Python's MongoDB module PyMongo operating method collection, mongodbpymongo

Python's MongoDB module PyMongo operating method collection, mongodbpymongo

Import the module before you start:

>>> import pymongo

Next, you must install and start the local mongodb server.

The Connection established on the Consumer Client:

Client = your client ('localhost', 27017) # or client = your client ('mongodb: // localhost: 27017 /')

Obtain the database:

>>> Db = client. test_database # Or >>> db = client ['test-database']

Get a data set:

Collection = db. test_collection # Or collection = db ['test-collection']

Data in MongoDB uses Json-style documents:

>>> import datetime>>> post = {"author": "Mike",...     "text": "My first blog post!",...     "tags": ["mongodb", "python", "pymongo"],...     "date": datetime.datetime.utcnow()}

Insert a document:

>>> posts = db.posts>>> post_id = posts.insert_one(post).inserted_id>>> post_idObjectId('...')

Find a piece of data:

>>> posts.find_one(){u'date': datetime.datetime(...), u'text': u'My first blog post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'mongodb', u'python', u'pymongo']}>>> posts.find_one({"author": "Mike"}){u'date': datetime.datetime(...), u'text': u'My first blog post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'mongodb', u'python', u'pymongo']}>>> posts.find_one({"author": "Eliot"})>>>

Search through ObjectId:

>>> post_idObjectId(...)>>> posts.find_one({"_id": post_id}){u'date': datetime.datetime(...), u'text': u'My first blog post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'mongodb', u'python', u'pymongo']}

Do not convert the ObjectId type to String:

>>> post_id_as_str = str(post_id)>>> posts.find_one({"_id": post_id_as_str}) # No result>>>

What if you have a post_id string?

from bson.objectid import ObjectId# The web framework gets post_id from the URL and passes it as a stringdef get(post_id):  # Convert from string to ObjectId:  document = client.db.collection.find_one({'_id': ObjectId(post_id)})

Insert multiple entries:

>>> 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)}]>>> result = posts.insert_many(new_posts)>>> result.inserted_ids[ObjectId('...'), ObjectId('...')]

Search for multiple data entries:

>>> for post in posts.find():...  post...{u'date': datetime.datetime(...), u'text': u'My first blog post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'mongodb', u'python', u'pymongo']}{u'date': datetime.datetime(2009, 11, 12, 11, 14), u'text': u'Another post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'bulk', u'insert']}{u'date': datetime.datetime(2009, 11, 10, 10, 45), u'text': u'and pretty easy too!', u'_id': ObjectId('...'), u'author': u'Eliot', u'title': u'MongoDB is fun'}

Of course, you can also restrict the search conditions:

>>> for post in posts.find({"author": "Mike"}):...  post...{u'date': datetime.datetime(...), u'text': u'My first blog post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'mongodb', u'python', u'pymongo']}{u'date': datetime.datetime(2009, 11, 12, 11, 14), u'text': u'Another post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'bulk', u'insert']}

Obtain the number of data entries in the Set:

>>> posts.count()

Or the number of data entries that meet certain search conditions:

>>> posts.find({"author": "Mike"}).count()

Range search, for example, time range:

>>> d = datetime.datetime(2009, 11, 12, 12)>>> for post in posts.find({"date": {"$lt": d}}).sort("author"):...  print post...{u'date': datetime.datetime(2009, 11, 10, 10, 45), u'text': u'and pretty easy too!', u'_id': ObjectId('...'), u'author': u'Eliot', u'title': u'MongoDB is fun'}{u'date': datetime.datetime(2009, 11, 12, 11, 14), u'text': u'Another post!', u'_id': ObjectId('...'), u'author': u'Mike', u'tags': [u'bulk', u'insert']}

$ Lt means less.

How to create an index? For example, the following query:

>>> posts.find({"date": {"$lt": d}}).sort("author").explain()["cursor"]u'BasicCursor'>>> posts.find({"date": {"$lt": d}}).sort("author").explain()["nscanned"]

Index creation:

>>> from pymongo import ASCENDING, DESCENDING>>> posts.create_index([("date", DESCENDING), ("author", ASCENDING)])u'date_-1_author_1'>>> posts.find({"date": {"$lt": d}}).sort("author").explain()["cursor"]u'BtreeCursor date_-1_author_1'>>> posts.find({"date": {"$lt": d}}).sort("author").explain()["nscanned"]

Connection Aggregation

>>> Account = db. Account # Or >>> account = db ["Account"]

 

View all cluster names

>>> db.collection_names()

 

View A aggregated record

>>> db.Account.find_one() >>> db.Account.find_one({"UserName":"keyword"})

 

View aggregated Fields

>>> db.Account.find_one({},{"UserName":1,"Email":1}){u'UserName': u'libing', u'_id': ObjectId('4ded95c3b7780a774a099b7c'), u'Email': u'libing@35.cn'} >>> db.Account.find_one({},{"UserName":1,"Email":1,"_id":0}){u'UserName': u'libing', u'Email': u'libing@35.cn'}

 

View multiple aggregated records

>>> for item in db.Account.find():    item >>> for item in db.Account.find({"UserName":"libing"}):    item["UserName"]

 

View aggregated record statistics

>>> db.Account.find().count() >>> db.Account.find({"UserName":"keyword"}).count()

 

Sort aggregate query results

>>> Db. account. find (). sort ("UserName") # The default value is ascending> db. account. find (). sort ("UserName", pymongo. ASCENDING) # ASCENDING> db. account. find (). sort ("UserName", pymongo. DESCENDING) # DESCENDING order

 

Multi-column sorting of clustered query results

>>> db.Account.find().sort([("UserName",pymongo.ASCENDING),("Email",pymongo.DESCENDING)])

 

Add record

>>> db.Account.insert({"AccountID":21,"UserName":"libing"})

 

Modify record

>>> db.Account.update({"UserName":"libing"},{"$set":{"Email":"libing@126.com","Password":"123"}})

 

Delete record

>>> Db. Account. remove () -- delete all >>> db. Test. remove ({"UserName": "keyword "})

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