MongoDB 及 scrapy 应用
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1.Scrapy 使用 MongoDB
https://doc.scrapy.org/en/latest/topics/item-pipeline.html#write-items-to-mongodb
Write items to MongoDB
In this example we’ll write items to MongoDB using pymongo. MongoDB address and database name are specified in Scrapy settings; MongoDB collection is named after item class.
The main point of this example is to show how to use from_crawler()
method and how to clean up the resources properly.:
- import pymongo
- class MongoPipeline(object):
- collection_name = 'scrapy_items'
- def __init__(self, mongo_uri, mongo_db):
- self.mongo_uri = mongo_uri
- self.mongo_db = mongo_db
- @classmethod
- def from_crawler(cls, crawler):
- return cls(
- mongo_uri=crawler.settings.get('MONGO_URI'),
- mongo_db=crawler.settings.get('MONGO_DATABASE', 'items')
- )
- def open_spider(self, spider):
- self.client = pymongo.MongoClient(self.mongo_uri)
- self.db = self.client[self.mongo_db]
- def close_spider(self, spider):
- self.client.close()
- def process_item(self, item, spider):
- self.db[self.collection_name].insert_one(dict(item))
- return item
2.MongoDB Tutorial
https://api.mongodb.com/python/current/tutorial.html
建立文件夹并运行 MongoDB instance
- C:\Users\win7>mongod --dbpath e:\mongodb\db
连接数据库
- from pymongo import MongoClient
- client = MongoClient()
- # client = MongoClient('localhost', 27017)
- # client = MongoClient('mongodb://localhost:27017/')
- db = client.test_database
- # db = client['test-database']
collection(等同于table) 插入一个个 document
- posts = db.posts
- # posts = db['posts']
- import datetime
- post = {"author": "Mike",
- "text": "My first blog post!",
- "tags": ["mongodb", "python", "pymongo"],
- "date": datetime.datetime.utcnow()}
- post2 = {"author": "Martin",
- "text": "My second blog post!",
- "tags": ["mongodb", "python", "pymongo"],
- "date": datetime.datetime.utcnow()}
- post_id = posts.insert_one(post).inserted_id #其实等于 result =posts.insert_one(post) 再 post_id = result.inserted_id, 而 insert_many 则是 inserted_ids 返回一个list
- posts.insert_one(post2)
允许插入重复 document
插入之后自动更新了 post3,再次执行 posts.insert_one(post3) 提示 ObjectId 重复
如果插入 post3 之前执行了 post4 = post3.copy() 其实可以插入相同内容
- In [689]: post3 = {"author": "Mike",
- ...: "text": "My first blog post!",
- ...: "tags": ["mongodb", "python", "pymongo"],
- ...: "date": datetime.datetime.utcnow()}
- In [690]: posts.insert_one(post3)
- Out[690]: <pymongo.results.InsertOneResult at 0xb803788>
- In [691]: post3
- Out[691]:
- {'_id': ObjectId('59e57919fca565500c8e3692'),
- 'author': 'Mike',
- 'date': datetime.datetime(2017, 10, 17, 3, 29, 14, 966000),
- 'tags': ['mongodb', 'python', 'pymongo'],
- 'text': 'My first blog post!'}
检查确认:
- db.collection_names(include_system_collections=False)
- posts.count()
- import pprint
- pprint.pprint(posts.find_one()) #满足限制条件,而且仅限一条。不设条件也即get the first document from the posts collection
- posts.find_one({"author": "Mike"})
- for i in posts.find(): #
find()
returns aCursor
instance, which allows us to iterate over all matching documents. 返回 Cursor 迭代器,同样支持 posts.find({"author": "Mike"})- print i
c:\program files\anaconda2\lib\site-packages\pymongo\cursor.py
A cursor / iterator over Mongo query results.
- In [707]: posts.find()
- Out[707]: <pymongo.cursor.Cursor at 0x118a62b0>
- In [708]: a=posts.find()
- In [709]: a?
- Type: Cursor
- String form: <pymongo.cursor.Cursor object at 0x00000000116C6208>
- File: c:\program files\anaconda2\lib\site-packages\pymongo\cursor.py
- Docstring:
- A cursor / iterator over Mongo query results.
