一、下载软件
1.https://pypi.python.org/pypi/pymongo/#downloads 下载 PYMONGO
下载后 用命令提示符 cmd进入目录 并运行命令 python setup.py install
2.下载 xlrd https://pypi.python.org/pypi/xlrd
利用pymongo包进行数据库的连接，使用xlrd包读取excel数据，由于二者数据结构的不同，要将excel格式数据转换为json格式数据。由于编码问题会出现“TypeError: ‘str‘ object does not support item assignment”，要利用json.loads方法对数据进行解码
代码如下
#coding=utf-8
import xlrd
import sys
import json
import pymongo
from pymongo import MongoClient
#连接数据库
client=MongoClient(‘localhost‘,27017)
db=client.scrapy
account=db.weibo
data=xlrd.open_workbook(‘test.xlsx‘)
table=data.sheets()[0]
#读取excel第一行数据作为存入mongodb的字段名
rowstag=table.row_values(0)
nrows=table.nrows
#ncols=table.ncols
#print rows
returnData={}
for i in range(1,nrows):
#将字段名和excel数据存储为字典形式，并转换为json格式
returnData[i]=json.dumps(dict(zip(rowstag,table.row_values(i))))
#通过编解码还原数据
returnData[i]=json.loads(returnData[i])
#print returnData[i]
account.insert(returnData[i])
MongoDB
是由C++语言编写的，是一个基于分布式文件存储的开源数据库系统。
在高负载的情况下，添加更多的节点，可以保证服务器性能。
MongoDB 旨在为WEB应用提供可扩展的高性能数据存储解决方案。
MongoDB 将数据存储为一个文档，数据结构由键值(key=>value)对组成。MongoDB 文档类似于 JSON 对象。字段值可以包含其他文档，数组及文档数组。
1.创建连接
import pymongo client = pymongo.MongoClient(‘mongodb://localhost:27017‘) #或 #client = pymongo.MongoClient(‘localhost‘，‘27017‘) ## 如果设置了权限,注意xxx用户权限要可以cover到后面使用到的数据库# client = pymongo.MongoClient(‘10.134.80.119‘, 20000, username=‘xxx‘, password=‘xxx‘)
2.连接数据库
#操作test数据库db_name = ‘test‘ db = client[db_name]
3.选择要操作的集合(表)
collection_set01 = db[‘set01‘]
下面就可以使用collection_set01进行增删改查操作了.
4.增删改查操作
- 增
‘‘‘
###################--插入文档--####################
save() vs insert()
mongodb的save和insert函数都可以向collection里插入数据，但两者是有两个区别
1. save函数实际就是根据参数条件,调用了insert或update函数.如果想插入的数据对象存在,insert函数会报错,而save函数是改变原来的对象;如果想插入的对象不存在,那么它们执行相同的插入操作.这里可以用几个字来概括它们两的区别,即所谓"有则改之,无则加之".
2. insert可以一次性插入一个列表，而不用遍历，效率高， save则需要遍历列表，一个个插入.
‘‘‘
record_l = [
{‘_id‘:0,‘name‘: ‘zzzzz‘,‘age‘: -27,‘high‘: 176},
{‘_id‘:1,‘name‘: ‘zhangweijian‘,‘age‘: 27,‘high‘: 171},
{‘_id‘:2,‘name‘: ‘zhang‘,‘age‘: 26,‘high‘: 173},
{‘_id‘:3,‘name‘: ‘wei‘,‘age‘: 29,‘high‘: 180},
{‘_id‘:4,‘name‘: ‘weijian‘,‘age‘: 30,‘high‘: 158},
{‘_id‘:5,‘name‘: ‘zhangjian‘,‘age‘: 22,‘high‘: 179},
{‘_id‘:6,‘name‘: ‘zwj‘,‘age‘: 19,‘high‘: 166},
{‘_id‘:100,‘name‘: ‘zwj‘,‘age‘: 19,‘list‘:[2,3,5]},
{‘_id‘:101,‘name‘: ‘zwj‘,‘age‘: 19,‘list‘:[1,2,3,4,5,6,7]},
]
try:
for record in record_l:
collection_set01.save(record)
except pymongo.errors.DuplicateKeyError:
print ‘record exists‘
except Exception as e:
print e
- 删
####################--删除数据--####################
remove()
delete_one(self, filter, collation=None)
delete_many(self, filter, collation=None)
>>> db.test.count({‘x‘: 1})
3
>>> result = db.test.delete_one({‘x‘: 1})
>>> result.deleted_count
1
>>> db.test.count({‘x‘: 1})
2
:Parameters:
- `filter`: A query that matches the document to delete.
