Difference between revisions of "AGGREGATE examples"

Revision as of 13:16, 16 July 2015

#ENCODING
import io
import sys
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-16')
#MONGO
from pymongo import MongoClient
client = MongoClient()
client.progzoo.authenticate('scott','tiger')
db = client['progzoo']
#PRETTY
import pprint
pp = pprint.PrettyPrinter(indent=4)

Introducing the aggregation framework

These examples introduce the aggregation framework and its operators. Again we will be using the collection world

$match Allows us to perform queries in a similar way to find()

Show all the details for France

pp.pprint(list(
    db.world.aggregate([
        {"$match":{"name":"France"}}
    ])
))

pp.pprint(list(db.world.aggregate([{"$match":{"name":"France"}}])))

$project Allows us to select what fields to display.
It can also has the ability to insert new fields and allows you to compare fields against each other without using $where

Show the name and per capita GDP of all countries. (gdp/population)

pp.pprint(list(
    db.world.aggregate([
        {"$project":{
            "_id":0,
            "name":1,
            "per capita GDP": {"$divide": ["$gdp","$population"]}
        }}
    ])
))

pp.pprint(list(db.world.aggregate([{"$project":{"_id":0,"name":1,"per capita GDP": {"$divide": ["$gdp","$population"]}}}])))

@@ Line 49: / Line 49: @@
 </pre>
 <div class=ans>
-pp.pprint(list(db.world.aggregate([{"$project":{"_id":0,"name":1,"per capita GDP": {"$divide":["$gdp","$population"]}}}])
+pp.pprint(list(db.world.aggregate([{"$project":{"_id":0,"name":1,"per capita GDP": {"$divide": ["$gdp","$population"]}}}])))
-))["$population","$area"]}}}])))
 </div>
 </div>