docker pull mongo:6.0.2

docker run --name mongo -d -p 27017:27017 mongo:6.0.2

pip install pymongo

from pymongo import MongoClient

# 連接到MongoDB
client = MongoClient('localhost', 27017)

# 選擇或創(chuàng)建數(shù)據(jù)庫
db = client['mydatabase']

# 選擇或創(chuàng)建集合
collection = db['mycollection']

# 插入單條數(shù)據(jù)
doc = {"name": "John", "age": 30, "city": "New York"}
result = collection.insert_one(doc)

# 打印插入的文檔的ID
print(result.inserted_id)

# 插入多條數(shù)據(jù)
docs = [
    {"name": "Amy", "age": 25, "city": "Los Angeles"},
    {"name": "Hannah", "age": 22, "city": "Chicago"},
    {"name": "Michael", "age": 27, "city": "Boston"}
]
result = collection.insert_many(docs)

# 打印插入的文檔的ID列表
print(result.inserted_ids)

# 查詢所有文檔
for doc in collection.find():
    print(doc)

# 查詢單個文檔
doc = collection.find_one({"name": "John"})
print(doc)

# 帶條件查詢
docs = collection.find({"age": {"$gt": 25}})
for doc in docs:
    print(doc)

# 模糊查詢
import re
docs = collection.find({"name": re.compile("^J")})
for doc in docs:
    print(doc)

# 使用$regex進行模糊查詢
docs = collection.find({"name": {"$regex": "^J"}})
for doc in docs:
    print(doc)

# 更新單個文檔
query = {"name": "John"}
newvalues = {"$set": {"age": 31}}
result = collection.update_one(query, newvalues)

# 打印匹配和修改的文檔數(shù)量
print(result.matched_count, result.modified_count)

# 更新多個文檔
query = {"age": {"$gt": 25}}
newvalues = {"$set": {"status": "senior"}}
result = collection.update_many(query, newvalues)

# 打印匹配和修改的文檔數(shù)量
print(result.matched_count, result.modified_count)

# 刪除單個文檔
query = {"name": "Amy"}
result = collection.delete_one(query)

# 打印刪除的文檔數(shù)量
print(result.deleted_count)

# 刪除多個文檔
query = {"status": "senior"}
result = collection.delete_many(query)

# 打印刪除的文檔數(shù)量
print(result.deleted_count)

# 創(chuàng)建索引
collection.create_index([("name", pymongo.ASCENDING)])

# 也可以為多個字段創(chuàng)建復(fù)合索引
collection.create_index([("name", pymongo.ASCENDING), ("age", pymongo.DESCENDING)])

# 使用聚合管道
pipeline = [
    {"$match": {"age": {"$gt": 25}}},
    {"$group": {"_id": "$city", "count": {"$sum": 1}}}
]

results = collection.aggregate(pipeline)

for result in results:
    print(result)

from pymongo import MongoClient

# 連接到MongoDB
client = MongoClient('localhost', 27017)

# 確保MongoDB在副本集模式下運行（事務(wù)需要副本集）
db = client['mydatabase']

# 開始一個會話
with client.start_session() as session:
    with session.start_transaction():
        # 在此執(zhí)行事務(wù)操作
        collection1.insert_one(doc1, session=session)
        collection2.insert_one(doc2, session=session)

# 注意：事務(wù)需要在副本集或分片集群上運行

from pymongo import MongoClient

# 創(chuàng)建一個連接池
client = MongoClient('localhost', 27017, maxPoolSize=100)

# 使用client進行數(shù)據(jù)庫操作
db = client['mydatabase']
collection = db['mycollection']

# 操作完成后，連接會自動返回到連接池中

# 設(shè)置游標超時時間
cursor = collection.find().batch_size(10).add_option(pymongo.cursor.NoCursorTimeout)

from pymongo import MongoClient
from gridfs import GridFS

# 連接到MongoDB
client = MongoClient('localhost', 27017)
db = client['mydatabase']

# 創(chuàng)建GridFS實例
fs = GridFS(db)

# 上傳文件
with open('large_file.dat', 'rb') as f:
    file_id = fs.put(f, filename='large_file.dat')

# 下載文件
with fs.get(file_id) as f:
    with open('downloaded_large_file.dat', 'wb') as out:
        out.write(f.read())

import asyncio
from motor.motor_asyncio import AsyncIOMongoClient

async def main():
    client = AsyncIOMongoClient('localhost', 27017)
    db = client['mydatabase']
    collection = db['mycollection']

    # 異步插入文檔
    await collection.insert_one({"name": "John Doe", "age": 30})

    # 異步查詢
    async for doc in collection.find({"age": 30}):
        print(doc)

    # 關(guān)閉連接
    await client.close()

# 運行異步主函數(shù)
asyncio.run(main())