Metadata-Version: 2.4
Name: witskit
Version: 0.1.0
Summary: The most comprehensive Python SDK for processing WITS (Wellsite Information Transfer Standard) data in the oil & gas drilling industry.
Project-URL: Homepage, https://github.com/Critlist/witskit
Project-URL: Documentation, https://github.com/Critlist/witskit#readme
Project-URL: Repository, https://github.com/Critlist/witskit
Project-URL: Issues, https://github.com/Critlist/witskit/issues
Author-email: Mikey Howk <howktechllc@gmail.com>
License-Expression: MIT
License-File: LICENSE
Keywords: drilling,logging,lwd,mwd,oil-gas,wits
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
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Description-Content-Type: text/markdown

# 🛠️ WitsKit

**WitsKit** is a Python toolkit for decoding and working with WITS (Wellsite Information Transfer Standard) data.

<sub>
*Please note: I’m still learning, so if you spot something incorrect or suboptimal, feel free to submit a PR. The codebase isn’t perfect yet, but I’m working on it!
</sub>


## 🚩 What It Does

- Parses raw WITS frames into structured, validated Python objects
- Ships with 724 symbols across 20+ record types—auto-parsed from the spec
- Includes CLI tools for symbol search, frame decoding, and validation
- **🗄️ SQL Storage**: Stream WITS data directly to SQLite, PostgreSQL, or MySQL databases
- **📊 Time-series Analysis**: Query and analyze historical drilling data with time-based filtering
- Built to be extended: transports (serial, TCP) and outputs (SQL, JSON) are plug-and-play

## 💡 Why Use It?

- 🧠 You get the *full* WITS symbol database, not someone's half-finished Excel copy
- 🔍 CLI lets you find, filter, and explore symbols without opening the spec (again)
- 📏 Works in both metric and FPS—because a boat sank and now we have 2 standards
- 🗄️ **Production-ready SQL storage** for time-series drilling data analysis
- 📊 **Query historical data** with time filters, symbol selection, and export to CSV/JSON
- 🧱 Modular and testable, built with real-world telemetry in mind
- 🔒 Type-checked with `pydantic`, so your data actually means what you think it does


## 🧑‍💻 Getting Started

### Installation

**For Development:**

```bash
git clone https://github.com/Critlist/witskit
cd witskit
pip install -e .
```

**For Production (when published):**

```bash
pip install witskit
```

**With SQL storage support:**

```bash
pip install witskit[sql]  # Includes PostgreSQL and MySQL drivers
```

**With uv (recommended):**

```bash
git clone https://github.com/yourusername/witskit
cd witskit
uv pip install -e .
```

### Quick Start - Decode a WITS Frame

```python
from witskit import decode_frame

frame = """&&
01083650.40
01133.5
01142850.7
!!"""

result = decode_frame(frame)
for dp in result.data_points:
    print(f"{dp.symbol_name}: {dp.parsed_value} {dp.unit}")
```

Output:
```
DBTM: 3650.4 M
ROPA: 3.5 M/HR
HKLA: 2850.7 KDN
```

## 🕹️ CLI Commands

After installation, the `witskit` command is available globally:

**Try the demo:**

```bash
witskit demo
```

**Explore symbol database:**

```bash
witskit symbols --list-records
witskit symbols --search "depth"
witskit symbols --record 8 --search "resistivity"
```

**Decode WITS from a file:**

```bash
witskit decode sample.wits
witskit decode sample.wits --fps
witskit decode sample.wits --output results.json
```

**Decode WITS directly:**

```bash
witskit decode "&&\n01083650.40\n!!" --format table
```

**Validate WITS data:**

```bash
witskit validate "&&\n01083650.40\n!!"
```

**Convert units:**

```bash
witskit convert 3650.4 M F  # Convert 3650.4 meters to feet
witskit convert 1000 PSI KPA  # Convert 1000 PSI to kilopascals
```

### WITS File Format

Example WITS file format (sample.wits):
```
&&
01083650.40
01133.5
01142850.7
!!
&&
01083651.20
01133.7
01142855.3
!!
```

Each frame must include:

- Start line (`&&`)
- One or more data lines (4-digit symbol code + value)
- End line (`!!`)

Multiple frames can be included in a single file.

