Saving User Scrub Changes In Supabase: A Developer's Guide

Welcome, fellow developers! Today, we're diving into a crucial aspect of building robust and user-friendly applications: persisting user modifications within a Supabase database. Specifically, we'll focus on how to effectively store user changes to scrub results, ensuring that their validations are preserved across sessions and re-scrubs. This is a common requirement when building applications that involve data cleaning, validation, and enrichment, and this guide will provide you with a clear roadmap to implement it in your Supabase project.

The Core Challenge: Persisting User-Specific Scrub Modifications

Imagine a scenario where users are reviewing and modifying data scrub results. For instance, they might be correcting or verifying the values of certain tags, such as "landlocked" or "flood_zone." The fundamental problem is how to ensure that these user-specific modifications are saved and consistently applied whenever the user revisits the data or re-runs the scrub process. Without a proper persistence mechanism, all the user's hard work would be lost, leading to a frustrating user experience. This guide will solve the core challenge, allowing you to build applications where user input is valued and remembered.

This is where Supabase comes in. Supabase offers a powerful and flexible platform for building backend functionality, including a Postgres database, authentication, and real-time capabilities. By leveraging Supabase, we can create a system that elegantly stores user modifications, making sure that their data corrections are always available.

Step-by-Step Implementation: Building the User Scrub Modifications System

Let's break down the implementation into a series of actionable steps, covering table creation, data management, and security considerations.

1. Creating the user_scrub_modifications Table

The cornerstone of our solution is the user_scrub_modifications table. This table will hold all the user-specific modifications to scrub results. Here's a breakdown of the table structure:

• id (primary key, UUID): A unique identifier for each modification record.
• user_id (foreign key to the users table): Links the modification to the specific user.
• property_id (string, from GHL or backend): Identifies the specific property being modified. This could be a unique identifier from your data source, such as a property ID from a GHL integration.
• scrub_tag (string, e.g., "landlocked", "flood_zone"): The specific scrub tag that the user has modified.
• original_value (string: "true", "false", "unknown"): The original value of the scrub tag.
• user_value (string: "true", "false", "unknown"): The value the user has set.
• modified_at (timestamp): The timestamp when the modification was made.
• scrub_session_id (optional, to group modifications from the same scrub): An optional field to group modifications made during a single scrub session. This can be useful for tracking changes made within a specific context.

To create this table in Supabase, you can use the SQL query provided as follows:

create table user_scrub_modifications (
    id uuid primary key default gen_random_uuid(),
    user_id uuid references auth.users (id) not null,
    property_id text not null,
    scrub_tag text not null,
    original_value text,
    user_value text,
    modified_at timestamptz default now(),
    scrub_session_id uuid
);

-- Unique constraint to prevent duplicate modifications
alter table user_scrub_modifications
add constraint user_property_tag_unique unique (user_id, property_id, scrub_tag);

-- Index for improved query performance
create index idx_user_property on user_scrub_modifications (user_id, property_id);

2. Implementing Insert/Update Logic

When a user modifies a scrub tag value, you need to store this change in the user_scrub_modifications table. This involves either inserting a new record or updating an existing one. Consider these key aspects:

• Insert: If no modification exists for the given user_id, property_id, and scrub_tag, you'll insert a new record.
• Update: If a modification already exists, you'll update the user_value and modified_at fields.
• Concurrency: To handle potential concurrent modifications, use the ON CONFLICT clause in your SQL queries. This clause allows you to specify what happens if a unique constraint violation occurs (e.g., if two users try to modify the same tag at the same time). In this case, you can choose to update the existing record, ensuring the "last write wins" strategy.

Here's an example of how you might handle this using the INSERT ... ON CONFLICT statement in SQL:

insert into user_scrub_modifications (user_id, property_id, scrub_tag, original_value, user_value)
values
    (
        'user_id',
        'property_id',
        'scrub_tag',
        'original_value',
        'user_value'
    )
on conflict (user_id, property_id, scrub_tag)
do
update
set user_value = excluded.user_value,
    modified_at = now();

3. Loading User Modifications

Before displaying scrub results to the user, you must load their modifications. This typically involves querying the user_scrub_modifications table, filtering by the user_id and property_id (and optionally, the scrub_session_id).

Here's an example query:

select scrub_tag,
    user_value
from user_scrub_modifications
where
    user_id = 'user_id'
    and property_id = 'property_id';

4. Merging Modifications with Scrub Results

Once you've loaded both the original scrub results and the user modifications, you need to merge them. The user's modifications should take precedence. In other words, if a user has modified a tag value, that value should be displayed instead of the original value.

This can be done in your application code. For example, you can iterate through the scrub results and check if a corresponding modification exists. If it does, use the user_value from the modification. Otherwise, use the original value.

5. Implementing Row Level Security (RLS)

Security is paramount, and RLS is essential for ensuring users can only access their own modifications. Implement RLS policies on the user_scrub_modifications table to restrict access based on the user_id.

Here's an example of an RLS policy:

alter table user_scrub_modifications
    enable row level security;

create policy "Users can only view their own modifications" on user_scrub_modifications
    for select
    using (auth.uid() = user_id);

create policy "Users can modify their own modifications" on user_scrub_modifications
    for update
    using (auth.uid() = user_id);

create policy "Users can insert their own modifications" on user_scrub_modifications
    for insert
    with check (auth.uid() = user_id);

create policy "Users can delete their own modifications" on user_scrub_modifications
    for delete
    using (auth.uid() = user_id);

6. Indexing for Performance

Indexes significantly improve query performance, especially as your data grows. Make sure to create indexes on the user_id and property_id columns in the user_scrub_modifications table. This will speed up queries for loading user modifications.

7. Handling Concurrent Modifications

To gracefully handle concurrent modifications (multiple users potentially modifying the same data at the same time), the "last write wins" strategy is the recommended approach. This can be achieved using the ON CONFLICT clause in your INSERT statements, as demonstrated earlier. This ensures that the most recent update is always reflected.

Advanced Considerations and Best Practices

Data Validation

Always validate the user_value to ensure it's a valid value for the scrub tag. For example, if the scrub_tag is "landlocked", the user_value should ideally be limited to a predefined set of values (e.g., "true", "false", "unknown").

Scrub Session Management

Consider using the scrub_session_id field to group modifications from the same scrub session. This can be useful for:

• Tracking changes: Identifying all the modifications made during a specific scrub process.
• Rollback/Undo: Allowing users to revert all changes made during a single scrub session.
• Auditing: Providing a clear audit trail of changes.

Error Handling

Implement robust error handling to gracefully handle any issues during the insert/update process. This includes catching potential database errors and providing informative error messages to the user.

User Interface (UI) Considerations

Provide clear visual feedback to the user about their modifications. For example, highlight modified tag values or display a "saved" indicator when changes are saved.

Conclusion: Building a Better User Experience

By implementing these steps, you can create a system that reliably stores and retrieves user modifications to scrub results within your Supabase application. This leads to a more intuitive and user-friendly experience, where users feel in control of their data and their changes are preserved. This persistence is a key component of data validation and cleaning applications, improving user satisfaction and data quality. Remember to prioritize security and performance throughout the process. Following these guidelines will enable you to build a robust and reliable system for managing user modifications.

We encourage you to experiment with these techniques and adapt them to your specific requirements. Happy coding!

External Resources:

• Supabase Documentation: For detailed information on Supabase features, including the database, authentication, and RLS: https://supabase.com/docs