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barangay

★ 30 Open GitHub ↗

July 2026 | List of Philippine barangays, municipalities, cities, provinces, and regions. PSGC authoritative master list.

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# 🇵🇭 barangay

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Philippine Standard Geographic Code (PSGC) Python package with fuzzy search for barangays, municipalities, cities, provinces, and regions. Based on the official July 2026 PSGC masterlist. Offline access to all 42,000+ barangays — no API calls or database needed.

---

## Quick Start

```bash
pip install barangay
```

```python
from barangay import barangays, search_fuzzy

# Browse all 42,000+ barangays
print(barangays)  # <PSGC barangay database: 42010 records>

# Get a specific barangay
brgy = barangays.get(name="Tongmageng")
print(brgy.region)    # Bangsamoro Autonomous Region In Muslim Mindanao (BARMM)
print(brgy.province)  # Tawi-Tawi
print(brgy.psgc_id)   # 1907005010

# Fuzzy search
for r in search_fuzzy("Tongmagen, Tawi-Tawi"):
    print(f"{r.name} — score: {r.score}")
```

---

## Features

| Feature | Description |
|---------|-------------|
| 🔍 **Fuzzy Search** | Fast, customizable matching for unstandardized addresses |
| 🏛️ **Hierarchy Traversal** | Navigate parent, children, and ancestors of any admin division |
| 📊 **Pandas Export** | Direct `to_frame()` / `to_dicts()` export from database views |
| ✅ **Address Validation** | `validate()` and `validate_many()` for automated address checking |
| 📅 **Historical Data** | Access previous PSGC releases by date |
| 👩‍💻 **Command Line Interface** | Easy-to-use command line interface |
| 📚 **Multiple Data Models** | Choose the structure that fits your use case |
| 💾 **Smart Caching** | Automatic caching for faster subsequent loads |
| 🧩 **Plug-in System** | Enrich PSGC data with custom extensions via plug-ins |

---

## Installation

```bash
pip install barangay
```

**Requirements:** Python 3.13+

---

## CLI

```bash
# Search for barangays
barangay search "Tongmageng, Tawi-Tawi"

# Export data
barangay export --model flat --format json --output data.json

# Show information
barangay info version
barangay info stats

# Work with historical data
barangay history list-dates
barangay history search-history "Tongmageng" --as-of "2025-07-08"

# Manage cache
barangay cache info
barangay cache clear

# Search with plugin enrichment
barangay search "Tongmageng" --plugin psgc-aux-data --format json

# Export with plugin enrichment
barangay export --model flat --plugin psgc-aux-data --format json --output enriched.json

# Batch operations
barangay batch batch-search queries.txt --limit 5 --output results.json
barangay batch validate barangay_names.txt
```

📖 **Full CLI Reference:** [quarto-docs/reference/cli.qmd](https://bendlikeabamboo.github.io/barangay/reference/cli.html)
📖 **Plugin Guide:** [quarto-docs/plugins/index.qmd](https://bendlikeabamboo.github.io/barangay/plugins/)

---

## Python API

### Database Views

Pre-built views let you browse and search any admin level directly:

```python
from barangay import regions, provinces, municipalities, cities, barangays

print(regions)     # <PSGC region database: 18 records>
print(barangays)   # <PSGC barangay database: 42010 records>

# Look up by name
brgy = barangays.get(name="Tongmageng")
print(brgy.province)  # Tawi-Tawi

# Look up by PSGC ID
brgy = barangays.lookup("1907005010")
print(brgy)  # <barangay: Tongmageng (1907005010)>

# Iterate over records
for region in regions:
    print(region.name)
```

### Hierarchy Traversal

Each record exposes its position in the administrative hierarchy:

```python
brgy = barangays.get(name="Tongmageng")
print(brgy.region)      # Bangsamoro Autonomous Region In Muslim Mindanao (BARMM)
print(brgy.province)    # Tawi-Tawi
print(brgy.municipality)  # Sitangkai
print(brgy.parent)      # <municipality: Sitangkai (1907005000)>
print(brgy.ancestors)   # [<municipality: Sitangkai ...>, <province: Tawi-Tawi ...>, ...]

manila = cities.get(name="City of Manila")
print(manila.children[:2])  # [<submunicipality: Tondo I/II ...>, <submunicipality: Binondo ...>]
```

### Fuzzy Search

```python
from barangay import search_fuzzy

results = search_fuzzy("Tongmagen, Tawi-Tawi", threshold=60.0, limit=5)
for r in results:
    print(f"{r.name} ({r.psgc_id}) — score: {r.score}")
# Tongmageng (1907005010) — score: 100.0
# Tonggosong (1907004005) — score: 84.21
# ...
```

### Address Validation

```python
from barangay import validate, validate_many

v = validate("Tongmageng, Tawi-Tawi")
print(v.valid, v.matched_name, v.score)  # True Tongmageng 100.0

results = validate_many(["Tongmageng, Tawi-Tawi", "Nonexistent Place"])
for r in results:
    print(f"{r.input!r} -> {'valid' if r.valid else 'invalid'}")
```

