From d1183168b8e1ebb9ebf75c3ac0b05a8cad3dabd8 Mon Sep 17 00:00:00 2001
From: Backend IM Bot <bot@backend.im>
Date: Tue, 25 Mar 2025 15:18:23 +0100
Subject: [PATCH] Update code in endpoints/girl.get.py

---
 endpoints/girl.get.py | 80 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 80 insertions(+)
 create mode 100644 endpoints/girl.get.py

diff --git a/endpoints/girl.get.py b/endpoints/girl.get.py
new file mode 100644
index 0000000..e386592
--- /dev/null
+++ b/endpoints/girl.get.py
@@ -0,0 +1,80 @@
+Sure, here's an example of a FastAPI endpoint that returns a list of girls from the database using SQLAlchemy and Pydantic:
+
+```python
+from fastapi import APIRouter, Depends
+from sqlalchemy.orm import Session
+from typing import List
+
+from database import get_db
+from models import Girl
+from schemas import GirlSchema
+
+router = APIRouter()
+
+@router.get("/girl", response_model=List[GirlSchema])
+def get_girls(db: Session = Depends(get_db)):
+    girls = db.query(Girl).all()
+    return girls
+```
+
+**Explanation:**
+
+1. We import the necessary modules and classes from FastAPI, SQLAlchemy, and Pydantic.
+2. We create an instance of `APIRouter` to define our endpoint routes.
+3. We define the `get_girls` function, which is a GET endpoint at `/girl`.
+4. The `response_model` parameter specifies that the response will be a list of `GirlSchema` objects.
+5. We use the `Depends` function to inject the database session (`db`) as a dependency.
+6. Inside the function, we query the `Girl` model from the database using `db.query(Girl).all()`.
+7. We return the list of `Girl` objects, which will be automatically converted to `GirlSchema` objects by Pydantic.
+
+**Models and Schemas:**
+
+Here's an example of the `Girl` model and `GirlSchema` schema:
+
+```python
+# models.py
+from sqlalchemy import Column, Integer, String
+from database import Base
+
+class Girl(Base):
+    __tablename__ = "girls"
+
+    id = Column(Integer, primary_key=True, index=True)
+    name = Column(String)
+    age = Column(Integer)
+```
+
+```python
+# schemas.py
+from pydantic import BaseModel
+
+class GirlSchema(BaseModel):
+    id: int
+    name: str
+    age: int
+
+    class Config:
+        orm_mode = True
+```
+
+In this example, the `Girl` model is a SQLAlchemy model that defines the `girls` table with columns for `id`, `name`, and `age`. The `GirlSchema` is a Pydantic model that defines the shape of the data that will be returned by the API endpoint.
+
+When you make a GET request to `/girl`, the API will return a JSON response containing a list of girls, like this:
+
+```json
+[
+  {
+    "id": 1,
+    "name": "Alice",
+    "age": 25
+  },
+  {
+    "id": 2,
+    "name": "Bob",
+    "age": 30
+  },
+  ...
+]
+```
+
+Note that you'll need to set up the database connection and create the necessary tables before running this code. Additionally, you may want to add error handling, authentication, and other features to make the API more robust and secure.
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