Python PyMongo usage summary, pythonpymongo Summary

Python PyMongo usage summary, pythonpymongo Summary

What is PyMongo?

PyMongo is a driver that enables python programs to use Mongodb databases and be compiled using python.

Install

Environment: Ubuntu 14.04 + python2.7 + MongoDB 2.4

Download the software package from the official website. Click the link to open the package. decompress the package and use python setup. py install for installation.

Or use pip to install pip-m install pymongo.

Basic usage

Create a connection

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

Or

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

Connect to database

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

Connection Aggregation

Clustering is equivalent to a table in a relational database.

Collection = db. my_collection # Or collection = db ['my _ collection']

View all cluster names in the database

db.collection_names() 

Insert record

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

Delete record

Delete all

collection.remove() 

Delete based on conditions

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

Update record

Copy codeThe Code is as follows:
Collection. update ({"key1": "value1" },{ "$ set": {"key2": "value2", "key3": "value3 "}})

Query records

Query a record: find_one () returns the first record without any parameters. If the record contains any parameters, the record is searched and returned based on the conditions.

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

Query multiple records: find () returns all records without parameters and returns results with parameters based on conditions

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

View multiple aggregated records

for item in collection.find():     print item 

View the total number of clustered records

print collection.find().count() 

Sort query results

Sort on a single column

Collection. find (). sort ("key1") # The default value is collection in ascending order. find (). sort ("key1", pymongo. ASCENDING) # collection in ASCENDING order. find (). sort ("key1", pymongo. DESCENDING) # DESCENDING order

Sort on multiple columns

Copy codeThe Code is as follows:
Collection. find (). sort ([("key1", pymongo. ASCENDING), ("key2", pymongo. DESCENDING)])

Instance 1:

#! /Usr/bin/env python # coding: UTF-8 # Author: -- <qingfengkuyu> # Purpose: Use of MongoDB # Created: # The 32-bit version can only store up to GB of data (NoSQLFan: The maximum file size is 2 GB, and the production environment recommends 64-bit) import py1_import datetimeimport random # create connection conn = pymongo. connection ('10. 11.1.70', 27017) # connect to the database db = conn. study # db = conn ['Study '] # print all clustering names and connect the clustered print u'all clustering:', db. collection_names () posts = db. post # posts = db ['post'] print posts # insert record 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 ()}] # The insert time of each record is different from that of posts. insert (new_post) # posts. insert (new_posts) # insert multiple data records in batches # Delete record print u'delete specified record: \ n', posts. find_one ({"AccountID": 22, "UserName": "libing"}) posts. remove ({"AccountID": 22, "UserName": "libing"}) # modify the posts record in the aggregation. update ({"UserName": "urling"}, {"$ set": {'accountid': random. randint (20, 50)}) # query records. The total number of statistical records 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 the specified record # for item in posts. find (). sort ("UserName"): # the query results are sorted by UserName. The default value is ascending. # for item in posts. find (). sort ("UserName", pymongo. ASCENDING): # the query results are sorted by UserName. ASCENDING is in ASCENDING order, and DESCENDING is in DESCENDING order for item in posts. find (). sort ([("UserName", pymongo. ASCENDING), ('date', pymongo. DESCENDING)]): # the query results are sorted by multiple columns. print item # view the query statement performance # posts. create_index ([("UserName", pymongo. ASCENDING), ("date", pymongo. DESCENDING)]) # Add the index print posts. find (). sort ([("UserName", pymongo. ASCENDING), ('date', pymongo. DESCENDING)]). explain () ["cursor"] # print posts. find (). sort ([("UserName", pymongo. ASCENDING), ('date', pymongo. DESCENDING)]). explain () ["nscanned"] # number of records queried during statement execution

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