使用FastAPI和React以及MongoDB構建全棧Web應用04 MongoDB快速入門

一、NoSQL 概述

1.1 了解關系數據庫的局限性

Before diving into NoSQL, it’s essential to understand the challenges posed by traditional Relational Database Management Systems (RDBMS). While RDBMS have been the cornerstone of data management for decades, they face limitations when dealing with massive datasets, complex data structures, and high-performance demands.

Scalability Issues: RDBMS often struggle with horizontal scaling, making it challenging to handle increasing data volumes and user loads.
Data Structure Rigidity: The rigid schema of RDBMS can hinder flexibility, especially when dealing with rapidly evolving data structures.
Complex Queries: Complex queries on large datasets can be computationally expensive and slow in RDBMS.

在深入研究 NoSQL 之前，了解傳統關系數據庫管理系統（RDBMS）帶來的挑戰至關重要。雖然 RDBMS 幾十年來一直是數據管理的基石，但在處理海量數據集、復雜數據結構和高性能需求時，它們面臨著限制。

可擴展性問題： RDBMS 經常難以進行水平擴展，這使得處理不斷增長的數據量和用戶負載變得具有挑戰性。
數據結構剛性： RDBMS 的僵化架構會阻礙靈活性，尤其是在處理快速發展的數據結構時。
復雜查詢：在 RDBMS 中，對大型數據集的復雜查詢可能計算成本高昂且速度緩慢。

1.2 什么是NoSQL?

NoSQL, which stands for “Not Only SQL,” is a broad category of database management systems that offer alternatives to traditional relational databases. These databases are designed to handle large volumes of unstructured or semi-structureddata with high performance and scalability.

NoSQL 代表“不僅僅是 SQL”，是一大類數據庫管理系統，可替代傳統的關系數據庫。這些數據庫旨在以高性能和可擴展性處理大量非結構化或半結構化數據。

Key Characteristics of NoSQL Databases:

Flexible Data Models: NoSQL databases support various data models, including document, key-value, wide-column, and graph, allowing for more adaptable data structures.
Scalability: They excel at horizontal scaling, enabling you to distribute data across multiple servers to handle increasing loads.
High Performance: NoSQL databases are often optimized for fast read and write operations, making them suitable for real-time applications.
Distributed Systems: Many NoSQL databases are designed for distributed environments, providing fault tolerance and high availability.

NoSQL 數據庫的主要特點：

靈活的數據模型：NoSQL 數據庫支持各種數據模型，包括文檔、鍵值、寬列和圖形，允許使用更具適應性的數據結構。
可擴展性： 它們擅長水平擴展，使您能夠在多個服務器之間分配數據以處理不斷增加的負載。
高性能： NoSQL 數據庫通常針對快速讀寫操作進行了優化，使其適用于實時應用程序。
分布式系統： 許多 NoSQL 數據庫都是為分布式環境設計的，提供容錯和高可用性。

1.3 NoSQL 數據庫類型

Document Databases:

Store data in flexible JSON-like documents.
Examples: MongoDB, Couchbase
Ideal for: Content management systems, user profiles, and application data.

文檔數據庫：

將數據存儲在靈活的類似 JSON 的文檔中。
示例：MongoDB、Couchbase
適用于：內容管理系統、用戶配置文件和應用程序數據。

Key-Value Stores:

Store data as simple key-value pairs.
Examples: Redis, Amazon DynamoDB
Ideal for: Session management, caching, and high-performance counters.

鍵值存儲：

將數據存儲為簡單的鍵值對。
示例：Redis、Amazon DynamoDB
適用于：會話管理、緩存和高性能計數器。

Wide-Column Stores:

Store data in columns, allowing for flexible schema and efficient data retrieval.
Examples: Cassandra, HBase
Ideal for: Time-series data, analytics, and large-scale data processing.

寬列存儲：

將數據存儲在列中，從而實現靈活的架構和高效的數據檢索。
示例：Cassandra、HBase
適用于：時間序列數據、分析和大規模數據處理。

Graph Databases:

Store data as nodes and relationships between them.
Examples: Neo4j, Amazon Neptune
Ideal for: Social networks, recommendation systems, and fraud detection.

圖形數據庫：

將數據存儲為節點以及它們之間的關系。
示例：Neo4j、Amazon Neptune
適用于：社交網絡、推薦系統和欺詐檢測。

1.4 MongoDB數據庫

MongoDB, a document-oriented NoSQL database, is widely used in web applications. Its flexibility, scalability, and rich feature set make it a popular choice for developers.