- `collation` (optional): An instance of
:class:`~pymongo.collation.Collation`. This option is only supported
on MongoDB 3.4 and above.
:Returns:
- An instance of :class:`~pymongo.results.DeleteResult`.
‘‘‘
newinsert1 = {‘_id‘:7,‘comment‘:‘test delete‘}
newinsert2 = {‘_id‘:8,‘comment‘:‘test delete‘}
newinsert3 = {‘_id‘:9,‘comment‘:‘test delete‘}
collection_set01.save(newinsert1)
collection_set01.save(newinsert2)
collection_set01.save(newinsert3)
remove_before = collection_set01.find()
print ‘delete before‘
for obj in remove_before:
print obj
collection_set01.delete_many({‘_id‘:{‘$gt‘:6,‘$lt‘:100}}) #删除所有满足条件的文档,删除_id大于6，小于100
collection_set01.delete_one({‘_id‘:6}) #删除一条满足条件的文档,删除_id=6
#collection_set01.delete_many({}) #删除整个集合
remove_after = collection_set01.find()
print ‘delete after‘
for obj in remove_after:
print obj
#输出结果delete before{u‘comment‘: u‘after replace_one operation just exists comment(key)‘, u‘_id‘: 1}{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}{u‘high‘: 166, u‘age‘: 19, u‘_id‘: 6, u‘name‘: u‘zwj‘}{u‘comment‘: u‘test delete‘, u‘_id‘: 7}{u‘comment‘: u‘test delete‘, u‘_id‘: 8}{u‘comment‘: u‘test delete‘, u‘_id‘: 9}delete after{u‘comment‘: u‘after replace_one operation just exists comment(key)‘, u‘_id‘: 1}{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}
- 改
‘‘‘
###################--更新数据--####################
replace_one(self, filter, replacement, upsert=False, bypass_document_validation=False, collation=None)
update_one(self, filter, update, upsert=False, bypass_document_validation=False, collation=None)
update_many(self, filter, update, upsert=False, bypass_document_validation=False, collation=None)
‘‘‘
collection_set01.replace_one({‘_id‘: 1},{‘comment‘: ‘after replace_one operation just exists comment(key)‘}) #replace_one用指定的key-value替代原来所有的key-value
collection_set01.update_one({ "high" : { ‘$gt‘ : 170 } } , { ‘$set‘ : { "comment" : "更新于身高高于170的一条记录"}}) #update_one更新已经对应的key-value，其它不变
collection_set01.update_many({‘high‘:{‘$gt‘:171}},{‘$set‘:{‘comment‘:‘use update_many‘}}) #同上，能够update所有符合匹配条件的文档
- 查
‘‘‘
########################--查询--###################
find(self, filter=None, *args, **kwargs)
find_one(self, filter=None, *args, **kwargs)
params:projection/limit/skip
‘‘‘
find方法源码
find(self, *args, **kwargs) method of pymongo.collection.Collection instance
Query the database.
The `filter` argument is a prototype document that all results
must match. For example:
>>> db.test.find({"hello": "world"})
only matches documents that have a key "hello" with value
"world". Matches can have other keys *in addition* to
"hello". The `projection` argument is used to specify a subset
of fields that should be included in the result documents. By
limiting results to a certain subset of fields you can cut
down on network traffic and decoding time.
Raises :class:`TypeError` if any of the arguments are of
improper type. Returns an instance of
:class:`~pymongo.cursor.Cursor` corresponding to this query.
The :meth:`find` method obeys the :attr:`read_preference` of
this :class:`Collection`.
:Parameters:
- `filter` (optional): a SON object specifying elements which
must be present for a document to be included in the
result set
- `projection` (optional): a list of field names that should be
returned in the result set or a dict specifying the fields
to include or exclude. If `projection` is a list "_id" will
always be returned. Use a dict to exclude fields from
the result (e.g. projection={‘_id‘: False}).
- `skip` (optional): the number of documents to omit (from
the start of the result set) when returning the results
- `limit` (optional): the maximum number of results to
return
- `no_cursor_timeout` (optional): if False (the default), any
returned cursor is closed by the server after 10 minutes of
inactivity. If set to True, the returned cursor will never
time out on the server. Care should be taken to ensure that
cursors with no_cursor_timeout turned on are properly closed.
- `cursor_type` (optional): the type of cursor to return. The valid
options are defined by :class:`~pymongo.cursor.CursorType`:
- :attr:`~pymongo.cursor.CursorType.NON_TAILABLE` - the result of
this find call will return a standard cursor over the result set.
