Persistent Data
Building a Statistics Bot
This guide provides a detailed, step-by-step walkthrough of the implementation of the Statistics Bot. The Statistics Bot is a bot for the Highrise platform that tracks and reports user activity. It also features a leaderboard for the most active users.
Prerequisites:
- Python 3.11 or higher installed.
- Highrise Python SDK installed
- Make sure that an empty
data.jsonfile exists in the same directory as your bot file. This file will be used to store user activity data in JSON format. You can create it with the following content:
{
}
Step 1: Import Required Libraries
The first step in creating the Statistics Bot is to import the necessary libraries. These libraries provide the functions and classes we need to interact with Highrise and perform calculations.
from json import load, dump
from time import time
from math import sqrt
from highrise import BaseBot, User, Position, AnchorPosition
Here's what each import is for:
json: This module is used to work with JSON data.time: This module is used to get the current time, which helps in calculating the time spent by a user in the room.sqrt: This function from themathmodule is used to calculate the distance a user travels in the room.BaseBot, User, Position, AnchorPosition: These classes from thehighrisemodule are used to interact with the Highrise platform.
3. Defining the StatisticsBot Class
Next, we define the StatisticsBot class, which extends the BaseBot class from the Highrise library. This class will contain all the functionality for our bot.
class StatisticsBot(BaseBot):
identifier: str = "/s " # Command prefix for the bot
lobby: Dict[str, dict] = {} # A dictionary to store user activity data temporarily
We define two class variables: identifier and lobby. identifier is the command prefix that users will use to interact with the bot. lobby is a dictionary that will temporarily store user data while they are in the room.
4. Implementing Event Handlers
We override several event handlers from the BaseBot class to track user activity in the room. These handlers respond to events such as users joining the room, leaving the room, moving within the room, and sending chat message
4.1 on_chat Event Handler
The on_chat method is called whenever a user sends a chat message in the room. Here, we perform two tasks: we update the total number of characters the user has sent in chat messages, and we check if the message is a command for our bot.
async def on_chat(self, user: User, message: str) -> None:
num_chars = len(message)
self.write_data(user, "chat_message_chars", num_chars)
if (message.startswith(self.identifier)):
await self.handle_command(user, message.removeprefix(self.identifier))
In this method, num_chars is the number of characters in the chat message. We then call write_data to update the user's total chat message characters in the data.json file (which we will define later). Finally, we check if the message starts with our bot's command prefix (/s ), and if it does, we call handle_command to process the command.
4.2 on_user_join Event Handler
The on_user_join method is called whenever a user joins the room. In this method, we add the user to our lobby dictionary with a default data set if they are not already in it.
async def on_user_join(self, user: User) -> None:
if not user.id in self.lobby:
self.lobby[user.id] = self.create_default()
4.3 on_user_leave Event Handler
The on_user_leave method is called whenever a user leaves the room. Here, we calculate the total time the user spent in the room, update this in the data.json file, and then remove the user from our lobby dictionary.
async def on_user_leave(self, user: User) -> None:
if user.id in self.lobby:
time_spent = round(time() - self.lobby[user.id]["time_joined"])
self.write_data(user, "time_spent", time_spent)
del self.lobby[user.id]
4.4 on_user_move Event Handler
The on_user_move method is called whenever a user moves within the room. We use this method to track the distance the user travels. If the user's position is of type Position, we calculate the distance between their new position and their last position, update this in the data.json file, and then update their last position in our lobby dictionary.
async def on_user_move(self, user: User, pos: Position | AnchorPosition) -> None:
if isinstance(pos, Position):
if not user.id in self.lobby:
self.lobby[user.id] = self.create_default()
distance = self.calculate_distance(self.lobby[user.id]["last_pos"], pos)
self.write_data(user, "distance_travelled", distance)
self.lobby[user.id]["last_pos"] = pos
5. Implementing Helper Methods
Several helper methods are used to perform various tasks such as writing data to the JSON file, handling bot commands, calculating the distance a user has traveled, and generating the leaderboard.
