/how-to-build-lovable

How to build Reporting tool with Lovable?

Discover how to build a robust reporting tool with Lovable. This guide provides practical steps and insights to streamline analytics for better decisions.

Book a free  consultation
Matt Graham, CEO of Rapid Developers

Book a call with an Expert

Starting a new venture? Need to upgrade your web app? RapidDev builds application with your growth in mind.

Book a free No-Code consultation

How to build Reporting tool with Lovable?

 
Creating a New Lovable Project
 

Create a new project by using Lovable’s project creation interface. Name the project (for example, "ReportingTool") and set up the basic file structure. In your project, you will have the following files:

  • A main HTML file (index.html) for the user interface.
  • A JavaScript file (main.js) to handle interactions.
  • A JavaScript file (report.js) to generate and manage reports.
  • A configuration file (lovable.json) to manage dependencies.

 
Configuring Dependencies in Lovable
 

Since Lovable does not have a terminal, you need to install dependencies by adding them inside the configuration file. Create a file called lovable.json in your project root and add the dependency for the report generation library (for this example, we assume the library is called "lovable-report").


{
  "dependencies": {
    "lovable-report": "latest"
  }
}

This configuration tells Lovable to automatically download and include the "lovable-report" library when your project loads.

 
Building the Report Component
 

Create a new file named report.js which will contain the logic to generate reports. Paste the following code into report.js. This code uses the "lovable-report" library to create a report based on provided data.


function generateReport(data) {
  // Create a new report instance using the lovable-report library.
  const report = new LovableReport();

  // Add a title to the report.
  report.addTitle("Sales Report");

  // Example: Add a bar chart with the provided data.
  report.addChart("bar", data);

  // Return the final rendered report as HTML.
  return report.render();
}

Save this file in the same directory as your other JavaScript files.

 
Setting Up the User Interface
 

Create or modify your main HTML file (index.html) to include the elements necessary for interacting with your reporting tool. This file will load the JavaScript files and display a button to generate the report and a container to show it. Paste the code snippet below into index.html:


<!DOCTYPE html>
<html>
  <head>
    <meta charset="UTF-8">
    <title>Reporting Tool</title>
    <script src="report.js"></script>
    <script src="main.js"></script>
  </head>
  <body>
    <button id="generateButton">Generate Report</button>
    <div id="reportContainer"></div>
  </body>
</html>

This will create a simple UI with a button and a container for displaying reports.

 
Integrating Report Generation into the Main Script
 

Edit the main.js file to handle user interactions. This file will contain the code that triggers report generation when the user clicks the "Generate Report" button. Paste the following code into main.js:


function fetchData() {
  // In a real-world scenario, replace this with actual data retrieval logic.
  // For example, you might fetch data from an API endpoint.
  return [
    { label: "January", value: 150 },
    { label: "February", value: 200 },
    { label: "March", value: 170 }
  ];
}

document.getElementById("generateButton").addEventListener("click", function() {
  // Retrieve data required for the report.
  const data = fetchData();
  
  // Generate the report using the generateReport function from report.js.
  const reportHTML = generateReport(data);

  // Insert the report HTML into the reportContainer div.
  document.getElementById("reportContainer").innerHTML = reportHTML;
});

This script connects the UI to your reporting logic.

 
Testing Your Reporting Tool
 

With all files saved and dependencies configured in lovable.json, use Lovable’s built-in preview feature to test your tool. Open the preview window in Lovable. When you click the "Generate Report" button, the generated report should appear within the designated container.

If the report displays correctly with a title and a bar chart reflecting the sample data, your reporting tool is successfully built.

 
Updating and Debugging Your Code
 

Each time you modify your code files (index.html, main.js, or report.js), simply save your changes and refresh the Lovable preview to see updates. Use Lovable’s built-in logging and debugging features (if available) to troubleshoot any issues that arise.

