# Programmatic config

It is possible to extend and modify SnowDDL [<mark style="color:purple;">**config**</mark>](/advanced/architecture-overview/config.md) programmatically using pure Python.

A few examples of real business use cases which can be implemented with this technique:

* Get list of users dynamically from single sign-on data provider;
* Generate a view for each table in specific schemas;
* Generate masking policy for each table containing columns named "email" and "phone";
* Skip certain types of objects in DEV environment;

There are not restrictions. Any external data source and any Python package can be used.

### Implementation steps

1. Create a standard directory with [YAML config](/basic/yaml-configs.md). You may optionally fill it with YAML files.
2. Create a sub-directory with name `__custom` (starting with two underscores) in config directory.
3. Place one or more python modules (`.py` files) in `__custom` sub-directory.

During SnowDDL execution YAML configs are resolved first. After that Python modules are resolved one-by-one in alphanumeric order.

It is highly recommended to start module names with zero-padded numbers to make sure you have a precise control of resolution order, for example: `01_foo.py`, `02_bar.py`, `03_baz.py`.

### Module requirements

* Each module should have a function with name `handler`, which accepts instance of [`SnowDDLConfig`](/advanced/architecture-overview/config.md) as a single argument. This function does not return anything.
* In `handler` function you may build [<mark style="color:blue;">**blueprint**</mark>](/advanced/architecture-overview/blueprints.md) objects representing the desired state of objects in Snowflake, and use [<mark style="color:purple;">**config**</mark>](/advanced/architecture-overview/config.md) methods `.add_blueprint()` and `.remove_blueprint()` to manipulate the collection of blueprints.
* You may access existing [<mark style="color:blue;">**blueprints**</mark>](/advanced/architecture-overview/blueprints.md) using methods `.get_blueprints_by_type()` and `.get_blueprints_by_type_and_pattern()`.

### Examples

* Complete example of config with `__custom` sub-directory: <https://github.com/littleK0i/SnowDDL/tree/master/snowddl/_config/sample02_01>
* Example of Python module adding a few custom tables:

```python
from snowddl import DataType, Ident, TableBlueprint, TableColumn, SchemaObjectIdent, SnowDDLConfig


def handler(config: SnowDDLConfig):
    # Add custom tables
    for i in range(1, 5):
        bp = TableBlueprint(
            full_name=SchemaObjectIdent(config.env_prefix, "test_db", "test_schema", f"custom_table_{i}"),
            columns=[
                TableColumn(
                    name=Ident("id"),
                    type=DataType("NUMBER(38,0)"),
                ),
                TableColumn(
                    name=Ident("name"),
                    type=DataType("VARCHAR(255)"),
                ),
            ],
            is_transient=True,
            comment="This table was created programmatically",
        )

        config.add_blueprint(bp)
```

* Example of Python module which scans current config for custom tables and generates a consolidated view dynamically:

```python
from snowddl import SchemaObjectIdent, SnowDDLConfig, TableBlueprint, ViewBlueprint


def handler(config: SnowDDLConfig):
    # Add view combining all custom tables
    parts = []

    for full_name, bp in config.get_blueprints_by_type_and_pattern(TableBlueprint, "test_db.test_schema.custom_table_*").items():
        parts.append(f"SELECT id, name FROM {full_name}")

    bp = ViewBlueprint(
        full_name=SchemaObjectIdent(config.env_prefix, "test_db", "test_schema", "custom_view"),
        text="\nUNION ALL\n".join(parts),
        comment="This view was created programmatically",
    )

    config.add_blueprint(bp)
```


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