# Snowflake integration

The `SnowflakeConnection` class enables seamless connectivity and data operations on **Snowflake** within the Datalake infrastructure. It is designed for AI agents and developers who need to read/write structured data securely and efficiently from Snowflake databases.

***

### Requirements

* A valid Snowflake account
* A user with appropriate read/write access
* The `groclake.datalake.connection` module

***

###  Class: `SnowflakeConnection`

Handles secure connection establishment, data querying, and writing to Snowflake.

***

#### Constructor

```python
SnowflakeConnection(config: dict)
```

**Parameters:**

* `config` (`dict`): Connection configuration dictionary containing:

  | Key         | Description                  | Example Value        |
  | ----------- | ---------------------------- | -------------------- |
  | `user`      | Snowflake username           | `"your_user"`        |
  | `password`  | Snowflake password           | `"your_password"`    |
  | `account`   | Snowflake account identifier | `"xyz12345.us-east"` |
  | `warehouse` | Compute warehouse name       | `"COMPUTE_WH"`       |
  | `database`  | Database to connect to       | `"your_database"`    |
  | `schema`    | Schema within the database   | `"your_schema"`      |

***

#### Method: `connect()`

Establishes a live connection to the Snowflake instance using the provided credentials.

**Example:**

```python
conn = SnowflakeConnection(config)
conn.connect()
```

***

#### Method: `read(query: str) → list[dict]`

Executes a `SELECT` query and returns the result as a list of dictionaries.

**Example:**

```python
result = conn.read('SELECT * FROM "your_database".your_schema.employee;')
print(result)
```

***

#### Method: `write(query: str, data: tuple)`

Executes an `INSERT`, `UPDATE`, or `DELETE` query with parameterized values.

**Example:**

```python
insert_query = """
INSERT INTO "your_database".your_schema.employee (id, name, age, department, salary)
VALUES (%s, %s, %s, %s, %s);
"""
data = (3, 'John', 52, 'Electrical', 60000)
conn.write(insert_query, data)
```

***

#### Method: `close()`

Closes the active Snowflake connection.

**Example:**

```python
pythonCopyEditconn.close()
```

***

#### ✅ Full Example

```python
from groclake.datalake.connection import SnowflakeConnection

config = {
    "user": "your_user",
    "password": "your_password",
    "account": "your_account_id",
    "warehouse": "COMPUTE_WH",
    "database": "your_database",
    "schema": "your_schema"
}

conn = SnowflakeConnection(config)
conn.connect()

# Read from table
print(conn.read('SELECT * FROM "your_database".your_schema.employee;'))

# Insert into table
insert_query = """
INSERT INTO "your_database".your_schema.employee (id, name, age, department, salary)
VALUES (%s, %s, %s, %s, %s);
"""
data = (3, 'John', 52, 'Electrical', 60000)
conn.write(insert_query, data)

print("Data inserted successfully!")

conn.close()
```

***

#### 🛡️ Best Practices

* Always store credentials securely using environment variables or secrets management tools.
* Use parameterized queries to avoid SQL injection.
* Limit access privileges for the user specified in the config for safer operation


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.groclake.ai/lakes/data-and-model-management/datalake/markdown-3/snowflake-integration.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.