By following these detailed steps, you have built a reporting tool with Lovable that seamlessly integrates a report generation library, a user interface, and interaction logic—all without needing a terminal.

Want to explore opportunities to work with us?

Connect with our team to unlock the full potential of no-code solutions with a no-commitment consultation!

Book a Free Consultation

How to Build a Daily Aggregated Reporting API with Lovable


const express = require('express');
const \_ = require('lodash');
const app = express();

app.use(express.json());

// Example dataset representing raw transactional data.
const rawData = [
  { id: 1, service: 'subscription', amount: 1200, timestamp: '2023-09-24T10:00:00Z' },
  { id: 2, service: 'subscription', amount: 800, timestamp: '2023-09-24T12:30:00Z' },
  { id: 3, service: 'support', amount: 300, timestamp: '2023-09-24T15:45:00Z' },
  { id: 4, service: 'subscription', amount: 500, timestamp: '2023-09-25T09:20:00Z' },
  { id: 5, service: 'support', amount: 150, timestamp: '2023-09-25T14:10:00Z' },
  { id: 6, service: 'analytics', amount: 400, timestamp: '2023-09-25T16:50:00Z' }
];

// API endpoint to group and aggregate reporting data by date and service.
// This demonstrates a complex backend data structuring task for a Lovable-based reporting tool.
app.get('/api/report/daily', (req, res) => {
  // Convert timestamp into date.
  const dataWithDate = rawData.map(item => ({
    ...item,
    date: new Date(item.timestamp).toISOString().split('T')[0]
  }));

  // Group data by date
  const groupedByDate = \_.groupBy(dataWithDate, 'date');

  // Build report aggregating amounts and count per service per date.
  const report = Object.keys(groupedByDate).map(date => {
    const records = groupedByDate[date];
    const serviceAggregation = _.mapValues(_.groupBy(records, 'service'), items => ({
      totalAmount: \_.sumBy(items, 'amount'),
      count: items.length
    }));
    return { date, services: serviceAggregation };
  });

  res.json(report);
});

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
  console.log(`Reporting API is running on port ${PORT}`);
});

How to create an enhanced transaction reporting endpoint with currency conversion using Lovable.


const express = require('express');
const axios = require('axios');
const app = express();

// Sample dataset of transactions in USD.
const transactions = [
  { id: 1, service: 'subscription', amount: 1200, timestamp: '2023-09-24T10:00:00Z' },
  { id: 2, service: 'subscription', amount: 800, timestamp: '2023-09-24T12:30:00Z' },
  { id: 3, service: 'support', amount: 300, timestamp: '2023-09-24T15:45:00Z' },
  { id: 4, service: 'subscription', amount: 500, timestamp: '2023-09-25T09:20:00Z' },
  { id: 5, service: 'support', amount: 150, timestamp: '2023-09-25T14:10:00Z' },
  { id: 6, service: 'analytics', amount: 400, timestamp: '2023-09-25T16:50:00Z' }
];

// Endpoint to fetch an enhanced report that converts transaction amounts using external exchange rates.
app.get('/api/report/enhanced', async (req, res) => {
  const { targetCurrency } = req.query; // e.g., EUR, GBP, etc.
  
  try {
    // Call external API to fetch exchange rates (base: USD)
    const response = await axios.get('https://api.exchangerate-api.com/v4/latest/USD');
    const rates = response.data.rates;
    const conversionRate = targetCurrency && rates[targetCurrency] ? rates[targetCurrency] : 1;
    
    // Adjust transactions by converting USD amounts to the target currency.
    const adjustedTransactions = transactions.map(tx => ({
      ...tx,
      convertedAmount: Math.round(tx.amount _ conversionRate _ 100) / 100,
      targetCurrency: targetCurrency || 'USD'
    }));