- :attr:`~pymongo.cursor.CursorType.TAILABLE` - the result of this
find call will be a tailable cursor - tailable cursors are only
for use with capped collections. They are not closed when the
last data is retrieved but are kept open and the cursor location
marks the final document position. If more data is received
iteration of the cursor will continue from the last document
received. For details, see the `tailable cursor documentation
<http://www.mongodb.org/display/DOCS/Tailable+Cursors>`_.
- :attr:`~pymongo.cursor.CursorType.TAILABLE_AWAIT` - the result
of this find call will be a tailable cursor with the await flag
set. The server will wait for a few seconds after returning the
full result set so that it can capture and return additional data
added during the query.
- :attr:`~pymongo.cursor.CursorType.EXHAUST` - the result of this
find call will be an exhaust cursor. MongoDB will stream batched
results to the client without waiting for the client to request
each batch, reducing latency. See notes on compatibility below.
- `sort` (optional): a list of (key, direction) pairs
specifying the sort order for this query. See
:meth:`~pymongo.cursor.Cursor.sort` for details.
- `allow_partial_results` (optional): if True, mongos will return
partial results if some shards are down instead of returning an
error.
- `oplog_replay` (optional): If True, set the oplogReplay query
flag.
- `modifiers` (optional): A dict specifying the MongoDB `query
modifiers`_ that should be used for this query. For example::
>>> db.test.find(modifiers={"$maxTimeMS": 500})
- `batch_size` (optional): Limits the number of documents returned in
a single batch.
- `manipulate` (optional): **DEPRECATED** - If True (the default),
apply any outgoing SON manipulators before returning.
- `collation` (optional): An instance of
:class:`~pymongo.collation.Collation`. This option is only supported
on MongoDB 3.4 and above.
.. note:: There are a number of caveats to using
:attr:`~pymongo.cursor.CursorType.EXHAUST` as cursor_type:
- The `limit` option can not be used with an exhaust cursor.
- Exhaust cursors are not supported by mongos and can not be
used with a sharded cluster.
The :meth:`find` method obeys the :attr:`read_preference` of
this :class:`Collection`.
:Parameters:
- `filter` (optional): a SON object specifying elements which
must be present for a document to be included in the
result set
- `projection` (optional): a list of field names that should be
returned in the result set or a dict specifying the fields
to include or exclude. If `projection` is a list "_id" will
always be returned. Use a dict to exclude fields from
the result (e.g. projection={‘_id‘: False}).
- `skip` (optional): the number of documents to omit (from
the start of the result set) when returning the results
- `limit` (optional): the maximum number of results to
return
- `no_cursor_timeout` (optional): if False (the default), any
returned cursor is closed by the server after 10 minutes of
inactivity. If set to True, the returned cursor will never
time out on the server. Care should be taken to ensure that
cursors with no_cursor_timeout turned on are properly closed.
- `cursor_type` (optional): the type of cursor to return. The valid
options are defined by :class:`~pymongo.cursor.CursorType`:
- :attr:`~pymongo.cursor.CursorType.NON_TAILABLE` - the result of
this find call will return a standard cursor over the result set.
- :attr:`~pymongo.cursor.CursorType.TAILABLE` - the result of this
find call will be a tailable cursor - tailable cursors are only
for use with capped collections. They are not closed when the
last data is retrieved but are kept open and the cursor location
marks the final document position. If more data is received
iteration of the cursor will continue from the last document
received. For details, see the `tailable cursor documentation
<http://www.mongodb.org/display/DOCS/Tailable+Cursors>`_.
- :attr:`~pymongo.cursor.CursorType.TAILABLE_AWAIT` - the result
of this find call will be a tailable cursor with the await flag
set. The server will wait for a few seconds after returning the
full result set so that it can capture and return additional data
added during the query.
- :attr:`~pymongo.cursor.CursorType.EXHAUST` - the result of this
find call will be an exhaust cursor. MongoDB will stream batched
results to the client without waiting for the client to request
each batch, reducing latency. See notes on compatibility below.
- `sort` (optional): a list of (key, direction) pairs
specifying the sort order for this query. See
:meth:`~pymongo.cursor.Cursor.sort` for details.
- `allow_partial_results` (optional): if True, mongos will return
partial results if some shards are down instead of returning an
error.
- `oplog_replay` (optional): If True, set the oplogReplay query
flag.
- `modifiers` (optional): A dict specifying the MongoDB `query
modifiers`_ that should be used for this query. For example::
>>> db.test.find(modifiers={"$maxTimeMS": 500})
- `batch_size` (optional): Limits the number of documents returned in
a single batch.
- `manipulate` (optional): **DEPRECATED** - If True (the default),
apply any outgoing SON manipulators before returning.
