#coding：utf-8
__author__
=
'hdfs'
import
pymongo
from
pymongo
import
MongoClient
client
=
MongoClient()
client
=
MongoClient(
'10.0.0.9'
,
27017
)
#连接mongodb数据库
client
=
MongoClient(
'mongodb://10.0.0.9:27017/'
)
#指定数据库名称
db
=
client.test_database
#获取非系统的集合
db.collection_names(include_system_collections
=
False
)
#获取集合名
posts
=
db.posts
#查找单个文档
posts.find_one()
#给定条件的一个文档
posts.find_one({
"author"
:
"Mike"
})
#使用ID查找需要ObjectID
from
bson.objectid
import
ObjectId
post_id
=
'5728aaa96795e21b91c1aaf0'
document
=
client.db.collection.find_one({
'_id'
: ObjectId(post_id)})
import
datetime
new_posts
=
[{
"author"
:
"Mike"
,
"text"
:
"Another post!"
,
"tags"
: [
"bulk"
,
"insert"
],
"date"
: datetime.datetime(
2009
,
11
,
12
,
11
,
14
)},
{
"author"
:
"Eliot"
,
"title"
:
"MongoDB is fun"
,
"text"
:
"and pretty easy too!"
,
"date"
: datetime.datetime(
2009
,
11
,
10
,
10
,
45
)}]
#插入多条记录
result
=
posts.insert_many(new_posts)
#返回插入的ID
result.inserted_ids
#递归集合
for
post
in
posts.find():
post
#递归条件集合
for
post
in
posts.find({
"author"
:
"Mike"
}):
post
#文档的记录数
posts.count()
#区间查询
d
=
datetime.datetime(
2009
,
11
,
12
,
12
)
for
post
in
posts.find({
"date"
: {
"$lt"
: d}}).sort(
"author"
):
print
post
#给集合profiles建立索引 唯一索引
result
=
db.profiles.create_index([(
'user_id'
, pymongo.ASCENDING)],unique
=
True
)
#查看索引信息
list
(db.profiles.index_information())
#
user_profiles
=
[
{
'user_id'
:
211
,
'name'
:
'Luke'
},
{
'user_id'
:
212
,
'name'
:
'Ziltoid'
}]
result
=
db.profiles.insert_many(user_profiles)
#聚合查询
from
pymongo
import
MongoClient
db
=
MongoClient(
'mongodb://10.0.0.9:27017/'
).aggregation_example
#准备数据
result
=
db.things.insert_many([{
"x"
:
1
,
"tags"
: [
"dog"
,
"cat"
]},
{
"x"
:
2
,
"tags"
: [
"cat"
]},
{
"x"
:
2
,
"tags"
: [
"mouse"
,
"cat"
,
"dog"
]},
{
"x"
:
3
,
"tags"
: []}])
result.inserted_ids
'''
{ "_id" : ObjectId("576aaa973e5269020848cc7c"), "x" : 1, "tags" : [ "dog", "cat" ] }
{ "_id" : ObjectId("576aaa973e5269020848cc7d"), "x" : 2, "tags" : [ "cat" ] }
{ "_id" : ObjectId("576aaa973e5269020848cc7e"), "x" : 2, "tags" : [ "mouse", "cat", "dog" ] }
{ "_id" : ObjectId("576aaa973e5269020848cc7f"), "x" : 3, "tags" : [ ] }
'''
from
bson.son
import
SON
#$unwind 解开-后面的变量
pipeline
=
[
{
"$unwind"
:
"$tags"
},
{
"$group"
: {
"_id"
:
"$tags"
,
"count"
: {
"$sum"
:
1
}}},
{
"$sort"
: SON([(
"count"
,
-
1
), (
"_id"
,
-
1
)])}
]
list
(db.things.aggregate(pipeline))
#使用聚合函数with command
db.command(
'aggregate'
,
'things'
, pipeline
=
pipeline, explain
=
True
)