MongoDB 是一種面向文檔的 NoSQL 數據庫，廣泛用于 Web 應用程序。它的靈活性、可擴展性和豐富的功能集使其成為開發人員的熱門選擇。

Basic MongoDB Concepts:

Database: A container for collections.
Collection: A group of documents.
Document: A JSON-like structure representing a record.

基本 MongoDB 概念：

數據庫： 集合的容器。
集合： 一組文檔。
文檔：表示記錄的類似 JSON 的結構。

1.5 MongoDB 使用步驟

To build a web application using FastAPI, React, and MongoDB, you’ll typically follow these steps:

要使用 FastAPI、React 和 MongoDB 構建 Web 應用程序，您通常需要遵循以下步驟：

Set up the MongoDB environment: Install MongoDB and create a database.

設置 MongoDB 環境：安裝 MongoDB 并創建數據庫。

Create a FastAPI backend:

Install required libraries: fastapi, pymongo, uvicorn
Establish a connection to the MongoDB database:

創建一個 FastAPI 后端：

安裝所需的庫：fastapi、pymongo、uvicorn
建立與 MongoDB 數據庫的連接：

Create a React frontend:

Use a library like axios to make requests to the FastAPI backend.
Display data retrieved from the backend.
Allow users to create and update data.

創建一個 React 前端：

使用像 axios 這樣的庫向 FastAPI 后端發出請求。
顯示從后端檢索到的數據。
允許用戶創建和更新數據。

1.6 使用 NoSQL 的優勢

Advantages of Using NoSQL

Scalability: Handle massive datasets and high traffic efficiently.
Flexibility: Adapt to changing data structures without major schema modifications.
Performance: Achieve fast read and write operations.
Cost-effectiveness: Often lower hardware and maintenance costs compared to RDBMS.

使用 NoSQL 的優勢

可擴展性：高效處理海量數據集和高流量。
靈活性：適應不斷變化的數據結構，無需進行重大架構修改。
性能：實現快速讀寫作。
成本效益：與 RDBMS 相比，通常更低的硬件和維護成本。

1.7 何時使用 NoSQL

When to Use NoSQL

Large volumes of unstructured or semi-structured data.
High write throughput and low latency requirements.
Complex data structures that evolve over time.
Horizontal scalability needs.

何時使用 NoSQL

大量非結構化或半結構化數據。
高寫入吞吐量和低延遲要求。
隨時間演變的復雜數據結構。
水平可擴展性需求。

NoSQL databases offer a powerful and flexible alternative to traditional relational databases. By understanding the different types of NoSQL databases and their use cases, you can make informed decisions about when and how to leverage them in your web applications. MongoDB, with its document-oriented model, is a popular choice for many developers due to its ease of use and scalability.

NoSQL 數據庫為傳統關系數據庫提供了強大而靈活的替代方案。通過了解不同類型的 NoSQL 數據庫及其使用案例，您可以就何時以及如何在 Web 應用程序中利用它們做出明智的決策。MongoDB 具有面向文檔的模型，由于其易用性和可擴展性，是許多開發人員的熱門選擇。

For our web application, we’ll focus on MongoDB as our NoSQL database. It’s a popular choice due to its flexibility, scalability, and ease of use. Let’s consider a simple blog application as an example.

對于我們的 Web 應用程序，我們將重點關注 MongoDB 作為我們的 NoSQL 數據庫。由于其靈活性、可擴展性和易用性，它是一個受歡迎的選擇。讓我們以一個簡單的博客應用程序為例。

1.8 博客列表實戰

Before we start coding, let’s define our data structure. In MongoDB, we use collections to store similar documents. For our blog, we might have collections for:

posts: Stores blog posts with title, content, author, creation date, etc.
users: Stores user information like username, email, password, etc.
comments: Stores comments for each post with comment text, author, and timestamp.

