Shulou(Shulou.com)06/01 Report--

使用pip install pymongo安装

1.连接MongoDB实例

In [60]: from pymongo import MongoClientIn [61]: client=MongoClient('mongodb://10.10.41.25:2911')In [62]: client=MongoClient('10.10.41.25',2911)

两种写法都行

2.获取数据库信息

In [63]: db=client.gameIn [64]: db=client['game']

两种写法都行

3.获取集合信息

In [85]: collection=db.playerIn [86]: collection=db['player']

两种写法都行

4.插入一个文档记录

MongoDB以JSON格式存储和显示数据。在pymongo中以字典的方式显示数据。

In [95]: import datetimeIn [96]: post={"author":"Mike","text":"My first blog post!","tags":["mongodb","python","pymongo"],"date":datetime.datetime.utcnow()}In [132]: posts=db.postsIn [133]: post_id=posts.insert(post)In [134]: post_idOut[134]: ObjectId('550ad8677a50900165feae9d')

当插入一个文档时，一个特殊的key，"_id"将自动添加到这个文档中。

In [136]: db.collection_names()Out[136]: [u'system.indexes',u'posts']

5.使用find_one()获取单个文档

In [141]: posts.find_one()Out[141]: {u'_id': ObjectId('550ad8677a50900165feae9d'), u'author': u'Mike', u'date': datetime.datetime(2015, 3, 19, 14, 7, 14, 572000), u'tags': [u'mongodb', u'python', u'pymongo'], u'text': u'My first blog post!'}In [142]: posts.find_one({"author":"Mike"})Out[142]: {u'_id': ObjectId('550ad8677a50900165feae9d'), u'author': u'Mike', u'date': datetime.datetime(2015, 3, 19, 14, 7, 14, 572000), u'tags': [u'mongodb', u'python', u'pymongo'], u'text': u'My first blog post!'}In [143]: posts.find_one({"author":"Eliot"})In [144]:

MongoDB以BSON格式存储字符，而BSON字符串是以UTF-8编码，所以PyMongo必须要确保它存储的数据是有效的UTF-8编码的数据。常规字符串直接存储，但是经过编码的字符串首先以UTF-8编码存储。

6.使用ObjectID查找文档

In [151]: post_idOut[151]: ObjectId('550ad8677a50900165feae9d')In [152]: posts.find_one({"_id":post_id})Out[152]: {u'_id': ObjectId('550ad8677a50900165feae9d'), u'author': u'Mike', u'date': datetime.datetime(2015, 3, 19, 14, 7, 14, 572000), u'tags': [u'mongodb', u'python', u'pymongo'], u'text': u'My first blog post!'}

ObjectID和它表示的字符串不一样

In [154]: post_id_as_str=str(post_id)In [155]: posts.find_one({"_id":post_id_as_str})

没有任何结果显示

在一些WEB应用中，需要更加URL获取post_id进而根据post_id查找匹配的文档。在使用find_one()查找之前有必要将post_id从字符串转换成为ObjectID

7.批量插入文档数据

>>> 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)}] >>> posts.insert(new_posts)[ObjectId('...'), ObjectId('...')]

8.查询多个文档数据

In [165]: for post in posts.find(): post .....: .....: Out[166]: {u'_id': ObjectId('550ad8677a50900165feae9d'), u'author': u'Mike', u'date': datetime.datetime(2015, 3, 19, 14, 7, 14, 572000), u'tags': [u'mongodb', u'python', u'pymongo'], u'text': u'My first blog post!'}Out[166]: {u'_id': ObjectId('550b87d47a50907021e3473b'), u'author': u'Mike', u'date': datetime.datetime(2009, 11, 12, 11, 14), u'text': u'Another post!'}Out[166]: {u'_id': ObjectId('550b87d47a50907021e3473c'), u'author': u'Eliot', u'title': u'MongoDB is fun'}In [169]: for post in posts.find({"author" : "Mike"}): .....: post .....: .....: Out[169]: {u'_id': ObjectId('550ad8677a50900165feae9d'), u'author': u'Mike', u'date': datetime.datetime(2015, 3, 19, 14, 7, 14, 572000), u'tags': [u'mongodb', u'python', u'pymongo'], u'text': u'My first blog post!'}Out[169]: {u'_id': ObjectId('550b87d47a50907021e3473b'), u'author': u'Mike', u'date': datetime.datetime(2009, 11, 12, 11, 14), u'text': u'Another post!'}

9.总计

In [170]: posts.count()Out[170]: 3In [171]: posts.find({"author":"Mike"}).count()Out[171]: 2

10.范围查询

In [183]: d=datetime.datetime(2009,11,12,12)In [184]: for post in posts.find({"date":{"$lt":d}}).sort("author"): .....: print post .....: .....: {u'date': datetime.datetime(2009, 11, 12, 11, 14), u'text': u'Another post!', u'_id': ObjectId('550b87d47a50907021e3473b'), u'author': u'Mike'}

11.索引

使用索引可以加快查询速度，缩小查询范围。

In [201]: posts.find({"date" : {"$lt":d}}).sort("author").explain()["cursor"]Out[201]: u'BasicCursor'In [202]: posts.find({"date" : {"$lt":d}}).sort("author").explain()["nscanned"]Out[202]: 3

创建组合索引

In [241]: from pymongo import ASCENDING,DESCENDINGIn [242]: posts.create_index([("date",DESCENDING),("author",ASCENDING)])Out[242]: u'date_-1_author_1'In [243]: posts.find({"date" : {"$lt":d}}).sort("author").explain()["nscanned"]Out[243]: 1

12.

参考文档

http://api.mongodb.org/python/current/tutorial.html?_ga=1.58141740.722641156.1410499072

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.