    // Aggregate data grouped by service.
    const report = adjustedTransactions.reduce((acc, tx) => {
      if (!acc[tx.service]) {
        acc[tx.service] = { totalConvertedAmount: 0, transactionCount: 0 };
      }
      acc[tx.service].totalConvertedAmount += tx.convertedAmount;
      acc[tx.service].transactionCount += 1;
      return acc;
    }, {});

    res.json({
      baseCurrency: 'USD',
      targetCurrency: targetCurrency || 'USD',
      conversionRate,
      report
    });
  } catch (error) {
    res.status(500).json({ error: 'Failed to retrieve exchange rates' });
  }
});

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => console.log(`Server listening on port ${PORT}`));

How to Build a Lovable Report Overview API with Express and NodeCache


const express = require('express');
const axios = require('axios');
const NodeCache = require('node-cache');

const app = express();
const cache = new NodeCache({ stdTTL: 120 });

app.use(express.json());

app.get('/api/report/overview', async (req, res) => {
  const cacheKey = 'lovable_overview_report';
  const cachedReport = cache.get(cacheKey);
  if (cachedReport) {
    return res.json({ source: 'cache', report: cachedReport });
  }

  try {
    const authResponse = await axios.post('https://lovable.example.com/auth/token', {
      clientId: process.env.LOVABLE_CLIENT_ID,
      clientSecret: process.env.LOVABLE_CLIENT_SECRET
    });
    const token = authResponse.data.access\_token;

    const metricsResponse = await axios.get('https://lovable.example.com/api/metrics', {
      headers: { Authorization: `Bearer ${token}` }
    });

    const metrics = metricsResponse.data;
    const overview = metrics.reduce((acc, entry) => {
      if (!acc[entry.category]) {
        acc[entry.category] = { totalValue: 0, count: 0 };
      }
      acc[entry.category].totalValue += entry.value;
      acc[entry.category].count += 1;
      return acc;
    }, {});

    cache.set(cacheKey, overview);
    res.json({ source: 'live', report: overview });
  } catch (error) {
    res.status(500).json({ error: 'Unable to generate report overview.' });
  }
});

const PORT = process.env.PORT || 3001;
app.listen(PORT, () => console.log(`Server running on port ${PORT}`));

Want to explore opportunities to work with us?

Connect with our team to unlock the full potential of no-code solutions with a no-commitment consultation!

Book a Free Consultation
Matt Graham, CEO of Rapid Developers

Book a call with an Expert

Starting a new venture? Need to upgrade your web app? RapidDev builds application with your growth in mind.

Book a free No-Code consultation

Best Practices for Building a Reporting tool with AI Code Generators

 

Understanding the Reporting Tool and AI Code Generators

 

  • This guide explains how to build a reporting tool using AI code generators, designed for non-technical users.
  • The reporting tool collects data, processes it, and presents insights through clear and accurate reports.
  • AI code generators assist in writing code quickly by learning from previous patterns, saving time and reducing errors.

 

Prerequisites

 

  • A basic understanding of concepts like data sources, code, and reporting.
  • Access to an AI code generator platform such as GitHub Copilot or Tabnine.
  • An environment to run code; for example, a computer with Python installed.
  • Clarity on the reporting requirements including key metrics and data sources.

 

Setting Clear Reporting Requirements

 

  • Determine the main objectives of your report, such as tracking sales, monitoring performance, or analyzing trends.
  • Identify the data sources that will feed into the report (e.g., databases, CSV files, APIs).
  • Create a list of desired report sections (e.g., summary, detailed analysis, charts) and their specific data points.

 

Choosing the Right AI Code Generator

 

  • Research available AI code generators to see which one best fits your needs.
  • Look for features that include suggesting code snippets, auto-completion, and debugging support.
  • Decide on a code generator that integrates well with your development environment.

 

Planning Your Reporting Tool Architecture

 

  • Break down the reporting tool into smaller components such as data extraction, data processing, and generation of visual reports.
  • Define how each component will interact and the data formats that will be shared between them.
  • Sketch a simple flowchart outlining data collection, processing, and output to ensure a logical sequence.

