Abstracted data loading so that data can be loaded simply through the config file. Moved Mike's LLM data generation code and my own dummy data generating code to the database folder.

app/database/create_basic_dummy_data.py

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+# Quick script to create basic dummy data for the caching system
+# Current theme/usage is in a social media microservice setting such as Twitter
+# Current database schema:
+### user_id (primary key), str
+### username, string
+### num_followers, int
+### posts, str (for now, can be list later on)
+### friends, list[user_id]
+
+import json
+import random
+
+# Parameters to change the distribution/random ranges
+TOTAL_USERS = 20
+MIN_FOLLOWERS, MAX_FOLLOWERS = 0, 5
+MIN_POSTS, MAX_POSTS = 5, 10
+MIN_FRIENDS, MAX_FRIENDS = 1, 5
+
+# Create the user data
+# TODO if we want to vary the user data more, we can inflate the posts into a list of strings and make the strings very long :3"
+data = {}
+for user_id in range( TOTAL_USERS ):
+    user = {}
+    user["user_id"] = str( user_id )
+    user["username"] = "user" + str( user_id )
+    user["num_followers"] = random.randint( MIN_FOLLOWERS, MAX_FOLLOWERS )
+    
+    # Just make a single post for now, can consider mutliple posts later
+    user["posts"] = f"This is user {user_id}'s post!"
+
+    # posts = []
+    # for post_num in range( random.randint( MIN_FOLLOWERS, MAX_FOLLOWERS ) ):
+    #     posts.append( f"This is user {user_id}'s post {str( post_num + 1 )}!" )
+    # user["posts"] = posts
+    
+    friends = []
+    user["friends"] = random.sample( [u_id for u_id in range( TOTAL_USERS ) if u_id != user_id], random.randint( MIN_FOLLOWERS, MAX_FOLLOWERS ) )
+
+    data[user_id] = user
+
+# Load the data into a json object and write it into the datastore folder
+json_object = json.dumps( {"_default": data}, indent=4 )
+with open( "datastore/basicDummy_sns.json", "w" ) as f:
+    f.write( json_object )