Welcome to today's lesson on applying data filtering and aggregation in a real-world scenario using a user management system. We'll start by building a foundational structure that can handle basic user operations. Then, we'll expand it by introducing more advanced functionalities that allow filtering and aggregating user data.

In our starter task, we will implement a class that manages basic operations on a collection of user data, specifically handling adding new users, retrieving user profiles, and updating user profiles.

Here are the starter task methods with TypeScript type annotations:

• addUser(userId: string, age: number, country: string, subscribed: boolean): boolean - adds a new user with the specified attributes. Returns true if the user was added successfully and false if a user with the same userId already exists.
• getUser(userId: string): UserProfile | null - returns the user's profile as an object if the user exists; otherwise, returns null.
• updateUser(userId: string, age: number | null, country: string | null, subscribed: boolean | null): boolean - updates the user's profile based on non-null parameters. Returns true if the user exists and was updated, false otherwise.

The UserProfile data type is an interface that defines the structure of a user's profile, consisting of three properties: age which is a number, country which is a , and which is a . This interface ensures that every user profile adheres to this defined structure.

The TypeScript implementation of our starter task is shown below:

This implementation covers all our starter methods. Let's move forward and introduce more complex functionalities.

With our foundational structure in place, it's time to add functionalities for filtering user data and aggregating statistics.

Here are the new methods to implement with TypeScript type annotations:

• filterUsers(minAge: number | null, maxAge: number | null, country: string | null, subscribed: boolean | null): string[]:
  • Returns the list of user IDs that match the specified criteria. Criteria can be null, meaning that the criterion should not be applied during filtering.
• aggregateStats(): { totalUsers: number; averageAge: number; subscribedRatio: number } - returns statistics in the form of an object:
  • totalUsers: Total number of users
  • averageAge: Average age of all users (rounded down to the nearest integer)
  • subscribedRatio: Ratio of subscribed users to total users (as a float with two decimals)

This method filters users based on the criteria provided. Let's see how it works in TypeScript:

• The filterUsers method filters users based on minAge, maxAge, country, and subscribed status criteria.
• It iterates over the users object and checks each user's profile against the provided criteria.
• Users who meet all the criteria are added to the filteredUsers list, which is then returned.

This method aggregates statistics from the user profiles. Let's implement it in TypeScript:

• The aggregateStats method calculates aggregate statistics about users and returns them as an object.
• It begins by determining totalUsers, the total number of users.
• If no users exist, it returns an object with all statistics set to zero.
• With users present, it calculates totalAge by summing up all users' ages and counts how many are subscribedUsers.
• Next, it computes averageAge by dividing totalAge by totalUsers and rounding down to the nearest integer.

Here's the complete UserManager class with all methods, including the new ones for filtering and aggregation, all implemented in TypeScript:

Great job! Today, you've learned how to effectively handle user data in TypeScript by implementing advanced functionalities like filtering and aggregation on top of a basic system. TypeScript's robust typing aids significantly in data management and helps catch potential errors during development. This is a critical skill in real-life software development, where you often need to extend existing systems to meet new requirements.

I encourage you to practice solving similar challenges to solidify your understanding of data filtering and aggregation with strong type support. Happy coding, and see you in the next lesson!