在開始編碼之前，我們先定義一下數據結構。在 MongoDB 中，我們使用集合來存儲類似的文檔。對于我們的博客，我們可能有以下集合：

posts：存儲包含標題、內容、作者、創建日期等的博客文章。
users：存儲用戶名、電子郵件、密碼等用戶信息。
comments：存儲每個帖子的評論以及評論文本、作者和時間戳。

后端代碼：

from bson import ObjectId
from fastapi import FastAPI, HTTPException
from pymongo import MongoClient
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModelapp = FastAPI()
# MongoDB 連接對象
client = MongoClient("mongodb://zhangdapeng:zhangdapeng520@localhost:27017/")
# 數據庫
db = client["blog_db"]
# 博客集合
posts = db["posts"]
# 用戶集合
users = db["users"]
# 評論集合
comments = db["comments"]# 配置跨域
app.add_middleware(CORSMiddleware,allow_origins=["*"],allow_credentials=True,allow_methods=["*"],allow_headers=["*"],
)class Post(BaseModel):"""博客模型"""# 標題title: str# 內容content: str# 作者author: str# 創建時間created_at: strclass User(BaseModel):"""用戶模型"""# 用戶名username: str# 郵箱email: str# 密碼password: strclass Comment(BaseModel):"""評論模型"""# 博客IDpost_id: str# 作者author: str# 評論文本text: str# 評論時間created_at: str@app.post("/posts", summary="創建博客", description="創建一個新的博客")
async def create_post(post: Post):result = posts.insert_one(post.dict())return {"post_id": str(result.inserted_id)}@app.get("/posts", summary="獲取所有博客", description="獲取所有博客")
async def get_posts():all_posts = list(posts.find())data = []for post in all_posts:post["_id"] = str(post["_id"])data.append(post)return dataif __name__ == '__main__':import uvicornuvicorn.run(app, host="0.0.0.0", port=8080)

測試JSON：

{"title": "測試博客","content": "今天學習了fastapi+React前后端分離開發","author": "源滾滾編程","created_at": "2025-05-10 12:33:33"
}

前端渲染：

import {useEffect, useState} from "react";
import axios from "axios";function App() {// 博客列表數據const [posts, setPosts] = useState([]);// 會在頁面加載時執行useEffect(() => {axios.get('http://localhost:8080/posts').then(res => {console.log("fastapi傳過來的數據", res.data)setPosts(res.data);}).catch(err => {console.log(err);});}, [])return (<><div><h1>博客列表</h1><div>{posts.map((blog) => (<div key={blog._id} className="blog-card"><h2>{blog.title}</h2><p>{blog.content}</p><p>作者: {blog.author}</p><p>創建時間: {blog.created_at}</p></div>))}</div></div></>)
}export default App

Key Advantages of Using MongoDB in this Scenario

Flexible data structure: Easily adapt to changes in post or user information.
Scalability: Handle increasing numbers of posts, users, and comments efficiently.
Performance: MongoDB is optimized for fast read and write operations.
Rich query language: MongoDB’s query language allows for complex data retrieval.

在此場景中使用 MongoDB 的主要優勢

靈活的數據結構： 輕松適應帖子或用戶信息的變化。
可擴展性：有效處理越來越多的帖子、用戶和評論。
性能：MongoDB 針對快速讀寫作進行了優化。
豐富的查詢語言：MongoDB 的查詢語言允許復雜的數據檢索。

Additional Considerations

Indexing: Create appropriate indexes to improve query performance.
Data validation: Use Pydantic or built-in MongoDB validation for data integrity.
Security: Implement proper authentication and authorization mechanisms.
Error handling: Handle potential errors gracefully.

其他注意事項

索引：創建適當的索引以提高查詢性能。
數據驗證：使用 Pydantic 或內置 MongoDB 驗證來實現數據完整性。
安全性：實施適當的身份驗證和授權機制。
錯誤處理：妥善處理潛在錯誤。

二、理解MongoDB

2.1 什么是 MongoDB

MongoDB is a popular NoSQL database that uses a document-oriented data model. Unlike traditional relational databases, which store data in tables, MongoDB stores data in flexible, JSON-like documents. This provides significant advantages in terms of scalability, performance, and ease of development.

MongoDB 是一種流行的 NoSQL 數據庫，它使用面向文檔的數據模型。與將數據存儲在表中的傳統關系數據庫不同，MongoDB 將數據存儲在靈活的類似 JSON 的文檔中。這在可伸縮性、性能和易開發性方面提供了顯著的優勢。

Core Concepts

Document: A fundamental unit of data storage in MongoDB. It’s a key-value pair structure similar to JSON.
Collection: A group of documents. Think of it as a table in a relational database.
Database: A container for collections.

核心概念

文檔：MongoDB 中數據存儲的基本單元。它是一個類似于 JSON 的鍵值對結構。
集合：一組文檔。將其視為關系數據庫中的表。
數據庫：集合的容器。

2.2 MongoDB 的靈活性

One of the key strengths of MongoDB is its flexible schema. This means you don’t need to define a rigid structure for your documents upfront. You can add or remove fields as needed, making it ideal