mongodb学习经验

0、ObjectId 不能直接return前端，需要2次包裹

一、repl包裹
二、dict包裹
return {'msg': repr(docs)}
return {'code': 1, 'msg': '查询成功', 'data': {'auth_list': repr(result)}}

聚合（$group $match）
cursor = await db.running.aggregate([
    {"$match": {"company_id": {'$in': [3, 1]}}},
    {"$group": {"_id": "$company_id", 'locks': {'$addToSet': '$lock_id'}}},
]).to_list(length=None)

users = await db.user.find({'role_id': {'$in': [1, 2]}}).sort('mobile', -1).skip(1).limit(8).to_list(length=None)

计数
total = coll.count_documents({'name': 'zhangsan'})
total = await db.test.count_documents({'$and': [{'i': {'$gt': 6000000}}, {'i': {'$lt': 6508000}}]})

查询条件
match =  {"company_id": {'$in': [3, 1]}}   # 查符合条件的
match =  {}  # 查全部

1、ObjectId与String相互转换

ObjectId类型 —→ String类型
这个非常简单，直接强制类型转换就可以了
_id = str(ObjectId('类型'))

String类型 —→ ObjectId类型
from bson.objectid import ObjectId
_id = ObjectId("字符串")

2、连接数据库

# 一、AsyncIOMotorClient 异步
DB_CLIENT = AsyncIOMotorClient('127.0.0.1', 27017)
db = DB_CLIENT['xy']  # 库名称

# 二、pymongo 同步
server = "mongodb://127.0.0.1:27017"
conn = pymongo.MongoClient(server)
db1 = conn["xy"]
xyuser = db1.get_collection('xyuser')

3、常用

一、ObjectId返回前端后，可以传参过来直接在_id字段使用
async def mongodb(oid: str, request: Request):
    oid = ObjectId('632bd220c66f6b200868ed6c')
    cursor = db.user.find({'_id': {'$eq': oid}})  # 返回cursor
    docs = await cursor.to_list(None)             # 注意cursor的处理
    print(str(docs[0].get('_id')))

二、插入多个值，返回_id列表
    docs = await Userorg.all().values()
    print(docs)
    insert_many = await db.userorg.insert_many(docs)
    print(insert_many.inserted_ids)
    return {'msg': repr(len(insert_many.inserted_ids))}

三、插入和返回多个值
    result = await db.test.insert_many(
        [{'i': i} for i in range(200000)])
    async for document in db.xyuser.find():
        print(document)
    print('inserted %d docs' % (len(result.inserted_ids),))

四、find（）  cursor
　　cursor = db.test_collection.find({'i': {'$lt': 4}})
　　cursor.sort('i', -1).skip(1).limit(2)  # Modify the query before iterating
　　docs = await cursor.to_list(None)             # 注意cursor的处理
　　async for document in cursor:
    　　print(document)

 

4、增删查改

增
    document = {'key': 'value'}
    result = await db.test_collection.insert_one(document)
    print('result %s' % repr(result.inserted_id))

    result = await db.test_collection.insert_many(
        [{'i': i} for i in range(2000)])
    print('inserted %d docs' % (len(result.inserted_ids),))

删
    n = await coll.count_documents({})
    print('%s documents before calling delete_one()' % n)
    result = await db.test_collection.delete_one({'i': {'$gte': 1000}})
    print('%s documents after' % (await coll.count_documents({})))

    n = await coll.count_documents({})
    print('%s documents before calling delete_many()' % n)
    result = await db.test_collection.delete_many({'i': {'$gte': 1000}})
    print('%s documents after' % (await coll.count_documents({})))

查
    document = await coll.find_one({'i': 51})

    cursor = db.test_collection.find({'i': {'$lt': 4}})
    # Modify the query before iterating
    cursor.sort('i', -1).skip(1).limit(2)
    docs=await cursor.to_list(length=100)
    async for document in cursor:
        pprint.pprint(document)

改
    result = await coll.update_one({'i': 51}, {'$set': {'key': 'value'}})
    print(result.modified_count)

    await coll.update_many({'i': {'$gt': 100}},
                       {'$set': {'key': 'value'}})
    print(result.modified_count)

数
    n = await db.test_collection.count_documents({})
    print('%s documents in collection' % n)
    n = await db.test_collection.count_documents({'i': {'$gt': 1000}})
    print('%s documents where i > 1000' % n)

5、querying

    cursor = db.test_collection.find({'i': {'$lt': 5}}).sort('i')
    for document in await cursor.to_list(length=100):
        pprint.pprint(document)

    c = db.test_collection
    async for document in c.find({'i': {'$lt': 2}}):
        pprint.pprint(document)

    cursor = db.test_collection.find({'i': {'$lt': 4}})
    # Modify the query before iterating
    cursor.sort('i', -1).skip(1).limit(2)
    async for document in cursor:
        pprint.pprint(document)

6、事务

操作
# Use "await" for start_session, but not for start_transaction.
async with await client.start_session() as s:
    async with s.start_transaction():
        await collection.delete_one({'x': 1}, session=s)
        await collection.insert_one({'x': 2}, session=s)

示例
async def coro(session):
    orders = session.client.db.orders
    inventory = session.client.db.inventory
    inserted_id = await orders.insert_one(
        {"sku": "abc123", "qty": 100}, session=session)
    await inventory.update_one(
        {"sku": "abc123", "qty": {"$gte": 100}},
        {"$inc": {"qty": -100}}, session=session)
    return inserted_id

async with await client.start_session() as session:
    inserted_id = await session.with_transaction(coro)

7、增删查改 返回result：（https://pymongo.readthedocs.io/en/stable/api/pymongo/results.html）

class pymongo.results.InsertManyResult(inserted_ids: List[Any], acknowledged: bool)
property acknowledged: bool
property inserted_ids: List

class pymongo.results.InsertOneResult(inserted_id: Any, acknowledged: bool)
property acknowledged: bool
property inserted_id: Any
     #The inserted document’s _id.

class pymongo.results.UpdateResult(raw_result: Dict[str, Any], acknowledged: bool)
     #The return type for update_one(), update_many(), and replace_one().
property acknowledged: bool
property matched_count: int
     # The number of documents matched for this update.
property modified_count: int
     #The number of documents modified.
property raw_result: Dict[str, Any]
     #The raw result document returned by the server.
property upserted_id: Any
     #The _id of the inserted document if an upsert took place. Otherwise None.

