mongo 中的聚合查询有效，Pymongo 中无效 [英] Aggregate query in mongo works, does not in Pymongo

问题描述

我遇到了问题.我尝试通过COL"数组之外的 LOC 标识符查询此文档以获取金额和分组的总和.

I encountered a problem. I try to query this document to obtain the sum the amount and group by the LOC identifier that is outside the "COL" array.

{
"_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，但我无法使用 Pymongo 包使其在 Python 中运行:

This command works in mongo but I cannot make it work in Python with the Pymongo package:

db.perfiles.aggregate({"$unwind": "$COL"},
{ "$group": { _id: "$LOC", "sum" : {"$sum" : "$COL.amount" }}})

Pymongo(不工作)

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))

有什么建议可以在 Pymongo 中查询相同的查询?谢谢！

Any suggestion to query this same query but in Pymongo? Thanks!

推荐答案

我假设您在 Python 中有一个到 MongoDB 的有效连接.
以下代码片段将在 result.

I assume you have a valid connection to MongoDB in Python.
The following code snippet will return a MongoDB cursor in result.

pipeline = [
    {"$unwind": "$COL"},
    {"$group": {"_id": "$LOC", "sum": {"$sum": "$COL.amount"}}}
]

cursor = collection.aggregate(pipeline)

现在您可以将cursor 转换为列表

Now you can convert cursor to list

result = list(cursor)

如果您打印结果的值，您将获得与 Shell 查询完全相同的结果.

and if you print result's value, you'll get exactly the same result as in your Shell query.

[{u'sum': 200.0, u'_id': u'User001'}]

更新:

我看到您在 python 代码中将 aggregate 函数调用为 db.docs.aggregate(pipeline).您需要将其称为 docs.aggregate... 而无需 db.请参阅上面的示例.

I see that you are calling the aggregate function in python code as db.docs.aggregate(pipeline). You need to call it as docs.aggregate... without db. See example above.

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