5.1 write_data Helper Method
The write_data method is used to write user activity data to the data.json file. It takes as arguments the user, the key of the data (e.g., "time_spent"), and the value of the data.
def write_data(self, user: User, key: str, value: int) -> None:
with open("./data.json", "r+") as file:
data = load(file)
file.seek(0)
if user.id in data:
data[user.id][key] = data[user.id][key] + value
else:
data[user.id] = {
"time_spent": 0,
"chat_message_chars": 0,
"distance_travelled": 0,
"username": user.username
}
data[user.id][key] = value
print(f"Updated {user.username} with {value} of {key}")
dump(data, file)
file.truncate()
(Ideally, reading and writing to the file system should be done asynchronously, with a library like aiofiles)
5.2 handle_command Helper Method
The handle_command method is used to process the commands sent by users in the chat. It takes as arguments the user and the message (without the command prefix).
async def handle_command(self, user: User, message: str) -> None:
match message:
case "leaderboard":
with open("./data.json", "r") as file:
data = load(file)
top_five = self.get_leaderboard(data)
await self.highrise.chat("Leaderboard:\n" + "\n".join(top_five))
case username if message.startswith("@") and len(message[1:]) > 0:
with open("./data.json", "r") as file:
data = load(file)
username = username[1:]
for value in data.values():
if value["username"] == username:
stats = [
f"Distance Walked: {value['distance_travelled']}",
f"Time Spent: {value['time_spent']}",
f"Characters Messaged: {value['chat_message_chars']}"
]
return await self.highrise.chat(f"{username}:\n" + "\n".join(stats))
return await self.highrise.chat(f"{username} does not exist or has not joined this room before")
case _:
await self.highrise.send_whisper(user.id, f"Not a valid command. Use {self.identifier}help to see the list of commands")
This method supports two commands: /s leaderboard to generate a leaderboard of the top five most active users, and /s @<username> to display activity metrics for the specified user.
5.3 calculate_distance Helper Method
The calculate_distance method is used to calculate the distance a user has traveled based on their last and next positions.
def calculate_distance(self, lastpos: Position, nextpos: Position) -> None:
return round(sqrt(pow(lastpos.x - nextpos.x, 2) + pow(lastpos.y - nextpos.y, 2) + pow(lastpos.z - nextpos.z, 2)))
This completes the implementation of the Statistics Bot. To use the bot, simply type /s leaderboard or /s @<Myusername> in the chat room where your bot is active. Replace <Myusername> with your desired username.
Here is the full code:
from json import load, dump
from time import time
from math import sqrt
from highrise import BaseBot, User, Position, AnchorPosition
"""
Note:
Make sure there exists an empty data.json file in the directory of the bot file.
Usage:
To start interacting with the statistics bot, use any of the following commands in the chat of the
room your bot is currently in to see statistics of users who have entered your room:
/s leaderboard
/s @<username>
Example:
/s @Myusername
The Statistics Bot will provide you with activity metrics for the specified user.
"""
class StatisticsBot(BaseBot):
"""
A Highrise bot that passively tracks user activity in a room.
This class extends the base Highrise bot and uses a local JSON file to record
user activity. It offers commands to view specific users' activity, along with
a leaderboard of the most active users in the room.
"""
identifier: str = "/s " # Command prefix for the bot
lobby: dict[str, dict] = {} # A dictionary to store user activity data temporarily
async def on_chat(self, user: User, message: str) -> None:
"""On a received room-wide chat."""