 

 

 8、log写入数据库（https://blog.csdn.net/wangteng13/article/details/122110701）

 9、内嵌数组分页

内嵌数组数据
{
    "_id" : ObjectId("5aa877e4aa25752ab4d4cae3"),
    "Records" : [ 
        {
            "Data" : 1962163552.0,
            "RecorDateTime" : ISODate("2018-03-16T10:01:14.931Z")
        }, 
        {
            "Data" : 1111405346.0,
            "RecorDateTime" : ISODate("2018-03-16T08:53:14.931Z")
        },
        ......
    ]
}

分页代码
aggregate(
[
    {"$match" : { "_id" : ObjectId("5aa877e4aa25752ab4d4cae3") } }, 
    { "$unwind" : "$Records" }, 
    { "$project" : { "Records" : "$Records", "_id" : 0 } }, 
    { "$sort" : { "Records.RecorDateTime" : 1 } }, { "$skip" : 30 }, { "$limit" : 10 }
]);

{
  _id: 4,
  grades: [
     { grade: 80, mean: 75, std: 8 },
     { grade: 85, mean: 90, std: 5 },
     { grade: 90, mean: 85, std: 3 }
  ]
}

db.students.update(
   { _id: 4, "grades.grade": 85 },
   { $set: { "grades.$.std" : 6 } }
)

db.students.update(
   {
     _id: 4,
     grades: { $elemMatch: { grade: { $lte: 90 }, mean: { $gt: 80 } } }
   },
   { $set: { "grades.$.std" : 6 } }
)

{
name:"scy",
mArray:[{age:13,weight:50},{age:13,weight:30}]
}

User.update({name:"scy"},{$pull:{"mArray":{"weight":30}}});//删除所有weight属性值为30的对象
db.user.update({'_id': user_id},{$pull:{"company":{"oid": company_id}}}) # 从用户资料中删除内嵌公司id

本方式可用**************************************************

查询内嵌数组
match = {'_id': ObjectId('6331746228d5a457ed763f78')}
users = await db.coltd.find_one(match, {'employee': {'$elemMatch': {"id": "997454981"}}})

修改内嵌数组
match = {'_id': ObjectId('63310eb84fccc40e5f2058f9'), 'company.id': "21807313636737386"}
user = {"company.$.name": '中华人民共和国', "company.$.dept": '中华人民共和国中华人民共和d  国中华人民共和国'}
update = await db.test.update_one(match, {'$set': user})
本方式可用**************************************************

user = {"company.nickname": i.nickname, "company.dept": i.dept}
update = await db.user.aggregate(
    {"$match": {'_id': i.user_id}},
    {"$unwind": "$company"},
    {"$match": {'company.oid': ObjectId(company_id)}},
    {'$set': user}  # 从用户资料中修改内嵌公司相关资料
)

 

10、中间件、执行时间计算、随机数生成二维数组

中间件
@app.middleware("http")
async def add_process_time_header(request: Request, call_next):
    start_time = time.time()
    response = await call_next(request)
    process_time = time.time() - start_time
    response.headers["X-Process-Time"] = str(process_time)
    print(repr(response.__repr__()))
    return response

执行时间计算、随机数生成二维数组
    start_time = time.time()
    array = []
    for i in range(200000):
        row = []
        for j in range(100):
            company = {'id': str(random.randint(10000, 3000000000)), 'name': str(random.randint(10000, 3000000000)),
                       'dept': str(random.randint(10000, 3000000000))}
            row.append(company)
        item = {'i': i, 'company': row}
        array.append(item)

    crate_time = time.time() - start_time
    print(str(crate_time))

    result = await db.test.insert_many(array, ordered=False)

    print('inserted %d docs' % (len(result.inserted_ids),))
    insert_time = time.time() - start_time
    print(str(insert_time))

11、聚合代码（可用）

本方式可用**************************************************

1、查询内嵌数组并展开后输出多条数据

    start_time = time.time()
    companys = await db.test.aggregate([
        {'$match': {'_id': ObjectId('6331038c29964c0e72facb1d')}},
        {"$unwind": "$company"},
        {'$skip': 8},
        {'$limit': 8},
        {'$project': {'_id': 0, 'company.id': 1}}
    ]).to_list(length=None)
    crate_time = time.time() - start_time
    print(str(crate_time))
    print(companys)

2、查询内嵌数组中单条数据

match = {'_id': ObjectId('6331746228d5a457ed763f78')}
users = await db.coltd.find_one(match, {'employee': {'$elemMatch': {"id": "997454981"}}})

3、修改内嵌数组
match = {'_id': ObjectId('63310eb84fccc40e5f2058f9'), 'company.id': "21807313636737386"}
user = {"company.$.name": '中华人民共和国', "company.$.dept": '中华人民共和国中华人民共和d  国中华人民共和国'}
update = await db.test.update_one(match, {'$set': user})

本方式可用**************************************************