> ## Documentation Index
> Fetch the complete documentation index at: https://kumo.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Snowflake Connector

> Connect KumoRFM to data stored in Snowflake

KumoRFM can connect directly to Snowflake data warehouses, enabling predictions on enterprise-scale data without moving it out of Snowflake.

## Installation

The Snowflake backend requires the Snowflake connector:

```bash theme={null}
pip install kumoai[snowflake]
```

## Quick Start

**From a Snowflake notebook** (uses the active session automatically):

```python theme={null}
import kumoai.rfm as rfm

graph = rfm.Graph.from_snowflake(database="MY_DATABASE", schema="MY_SCHEMA")
```

**With explicit credentials:**

```python theme={null}
graph = rfm.Graph.from_snowflake(
    connection={
        "account": "my_account",
        "user": "my_user",
        "password": "my_password",
        "warehouse": "my_warehouse",
    },
    database="MY_DATABASE",
    schema="MY_SCHEMA",
)
```

This will:

1. Connect to the Snowflake database and schema
2. Discover all tables in the schema
3. Infer column metadata (data types, semantic types, primary keys, time columns)
4. Detect foreign key relationships
5. Print a summary of the inferred metadata and links

## Specifying Tables

Control which tables to include and customize their configuration:

```python theme={null}
graph = rfm.Graph.from_snowflake(
    tables=[
        "USERS",                                           # Include by name
        dict(name="ORDERS", source_name="ORDERS_SNAPSHOT"),# Rename source
        dict(name="ITEMS", schema="OTHER_SCHEMA"),         # Different schema
    ],
    database="DEFAULT_DB",
    schema="DEFAULT_SCHEMA",
)
```

Table configuration options:

| Key           | Description                                                   | Required |
| ------------- | ------------------------------------------------------------- | -------- |
| `name`        | The table name used in PQL queries                            | Yes      |
| `source_name` | The actual table name in Snowflake (if different from `name`) | No       |
| `database`    | Override the default database for this table                  | No       |
| `schema`      | Override the default schema for this table                    | No       |
| `primary_key` | Override the auto-detected primary key                        | No       |

## Connection Options

There are several ways to establish a Snowflake connection:

**1. Active session** (Snowflake notebooks):

```python theme={null}
# No connection needed — uses the active Snowpark session
graph = rfm.Graph.from_snowflake(database="MY_DATABASE", schema="MY_SCHEMA")
```

**2. Credentials dictionary:**

```python theme={null}
graph = rfm.Graph.from_snowflake(connection={
    "account": "my_account",
    "user": "my_user",
    "password": "my_password",
    "warehouse": "my_warehouse",
})
```

**3. Existing connection:**

```python theme={null}
import snowflake.connector
conn = snowflake.connector.connect(...)
graph = rfm.Graph.from_snowflake(connection=conn, schema="MY_SCHEMA")
```

## Database and Schema Defaults

The `database` and `schema` parameters set defaults for all tables. If not specified, the current database and schema from the active session are used.

Individual tables can override these defaults using the `database` and `schema` keys in their configuration dictionary.

## Controlling Metadata Inference

```python theme={null}
graph = rfm.Graph.from_snowflake(
    schema="MY_SCHEMA",
    infer_metadata=False,  # Skip automatic type inference
    verbose=False,         # Suppress output
)

# Manually configure metadata afterwards:
graph.infer_metadata()
graph.infer_links()
```

## Manual Edge Specification

```python theme={null}
graph = rfm.Graph.from_snowflake(
    schema="MY_SCHEMA",
    edges=[
        ("ORDERS", "USER_ID", "USERS"),
        ("ORDERS", "ITEM_ID", "ITEMS"),
    ],
)
```

## Supported Snowflake Types

KumoRFM maps Snowflake data types as follows:

| Snowflake Type                                 | KumoRFM Dtype    | Default Stype      |
| ---------------------------------------------- | ---------------- | ------------------ |
| NUMBER, DECIMAL, INT, BIGINT, FLOAT, DOUBLE    | `float` or `int` | numerical          |
| VARCHAR, STRING, TEXT, CHAR                    | `string`         | categorical / text |
| BOOLEAN                                        | `bool`           | categorical        |
| DATE, TIMESTAMP, TIMESTAMP\_NTZ, TIMESTAMP\_TZ | `date`           | timestamp          |
| ARRAY                                          | `stringlist`     | multicategorical   |
| VECTOR                                         | `floatlist`      | sequence           |