Blocks API¶

Block-level geospatial data and lookups. Blocks are administrative subdivisions within districts - there are roughly 220 blocks across all 35 districts in Assam. Each block carries dozens of indicator variables covering agriculture, water, infrastructure, livestock, and socio-economic factors.

Get All Blocks¶

Returns all blocks as a GeoJSON FeatureCollection with all variable data as feature properties. This is the primary data endpoint used by the map frontend.

GET /api/blocks
GET /api/blocks/geojson

Both paths return identical data.

Response¶

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {
        "BLOCK_ID": "1234",
        "Block_name": "Digboi",
        "Dist_Name": "Tinsukia",
        "DISTRICT_I": "134",
        "AD": 45.2,
        "WA": 30.1,
        "CF": 62.3,
        "CI": 28.7
      },
      "geometry": {
        "type": "Polygon",
        "coordinates": [[[95.1, 27.3], [95.2, 27.3], [95.2, 27.4], [95.1, 27.3]]]
      }
    }
  ]
}

Key Property Fields¶

Field	Type	Description
`BLOCK_ID`	string	Unique block identifier
`Block_name`	string	Human-readable block name
`Dist_Name`	string	District name (mapped from `DISTRICT_I`)
`DISTRICT_I`	string	District ID code
Variable codes	number	Indicator values (AD, WA, CF, CI, etc.) - see Variables API for metadata

Geometry

Geometries are simplified (tolerance 0.001) for web performance. Coordinates are in WGS84 (EPSG:4326). For full-resolution geometries, access the raw shapefile directly.

Example¶

cURLPythonJavaScript

curl https://leaf-asrlm.in/api/blocks

import requests
import geopandas as gpd

response = requests.get("https://leaf-asrlm.in/api/blocks")
geojson = response.json()
print(f"Total blocks: {len(geojson['features'])}")

# Load into GeoPandas for analysis
gdf = gpd.GeoDataFrame.from_features(geojson['features'])
print(gdf[['Block_name', 'Dist_Name', 'AD']].head())

const response = await fetch('/api/blocks');
const geojson = await response.json();
console.log(`Total blocks: ${geojson.features.length}`);

// Add to Leaflet map
L.geoJSON(geojson).addTo(map);

Get Block by ID¶

Returns a single block's GeoJSON by its BLOCK_ID field.

GET /api/blocks/{block_id}

Parameters¶

Parameter	In	Type	Required	Description
`block_id`	path	string	Yes	The BLOCK_ID identifier

Response¶

Returns a GeoJSON FeatureCollection containing the single matching block with all properties and geometry.

Errors¶

Code	Description
`404`	No block found with the given BLOCK_ID

Example¶

cURLPython

curl https://leaf-asrlm.in/api/blocks/1234

import requests

r = requests.get("https://leaf-asrlm.in/api/blocks/1234")
if r.status_code == 200:
    block = r.json()
    props = block['features'][0]['properties']
    print(f"Block: {props['Block_name']}, District: {props['Dist_Name']}")
else:
    print(f"Error: {r.json()['error']}")

Get Block by Name¶

Returns a single block's GeoJSON by its Block_name value.

GET /api/blocks/by-name/{block_name}

Parameters¶

Parameter	In	Type	Required	Description
`block_name`	path	string	Yes	Block name, case-sensitive (e.g. "Digboi")

Response¶

Returns a GeoJSON FeatureCollection for the matching block.

Errors¶

Code	Description
`404`	No block found with the given name

Example¶

cURLPythonJavaScript

curl https://leaf-asrlm.in/api/blocks/by-name/Digboi

import requests

r = requests.get("https://leaf-asrlm.in/api/blocks/by-name/Digboi")
block = r.json()
print(f"Features: {len(block['features'])}")

const name = 'Digboi';
const r = await fetch(`/api/blocks/by-name/${encodeURIComponent(name)}`);
const block = await r.json();
console.log(block.features[0].properties);

URL Encoding

Block names with spaces must be URL-encoded (e.g., Doom%20Dooma). Most HTTP libraries handle this automatically.

Get SHG Summary for a Block¶

Aggregates the village-level SHG form data (Kobo export) for one block. Returned shape drives the right-side summary panel in the Cluster Planner.

Blocks absent from the Kobo export fall back to the village master (villages.csv) aggregates: same shape with "source": "village_master", and empty other / activities_raw (the master has no per-activity breakdown).

GET /api/blocks/{block_name}/shg-summary

Parameters¶

Parameter	In	Type	Required	Description
`block_name`	path	string	Yes	Block name, case-insensitive (e.g. `NAHARKATIA`).

