Implement Athkar Streak Tracking: A Comprehensive Guide

by Alex Johnson 56 views

In this article, we'll delve into the intricacies of implementing Athkar streak tracking, a powerful feature that encourages users to maintain a consistent daily dhikr practice. This feature not only helps users stay on track but also provides a sense of accomplishment as they witness their streaks grow. Let's explore the objectives, scope, and acceptance criteria for implementing this valuable functionality.

Overview of Athkar Streak Tracking

Athkar streak tracking is a system designed to help users maintain a daily practice of dhikr (remembrance of God). By tracking consecutive days of practice, users are motivated to continue their streak and avoid missing a day. This feature involves several key components, including persistence of a daily streak counter, tracking all-time highest streaks, evaluating timezones for accurate day tracking, and implementing safeguards to prevent errors.

Objectives of Athkar Streak Tracking

The primary objective of Athkar streak tracking is to encourage consistent engagement with dhikr. This is achieved through several specific goals:

  • Persisting a daily streak counter for each user, with a default value of zero. This ensures that every user has a starting point from which to build their streak.
  • Tracking each user’s all-time highest streak and updating it whenever a new maximum is reached. This provides users with a long-term goal and a sense of progress.
  • Evaluating “today/yesterday” based on each user’s configured timezone, with UTC as a fallback when no preference exists. This ensures accurate tracking regardless of the user's location.
  • Exposing a safe increment flow that enforces consecutive-day rules. This prevents users from artificially inflating their streaks.
  • Clearing streaks automatically when a user misses a day, maintaining the integrity of the streak system.

Scope of Implementation

The implementation of Athkar streak tracking spans both the backend and frontend of the application. Each area has specific responsibilities to ensure the feature functions correctly.

Backend Implementation

The backend is responsible for the core logic and data management of the streak tracking system. This includes:

  • Introducing a streak persistence model, such as a database table or entity, with fields for streak_count (default 0), highest_streak (default 0), and last_completed_at timestamp. This model will store the streak data for each user.
  • Ensuring a streak row exists at zero upon user creation or first Athkar interaction. This sets the baseline for tracking.
  • Pulling the user’s timezone from the profile service and converting “now” plus last_completed_at into that zone before comparing. UTC should be used as a fallback when no timezone is stored. This ensures accurate date comparisons across different timezones.
  • Providing an endpoint or service method to increment the streak. This method should:
    • If streak_count is 0, accept the increment and set last_completed_at to the current day.
    • If streak_count > 0, compare last_completed_at:
      • If it equals yesterday, increment and update the timestamp.
      • If it equals today, reject as “already counted”.
      • If it is older than yesterday (missed day), reject with “streak reset required”.
    • Any successful increment should update highest_streak when streak_count surpasses the previous maximum.
  • Adding idempotent safeguards, such as per-user locks or unique constraints, to prevent double increments from concurrent requests. This ensures data integrity.
  • Implementing an hourly background job that scans streaks with streak_count > 0 where last_completed_at is older than yesterday, resets them to zero, and optionally logs metrics. This job maintains the accuracy of the streaks by resetting those that are no longer valid.

Frontend Implementation

The frontend is responsible for displaying the streak data to the user and providing feedback on their progress. This includes:

  • Displaying daily checkmarks using the backend streak data, allowing users to visually track their progress.
  • Surfacing backend error states distinctly (already counted today vs. missed day) so the UI can prompt appropriate messaging. This provides users with clear feedback on their actions.

Acceptance Criteria for Athkar Streak Tracking

To ensure the Athkar streak tracking system functions correctly, several acceptance criteria must be met. These criteria cover various aspects of the system, from data initialization to error handling.

  1. Streak records should initialize at 0 with highest_streak = 0 and last_completed_at = null (or equivalent) automatically. This ensures a clean starting point for all users.
  2. The increment API should enforce the date validation rules mentioned above and respond with clear status codes and messages. This ensures the integrity of the streak data.
  3. Attempting to increment twice on the same day should return an “already counted” response without modifying data. This prevents users from artificially inflating their streaks.
  4. Attempting to increment after skipping a day should return a “streak reset” response without modifying data. This maintains the accuracy of the streak system.
  5. The hourly background job should reset stale streaks (older than 24 hours) and log how many records were cleared. This ensures that streaks are accurately maintained over time.
  6. Successfully incrementing beyond the prior best should update highest_streak; resets should never decrease highest_streak. This provides users with a sense of achievement and prevents loss of progress.
  7. Date comparisons should respect the user’s timezone configuration, with automated tests covering both custom zones and the UTC fallback. This ensures accurate tracking across different timezones.
  8. Unit and integration tests should cover first increment, consecutive-day success, duplicate-day rejection, missed-day rejection, highest_streak updates, timezone conversion, and the background job reset path. Thorough testing is crucial to ensure the system functions correctly under various conditions.

Backend: Core Logic and Data Management

Streak Persistence Model

The foundation of Athkar streak tracking lies in the streak persistence model. This model is responsible for storing and managing streak data for each user. A well-designed persistence model is crucial for the reliability and scalability of the streak tracking feature.

At a minimum, the streak persistence model should include the following fields:

  • user_id: A unique identifier for the user.
  • streak_count: The current streak count for the user. This represents the number of consecutive days the user has practiced dhikr.
  • highest_streak: The user's all-time highest streak. This provides a long-term goal and a sense of achievement.
  • last_completed_at: A timestamp indicating the last day the user completed their dhikr practice. This is essential for determining whether the user has maintained their streak.

This model can be implemented as a database table, an entity in an ORM (Object-Relational Mapping) system, or any other suitable data storage mechanism. The choice of implementation will depend on the specific technology stack and requirements of the application.

