malaysian-address-parser 0.1.1

Deterministic, offline Malaysian address parser (A1/A2/A3/Postcode/State) for messy real-world datasets.

Malaysian Address Parser

Deterministic, rule-based Malaysian address normalization engine built for messy real-world datasets.

This package extracts and standardizes Malaysian address strings into structured components:

ALAMAT1 | ALAMAT2 | ALAMAT3 | POSTCODE | STATE

Designed specifically for:

• Noisy Excel exports
• Local council datasets
• Mixed-format government records
• Inconsistent commas & whitespace
• Postcode false positives (LOT/PT/NO patterns)

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✨ Features

• ✅ Rule-based (no ML dependency)
• ✅ Offline-capable
• ✅ Canonical Malaysian state mapping
• ✅ False-positive postcode protection
• ✅ MELAKA TENGAH special case handling
• ✅ CLI tool
• ✅ Excel batch processing
• ✅ Unit-tested (pytest)
• ✅ CI-enabled (GitHub Actions)

---

📦 Installation

From PyPI (if published)

pip install malaysian-address-parser

Local Development

pip install -e ".[dev,excel]"

Optional extras:

• [excel] → Excel processing (pandas + openpyxl)
• [pdf] → PDF extraction (camelot)
• [dev] → pytest + ruff

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🚀 Usage

---

1️⃣ Parse Single Address (CLI)

malaysian-address-parser parse-one "Lot 123, Jalan Bunga, Taman Mawar, 70400 Seremban, Negeri Sembilan"

Pretty output:

malaysian-address-parser parse-one "..." --pretty

Example Output

{
  "alamat1": "LOT 123 JALAN BUNGA",
  "alamat2": "TAMAN MAWAR",
  "alamat3": "SEREMBAN",
  "poskod": "70400",
  "negeri": "NEGERI SEMBILAN DARUL KHUSUS"
}

---

2️⃣ Parse Excel File

malaysian-address-parser parse-excel input.xlsx --col address --out output.xlsx

Options

Flag	Description
--sheet	Sheet name or index
--col	Column containing raw address
--out	Output file (.xlsx or .csv)
--limit	Limit rows (debug mode)
--no-keep-original	Output only parsed fields

Example:

malaysian-address-parser parse-excel data/input.xlsx --col SEMASA_ALAMAT_RAW --out results/parsed.xlsx

Supports:

• Relative paths
• Absolute paths
• Auto-creates output directory if missing

---

🧠 Python API Usage

from malaysian_address_parser import classify_address_v2

address = "Lot 123, Jalan Bunga, Taman Mawar, 70400 Seremban, Negeri Sembilan"

a1, a2, a3, poskod, negeri = classify_address_v2(address)

print(a1)
print(a2)
print(a3)
print(poskod)
print(negeri)

---

📂 Project Structure

.
├── src/
│   └── malaysian_address_parser/
│       ├── classifier.py
│       ├── alamat_splitter.py
│       ├── postcode_state_extractor.py
│       ├── pre_cleaner.py
│       ├── normalizer.py
│       ├── cli.py
│       └── excel_runner.py
│
├── tests/
│
├── .github/workflows/ci.yml
├── pyproject.toml
└── README.md

---

🔍 Core Logic Highlights

Prefix Splitting

Splits prefix into:

• ALAMAT1 (A1) → Unit + Street
• ALAMAT2 (A2) → Area (Taman, Kampung, PPR, etc.)

Uses keyword-based heuristics instead of naive comma splitting.

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Postcode Detection

• Detects valid 5-digit Malaysian postcodes
• Ignores false positives like:

LOT 54321
PT 12345

Scoring system prefers postcodes appearing toward the end of address.

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State Canonicalization

Recognizes all Malaysian states including ceremonial names:

• JOHOR DARUL TAKZIM
• PERAK DARUL RIDZUAN
• SELANGOR DARUL EHSAN
• etc.

All states normalized into canonical format.

---

Special Case Handling

Protected case:

MELAKA TENGAH

Prevents accidental stripping of "MELAKA" during state extraction.

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🧪 Testing

Run tests locally:

pytest -q

CI runs tests across:

• Python 3.10
• Python 3.11
• Python 3.12
• Python 3.13

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⚠ Known Limitations

• Extremely ambiguous rural addresses may require manual review
• No postcode ↔ state validation yet
• No gazette-level mukim verification
• Fully rule-based (no ML fallback)

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🔮 Roadmap

• Postcode ↔ State validation layer
• Mukim-level canonical validation
• Performance benchmarking (rows/sec)
• Parallel Excel processing
• Docker packaging
• Web interface wrapper

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🎯 Intended Use Cases

• Local authority datasets
• Asset registers
• CRM normalization
• Data migration projects
• License databases
• Cukai taksiran records
• Address standardization pipelines

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📜 License

MIT

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Maintainer

Imaduddin
Built for real Malaysian address data.