeoParquet
metadata), or 'point'/'polygon' to write
GeoParquet (v1.1.0) with the corresponding
geometry type. [default: none]
--cell-id [string|uint64] Cell ID output form: 'string' (default) or
'uint64' (unsigned 64-bit integer; e.g. for
DuckDB interop). [default: string]
--tempdir PATH Temporary data is created during the execution
of this program. This parameter allows you to
control where this data will be written.
[default: (system temp dir)]
-co, --compact Compact the H3 cells up to the parent
resolution, grouping by id_field (explicit,
auto-detected, or the default 0...n sequence).
-o, --overwrite
--version Show the version and exit.
--help Show this message and exit.
vector2dggs is a command-line tool; the underlying Python API (vector2dggs.common.index) can be called directly but is not a stable, supported interface.
Visualising output
Output is in the Apache Parquet format, a directory with one file per partition. With --geo point or --geo polygon output will be written as GeoParquet (v1.1.0) with the respective geometry types. GeoParquet can be visualised using desktop GIS tools.
The Apache Parquet output is indexed by an ID column (which you can specify), so it should be ready for two intended use-cases:
- Joining attribute data from the original feature-level data onto computed DGGS cells.
- Joining other data to this output on the DGGS cell ID. (The output has a column like
{dggs}_\d, e.g.h3_09orh3_12according to the target resolution, zero-padded to account for the maximum resolution of the DGGS).
Compaction
Compaction is supported with the -co/--compact argument. The result respects overlapping polygons by considering each feature independently. (In the below example output for rHEALPix, cells are shown with opacity; overlap is visible where there is a darker shade.) This does mean that the index of the result is not necessarily unique (unless your input is a vector coverage, i.e. it does not have overlaps.)
For development
In brief, to get started:
- Install Poetry
- Create and populate the virtual environment with
poetry install. This will install necessary dependencies.
No system GDAL is required: vector data is read via pyogrio, whose wheels bundle GDAL. If you need a GDAL driver that pyogrio's bundled build lacks, build pyogrio from source against your own GDAL.
- Subsequently, activate the virtual environment with
eval "$(poetry env activate)".
If you run poetry install -E all --with dev and activate the environment with eval "$(poetry env activate)", the CLI tool will be aliased so you can simply use vector2dggs rather than poetry run vector2dggs.
For partial backend support you can consider poetry install --with dev -E h3 -E s2 etc. To check what is installed: poetry show --tree.
Alternatively, it is also possible to install using pip with pip install -e ., and bypass Poetry.
Code formatting, linting and type checking
Please run black ., ruff check . and mypy vector2dggs/ before committing. All three are enforced in CI.
Tests
Tests are included. Some tests (covering the PostgreSQL/PostGIS input path) spin up a throwaway PostGIS container via Docker; they'll be skipped automatically if Docker isn't available, rather than failing the run.
To run them, activate the Poetry environment first (eval "$(poetry env activate)"), then run:
python -m pytest -n auto tests/
Or without activating the shell:
poetry run pytest -n auto tests/
To test a specific DGGS:
python -m pytest tests/test_runthrough.py -k "a5" -v
Test data are included at tests/data/.
Example commands
With a local GPKG:
vector2dggs h3 -v DEBUG -id title_no -r 12 -o ~/Downloads/nz-property-titles.gpkg ~/Downloads/nz-property-titles.parquet
With a PostgreSQL/PostGIS connection:
vector2dggs h3 -v DEBUG -id ogc_fid -r 9 -pr 5 -t 4 --overwrite -lyr topo50_lake postgresql://user:password@host:port/db ./topo50_lake.parquet
Citation
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