Setting Up the Feature Progress Data File
 
Create a new file called features.json in the root directory of your project. This file will hold the current status of each feature in a simple JSON format. Copy and paste the following code into features.json:

{
  "login\_feature": "in development",
  "payment\_gateway": "pending review",
  "user\_profile": "completed",
  "notification\_system": "not started"
}

This file acts as your single source of truth for the status of various features.

 
Creating the Feature Tracker Script
 
Next, create a new file named feature_tracker.py in the root directory. This script will load the JSON data, allow you to update a feature’s status, and display the progress of all features. Since Lovable does not have terminal access, we include everything inside the code so that running this script within your environment will automatically handle the progress tracking.

Copy and paste the following code into feature_tracker.py:

import json

def load\_features():
    # Open the features data file and return the data as a dictionary.
    with open("features.json", "r") as file:
        features = json.load(file)
    return features

def save\_features(features):
    # Save updated feature statuses back into the JSON file.
    with open("features.json", "w") as file:
        json.dump(features, file, indent=2)

def update_feature(feature_name, new\_status):
    features = load\_features()
    if feature\_name in features:
        features[feature_name] = new_status
        save\_features(features)
        print(f"Updated {feature_name} to '{new_status}'")
    else:
        print(f"Feature '{feature\_name}' not found.")

def display\_features():
    features = load\_features()
    print("Current Feature Progress:")
    for feature, status in features.items():
        print(f" - {feature}: {status}")

# The following lines simulate a typical run where updates can occur.
if **name** == "**main**":
    display\_features()
    # To update a feature, call update\_feature with the feature name and new status.
    # For example, uncomment the following line to update 'login\_feature' to 'completed'.
    # update_feature("login_feature", "completed")
    # Then display again to see changes.
    # display\_features()

Since Lovable does not allow dependency installations via a terminal, note that this script uses Python’s built-in json module, which does not require extra installation. Simply ensure that you save both files in your project.

 
Integrating Feature Tracker into Your Main Application
 
It is important to connect your feature tracking to the rest of your project. Suppose you have a main application file (for example, main.py) where your project logic runs. In the appropriate section of main.py (for example, when the application starts or when a user action occurs), you can import and call the functions from feature_tracker.py.

Add the following code at the top or wherever you manage your application’s startup routines in main.py:

from feature_tracker import display_features, update\_feature

# Display current progress when the application starts.
display\_features()

# When a feature is updated (for example, after a user action), you can call:
# update_feature("payment_gateway", "in development")

Place these lines in main.py where you want to integrate feature progress tracking. For instance, if there is a setup section in the file, you might insert the code just before the application starts processing user inputs.

 
Explanation and Usage
 
The features.json file contains the roadmap details for your project’s features. The feature_tracker.py script reads that file, displays the progress, and updates the JSON file when a feature’s status changes. Finally, integrating these functions into main.py connects the tracker with your main application flow.

When your application runs (using your platform’s run button or equivalent), main.py will call display_features to show the current progress. You can later use update_feature to change any feature’s status, and then call display_features again to see the updated progress.

This setup ensures that all feature progress is neatly organized and tracked, allowing you to monitor and manage your v0 project’s development status easily.

 
Organizing Your Project Structure for Feature Tracking
 

• Create a new folder in your project directory named tracking. This folder will hold all files related to tracking the progress of your features.
• Inside the tracking folder, create a file called feature\_tracker.py. This file will act as a basic module to record and update the status of different features as you develop your project.
• In feature\_tracker.py, add the following code snippet. It defines a basic class that stores feature names and their current progress in a simple in-memory dictionary:

  
  class FeatureTracker:
      def **init**(self):
          self.features = {}
  
  def add\_feature(self, name):
      if name not in self.features:
          self.features[name] = 'not started'
          print(f"Feature '{name}' added.")
      else:
          print(f"Feature '{name}' already exists.")
  
  def update\_feature(self, name, status):
      if name in self.features:
          self.features[name] = status
          print(f"Feature '{name}' updated to: {status}.")
      else:
          print(f"Feature '{name}' not found. Please add it first.")
  
  def get\_progress(self):
      return self.features
  
  Example usage:
  if name == 'main':
      tracker = FeatureTracker()
      tracker.add_feature("Login")
      tracker.update_feature("Login", "in progress")
      print(tracker.get_progress())
      

  
  


• This file is self-contained and does not require external dependencies. Simply put this file under the tracking folder.

 
Implementing a Logging System for Feature Progress
 

• Create another file within the same tracking folder named logger.py. This file will contain a simple logging system to help you monitor feature tracking activity.
• Add the following code snippet to logger.py to implement a lightweight logging function:

  
  def log(message):
      # Here we simulate logging by simply printing the messages.
      # In production, you might want to write these logs to a file.
      print(f"[LOG]: {message}")
  
  Example usage:
  if name == 'main':
      log("Logger initialized and ready to record feature progress.")
      

  
  


• No additional dependencies are required as this uses basic Python functionality.

 
Integrating the Feature Tracker and Logger into Your Application
 

• In your main application file (commonly main.py), import the modules you created to start tracking and logging feature progress. This integration helps you monitor the progress of each feature as you work on them.
• Add the following code snippet to main.py:

  
  from tracking.feature\_tracker import FeatureTracker
  from tracking.logger import log
  
  Initialize the feature tracker
  tracker = FeatureTracker()
  Add new features
  tracker.add_feature("User Authentication")
  tracker.add_feature("Dashboard")
  Update progress of features
  tracker.update_feature("User Authentication", "in progress")
  tracker.update_feature("Dashboard", "not started")
  Log the current progress of features
  log(f"Current Feature Progress: {tracker.get_progress()}")
  Continue with the rest of your application code below
  </code></pre>
  
    

• This code should be placed at the beginning of main.py so that feature progress tracking and logging is available as soon as your application starts.

 
Documenting and Commenting Your Feature Tracking Code
 

• Ensure that each function and class in your feature\_tracker.py and logger.py files has clear comments. This helps any non-technical collaborator understand the purpose of each component.
• For instance, in feature\_tracker.py, comments like the ones in the provided snippet explain what the function is doing. Continue to add such comments as you expand functionality.
• Whenever a new feature is added or updated in the code, add an inline comment detailing the change.

 
Troubleshooting Feature Tracking Issues
 

• If you encounter an error where a feature is not being added or updated correctly, first ensure that the feature name is spelled consistently and that the FeatureTracker object is properly initialized in main.py.
• Use the logging system in logger.py to print out the state of feature progress. For example, if a feature is missing, you can add an extra log message in the update_feature method in feature_tracker.py:

  
  def update\_feature(self, name, status):
      if name in self.features:
          self.features[name] = status
          print(f"Feature '{name}' updated to: {status}.")
      else:
          print(f"Feature '{name}' not found. Please add it first.")
          # Debugging: Log an error if the feature does not exist
          from tracking.logger import log
          log(f"Error: Tried to update a non-existent feature '{name}'.")
      

• This approach allows you to track exactly when and where the error occurs, making it easier to fix the issue without having to delve into more complex debugging tools.