Python How to pass specific key from list of Dictionary to Map function-CodePudding

I have data in below format: and I have function which accepts 2 keyword argument I am unable to come with syntax or example where i can pass specific keys from list of dictionaries to Map function to run as multi threading

import concurrent.futures

data = [
    {
        "name": "abc",
        "org": "pqr"
    },
    {
        "name": "xyz",
        "org": "sdf"
    }
    ]
def process_data(org_name, cu_name):
    print(org_name)
    print(cu_name)

with concurrent.futures.ThreadPoolExecutor() as Executor:
   results = Executor.map(process_data, data)

Since data consists different key i need to map org to org_name , But I am not sure how to pass with map function

CodePudding user response：

When you use data as the iterable in map() what will happen is that each element in the list will be passed to process_data. That function only receives one parameter.

So...

from concurrent.futures import ThreadPoolExecutor as TPE

data = [
    {
        "name": "abc",
        "org": "pqr"
    },
    {
        "name": "xyz",
        "org": "sdf"
    }
]

def process_data(d):
    for k, v in d.items():
        print(f'{k} = {v}')

with TPE() as tpe:
    tpe.map(process_data, data)

...may help to clarify

CodePudding user response：

Let your process_data function accept the needed keys org and name, so each input dictionary can be then unpacked (**) onto respective keys:

def process_data(org, name):
    print(org, name)

with concurrent.futures.ThreadPoolExecutor() as Executor:
   results = Executor.map(lambda kargs: process_data(**kargs), data)

pqr abc
sdf xyz

CodePudding user response：

    import concurrent.futures

data = [
    {
        "name": "abc",
        "org": "pqr"
    },
    {
        "name": "xyz",
        "org": "sdf"
    }
]


def process_data(org_name, cu_name):
    print(f'org = {org_name}')
    print(f'cu ={cu_name}')



with concurrent.futures.ThreadPoolExecutor() as Executor:
    result = Executor.map(lambda d: process_data(org_name=d['name'], cu_name=d['org']), data)

This worked for me thanks to Michael