# Calculate the number of characters in the message
num_chars = len(message)
# Write the data to JSON
self.write_data(user, "chat_message_chars", num_chars)
# Handle commands
if message.startswith(self.identifier):
await self.handle_command(user, message.removeprefix(self.identifier))
async def on_user_join(self, user: User) -> None:
"""On a user joining the room."""
if not user.id in self.lobby:
# Add the user to the lobby
self.lobby[user.id] = self.create_default()
async def on_user_leave(self, user: User) -> None:
"""On a user leaving the room."""
if user.id in self.lobby:
# Calculate the number of seconds the user spent in the room
time_spent = round(
time() - self.lobby[user.id]["time_joined"])
# Write the data to JSON
self.write_data(user, "time_spent", time_spent)
# Remove the user's entry from the lobby
del self.lobby[user.id]
async def on_user_move(self, user: User, pos: Position | AnchorPosition) -> None:
"""On a user moving in the room."""
# We're only tracking distance for Position, not AnchorPosition
if isinstance(pos, Position):
if not user.id in self.lobby:
self.lobby[user.id] = self.create_default()
# Calculate the distance
distance = self.calculate_distance(
self.lobby[user.id]["last_pos"], pos)
# Write the data to JSON
self.write_data(user, "distance_travelled", distance)
# Set their new "last_pos"
self.lobby[user.id]["last_pos"] = pos
def write_data(self, user: User, key: str, value: int) -> None:
"""Writes data to local JSON file"""
with open("./data.json", "r+") as file:
data = load(file)
# Move the file pointer back to the beginning
file.seek(0)
# Perform desired operations on the data
if user.id in data:
data[user.id][key] = data[user.id][key] + value
else:
# New user in the room
data[user.id] = {
"time_spent": 0,
"chat_message_chars": 0,
"distance_travelled": 0,
"username": user.username
}
data[user.id][key] = value
# Print the updated data
print(f"Updated {user.username} with {value} of {key}")
# Write the updated data back to the file
dump(data, file)
file.truncate()
async def handle_command(self, user: User, message: str) -> None:
"""Handler for all bot commands"""
match message:
case "leaderboard" | "Leaderboard":
with open("./data.json", "r") as file:
data = load(file)
# Get the top 5 most active users by score
top_five = self.get_leaderboard(data)
await self.highrise.chat("Leaderboard:\n" + "\n".join(top_five))
case username if message.startswith("@") and len(message[1:]) > 0:
with open("./data.json", "r") as file:
data = load(file)
username = username[1:] # trim @ character
for value in data.values():
if value["username"] == username:
stats = [
f"Distance Walked: {value['distance_travelled']}",
f"Time Spent: {value['time_spent']}",
f"Characters Messaged: {value['chat_message_chars']}"
]
return await self.highrise.chat(f"{username}:\n" + "\n".join(stats))
# User does not exist in our JSON
return await self.highrise.chat(f"{username} does not exist or has not joined this room before")
case _:
await self.highrise.send_whisper(user.id, f"Not a valid command. Use {self.identifier}help to see the list of commands")
def calculate_distance(self, lastpos: Position, nextpos: Position) -> None:
"""Calculate the distance a user has travelled based on their last and next locations"""
return round(sqrt(pow(lastpos.x - nextpos.x, 2) + pow(lastpos.y - nextpos.y, 2) + pow(lastpos.z - nextpos.z, 2)))
def create_default(self) -> dict[str, object]:
"""Create a dictionary to track user data"""
return ({
"last_pos": Position(0, 0, 0, "FrontRight"),
"time_joined": time()
})
def get_leaderboard(self, data: dict[str, dict]) -> list[str]:
"""Returns the top 5 most active users based on their score, where the score is the sum of all metrics"""
# Calculate the score for each user
scores = {metrics["username"]: self.calculate_score(
metrics) for metrics in data.values()}
# Sort the users based on their scores in descending order
sorted_users = sorted(scores, key=scores.get, reverse=True)
# Get the top 5 users
top_five = sorted_users[:5]
return top_five
def calculate_score(self, data: dict[str, dict]) -> list[str]:
"""Calculates the score of a user to determine leaderboard rankings"""
return data["time_spent"] + data["chat_message_chars"] + data["distance_travelled"]
Updated 9 months ago
