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[英]Mongo aggregate query with forEach function in pymongo not working
[英]Aggregate query in mongo works, does not in Pymongo
我遇到了一個問題。 我嘗試通過“COL”數組之外的 LOC 標識符查詢此文檔以獲取金額和分組的總和。
{
"_id" : ObjectId("57506d74c469888f0d631be6"),
"LOC" : "User001",
"COL" : [
{
"date" : "25/03/2016",
"number" : "Folio009",
"amount" : 100
},
{
"date" : "25/04/2016",
"number" : "Folio010",
"amount" : 100
}
] }
此命令在 mongo 中有效,但我無法使用 Pymongo 包使其在 Python 中運行:
db.perfiles.aggregate({"$unwind": "$COL"},
{ "$group": { _id: "$LOC", "sum" : {"$sum" : "$COL.amount" }}})
from pymongo import MongoClient
client = MongoClient()
db = client['temporal']
docs = db.perfiles
pipeline = [{"$unwind": "$COL"},
{"$group": {"_id": "$LOC", "count": {"$sum": "$COL.amount"}}}
]
list(db.docs.aggregate(pipeline))
有什么建議可以在 Pymongo 中查詢相同的查詢? 謝謝!
我假設您在 Python 中有一個到 MongoDB 的有效連接。
以下代碼片段將在result.
返回一個 MongoDB 游標result.
pipeline = [
{"$unwind": "$COL"},
{"$group": {"_id": "$LOC", "sum": {"$sum": "$COL.amount"}}}
]
cursor = collection.aggregate(pipeline)
現在您可以將cursor
轉換為列表
result = list(cursor)
如果您打印結果的值,您將獲得與 Shell 查詢完全相同的結果。
[{u'sum': 200.0, u'_id': u'User001'}]
更新:
我看到你在 python 代碼中調用aggregate
函數作為db.docs.aggregate(pipeline)
。 您需要將其稱為docs.aggregate...
不帶db
。 請參閱上面的示例。
MongoDB Enterprise > db.test.aggregate([{$match:{name:'prasad'}},{$group : {_id : "$name", age : {$min : "$age"}}}]);
{ "_id" : "prasad", "age" : "20" }
MongoDB Enterprise > db.test.find()
{ "_id" : ObjectId("5890543bce1477899c6f05e8"), "name" : "prasad", "age" : "22" }
{ "_id" : ObjectId("5890543fce1477899c6f05e9"), "name" : "prasad", "age" : "21" }
{ "_id" : ObjectId("58905443ce1477899c6f05ea"), "name" : "prasad", "age" : "20" }
{ "_id" : ObjectId("5890544bce1477899c6f05eb"), "name" : "durga", "age" : "20" }
{ "_id" : ObjectId("58905451ce1477899c6f05ec"), "name" : "durga", "age" : "21" }
{ "_id" : ObjectId("58905454ce1477899c6f05ed"), "name" : "durga", "age" : "22" }
MongoDB Enterprise >
############code
import pymongo
from pymongo import MongoClient
client=MongoClient("localhost:27017")
db=client.prasad #####prasad is dbname, test is collection name
nameVar='prasad'
aggregation_string=[{"$match":{"name":nameVar}},{"$group" : {"_id" : "$name", "age" : {"$min" : "$age"}}}]
x=db.test.aggregate(aggregation_string)
print x
for r in x:
min_age=r.items()[0]
print(min_age[1]) #######output: 20
you are in a right track but add one more statement it will be fine.
from pymongo import MongoClient
client = MongoClient()
db = client['temporal']
docs = db.perfiles
pipeline = [{"$unwind": "$COL"},
{"$group": {"_id": "$LOC", "count": {"$sum": "$COL.amount"}}}
]
result = list(db.docs.aggregate(pipeline))
for i in result:
sum += i['sum']
print(sum)
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