FocusFlow α Sprint Blog Series (Part 4) - Homepage check-in & Overview

FOCUS_2025_SE 2025-12-19 20:42:55

1. Overview

Course	https://bbs.csdn.net/forums/2501_MU_SE_FZU
Assignment Requirement	https://bbs.csdn.net/topics/620061759
Team name	FocusFlow
Author	Hongzhi He(FZU:832302220 MU:23125390
Goal of this Assignment	Showcase the Alpha Sprint progress, including homepage check-in, homepage overview, etc.
Other References	IEEE Std 830-1998, GB/T 8567-2006

Sprint Burndown Chart
We tracked our progress meticulously throughout the sprint. The chart below illustrates our team's velocity in completing the task management user stories against our estimated timeline.

2. Function Realization Demonstration

We have implemented functions such as homepage check-in and homepage overview

2.1 Daily check-in system

In FocusFlow, the check-in function is not only a record of user login, but also an important incentive mechanism for cultivating study habits. Users gain a sense of achievement through continuous check-in, forming a positive feedback loop.

2.2 Data Overview Panel

The data overview panel can visually display learning progress, making users' goals clearer and their actions faster

3. Code Check-in Records (GitHub Commits)

Our development process is backed by regular code commits ensuring version control and collaboration.

4. Core Code Analysis

This task involves some core code, and the key parts will be presented below for analysis.
Firstly, the core code of the check-in function belongs to the data layer design
models.py

class Checkin:
    def __init__(self, id=None, user_id=None, date=None, created_at=None):
        self.id = id
        self.user_id = user_id
        self.date = date
        self.created_at = created_at

The Checkin class follows the "single responsibility principle" and is only responsible for storing the core information of check-in records By associating the user_id field with the User table, a one to many relationship between users and check-in records can be achieved. The date field is specifically used to store check-in dates (excluding specific times), making it easy to perform statistics and queries based on dates. The created date record is used to record the specific time point of check-in for subsequent auditing and analysis

The next step is the implementation of the check-in logic in the control layer, mainly consisting of the app.py file:
app.py

@app.route('/checkin', methods=['POST'])
@login_required
def checkin():
    user_id = session['user_id']
    today = datetime.now().strftime('%Y-%m-%d')  # 关键：标准化日期格式
    
    conn = get_db_connection()
    try:
        # 防重签机制：检查今天是否已经签到
        existing_checkin = conn.execute(
            'SELECT * FROM checkins WHERE user_id = ? AND date = ?',
            (user_id, today)
        ).fetchone()

        if existing_checkin:
            flash('You have already signed in today!', 'info')
        else:
            # 执行签到：插入新记录
            conn.execute(
                'INSERT INTO checkins (user_id, date) VALUES (?, ?)',
                (user_id, today)
            )
            conn.commit()
            flash('Sign in successful! Keep up the good work!', 'success')
    finally:
        conn.close()
    
    return redirect(url_for('dashboard'))

Ensure that the same user can only check in once on the same day through UNIQUE (user_id, date) database constraints and pre checks Perform operations in database transactions to ensure data consistency Provide instant feedback through flash messages to enhance user experience Store dates in% Y -% m -% d format to avoid time zone issues.

In addition, we have also implemented the function of continuous check-in, and the key part of it is also in the app.py file:
app.py

# 获取连续签到天数
streak_days = 0
checkin_dates = conn.execute('''
    SELECT date FROM checkins WHERE user_id = ? ORDER BY date DESC
''', (user_id,)).fetchall()

if checkin_dates:
    current_date = datetime.now().date()
    for checkin_date in checkin_dates:
        checkin_date_obj = datetime.strptime(checkin_date['date'], '%Y-%m-%d').date()
        if (current_date - checkin_date_obj).days == streak_days:
            streak_days += 1
        else:
            break

Calculate the consecutive days by checking the most recent check-in records in a loop Use (Current_date checkin_date_obj). days to calculate the date interval Sort by date DESC in descending order, starting from the most recent Terminate the loop immediately when discontinuous dates are detected.

In order to achieve real-time display of today's check-in status and task completion percentage, provide weekly learning trends, highlight consecutive check-in days, and other homepage functions, we still implement homepage aggregation in app.py. Some of the code is as follows:
app.py

# 获取签到信息
today = datetime.now().strftime('%Y-%m-%d')
has_checked_in = conn.execute('SELECT * FROM checkins WHERE user_id = ? AND date = ?',
                              (user_id, today)).fetchone() is not None

# 获取本周专注时长
week_start = (datetime.now() - timedelta(days=datetime.now().weekday())).strftime('%Y-%m-%d')
focus_time_query = conn.execute('''
    SELECT SUM(duration) as total_minutes 
    FROM focus_sessions 
    WHERE user_id = ? AND date(start_time) >= ?
''', (user_id, week_start)).fetchone()

# 获取任务统计
completed_tasks_query = conn.execute('''
    SELECT COUNT(*) as count FROM tasks WHERE user_id = ? AND status = 'completed'
''', (user_id,)).fetchone()

Aggregate data from the checkins, foci sessions, and tasks tables Calculate using relative time (this week, today) Reduce application layer computation by utilizing built-in functions such as SUM and COUNT in databases Only query relevant data when needed to avoid unnecessary database access.

Finally, we present the key code of our database design pattern:

-- 签到表的核心设计
CREATE TABLE checkins (
    id INTEGER PRIMARY KEY,
    user_id INTEGER NOT NULL,
    date DATE NOT NULL,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    UNIQUE(user_id, date)  -- 防止重复签到
);

The checkins table serves as the fact table, and the users table serves as the dimension table Store summary data such as stream_days in the users table to improve query performance Store check-in records by date partition for easy management of historical data.

5.Sprint Summary

5.1 Completed Deliverables

Core Homepage Redesign – Implemented dynamic dashboard with real-time data widgets
Daily Check-in System – Functional check-in button with streak tracking and calendar view
User Data Overview Panel – Displays pending tasks, study duration, completion rate, and weekly stats
Personalized Greetings – Time-based greetings (morning/afternoon/evening) with user name
Weekly Learning Trends – 7-day visual trend chart integrating check-ins and focus sessions
Database Schema Enhancement – Added checkins table and user statistics fields (current_streak, total_checkins, etc.)

5.2Technical Challenges and Resolutions:

Consecutive Day Calculation Logic:
Solution:Implemented date-difference iteration algorithm with early termination on break detection
Preventing Duplicate Check-ins:
Solution:Combined database UNIQUE constraint (user_id, date) with pre-check in application logic
Real-time Data Synchronization:
Solution:Used AJAX polling for stats updates and optimistic UI updates for check-in actions
Timezone Handling:
Solution:Stored all dates in UTC and converted to local time only for display purposes
Database Performance with Aggregates:
Solution:Added indexes on user_id, date fields and used SQL aggregation functions (SUM, COUNT)
Responsive Dashboard Layout:
Solution:Applied Bootstrap 5 grid system with conditional card stacking on mobile devices

The sprint successfully delivered a fully functional homepage with integrated check-in system and real-time learning analytics. All core acceptance criteria were met, with particular attention given to data accuracy, user experience, and system performance.

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