# Overture Map Data 2 HDX
This project is designed to export geographic data from Overture Maps and upload it to the Humanitarian Data Exchange (HDX). The data is processed using DuckDB and can be exported in various formats such as GeoJSON, GPKG, and ESRI Shapefile.
## Features
- Export geographic data from Overture Maps.
- Upload data to HDX.
- Support for multiple output formats.
- Configurable via YAML and environment variables.
- Logging setup using environment variables or parameters.
## Installation
```bash
pip install overture2hdx
```
## Configuration
The application is configured using a YAML file and environment variables.
### YAML Configuration
Example `config.yaml`:
```yaml
iso3: npl
geom: '{"type": "FeatureCollection", "features": [{"type": "Feature", "properties": {}, "geometry": {"coordinates": [[]], "type": "Polygon"}}]}'
key: osgeonepal_pkr
subnational: true
frequency: yearly
categories:
- Roads:
select:
- id
- names.primary as name
- class as class
- subclass as subclass
- UNNEST(JSON_EXTRACT(road_surface, '$[*].value')) as road_surface
- UNNEST(JSON_EXTRACT(sources, '$[*].dataset')) AS source
hdx:
title: Roads of Pokhara
notes: Overturemaps Export for Pokhara. Data might have errors but has gone through validation checks.
tags:
- geodata
- transportation
- roads
theme:
- transportation
feature_type:
- segment
formats:
- gpkg
- shp
```
### Code Overview
`Config`: Class to handle configuration.
`OvertureMapExporter`: Class to handle the export process.
`setup_logging`: Function to set up logging.
Example
```python
import json
geom = json.dumps(
{
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"properties": {},
"geometry": {
"coordinates": [
[
[83.98047393581618, 28.255338988044088],
[83.973540694181, 28.230486421513703],
[83.91927014759125, 28.214265947308945],
[83.97832224013575, 28.195093119231174],
[83.96971545741735, 28.158212628626416],
[84.00175181531534, 28.19361814379657],
[84.03187555483152, 28.168540447741847],
[84.01059767533235, 28.208788347541898],
[84.0342663278089, 28.255549578267903],
[83.99960011963498, 28.228801292171724],
[83.98047393581618, 28.255338988044088],
]
],
"type": "Polygon",
},
}
],
}
)
config_yaml_mini = f"""
iso3: npl
geom: {geom}
key: osgeonepal_pkr
subnational: true
frequency: yearly
categories:
- Roads:
select:
- id
- names.primary as name
- class as class
- subclass as subclass
- UNNEST(JSON_EXTRACT(road_surface, '$[*].value')) as road_surface
- UNNEST(JSON_EXTRACT(sources, '$[*].dataset')) AS source
hdx:
title: Roads of Pokhara Nepal
notes: Overturemaps Export for Pokhara . Data might known to have errors however gone through validation checks to detect map errors, breakage, and vandalism . Sources would be combination of OSM and Other openly available datasets in the region including facebook roads and ESRI community datasets
tags:
- geodata
- transportation
- roads
theme:
- transportation
feature_type:
- segment
formats:
- gpkg
- shp
- Buildings:
select:
- id
- names.primary as name
- class as class
- subtype as subtype
- height as height
- level as level
- num_floors as num_floors
- UNNEST(JSON_EXTRACT(sources, '$[*].dataset')) AS source
hdx:
title: Buildings of Pokhara Nepal
notes: Overturemaps Export for Nepal . Data might known to have errors however gone through validation checks to detect map errors, breakage, and vandalism . Sources would be combination of OSM and Other openly available datasets in the region including facebook roads and ESRI community datasets
tags:
- geodata
theme:
- buildings
feature_type:
- building
formats:
- gpkg
- shp
"""
from overture2hdx import Config, Exporter
config = Config(config_yaml=config_yaml_mini)
exporter = Exporter(config)
results = exporter.export()
print(results)
```
### Author and License
Kshitij Raj Sharma , License : GNU GENERAL PUBLIC LICENSE V3