Response¶

{
  "district_name": "DIBRUGARH",
  "block_name": "NAHARKATIA",
  "available": true,
  "villages_total": 190,
  "villages_with_gps": 175,
  "villages_without_gps": 15,
  "gp_count": 13,
  "gps": ["BALIMORA", "DHADUMIA", "..."],
  "members_total": 13919,
  "commodities": {
    "Dairy": 206,
    "Goatery": 4452,
    "Piggery": 3594,
    "Backyard_Poultry": 3852,
    "Duckery": 1277,
    "Fishery_Activity": 366
  },
  "other": {
    "Fodder cultivation": 3,
    "Feed manufacturing": 1,
    "Livestock transport": 1,
    "Meat shop": 167
  },
  "activities_raw": {
    "dairy_production": 206,
    "goat_farming": 4267,
    "...": "..."
  }
}

When the block is in neither the Kobo export nor the village master, the response is {"block_name": "...", "available": false}.

Field Notes¶

Field	Description
`villages_total`	Unique villages submitted from this block.
`villages_with_gps` / `villages_without_gps`	Of `villages_total`, how many carry lat/long. Only with-GPS villages are plotted on the map.
`commodities`	Sum of SHG members across the form's sub-activities mapped into each of the 6 clustering commodities.
`other`	Activities outside the 6 commodities (fodder, feed mfg, transport, meat shop).
`activities_raw`	All 25 raw form activity totals — useful for ad-hoc charts.

Example¶

cURLJavaScript

curl https://leaf-asrlm.in/api/blocks/NAHARKATIA/shg-summary

const r = await fetch(`/api/blocks/${encodeURIComponent(block)}/shg-summary`);
const summary = await r.json();
if (summary.available) renderPanel(summary);

Get Block Convergence¶

Returns the block's values for the variables the client tagged Biophysical or Infrastructure in the dss_input sheet's convergence tag column — the second Cluster column (column P, read as Cluster.1). Drives the Biophysical and Infrastructure (convergence) cards on the cluster drill-down.

GET /api/blocks/{block_name}/convergence

Parameters¶

Parameter	In	Type	Required	Description
`block_name`	path	string	Yes	Block name, case-insensitive (e.g. `Bajali`).

Response¶

{
  "block_name": "Bajali",
  "available": true,
  "biophysical": [
    { "code": "E", "label": "% villages with community rainwater harvesting system", "value": 10.71 }
  ],
  "infrastructure": [
    { "code": "S", "label": "% Villages connected to all weather road (< 5 km)", "value": 83.33 }
  ]
}

Field Notes¶

Field	Description
`available`	`true` once the block is found in the block_values sheet.
`biophysical` / `infrastructure`	One entry per tagged variable: `code` (the `I_variable`), `label` (`I_label`), and `value` (the block's value, rounded; `null` when the block has no value for that code).

Both lists are empty when the sheet has no convergence tags yet (not an error). Tags are deduped by code (first occurrence wins).

Example¶

cURLJavaScript

curl https://leaf-asrlm.in/api/blocks/Bajali/convergence

const r = await fetch(`/api/blocks/${encodeURIComponent(block)}/convergence`);
const conv = await r.json();
renderConvergenceCards(conv.biophysical, conv.infrastructure);

Get Block Statistics¶

Returns aggregate statistics for the block dataset including district distribution and available data columns.

GET /api/blocks/statistics
GET /api/statistics

Both paths return identical data.

Response¶

{
  "total_blocks": 220,
  "districts": {
    "Tinsukia": 8,
    "Dibrugarh": 7,
    "Jorhat": 6,
    "Kamrup Metropolitan": 5
  },
  "district_count": 35,
  "columns": ["BLOCK_ID", "Block_name", "Dist_Name", "DISTRICT_I", "AD", "WA", "CF", "CI"]
}

Counts come from the block shapefile

total_blocks, districts, and district_count are computed live from the loaded block shapefile (load_shapefile()), grouped by Dist_Name. Values shown here are illustrative; Assam currently has 35 districts and roughly 220 blocks.

Field	Type	Description
`total_blocks`	integer	Total number of blocks in the dataset
`districts`	object	Block count per district (key: district name, value: count)
`district_count`	integer	Number of distinct districts
`columns`	array	All available data columns (excluding geometry)

Example¶

cURLPython

curl https://leaf-asrlm.in/api/blocks/statistics

import requests

r = requests.get("https://leaf-asrlm.in/api/blocks/statistics")
stats = r.json()
print(f"Total blocks: {stats['total_blocks']}")
print(f"Districts: {stats['district_count']}")
print(f"Variables available: {len(stats['columns'])}")

# Top 5 districts by block count
sorted_districts = sorted(stats['districts'].items(), key=lambda x: x[1], reverse=True)
for name, count in sorted_districts[:5]:
    print(f"  {name}: {count} blocks")

Use for Discovery

The columns field is useful for discovering which variables are available before calling the Variables API for full metadata.