mongodb的python接口pymongo使用

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1. 连接

from pymongo import MongoClient
client = MongoClient("mongodb://mongodb0.example.net:27019")
# client = MongoClient()db = client['primer']coll = db.dataset
# coll = db['dataset']

2. 插入

from datetime import datetime
result = db.restaurants.insert_one(
{
"address": {
"street": "2 Avenue",
"zipcode": "",
"building": "",
"coord": [-73.9557413, 40.7720266]
},
"borough": "Manhattan",
"cuisine": "Italian",
"grades": [
{
"date": datetime.strptime("2014-10-01", "%Y-%m-%d"),
"grade": "A",
"score":
},
{
"date": datetime.strptime("2014-01-16", "%Y-%m-%d"),
"grade": "B",
"score":
}
],
"name": "Vella",
"restaurant_id": ""
}
)

3.查找

cursor = db.restaurants.find({"address.zipcode": ""})

for document in cursor:
print(document)

cursor = db.restaurants.find(
{"$or": [{"cuisine": "Italian"}, {"address.zipcode": "10075"}]})

4. 排序输出

import pymongo
cursor = db.restaurants.find().sort([
("borough", pymongo.ASCENDING),
("address.zipcode", pymongo.DESCENDING)
])

5. 更新

result = db.restaurants.update_many(
{"address.zipcode": "", "cuisine": "Other"},
{
"$set": {"cuisine": "Category To Be Determined"},
"$currentDate": {"lastModified": True}
}
)
print result.modified_count

6. 删除

result = db.restaurants.delete_many({"borough": "Manhattan"})

print result.deleted_count

7. 聚合

Group Documents by a Field and Calculate Count

Use the $group stage to group by a specified key. In the $group stage, specify the group by key in the _id field. $group accesses fields by the field path, which is the field name prefixed by a dollar sign $. The $group stage can use accumulators to perform calculations for each group. The following example groups the documents in the restaurants collection by the borough field and uses the $sum accumulator to count the documents for each group.

cursor = db.restaurants.aggregate(
[
{"$group": {"_id": "$borough", "count": {"$sum": }}}
]
)