clickhouse-driver-http 0.1.6
Lightweight HTTP client for ClickHouse
Requires Python: >=3.7
Keywords: clickhouse, http, driver, database

# ClickHouse HTTP Driver (`clickhouse-driver-http`)

Lightweight Python HTTP client for ClickHouse with minimal dependencies.

## Installation
```bash
pip install clickhouse-driver-http
```

## Quick Start
```python
from clickhouse_driver_http import ClickHouseHTTP

# Initialize client (supports both int/string ports)
client = ClickHouseHTTP(
    host="localhost",          # Required
    port=8123,                # Default: 8123 (can be string "8123")
    username="default",       # Default: "default"
    password="",              # Default: ""
    database="default",       # Default: "default"
    timeout=300,              # Default: 300s
    max_retries=3,            # Default: 3
    compression=False         # Default: False
)

# Execute query (returns raw tuples)
result = client.execute("SELECT now() AS current_time, version()")

# Get DataFrame (pandas required)
df = client.query_to_df("""
    SELECT table, engine 
    FROM system.tables 
    WHERE database = currentDatabase()
    LIMIT 5
""")
```

## Key Features
- **HTTP Interface** - No native protocol dependency
- **External Tables** - Pass data directly in queries
- **Smart Batching** - Automatic chunking for large results
- **Error Resilient** - Built-in retry mechanism
- **Pandas Support** - Direct DataFrame conversion

## Advanced Examples

### External Tables
```python
data = {
    'users': [
        {'user_id': 1, 'name': 'Alice'},
        {'user_id': 2, 'name': 'Bob'}
    ]
}

external = [{
    'name': 'ext_users',
    'structure': [('user_id', 'UInt32'), ('name', 'String')],
    'data': data['users']
}]

df = client.query_to_df("""
    SELECT u.name, count() as logins
    FROM ext_users u
    JOIN system.query_log q ON q.user = u.name
    GROUP BY u.name
""", external_tables=external)
```

### Batch Processing
```python
# Processes in 100k row batches with auto-retry
large_df = client.query_to_df(
    "SELECT * FROM billion_row_table",
    batch_size=100000,  # Initial batch size
    memory_safe=True    # Enables memory limits
)
```

## Configuration Reference

| Parameter       | Type       | Default     | Description                          |
|-----------------|------------|-------------|--------------------------------------|
| `host`          | str        | -           | Server hostname or IP                |
| `port`          | int/str    | 8123        | HTTP interface port                  |
| `username`      | str        | "default"   | Authentication username              |
| `password`      | str        | ""          | Authentication password              |
| `database`      | str        | "default"   | Default database context             |
| `timeout`       | int        | 300         | Query timeout in seconds             |
| `max_retries`   | int        | 3           | Connection retry attempts            |
| `compression`   | bool       | False       | Enable gzip/deflate compression      |
| `verify_ssl`    | bool       | True        | Verify SSL certificates              |

## License
MIT License - See [LICENSE](LICENSE) for full text.

> **Note**: Requires Python 3.7+ and `requests` package. Pandas needed for DataFrame support.