pipeline_penguin

"""pipeline_penguin is a python library used for validating data pipelines. It works by building
an abstraction of the data sources in your pipeline (represented as DataNodes) and setting up
expected behaviours (represented as DataPremises) for each of their columns.

Location: pipeline_penguin/

Example usage:

```python
pipe = PipelinePenguin()

# creating a node
pipe.nodes.create_node(
    name="Pipeline X - Table Y",
    node_factory=DataNodeBigQuery,
    project_id= "teste",
    dataset_id= "dataset_test",
    table_id= "table",
)

# Adding a connetor
bq_connector = ConnectorSQLBigQuery(credentials_path="credentials.json")
pipe.connectors.define_default(bq_connector) # Registering bq_connector
```

"""
from .data_node import NodeManager
from .connector import ConnectorManager


class PipelinePenguin:
    def __init__(self):
        """Constructor for instantiating the PipelinePenguin object.

        Attributes:
            nodes: NodeManager instance, storing all DataNode objects for the project
            conectors: ConnetorManager instance, storing the default Connector objects used in the
            project.
        """
        self.nodes = NodeManager()
        self.connectors = ConnectorManager()

class PipelinePenguin:
    def __init__(self):
        """Constructor for instantiating the PipelinePenguin object.

        Attributes:
            nodes: NodeManager instance, storing all DataNode objects for the project
            conectors: ConnetorManager instance, storing the default Connector objects used in the
            project.
        """
        self.nodes = NodeManager()
        self.connectors = ConnectorManager()