- `collation` (optional): An instance of
:class:`~pymongo.collation.Collation`. This option is only supported
on MongoDB 3.4 and above.
#直接上代码
#1.查询身高小于180的文档
print ‘-------------身高小于180:‘
print type(collection_set01.find({‘high‘:{‘$lt‘:180}})) #<class ‘pymongo.cursor.Cursor‘>
for r in collection_set01.find({‘high‘:{‘$lt‘:180}}):
print r
print type(collection_set01.find_one({‘high‘:{‘$lt‘:180}})) #<type ‘dict‘>
print ‘use find_one:‘,collection_set01.find_one({‘high‘:{‘$lt‘:180}})[‘high‘]
print ‘use find_one:‘,collection_set01.find_one({‘high‘:{‘$lt‘:180}})
#2.查询特定键(select key1,key2 from table;)
print ‘-------------查询特定键--------‘
print ‘-------------查询身高大于170,并只列出_id,high和age字段(使用列表形式_id默认打印出来,可以使用{}忽视_id):‘
for r in collection_set01.find({‘high‘:{‘$gt‘:170}},projection=[‘high‘,‘age‘]):print r
print ‘\n‘
print ‘--------------skip参数用法‘
for r in collection_set01.find({‘high‘:{‘$gt‘:170}},[‘high‘,‘age‘],skip=1):print r #skip=1跳过第一个匹配到的文档
for r in collection_set01.find({‘high‘:{‘$gt‘:170}},[‘high‘,‘age‘]).skip(1):print r #skip=1跳过第一个匹配到的文档
print ‘\n‘
print ‘--------------limit参数用法‘
for r in collection_set01.find({‘high‘:{‘$gt‘:170}},[‘high‘,‘age‘],limit=1):print r #limit=2限制显示2条文档
print ‘\n‘
print ‘--------------用{}描述特定键‘
for r in collection_set01.find({‘high‘:{‘$gt‘:170}},{‘high‘:1,‘age‘:1,‘_id‘:False}):print r
print ‘---------------------多条件查询‘
print collection_set01.find_one({‘high‘:{‘$gt‘:10},‘age‘:{‘$lt‘:26,‘$gt‘:10}})
#3.$in
print ‘----------------IN‘
for r in collection_set01.find({"age":{"$in":[23, 26, 32]}}): print r # select * from users where age in (23, 26, 32)
#for u in db.users.find({"age":{"$nin":(23, 26, 32)}}): print u # select * from users where age not in (23, 26, 32)
#4.count统计数目
print ‘----------------count‘
print collection_set01.find({"age":{"$gt":20}}).count() # select count(*) from set01 where age > 10
#5.$or
print ‘----------------条件或‘
print ‘大于等于29或者小于23‘
for r in collection_set01.find({"$or":[{"age":{"$lte":23}}, {"age":{"$gte":29}}]}): print r
#6.$exists，是否存在字段
print ‘------------exists‘
for r in collection_set01.find({‘age‘:{‘$exists‘:True}}):print ‘age exists‘,r # select * from 集合名 where exists 键1
for r in collection_set01.find({‘age‘:{‘$exists‘:False}}):print ‘age not exists‘,r # select * from 集合名 where not exists 键1
#7.正则表达式查询
print ‘正则表达式查询‘
#method 1
for r in collection_set01.find({‘name‘:{‘$regex‘:r‘.*wei.*‘}}):print r #找出name字段中包含wei的文档
#method 2
import re
Regex = re.compile(r‘.*zhang.*‘,re.IGNORECASE)
for r in collection_set01.find({‘name‘:Regex}):print r #找出name字段中包含wei的文档
#8.sort排序
print ‘--------------------使用sort排序(文档中没有排序的字段也会打印出来,表示最小)‘
#pymongo.ASCENDING 1
#pymongo.DESCENDING -1
#sort([[],()]),[],()均可
print ‘--------------age 升序‘
for r in collection_set01.find().sort([["age",pymongo.ASCENDING]]):print r
print ‘--------------age 降序‘
for r in collection_set01.find().sort([("age",-1)]):print r
print ‘--------------age升序,high升序‘
for r in collection_set01.find().sort((("age",pymongo.ASCENDING),("high",pymongo.ASCENDING))):print r
print ‘--------------age升序，high降序‘
for r in collection_set01.find(sort=[("age",pymongo.ASCENDING),("high",pymongo.ASCENDING)]):print r
#9.$all判断数组属性是否包含全部条件,注意与$in区别
print ‘-------------$all‘
for r in collection_set01.find({‘list‘:{‘$all‘:[2,3,4]}}):print r
print ‘-------------$in‘
for r in collection_set01.find({‘list‘:{‘$in‘:[2,3,4]}}):print r
#10.$size匹配数组属性元素数量
print ‘-------------$size‘
print ‘-------------size=3‘
for r in collection_set01.find({‘list‘:{‘$size‘:3}}):print r
print ‘-------------size=7‘
for r in collection_set01.find({‘list‘:{‘$size‘:7}}):print r
#11.$unset和$set相反表示移除文档属性
print ‘-------------------$unset‘