Ensuring Streak Row Existence

To ensure that every user has a streak record, the system should automatically create a streak row when a user is created or interacts with the Athkar feature for the first time. This can be achieved in several ways:

  • User Creation Hook: When a new user account is created, a hook or event handler can be triggered to create a corresponding streak record with default values (streak_count = 0, highest_streak = 0, last_completed_at = null).
  • First Athkar Interaction: When a user interacts with the Athkar feature for the first time, the system can check if a streak record exists for the user. If not, a new record is created with default values.

Ensuring that a streak record exists for every user is crucial for the proper functioning of the streak tracking system. Without a record, the system would not be able to track the user's streak accurately.

Timezone Handling

Accurate timezone handling is essential for Athkar streak tracking. Users may be located in different timezones, and the system must correctly determine whether a user has completed their dhikr practice for the day based on their local time.

To achieve accurate timezone handling, the system should:

  • Pull the user's timezone from the profile service. This service should store the user's preferred timezone.
  • Convert the current time and the last_completed_at timestamp into the user's timezone before comparing them. This ensures that the comparison is based on the user's local time.
  • Use UTC as a fallback when no timezone is stored for the user. This ensures that the system still functions correctly even if the user has not set a timezone preference.

Incrementing the Streak

The core logic for incrementing the streak is implemented in an endpoint or service method. This method is responsible for enforcing the rules of Athkar streak tracking and ensuring that streaks are incremented correctly.

The increment streak method should follow these steps:

  1. Check the current streak_count.
  2. If streak_count is 0, accept the increment and set last_completed_at to the current day.
  3. If streak_count is greater than 0, compare last_completed_at with the current date:
    • If last_completed_at equals yesterday, increment the streak and update the timestamp.
    • If last_completed_at equals today, reject the increment with an “already counted” message.
    • If last_completed_at is older than yesterday, reject the increment with a “streak reset required” message.
  4. If the increment is successful, update highest_streak if the new streak_count surpasses the previous maximum.

Idempotent Safeguards

To prevent double increments from concurrent requests, the system should implement idempotent safeguards. This ensures that the streak count is not inadvertently incremented multiple times due to multiple requests being processed simultaneously.

Two common techniques for implementing idempotent safeguards are:

  • Per-user locks: A lock can be acquired for each user before incrementing the streak and released after the increment is complete. This prevents concurrent requests from modifying the same user's streak data.
  • Unique constraints: A unique constraint can be added to the database table to prevent multiple records with the same user ID and date. This ensures that only one increment can be recorded for each user on each day.

Background Job for Resetting Streaks

To maintain the accuracy of the streak system, an hourly background job should be implemented to reset stale streaks. This job should scan all streaks with a streak_count greater than 0 where last_completed_at is older than yesterday and reset them to zero.

In addition to resetting streaks, the background job can also log metrics, such as the number of streaks cleared. This provides valuable insights into the usage of the Athkar streak tracking feature.

Frontend: Displaying Streak Data and Error States

The frontend plays a crucial role in displaying streak data to the user and providing feedback on their progress. A well-designed user interface can significantly enhance the user experience and motivation.

Displaying Daily Checkmarks

The most common way to display streak data is by using daily checkmarks. Each checkmark represents a day on which the user completed their dhikr practice. The checkmarks can be displayed in a calendar view or any other suitable format.

By visually representing their streak, users can easily track their progress and see how many consecutive days they have maintained their practice.

Surfacing Backend Error States

It is essential for the frontend to surface backend error states clearly. This provides users with valuable feedback on their actions and helps them understand why their streak may not have been incremented.

Two common error states that should be surfaced are:

  • “Already counted today”: This error indicates that the user has already incremented their streak for the current day.
  • “Streak reset required”: This error indicates that the user has missed a day and their streak has been reset.

The frontend should display these error messages in a clear and concise manner, prompting the user with appropriate messaging. For example, if the user has missed a day, the frontend could display a message encouraging them to start a new streak.

Acceptance Criteria: Ensuring System Functionality

The acceptance criteria for Athkar streak tracking are designed to ensure that the system functions correctly and meets the needs of users. These criteria cover various aspects of the system, from data initialization to error handling.

Data Initialization

The system should automatically initialize streak records with the following values:

  • streak_count = 0
  • highest_streak = 0
  • last_completed_at = null

This ensures that every user has a clean starting point for tracking their streak.

Increment API Validation

The increment API should enforce the date validation rules mentioned above and respond with clear status codes and messages. This ensures the integrity of the streak data.

Specifically, the API should:

  • Return an “already counted” response if the user attempts to increment their streak twice on the same day.
  • Return a “streak reset required” response if the user attempts to increment their streak after skipping a day.

Background Job Functionality

The hourly background job should reset stale streaks (older than 24 hours) and log how many records were cleared. This ensures that streaks are accurately maintained over time.

Highest Streak Updates

The system should correctly update the highest_streak value when a user successfully increments their streak beyond their prior best. Resets should never decrease the highest_streak value.

Timezone Handling

Date comparisons should respect the user’s timezone configuration, with automated tests covering both custom zones and the UTC fallback. This ensures accurate tracking across different timezones.

Unit and Integration Tests

Thorough unit and integration tests should be implemented to cover various scenarios, including:

  • First increment
  • Consecutive-day success
  • Duplicate-day rejection
  • Missed-day rejection
  • highest_streak updates
  • Timezone conversion
  • Background job reset path

Conclusion

Implementing Athkar streak tracking is a valuable addition to any application that promotes daily practice and consistency. By understanding the objectives, scope, and acceptance criteria, developers can create a robust and user-friendly feature that encourages users to maintain their dhikr practice. From backend data management to frontend display, every aspect of the system plays a crucial role in the success of Athkar streak tracking.

For more information on best practices in software development and project management, consider exploring resources from trusted websites such as agilealliance.org.