 

Integrating AI Code Generators into the Development Process

 

  • Begin by writing a general outline or pseudocode for the reporting tool.
  • Use the AI code generator to generate boilerplate code. For example, start by asking the AI for a function that processes data:

def generate\_report(data):
    # Process data to create report summary
    report = "Report Summary:\n"
    for key, value in data.items():
        report += f"{key}: {value}\n"
    return report
  • Review and modify the generated code to fit the specific requirements of your report.

 

Validating and Testing the Generated Code

 

  • After integrating AI-generated code, test each component individually.
  • Create small test data sets to ensure that data is processed accurately.
  • Use print statements or logging to check intermediate results during execution.
  • Refine the code if needed and re-run tests until the output matches your expectations.

 

Implementing Data Visualization

 

  • Decide on the type of visual output needed; this could be charts, graphs, or tables.
  • Use libraries that help generate visuals; for example, Python’s matplotlib can be integrated for charting.
  • Ask the AI code generator for examples of how to integrate a visualization library:

import matplotlib.pyplot as plt

def plot\_report(data):
    # Create a bar chart from the report data
    keys = list(data.keys())
    values = list(data.values())
    plt.bar(keys, values)
    plt.title('Report Data Visualization')
    plt.xlabel('Metrics')
    plt.ylabel('Values')
    plt.show()

# Example data
data = {'Sales': 100, 'Revenue': 200, 'Profit': 50}
plot\_report(data)

 

Establishing Feedback Loops and Iterative Improvements

 

  • Regularly review the output of the report tool with stakeholders to gather feedback.
  • Use insights from the feedback to refine the code and improve the report formats.
  • Continuously update the AI code generator’s prompts to better align with your evolving needs.

 

Best Practices for Maintaining Code Quality

 

  • Ensure that AI-generated code is always reviewed by a human for potential errors or inefficiencies.
  • Use version control (like Git) to track changes and manage iterations in your code.
  • Document each function and module clearly so that future updates are easier.
  • Integrate automated testing to catch bugs early in the development process.

 

Finalizing and Deploying the Reporting Tool

 

  • Combine all individual components and perform end-to-end testing.
  • Once testing is successful, deploy the reporting tool on a platform that suits your needs.

Client trust and success are our top priorities

When it comes to serving you, we sweat the little things. That’s why our work makes a big impact.

Rapid Dev was an exceptional project management organization and the best development collaborators I've had the pleasure of working with. They do complex work on extremely fast timelines and effectively manage the testing and pre-launch process to deliver the best possible product. I'm extremely impressed with their execution ability.

CPO, Praction - Arkady Sokolov

May 2, 2023

Working with Matt was comparable to having another co-founder on the team, but without the commitment or cost. He has a strategic mindset and willing to change the scope of the project in real time based on the needs of the client. A true strategic thought partner!

Co-Founder, Arc - Donald Muir

Dec 27, 2022

Rapid Dev are 10/10, excellent communicators - the best I've ever encountered in the tech dev space. They always go the extra mile, they genuinely care, they respond quickly, they're flexible, adaptable and their enthusiasm is amazing.

Co-CEO, Grantify - Mat Westergreen-Thorne

Oct 15, 2022

Rapid Dev is an excellent developer for no-code and low-code solutions.
We’ve had great success since launching the platform in November 2023. In a few months, we’ve gained over 1,000 new active users. We’ve also secured several dozen bookings on the platform and seen about 70% new user month-over-month growth since the launch.

Co-Founder, Church Real Estate Marketplace - Emmanuel Brown

May 1, 2024 

Matt’s dedication to executing our vision and his commitment to the project deadline were impressive. 
This was such a specific project, and Matt really delivered. We worked with a really fast turnaround, and he always delivered. The site was a perfect prop for us!

Production Manager, Media Production Company - Samantha Fekete

Sep 23, 2022