- Init docstring:
- Create a new cursor.
- Should not be called directly by application developers - see
- :meth:`~pymongo.collection.Collection.find` instead.
- .. mongodoc:: cursors
关于编码:
MongoDB stores data in BSON format. BSON strings are UTF-8 encoded
PyMongo decodes each BSON string to a Python unicode string, not a regular str.
存储时 str 不变,unicode 自动编码为 utf-8
输出统一解码为 unicode
- post = {"author": "Mike",
- {u'_id': ObjectId('...'),
- u'author': u'Mike',
Bulk Inserts 批量插入多条文档,每条文档可以不同 field,因此又称 schema-free
- >>> 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('...')]
查询数量:
- posts.count()
- posts.find({"author": "Mike"}).count()
##Range Queries 高级查询
##Indexing 索引
#Aggregation Examples 聚合
https://api.mongodb.com/python/current/examples/aggregation.html
- from pymongo import MongoClient
- db = MongoClient().aggregation_example
- result = db.things.insert_many([{"x": 1, "tags": ["dog", "cat"]},
- {"x": 2, "tags": ["cat"]},
- {"x": 2, "tags": ["mouse", "cat"]},
- {"x": 3, "tags": []}])
- result.inserted_ids
OperationFailure: $sort key ordering must be 1 (for ascending) or -1 (for descending)
- from bson.son import SON
- pipeline = [
- {"$unwind": "$tags"}, # tags 字段是一个 array,松绑
- {"$group": {"_id": "$tags", "count": {"$sum": 1}}}, #按照 tag 分组,即为唯一值
- {"$sort": SON([("count", -1), ("_id", 1)])} #先按 count 降序,再按 _id 升序
- ]
SON 有序字典
- In [773]: SON?
- Init signature: SON(cls, *args, **kwargs)
- Docstring:
- SON data.
- A subclass of dict that maintains ordering of keys and provides a
- few extra niceties for dealing with SON. SON objects can be
- converted to and from BSON.
- In [779]: db.things.aggregate(pipeline)
- Out[779]: <pymongo.command_cursor.CommandCursor at 0x118a6cc0>
- In [780]: list(db.things.aggregate(pipeline)) #list(迭代器)
- Out[780]:
- [{u'_id': u'cat', u'count': 3},
- {u'_id': u'dog', u'count': 1},
- {u'_id': u'mouse', u'count': 1}]
Map/Reduce
Copying a Database 复制备份数据库
https://api.mongodb.com/python/current/examples/copydb.html#copying-a-database
- from pymongo import MongoClient
- client = MongoClient()
- client.admin.command('copydb',
- fromdb='test_database',
- todb='test_database_bak')
- #{u'ok': 1.0}
跨服务器以及密码认证,见原文。
#Bulk Write Operations 批处理 InsertOne, DeleteMany, ReplaceOne, UpdateOne
Bulk Insert
https://api.mongodb.com/python/current/examples/bulk.html
- import pymongo
- db = pymongo.MongoClient().bulk_example
- db.test.insert_many([{'i': i} for i in range(10000)]).inserted_ids
- db.test.count()
Mixed Bulk Write Operations
1/2 Ordered Bulk Write Operations
Ordered bulk write operations are batched and sent to the server in the order provided for serial execution. 按照顺序执行操作
- from pprint import pprint
- from pymongo import InsertOne, DeleteMany, ReplaceOne, UpdateOne #类
- result = db.test.bulk_write([ #根据帮助:也可写成 requests = [InsertOne({'y': 1}),]
- DeleteMany({}), #类实例
- InsertOne({'_id': 1}),
- InsertOne({'_id': 2}),
- InsertOne({'_id': 3}),
- UpdateOne({'_id': 1}, {'$set': {'foo': 'bar'}}),
- UpdateOne({'_id': 4}, {'$inc': {'j': 1}}, upsert=True), #没有则插入
- ReplaceOne({'j': 1}, {'j': 2})]) #也可满足 {'j': 2}, 替换为{'i': 5}
- pprint(result.bulk_api_result)
#{'nInserted': 3,
#'nMatched': 2,
#'nModified': 2,
#'nRemoved': 4,
#'nUpserted': 1,
