How to extract two values from dict in python?

I would say try using pandas to group the user id’s together and convert it back to a dictionary

pd.DataFrame(slots_data).groupby('user_id')['id'].agg(list).reset_index().to_dict('records')

[{'user_id': 1, 'id': [551, 552, 553]},
 {'user_id': 2, 'id': [550]},
 {'user_id': 3, 'id': [525, 524]}]

The other answer added here has a nice solution, but here’s one without using pandas:

users = {}
for item in slots_data:
    # Check if we've seen this user before,
    if item['user_id'] not in users:
        # if not, create a new entry for them
        users[item['user_id']] = {'user_id': item['user_id'], 'slot_ids': []}

    # Add their slot ID to their dictionary
    users[item['user_id']]['slot_ids'].append(item['id'])

# We only need the values (dicts)
output_list = list(users.values())

thriough just simple loop way

>>> result = {}
>>> for i in slots_data:
...     if i['user_id'] not in result:
...             result[i['user_id']] = []
...     result[i['user_id']].append(i['id'])
... 
>>> output = []
>>> for i in result:
...     dict_obj = dict(user_id=i, slots_id=result[i])
...     output.append(dict_obj)
... 
>>> output
[{'user_id': 1, 'slots_id': [551, 552, 553]}, {'user_id': 3, 'slots_id': [525, 524]}, {'user_id': 2, 'slots_id': [550]}]

This can be made in a using listcomprehension:

final_list = [{"user_id": user_id, "id":sorted([slot["id"] for slot in slots_data if slot["user_id"] == user_id])} for user_id in sorted(set([slot["user_id"] for slot in slots_data]))]

A more verbose and better formatted version of the same code:

all_user_ids = [slot["user_id"] for slot in slots_data]
unique_user_ids = sorted(set(all_user_ids))
final_list = [
    {
        "user_id": user_id,
        "id": sorted([slot["id"] for slot in slots_data if slot["user_id"] == user_id])
    }
    for user_id in unique_user_ids]

Explanation:

1. get all the user ids with list comprehension
2. get the unique user ids by creating a set
3. create the final list of dictionaries using list comprehension.
4. each field id is of itself a list with list comprehension. We get the id of the slot, and only add it to the list, if the user ids match

You can use the following to get it done. Purely Python. Without any dependencies.

slots_data = [
        {
            "id":551,
            "user_id":1,
            "time":"199322002",
            "expire":"199322002"
        },
        {
            "id":552,
            "user_id":1,
            "time":"199322002",
            "expire":"199322002"
        },
        {
            "id":525,
            "user_id":3,
            "time":"199322002",
            "expire":"199322002"
        },
        {
            "id":524,
            "user_id":3,
            "time":"199322002",
            "expire":"199322002"
        },
        {
            "id":553,
            "user_id":1,
            "time":"199322002",
            "expire":"199322002"
        },
         {
            "id":550,
            "user_id":2,
            "time":"199322002",
            "expire":"199322002"
        }
    ]

user_wise_slots = {}
for slot_detail in slots_data:
    if not slot_detail["user_id"] in user_wise_slots:
        user_wise_slots[slot_detail["user_id"]] = {
            "user_id": slot_detail["user_id"],
            "slot_ids": []
        }
    user_wise_slots[slot_detail["user_id"]]["slot_ids"].append(slot_detail["id"])
print(user_wise_slots.values())

Using pandas you can easily achieve the result.
First install pandas if you don’t have as follow

pip install pandas

import pandas as pd
df = pd.DataFrame(slots_data) #create dataframe
df1 = df.groupby("user_id")['id'].apply(list).reset_index(name="slots_ids") #groupby on user_id and combine elements of id in list and give the column name is slots_ids
final_slots_data = df1.to_dict('records') # convert dataframe into a list of dictionary
final_slots_data

Output:

[{'user_id': 1, 'slots_ids': [551, 552, 553]},
 {'user_id': 2, 'slots_ids': [550]},
 {'user_id': 3, 'slots_ids': [525, 524]}]