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"description": "# Overture Map Data 2 HDX\n\nThis project is designed to export geographic data from Overture Maps and upload it to the Humanitarian Data Exchange (HDX). The data is processed using DuckDB and can be exported in various formats such as GeoJSON, GPKG, and ESRI Shapefile.\n\n## Features\n\n- Export geographic data from Overture Maps.\n- Upload data to HDX.\n- Support for multiple output formats.\n- Configurable via YAML and environment variables.\n- Logging setup using environment variables or parameters.\n\n\n## Installation\n\n```bash\npip install overture2hdx\n```\n\n## Configuration\n\nThe application is configured using a YAML file and environment variables.\n\n### YAML Configuration\n\nExample `config.yaml`:\n```yaml\niso3: npl\ngeom: '{\"type\": \"FeatureCollection\", \"features\": [{\"type\": \"Feature\", \"properties\": {}, \"geometry\": {\"coordinates\": [[]], \"type\": \"Polygon\"}}]}'\nkey: osgeonepal_pkr\nsubnational: true\nfrequency: yearly\ncategories:\n- Roads:\n select:\n - id\n - names.primary as name\n - class as class\n - subclass as subclass\n - UNNEST(JSON_EXTRACT(road_surface, '$[*].value')) as road_surface\n - UNNEST(JSON_EXTRACT(sources, '$[*].dataset')) AS source\n hdx:\n title: Roads of Pokhara\n notes: Overturemaps Export for Pokhara. Data might have errors but has gone through validation checks.\n tags:\n - geodata\n - transportation\n - roads\n theme:\n - transportation\n feature_type:\n - segment\n formats:\n - gpkg\n - shp\n\n```\n### Code Overview\n\n`Config`: Class to handle configuration.\n`OvertureMapExporter`: Class to handle the export process.\n`setup_logging`: Function to set up logging.\n\nExample \n```python\nimport json\n\ngeom = json.dumps(\n {\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [83.98047393581618, 28.255338988044088],\n [83.973540694181, 28.230486421513703],\n [83.91927014759125, 28.214265947308945],\n [83.97832224013575, 28.195093119231174],\n [83.96971545741735, 28.158212628626416],\n [84.00175181531534, 28.19361814379657],\n [84.03187555483152, 28.168540447741847],\n [84.01059767533235, 28.208788347541898],\n [84.0342663278089, 28.255549578267903],\n [83.99960011963498, 28.228801292171724],\n [83.98047393581618, 28.255338988044088],\n ]\n ],\n \"type\": \"Polygon\",\n },\n }\n ],\n }\n)\nconfig_yaml_mini = f\"\"\"\n iso3: npl\n geom: {geom}\n key: osgeonepal_pkr\n subnational: true\n frequency: yearly\n categories:\n - Roads:\n select:\n - id\n - names.primary as name\n - class as class\n - subclass as subclass\n - UNNEST(JSON_EXTRACT(road_surface, '$[*].value')) as road_surface\n - UNNEST(JSON_EXTRACT(sources, '$[*].dataset')) AS source\n hdx:\n title: Roads of Pokhara Nepal\n notes: Overturemaps Export for Pokhara . Data might known to have errors however gone through validation checks to detect map errors, breakage, and vandalism . Sources would be combination of OSM and Other openly available datasets in the region including facebook roads and ESRI community datasets\n tags:\n - geodata\n - transportation\n - roads\n theme:\n - transportation\n feature_type:\n - segment\n formats:\n - gpkg\n - shp\n\n - Buildings:\n select:\n - id\n - names.primary as name\n - class as class\n - subtype as subtype\n - height as height\n - level as level\n - num_floors as num_floors\n - UNNEST(JSON_EXTRACT(sources, '$[*].dataset')) AS source\n hdx:\n title: Buildings of Pokhara Nepal\n notes: Overturemaps Export for Nepal . Data might known to have errors however gone through validation checks to detect map errors, breakage, and vandalism . Sources would be combination of OSM and Other openly available datasets in the region including facebook roads and ESRI community datasets\n tags:\n - geodata\n theme:\n - buildings\n feature_type:\n - building\n formats:\n - gpkg\n - shp\n \"\"\"\n\n\nfrom overture2hdx import Config, Exporter\n\nconfig = Config(config_yaml=config_yaml_mini)\nexporter = Exporter(config)\nresults = exporter.export()\nprint(results)\n```\n\n### Author and License \nKshitij Raj Sharma , License : GNU GENERAL PUBLIC LICENSE V3\n\n",
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