I have this code in python to read a folder with jsons and create a list, as follows:

def get\_player\_jsons():
 print("Starting to read player jsons")
 current\_time = datetime.datetime.now()
 player\_actions\_list = list()
 for filename in os.listdir(PLAYER\_FOLDER):
 with open("%s/%s" % (PLAYER\_FOLDER,filename), "r",encoding="utf-8") as f:
 player\_id = filename.split(".")[0]
 player\_actions\_list.append({"playerId":player\_id,"actions":json.load(f)})
 end\_time = datetime.datetime.now()
 print("Time to load player jsons: %s" % (end\_time - current\_time))
 return player\_actions\_list

It takes 8 seconds to run for 557 items. Is there any way to speed it up?
 Yes, there are a few ways you could potentially speed up this code:

1. Use a faster JSON library: The standard `json` library in Python is not the fastest. You could try using a faster library such as `orjson` or `ujson`.
2. Use a list comprehension: Instead of using the `append` method to add items to the list one at a time, you can use a list comprehension to create the list in a single line of code. This can be faster because it avoids the overhead of calling the `append` method multiple times.
3. Use multiprocessing: If the JSON files are independent of each other, you can use multiprocessing to read and parse the files in parallel. This can be faster because it allows you to take advantage of multiple CPU cores.

Here's an example of how you could implement these suggestions:

```
import orjson
import os
from multiprocessing import Pool

PLAYER_FOLDER = "/path/to/player/folder"

def load_player_json(filename):
    with open(os.path.join(PLAYER_FOLDER, filename), "r", encoding="utf-8") as f:
        player_id = filename.split(".")[0]
        return {"playerId": player_id, "actions": orjson.
I have this code in python to read a folder with jsons and create a list, as follows:

def get\_player\_jsons():
 print("Starting to read player jsons")
 current\_time = datetime.datetime.now()
 player\_actions\_list = list()
 for filename in os.listdir(PLAYER\_FOLDER):
 with open("%s/%s" % (PLAYER\_FOLDER,filename), "r",encoding="utf-8") as f:
 player\_id = filename.split(".")[0]
 player\_actions\_list.append({"playerId":player\_id,"actions":json.load(f)})
 end\_time = datetime.datetime.now()
 print("Time to load player jsons: %s" % (end\_time - current\_time))
 return player\_actions\_list

It takes 8 seconds to run for 557 items. Is there any way to speed it up?

The time it takes to read and parse the files is likely dominated by the I/O operations and the parsing of the JSON files. Here are a few suggestions to potentially speed up your code:

1. Use a faster JSON library: The built-in `json` library in Python is not the fastest option available. You might consider using a faster library like `orjson` or `ujson` for parsing your JSON files.

2. Use multiprocessing: You can use Python's `multiprocessing` module to read multiple files concurrently. This can significantly reduce the time it takes to read the files if you have a multi-core CPU. Here's an example of how you can use `multiprocessing` to read the files:

```python
from multiprocessing import Pool

def process_file(filename):
    with open("%s/%s" % (PLAYER_FOLDER,filename), "r",encoding="utf-8") as f:
        player_id = filename.split(".")[0]
        player_actions = json.load(f)
        return {"playerId":player_id,"actions":player_actions}

def get_player_jsons():
    print("Starting to read player jsons")
    current_time = datetime.datetime.now()