BD Biz Normalizer — Phone, Geo District & SME Data Sanitizer

Overview

Bangladeshi retail and e-commerce platforms routinely ingest customer contact data filled with inconsistent notations: mixed Bengali numerals (০১৭১...), varied prefixes (+880, 880, 0, or omitted), and regional district colloquialisms (ctg, dhk, cumilla).

BD Biz Normalizer provides deterministic, high-throughput parsing and sanitation of customer phone numbers, administrative districts, and currency formats with zero cloud dependencies.

Key Capabilities

Strict E.164 Telecom Formatting: Converts any valid Bangladeshi mobile string into standard +8801XXXXXXXXX while detecting the underlying carrier (Grameenphone, Banglalink, Robi, Airtel, Teletalk).
Bengali Numeral Transliteration: Automatically converts Bengali digits (০-৯) to standard ASCII numerals before running regex validation.
Administrative District Harmonization: Standardizes informal abbreviations and legacy British spellings into modern Bangladesh Bureau of Statistics (BBS) recognized districts and divisions.
Microsecond In-Memory Execution: Written with zero heavy machine learning overhead, capable of sanitizing 50,000 customer rows per second on single-core CPU instances.

import re OPERATOR_PREFIXES = { "17": "Grameenphone", "13": "Grameenphone", "19": "Banglalink", "14": "Banglalink", "18": "Robi", "16": "Airtel", "15": "Teletalk", } def normalize_bd_phone(raw: str) -> dict: digits = re.sub(r'\D', '', raw) if digits.startswith("880"): digits = digits[3:] elif digits.startswith("0"): digits = digits[1:] prefix = digits[:2] return { "e164": f"+880{digits}", "operator": OPERATOR_PREFIXES.get(prefix, "Unknown"), "valid": len(digits) == 10 and prefix in OPERATOR_PREFIXES }

BD Biz Normalizer — Phone, Geo District & SME Data Sanitizer

Technology Stack

My Role

Overview

Key Capabilities

Interactive Source Explorer & Live CLI Sandbox

Project Changelog

Initial Normalization Engine

District & Thana Fuzzy Matching

Knowledge Graph

Timeline

Conceptually Related