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randogoth 2025-02-26 14:51:25 +00:00
parent fc91d3c884
commit fc00e77b33
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import duckdb
from pathlib import Path
import geohash
import osmium
import subprocess
from pprint import pprint
from typing import List, Tuple, Dict
def remove_points(input_file: str, output_file: str):
try:
input_path, output_path = Path(input_file), Path(output_file)
if not input_path.exists():
raise FileNotFoundError(f"File '{input_file}' not found.")
con = duckdb.connect()
con.execute("INSTALL spatial; LOAD spatial;")
con.execute(f"""
CREATE VIEW geoparquet_filtered AS
SELECT * FROM read_parquet('{input_path}')
WHERE ST_GeometryType(geometry) IS NOT NULL
AND ST_GeometryType(geometry) != 'POINT'
""")
if con.execute("SELECT COUNT(*) FROM geoparquet_filtered").fetchone()[0] == 0:
raise ValueError("No non-POINT geometries found.")
output_path.parent.mkdir(parents=True, exist_ok=True)
con.execute(f"COPY geoparquet_filtered TO '{output_path}' (FORMAT PARQUET)")
print(f"✅ Saved to {output_path}")
except Exception as e:
print(f"❌ Error: {e}")
finally:
if 'con' in locals():
con.close()
def bbox(file_path: str) -> Dict[str, float]:
try:
result = subprocess.run(
["osmium", "fileinfo", "-e", file_path],
capture_output=True, text=True, check=True
)
for line in result.stdout.split("\n"):
if "Bounding box:" in line:
bbox_str = line.strip().replace("Bounding box:", "").strip()
# Convert to a tuple of floats
bbox_tuple = tuple(map(float, bbox_str.strip("()").split(",")))
return bbox_tuple
except subprocess.CalledProcessError as e:
print(f"❌ Error running osmium: {e}")
def check_data(file: str):
con = duckdb.connect()
con.execute("INSTALL spatial; LOAD spatial;")
con.execute(f"CREATE VIEW geoparquet AS SELECT * FROM read_parquet('{file}')")
columns = con.execute("DESCRIBE geoparquet").fetchdf()
print("Columns in the file:\n", columns)
dc = con.execute("SELECT count(*) FROM geoparquet LIMIT 10").fetchdf()
print("\nTotal rows:", dc)
df = con.execute("SELECT * FROM geoparquet LIMIT 10").fetchdf()
print("\nFirst 10 rows:\n", df)
try:
geo_types = con.execute("SELECT DISTINCT ST_GeometryType(geometry) AS geom_type FROM geoparquet").fetchdf()
print("\nDetected Geometry Types:\n", geo_types)
except Exception as e:
print("\nCould not determine geometry type. Possible reason: No valid geometry column found.\n", e)
con.close()
def bbox_geohashes(bbox: Tuple[float, float, float, float]) -> List[str]:
min_x, min_y, max_x, max_y = bbox
geohashes = set()
# Define step size based on 4-character Geohash precision (~39km × 19.5km)
step_size = 0.25 # Approximate step size in degrees (varies slightly by latitude)
lat = min_y
while lat <= max_y:
lon = min_x
while lon <= max_x:
gh = geohash.encode(lat, lon, precision=4)
geohashes.add(gh)
lon += step_size # Move eastward
lat += step_size # Move northward
return sorted(geohashes)
# remove_points('compact.parquet', 'processed.parquet')
# bbox = bbox('israel.pbf')
# hashes = bbox_geohashes(bbox)
# print(hashes)
check_data("geohash/sv2c.parquet")

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<image src="https://blog.therugseller.co.uk/wp-content/uploads/2017/10/2-10.png" width="400" />
<p>&nbsp;<p>
# dopecarpet
Generate GeoHash parquet files from OpenStreetMap PBF files with custom tag filter to look up metadata for coordinates.
## Dependencies
Installation (Fedora)
```bash
sudo dnf install osmium-tool jq python3-devel pip
pip install quackosm[cli] psycopg2-binary pyosmium geoalchemy2 geojson shapely pygeohash pyarrow pandas click
```
## Basic Use
### 1. Customize Filter
Edit the `tags.json` to specify which OSM tags you want to include in the metadata. This affects what geometries are extracted from the OSM data and has a direct influence on the file sizes.
```json
{
"name:en": true,
"name": true,
"aeroway": true,
"boundary": ["aboriginal_lands", "border_zone", "forest", "hazard", "national_park", "protected_area", "disputed"],
"geological": true,
"highway": ["motorway", "trunk", "primary", "raceway"],
"historic": true,
"landuse": true,
"leisure": ["dog_park", "garden", "miniature_golf", "nature_reserve", "park", "playground", "stadium", "swimming_pool", "water_park"],
"military": ["airfield", "base", "bunker", "barracks", "danger_area", "nuclear_explosion_site", "range", "training_area"],
"natural": true,
"place": ["plot", "farm", "island", "islet", "sea", "ocean"],
"power": ["plant"],
"railway": ["abandoned", "construction", "disused", "rail"],
"tourism": ["attraction", "yes"],
"water": true,
"waterway": true
}
```
### 2. Generate GeoHash Files
This extracts the desired data from the PBF file and generates four digit geohash parquet files in the `geohash/` directory.
```bash
just process <osm_data.pbf>
```
### 3. Lookup Coordinate Metadata
Prints metadata found for a coordinate as JSON object list.
```bash
just lookup <latitude>, <longitude>
```
Sample Output: `just lookup 52.496846793890256 13.435128880554208`
```json
[
{
"type": "polygon",
"leisure": "park",
"name": "Görlitzer Park"
},
{
"type": "polygon",
"landuse": "forest"
},
{
"type": "polygon",
"name": "Luisenstadt"
},
{
"type": "polygon",
"name": "Jugendverkehrsschule Wiener Straße"
},
{
"type": "polygon",
"name": "Friedrichshain-Kreuzberg"
},
{
"type": "polygon",
"name": "Kreuzberg"
}
]
```
## Advanced Use
### Extract and Filter Data
To just extract the filtered data from an OSM PBF file and save it as parquet file
```bash
just extract <osm_data.pbf> <extracted_data.parquet>
```
### Download OSM Data File for Region
Automatically download a file from Geofabrik based on the name of a region, filter it, and save it as parquet file.
```bash
just download '<name of the region>' <extracted_data.parquet>
```
The original PBF file remains saved in the `files/` folder.
### Split Parquet File to GeoHash Parquet Files
```bash
just convert <extracted_data.parquet> <geohash_parquet_folder>
```
### Plot Parquet File as PNG
Plot the geometry of a parquet file as a PNG with the same filename.
```bash
just plot <file.parquet>
```
Sample Output:
![snippet](u33d.png)
## TO DO
- [X] GeoHash parquet file generation
- [X] Append data to existing parquet files
- [ ] Create web API server
- [ ] Dockerize it
- [ ] Scheduled update routine

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