So I have a dictionary which is a hash object I'm getting from Redis, similar to the following dictionary:

```
source_data = {
   b'key-1': b'{"age":33,"gender":"Male"}', 
   b'key-2': b'{"age":20,"gender":"Female"}'
}

```

My goal is extract all the values from this dictionary and have them as a list of Python dictionaries like so:

```
final_data = [
   {
      'age': 33,
      'gender': 'Male'
   },

   {
      'age': 20,
      'gender': 'Female'
   }
]

```

I tried list comprehension with json parsing:

```
import json
final_data = [json.loads(a) for a in source_data.values()]

```

It works but for large data set, it takes too much time.

I switch to using this 3rd party json module [ujson](https://pypi.org/project/ujson/) which is faster according to this [benchmark](https://artem.krylysov.com/blog/2015/09/29/benchmark-python-json-libraries/), but I haven't noticed any improvement.

I tried using multi-threading :

```
pool = Pool()
final_data = pool.map(ujson.loads, source_data.values(), chunksize=500)

pool.close()
pool.join()

```

I played a bit with `chunksize` but the result is the same, still taking too much time.

It would be super helpful if someone can suggest another solution or improvement to previous tries, it would be ideal if I could avoid using a loop.