print ‘---before‘
for r in collection_set01.find({‘name‘:‘weijian‘}):print r
collection_set01.update({‘name‘:‘weijian‘},{‘$unset‘:{‘age‘:1}})
print ‘---after‘
for r in collection_set01.find({‘name‘:‘weijian‘}):print r
#输出结果-------------查询测试------------------------身高小于180:<class ‘pymongo.cursor.Cursor‘>{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}<type ‘dict‘>use find_one: 173use find_one: {u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}-------------查询特定键---------------------查询身高大于170,并只列出_id,high和age字段(使用列表形式_id默认打印出来,可以使用{}忽视_id):{u‘high‘: 173, u‘age‘: 26, u‘_id‘: 2}{u‘high‘: 180, u‘age‘: 29, u‘_id‘: 3}{u‘high‘: 179, u‘age‘: 22, u‘_id‘: 5}{u‘high‘: 176, u‘age‘: -27, u‘_id‘: 0}
--------------skip参数用法{u‘high‘: 180, u‘age‘: 29, u‘_id‘: 3}{u‘high‘: 179, u‘age‘: 22, u‘_id‘: 5}{u‘high‘: 176, u‘age‘: -27, u‘_id‘: 0}{u‘high‘: 180, u‘age‘: 29, u‘_id‘: 3}{u‘high‘: 179, u‘age‘: 22, u‘_id‘: 5}{u‘high‘: 176, u‘age‘: -27, u‘_id‘: 0}
--------------limit参数用法{u‘high‘: 173, u‘age‘: 26, u‘_id‘: 2}
--------------用{}描述特定键{u‘high‘: 173, u‘age‘: 26}{u‘high‘: 180, u‘age‘: 29}{u‘high‘: 179, u‘age‘: 22}{u‘high‘: 176, u‘age‘: -27}---------------------多条件查询{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}----------------IN{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}----------------count4----------------条件或大于等于29或者小于23{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}------------exists用法age exists {u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}age exists {u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}age exists {u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}age exists {u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}age exists {u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}age exists {u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}age exists {u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}age not exists {u‘comment‘: u‘after replace_one operation just exists comment(key)‘, u‘_id‘: 1}正则表达式查询{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}--------------------使用sort排序(文档中没有排序的字段也会打印出来,表示最小)--------------age 升序{u‘comment‘: u‘after replace_one operation just exists comment(key)‘, u‘_id‘: 1}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}--------------age 降序{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}{u‘comment‘: u‘after replace_one operation just exists comment(key)‘, u‘_id‘: 1}--------------age升序,high升序{u‘comment‘: u‘after replace_one operation just exists comment(key)‘, u‘_id‘: 1}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}--------------age升序，high降序{u‘comment‘: u‘after replace_one operation just exists comment(key)‘, u‘_id‘: 1}{u‘high‘: 176, u‘comment‘: u‘use update_many‘, u‘age‘: -27, u‘_id‘: 0, u‘name‘: u‘zzzzz‘}{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}{u‘high‘: 179, u‘comment‘: u‘use update_many‘, u‘age‘: 22, u‘_id‘: 5, u‘name‘: u‘zhangjian‘}{u‘high‘: 173, u‘comment‘: u‘use update_many‘, u‘age‘: 26, u‘_id‘: 2, u‘name‘: u‘zhang‘}{u‘high‘: 180, u‘comment‘: u‘use update_many‘, u‘age‘: 29, u‘_id‘: 3, u‘name‘: u‘wei‘}{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}-------------$all{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}-------------$in{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}-------------$size用法-------------size=3{u‘age‘: 19, u‘_id‘: 100, u‘list‘: [2, 3, 5], u‘name‘: u‘zwj‘}-------------size=7{u‘age‘: 19, u‘_id‘: 101, u‘list‘: [1, 2, 3, 4, 5, 6, 7], u‘name‘: u‘zwj‘}-------------------$unset用法---before{u‘high‘: 158, u‘age‘: 30, u‘_id‘: 4, u‘name‘: u‘weijian‘}---after{u‘high‘: 158, u‘_id‘: 4, u‘name‘: u‘weijian‘}
时间： 2024-12-10 09:26:39