### Export to Pandas

```python
from barangay import barangays

df = barangays.to_frame()     # pd.DataFrame
data = barangays.to_dicts()   # List[dict]
```

### Data Access (Nested & Flat Models)

```python
from barangay import barangay, barangay_flat, barangay_extended

# Basic nested model (simple lookups)
ncr_cities = list(barangay["National Capital Region (NCR)"].keys())

# Extended model (recursive with metadata)
for region in barangay_extended.components:
    print(f"{region.name} ({region.type})")

# Flat model (search & filtering)
brgy = [loc for loc in barangay_flat if loc.name == "Marayos"][0]
```

### Search (Dict-based)

> **Deprecated:** The `search()` function returns raw dicts and will be removed in 2027.X.X.X. Use [`search_fuzzy()`](#fuzzy-search) instead for typed results.

```python
from barangay import search

# Simple search
results = search("Tongmageng, Tawi-Tawi")

# Custom search
search(
    "Tongmagen, Tawi-Tawi",
    n=4,                    # Number of results
    match_hooks=["municipality", "barangay"],  # Match levels
    threshold=70.0,         # Minimum similarity (0-100)
)
```

### Utilities

```python
from barangay import sanitize_input, resolve_date, get_available_dates, use_version

# Sanitize strings
cleaned = sanitize_input("City of San Jose", exclude=["city of "])
# Result: "san jose"

# Switch to historical data
use_version("2025-07-08")
brgy = barangays.lookup("1907005010")
use_version(None)  # back to latest
```

📖 **Full API Reference:** [quarto-docs/reference/index.qmd](https://bendlikeabamboo.github.io/barangay/reference/)

---

## Configuration

Configure via environment variables:

```bash
export BARANGAY_AS_OF="2025-07-08"      # Default dataset date
export BARANGAY_VERBOSE="true"          # Enable verbose logging
export BARANGAY_CACHE_DIR="/custom/path" # Custom cache directory
```

Or set programmatically:

```python
import barangay
barangay.as_of = "2025-07-08"
```

**Priority:** Function parameter → Module attribute → Environment variable → Default (latest)

📖 **Full Configuration Guide:** [quarto-docs/reference/configuration.qmd](https://bendlikeabamboo.github.io/barangay/reference/configuration.html)

---

## Data Models

Three data structures are available. Choose based on your use case:

| Model | Use Case | Structure |
|-------|----------|-----------|
| [`barangay`](https://bendlikeabamboo.github.io/barangay/api/#barangay-admindiv) | Simple lookups | Nested dictionary (region → city → barangay) |
| [`barangay_extended`](https://bendlikeabamboo.github.io/barangay/api/#barangay_extended-admindivextended) | Complex hierarchies | Recursive with rich metadata |
| [`barangay_flat`](https://bendlikeabamboo.github.io/barangay/api/#barangay_flat-listadmindivflat) | Search & filtering | Flat list with parent references |

**Note:** Pydantic models (`barangay`, `barangay_extended`, `barangay_flat`) are recommended. Dict versions (`BARANGAY`, `BARANGAY_EXTENDED`, `BARANGAY_FLAT`) are available for backward compatibility.

> **Deprecation:** `BARANGAY`, `BARANGAY_EXTENDED`, `BARANGAY_FLAT` dict aliases will be removed in 2027.X.X.X. Use the Database API instead (e.g. `from barangay import barangays; barangays.get(name="Tongmageng")`).

---

## Historical Data

Access previous PSGC releases by date. Data is automatically cached after first download.

**Current Data Version:** `2026-07-13` (July 13 2026 PSGC masterlist)

**Available Dates:**
- Current: `2026-07-13` (bundled)
- Historical: See [barangay-data-repository](https://github.com/bendlikeabamboo/barangay-data-repository)

```python
# Sample only, actual values might differ
import barangay
print(barangay.current)           # '2026-07-13'
print(barangay.available_dates)   # ['2026-07-13', '2026-04-13', '2026-01-13', '2025-08-29', '2025-10-13', '2025-07-08']
```

---

## Performance

Fuzzy search is optimized for speed:

| Configuration | Performance |
|---------------|-------------|
| Default (4 hooks) | ~80ms per search |
| Optimized (1–2 hooks) | ~10–25ms per search |

Use fewer `match_hooks` for better performance when appropriate.

---

## Resources

- 📚 [Full Documentation](https://bendlikeabamboo.github.io/barangay/) - Comprehensive guides and API reference
- 📩 [PSGC Source](https://psa.gov.ph/classification/psgc/node/1684083211) - April 2026 masterlist
- 📦 [PyPI Package](https://pypi.org/project/barangay/)
- 💻 [GitHub Repository](https://github.com/bendlikeabamboo/barangay)
- 📊 [Data Repository](https://github.com/bendlikeabamboo/barangay-data-repository) - Raw PSGC datasets (JSON, YAML)
- 🐳 [Barangay-API Docker](https://hub.docker.com/r/bendlikeabamboo/barangay-api) - REST API companion

---

## Contributing

Contributions are welcome! See our [Contributing Guide](CONTRIBUTING.md) and [Code of Conduct](CODE_OF_CONDUCT.md).

---

## License

barangay

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