python的mongodb模块pymongo操作方法集锦

开始之前当然要导入模块啦:

>>> import pymongo

下一步,必须本地mongodb服务器的安装和启动已经完成,才能继续下去。

建立于mongoclient 的连接:

client = mongoclient(‘localhost’, 27017)
# 或者
client = mongoclient(‘mongodb://localhost:27017/’)

得到数据库:

>>> db = client.test_database
# 或者
>>> db = client[‘test-database’]

得到一个数据集合:

collection = db.test_collection
# 或者
collection = db[‘test-collection’]

mongodb中的数据使用的是类似json风格的文档:

>>> import datetime
>>> post = {“author”: “mike”,
… “text”: “my first blog post!”,
… “tags”: [“mongodb”, “python”, “pymongo”],
… “date”: datetime.datetime.utcnow()}

插入一个文档:

>>> posts = db.posts
>>> post_id = posts.insert_one(post).inserted_id
>>> post_id
objectid(‘…’)

找一条数据:

>>> 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”})
>>>

通过objectid来查找:

>>> post_id
objectid(…)
>>> 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’]}

不要转化objectid的类型为string:

>>> post_id_as_str = str(post_id)
>>> posts.find_one({“_id”: post_id_as_str}) # no result
>>>

如果你有一个post_id字符串,怎么办呢?

from bson.objectid import objectid
# the web framework gets post_id from the url and passes it as a string
def get(post_id):
# convert from string to objectid:
document = client.db.collection.find_one({‘_id’: objectid(post_id)})

多条插入:

>>> 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(‘…’)]

查找多条数据:

>>> 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’}

当然也可以约束查找条件:

>>> 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’]}

获取集合的数据条数:

>>> posts.count()

或者说满足某种查找条件的数据条数:

>>> posts.find({“author”: “mike”}).count()

范围查找,比如说时间范围:

>>> 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是小于的意思。

如何建立索引呢?比如说下面这个查找:

>>> posts.find({“date”: {“$lt”: d}}).sort(“author”).explain()[“cursor”]
u’basiccursor’
>>> posts.find({“date”: {“$lt”: d}}).sort(“author”).explain()[“nscanned”]

建立索引:

>>> 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”]

连接聚集

>>> account = db.account
#或
>>> account = db[“account”]

查看全部聚集名称

>>> db.collection_names()

查看聚集的一条记录

>>> db.account.find_one()
>>> db.account.find_one({“username”:”keyword”})

查看聚集的字段

>>> 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’}

查看聚集的多条记录

>>> for item in db.account.find():
item
>>> for item in db.account.find({“username”:”libing”}):
item[“username”]

查看聚集的记录统计

>>> db.account.find().count()
>>> db.account.find({“username”:”keyword”}).count()

聚集查询结果排序

>>> db.account.find().sort(“username”) #默认为升序
>>> db.account.find().sort(“username”,pymongo.ascending) #升序
>>> db.account.find().sort(“username”,pymongo.descending) #降序

聚集查询结果多列排序

>>> db.account.find().sort([(“username”,pymongo.ascending),(“email”,pymongo.descending)])

添加记录

>>> db.account.insert({“accountid”:21,”username”:”libing”})

修改记录

>>> db.account.update({“username”:”libing”},{“$set”:{“email”:”libing@126.com”,”password”:”123″}})

删除记录

>>> db.account.remove() — 全部删除
>>> db.test.remove({“username”:”keyword”})