#'upserted': [{u'_id': 4, u'index': 5}],
#'writeConcernErrors': [],
#'writeErrors': []}
- for i in db.test.find():
- print i
- #{u'_id': 1, u'foo': u'bar'}
- #{u'_id': 2}
- #{u'_id': 3}
- #{u'_id': 4, u'j': 2}
清空col
- In [844]: r=db.test.delete_many({})
- In [845]: r.deleted_count
- Out[845]: 4
删除col
- In [853]: db.name
- Out[853]: u'bulk_example'
- In [855]: db.collection_names()
- Out[855]: [u'test']
- In [860]: db.test.drop() #无返回,不报错,建议用下面的
- In [861]: db.drop_collection('test')
- Out[861]:
- {u'code': 26,
- u'codeName': u'NamespaceNotFound',
- u'errmsg': u'ns not found',
- u'ok': 0.0}
The first write failure that occurs (e.g. duplicate key error) aborts the remaining operations, and PyMongo raises BulkWriteError
. 出错则中止后续操作。
- >>> from pymongo import InsertOne, DeleteOne, ReplaceOne
- >>> from pymongo.errors import BulkWriteError
- >>> requests = [
- ... ReplaceOne({'j': 2}, {'i': 5}),
- ... InsertOne({'_id': 4}), # Violates the unique key constraint on _id.
- ... DeleteOne({'i': 5})]
- >>> try:
- ... db.test.bulk_write(requests)
- ... except BulkWriteError as bwe:
- ... pprint(bwe.details)
- ...
- {'nInserted': 0,
- 'nMatched': 1,
- 'nModified': 1,
- 'nRemoved': 0,
- 'nUpserted': 0,
- 'upserted': [],
- 'writeConcernErrors': [],
- 'writeErrors': [{u'code': 11000,
- u'errmsg': u'...E11000...duplicate key error...',
- u'index': 1,
- u'op': {'_id': 4}}]}
2/2 Unordered Bulk Write Operations 并行无序操作,最后报告出错的部分操作
- db.test.bulk_write(requests, ordered=False)
#Datetimes and Timezones
https://api.mongodb.com/python/current/examples/datetimes.html
避免使用本地时间 datetime.datetime.now()
- import datetime
- result = db.objects.insert_one({"last_modified": datetime.datetime.utcnow()})
关于时区读写,详见原文
#GridFS Example 存储二进制对象,比如文件
This example shows how to use gridfs
to store large binary objects (e.g. files) in MongoDB.
- from pymongo import MongoClient
- import gridfs
- db = MongoClient().gridfs_example
- fs = gridfs.GridFS(db) # collection 表
读写doc: str,unicode,file-like
- In [883]: fs.get(fs.put('hello world')).read()
- Out[883]: 'hello world'
- In [885]: fs.get(fs.put(u'hello world')).read()
- TypeError: must specify an encoding for file in order to write unicode
- In [886]: fs.get(fs.put(u'hello world',encoding='utf-8')).read() # 写入 unicode 必须传入 encoding,没有默认
- Out[886]: 'hello world'
- In [888]: fs.get(fs.put(open('abc.txt'),filename='abc',filetype='txt')).read() # file-like object (an object with a
read()
method),自定义属性为可选 filename ,filetype
- Out[888]: 'def'
相比第一个doc,第二个多出 encoding 字段,第三个多出 filenname 和 filetype
这里将 doc 看成 file 更容易理解
- In [896]: for doc in fs.find():
- ...: print doc.upload_date
- ...:
- 2017-10-18 03:28:04
- 2017-10-18 03:28:42.036000
- 2017-10-18 03:29:01.740000
print dir(doc)
'aliases', 'chunk_size', 'close', 'content_type', 'filename', 'length', 'md5', 'metadata', 'name', 'read', 'readchunk', 'readline', 'seek', 'tell', 'upload_date'
- In [899]: doc?
- Type: GridOut
- String form: <gridfs.grid_file.GridOut object at 0x000000000AB2B8D0>
- File: c:\program files\anaconda2\lib\site-packages\gridfs\grid_file.py
- Docstring:
- Class to read data out of GridFS.
- Init docstring:
- Read a file from GridFS
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