What is PyMongo

PyMongo is the driver that enables the python program to use the Mongodb database, written using python.

The installation

Environment: Ubuntu 14.04+ python2.7 +MongoDB 2.4

Go to the official website to download the package, and click the link to open the address. Unzipped and entered, installed using python setup.py install

Or install pip-m install pymongo with pip

The basic use

Create a connection

import pymongo
client = pymongo.MongoClient('localhost', 27017)

Or you could do this

import pymongo
client = MongoClient('mongodb://localhost:27017/')

Connect to database

db = client.mydb
# or
db = client['mydb']

The connection to gather

Aggregation is the equivalent of a table in a relational database

collection = db.my_collection
# or
collection = db['my_collection']

View all aggregation names under the database

db.collection_names()

Insert records

collection.insert({"key1":"value1","key2","value2"})

Delete records

Delete all

collection.remove()

Conditional deletion

collection.remove({"key1":"value1"})

Update record

collection.update({"key1": "value1"}, {"$set": {"key2": "value2", "key3": "value3"}}) 

Query log

Query 1 record: find_one() returns the first record without any parameters. Returns a conditional lookup with a parameter

collection.find_one()
collection.find_one({"key1":"value1"})

Query multiple records: find() returns all records without parameters, and returns them by conditional search with parameters

collection.find()
collection.find({"key1":"value1"})

View multiple records gathered

import pymongo
client = MongoClient('mongodb://localhost:27017/')

0

View the total number of clustered records

import pymongo
client = MongoClient('mongodb://localhost:27017/')

1

Query result sorting

Sort on a single column

import pymongo
client = MongoClient('mongodb://localhost:27017/')

2

Sort on multiple columns

collection.find().sort([("key1", pymongo.ASCENDING), ("key2", pymongo.DESCENDING)]) 

Example 1:

#!/usr/bin/env python
#coding:utf-8
# Author:  --<qingfengkuyu>
# Purpose: MongoDB The use of
# Created: 2014/4/14
#32 A version of a bit can only be stored at most 2.5GB The data ( NoSQLFan : the maximum file size is 2G , recommended production environment 64 A)

import pymongo
import datetime
import random

# Create a connection
conn = pymongo.Connection('10.11.1.70',27017)
# Connect to database
db = conn.study
#db = conn['study']

# Print all aggregation names and join the aggregation
print u' All gathered :',db.collection_names()
posts = db.post
#posts = db['post']
print posts

# Insert records
new_post = {"AccountID":22,"UserName":"libing",'date':datetime.datetime.now()}
new_posts = [{"AccountID":22,"UserName":"liuw",'date':datetime.datetime.now()},
       {"AccountID":23,"UserName":"urling",'date':datetime.datetime.now()}]# Each record is inserted at a different time 1 sample

posts.insert(new_post)
#posts.insert(new_posts)# Batch insert multiple pieces of data

# Delete records
print u' Delete specified record :\n',posts.find_one({"AccountID":22,"UserName":"libing"})
posts.remove({"AccountID":22,"UserName":"libing"})

# Modify the records in the aggregation
posts.update({"UserName":"urling"},{"$set":{'AccountID':random.randint(20,50)}})

# Query records and count the number of records
print u' The total record is: ',posts.count(),posts.find().count()
print u' Query a single record :\n',posts.find_one()
print posts.find_one({"UserName":"liuw"})

# Query all records
print u' Query multiple records :'
#for item in posts.find():# Query all records
#for item in posts.find({"UserName":"urling"}):# Query specified record
#for item in posts.find().sort("UserName"):# Query results based on UserName Sort, by default, in ascending order
#for item in posts.find().sort("UserName",pymongo.ASCENDING):# Query results based on UserName Sorting, ASCENDING For the ascending ,DESCENDING For the descending order
for item in posts.find().sort([("UserName",pymongo.ASCENDING),('date',pymongo.DESCENDING)]):# Query results are sorted by multiple columns
  print item

# View the performance of query statements
#posts.create_index([("UserName", pymongo.ASCENDING), ("date", pymongo.DESCENDING)])# indexed
print posts.find().sort([("UserName",pymongo.ASCENDING),('date',pymongo.DESCENDING)]).explain()["cursor"]# Not indexed BasicCursor Query log
print posts.find().sort([("UserName",pymongo.ASCENDING),('date',pymongo.DESCENDING)]).explain()["nscanned"]# The number of records queried when the query statement is executed