Indian place name identifier with SymSpell-style fuzzy lookup and OCR word segmentation
Project description
Indic Names Library - India Places Database
A comprehensive database of 165,627 Indian place names (post offices, villages, towns, cities) sourced from India Post, covering all 37 states & Union Territories.
Stats
| Metric | Count |
|---|---|
| Total records | 165,627 |
| Unique place names | 145,086 |
| States & UTs covered | 37 |
Structure
data/
├── india_places_full.csv # Full dataset as CSV
├── unique_place_names.txt # 145,086 unique place names
├── state_summary.json # Stats per state/UT
├── chunks/india_places_part01-06.json # Split JSON (30K records each)
└── by_state/<STATE>.json # One file per state/UT
Schema
{
"place_name": "Kothimir B.O",
"district": "KUMURAM BHEEM ASIFABAD",
"state": "TELANGANA",
"pincode": "504273",
"office_type": "BO",
"delivery": true,
"division": "Adilabad Division",
"region": "Hyderabad Region",
"circle": "Telangana Circle",
"latitude": 19.3638689,
"longitude": 79.5376658
}
Usage (Python)
import csv, json
# Load all records
with open("data/india_places_full.csv") as f:
places = list(csv.DictReader(f))
print(len(places), "records")
# Load by state
with open("data/by_state/KARNATAKA.json") as f:
karnataka = json.load(f)
# Unique names
names = open("data/unique_place_names.txt").read().splitlines()
Source
India Post pincode directory via india-pincode npm package.
Project details
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