## 🗄️ SQL Storage & Time-Series Analysis

WitsKit includes production-ready SQL storage for time-series drilling data analysis:

### Supported Databases
- **SQLite**: Perfect for development and single-user analysis
- **PostgreSQL**: Production-ready with advanced time-series capabilities  
- **MySQL**: Enterprise database support

### Key Features
- **Optimized Schema**: Time-series optimized tables with proper indexing
- **Batch Processing**: Configurable batch sizes for high-performance streaming
- **Time-Based Queries**: Filter data by time ranges with ISO timestamp support
- **Symbol Management**: Automatic population of WITS symbol definitions
- **Export Options**: JSON, CSV, and table formats for data analysis
- **Multi-source Support**: Handle data from multiple drilling rigs simultaneously

### Quick Example

```python
from witskit.storage.sql_writer import SQLWriter, DatabaseConfig

# Configure database
config = DatabaseConfig.sqlite("drilling_data.db")
writer = SQLWriter(config)

# Stream and store data
await writer.initialize()
async for frame in stream_source:
    await writer.store_frame(frame)

# Query historical data
async for data_point in writer.query_data_points(
    symbol_codes=["0108", "0113"], 
    start_time=datetime(2024, 1, 1),
    limit=1000
):
    print(f"{data_point.symbol_name}: {data_point.parsed_value}")
```

See [docs/sql_storage.md](docs/sql_storage.md) for complete documentation.

## 🧱 Project Layout

```
witskit/
├── witskit/             # Main package
│   ├── models/          # Symbol metadata, Pydantic schemas
│   ├── decoder/         # WITS frame parsing
│   ├── transport/       # Serial, TCP, file readers
│   ├── storage/         # SQL storage backends
│   │   ├── base.py      # Abstract storage interface
│   │   ├── schema.py    # Database schema definitions
│   │   └── sql_writer.py # SQL storage implementation
│   └── cli.py          # Command-line interface
├── tests/              # Unit tests
├── docs/               # Documentation
│   ├── sql_storage.md  # Complete SQL storage guide
│   ├── guide/          # User guides
│   │   ├── getting-started.md
│   │   ├── cli-usage.md
│   │   └── wits-format.md
│   └── api/            # API documentation
├── examples/           # Example scripts and demos
├── pyproject.toml      # Package configuration
└── README.md           # This file
```

## 📊 Supported Record Types

| Record | Category | Description | Symbols |
|--------|----------|-------------|---------|
| 1 | Drilling | Time-Based | 40 |
| 2 | Drilling | Depth-Based | 26 |
| 8 | MWD/LWD | Formation Evaluation | 46 |
| 15 | Evaluation | Cuttings/Lithology | 54 |
| 19 | Configuration | Equipment setup | 89 |
| ... | ... | 20+ types total | 724 |

Records 5, 22–25 are defined but not implemented. You're not missing much.

## 🧪 Testing

```bash
# Run the full test suite
pytest tests/ -v

# Run specific test categories
pytest tests/test_decoder.py -v
pytest tests/test_symbols.py -v
```

## 📈 Roadmap

- ✅ Symbol parser & decoder engine
- 🚧 Transport support (serial, TCP, file) (WIP)
- ✅ **SQL Storage** (SQLite, PostgreSQL, MySQL)
- ✅ **Time-series analysis** with time-based filtering and export
- 🔜 Real-time decoding pipeline with WebSocket/MQTT
- 🔜 Web UI for monitoring decoded streams
- 🔜 Parquet export for big data analysis

## 🤝 Contributing

This project uses:

- Python 3.11+
- pydantic for type validation
- typer for CLI
- rich for terminal formatting
- pytest for testing
- SQLAlchemy for SQL storage
- asyncpg/aiomysql for async database drivers

PRs welcome. Bonus points if you've ever debugged WITS Comms while on standby waiting for the Rig to pick up tools. 

## 📚 References

- [WITS Specification](https://witsml.org)
- [SPE Petrowiki](https://petrowiki.spe.org)
- [SLB Oilfield Glossary](https://glossary.oilfield.slb.com)

## 📄 License

MIT. Do what you want with it—just don't sell it back to Halliburton.

---

Made by someone who got bored and wanted a tool to create a diferent approach to WITS data transfer. If you work with WITS data, WitsKit's here to make your life less painful.