add example usage

Author: jlaneve

README.md

@@ -2,6 +2,45 @@
 
 A framework for generating Apache Airflow DAGs from other workflows.
 
+### Principles
+
+`cosmos` provides a framework for generating Apache Airflow DAGs from other workflows. Every provider comes with two main components:
+
+- `extractors`: These are responsible for extracting the workflow from the provider and converting it into `Task` and `Group` objects.
+- `operators`: These are used when the workflow is converted into a DAG. They are responsible for executing the tasks in the workflow.
+
+`cosmos` is not opinionated in the sense that it does not enforce any rendering method. Rather, it comes with the tools to render workflows as Airflow DAGs, task groups, or individual tasks.
+
+### Example Usage
+
+Imagine we have a dbt project located at `./dbt/my_project`.
+
+```python
+from cosmos.providers.dbt import DbtDag, DbtTaskGroup, DbtTask
+
+# render as a DAG
+dag = DbtDag(
+    project_dir="./dbt/my_project",
+    dag_id="my_dag",
+    schedule_interval="@daily",
+    default_args={"owner": "airflow"},
+)
+
+# render as a task group
+with DAG("my_dag", default_args={"owner": "airflow"}) as dag:
+    task_group = DbtTaskGroup(
+        project_dir="./dbt/my_project",
+        task_group_id="my_task_group",
+    )
+
+# render as an individual task
+with DAG("my_dag", default_args={"owner": "airflow"}) as dag:
+    task = DbtTask(
+        project_dir="./dbt/my_project",
+        task_id="my_task",
+    )
+```
+
 ### Development
 
 We use pre-commit to run a number of checks on the code before committing. To install pre-commit, run:

core/types/group.py core/base/group.py

@@ -1,8 +1,7 @@
 from typing import List
 
-from pydantic import BaseModel, Field
-
 from core.types.task import Task
+from pydantic import BaseModel, Field
 
 
 class Group(BaseModel):