7 posts tagged with "nestjs"

“Democracy thrives on information. RajnitiReport makes political history, performance, and accountability visible to all.”

1. Project Overview​

RajnitiReport (publicly known as NepalTracks.com) is a comprehensive political analytics and civic transparency platform designed to empower citizens, journalists, and policy analysts in Nepal. In a landscape often characterized by opaque political processes, the platform aims to be a definitive source of truth, providing data-driven insights into the activities of elected officials, governments, and political parties.

Value Proposition:

• For Citizens: Offers an accessible way to track the performance of their representatives, understand government actions, and participate in public discourse through features like polls and ratings.
• For Journalists & Analysts: Provides a rich, queryable database of political information, from historical election data to real-time cabinet reshuffles, facilitating in-depth research and reporting.
• For Policy-Tech Enthusiasts: Serves as a case study in building a complex, data-centric application with a modern technology stack.

The platform's core mission is to foster accountability and transparency in Nepali politics by making political data easily accessible and understandable.

In today's digital landscape, maintaining a consistent and engaging social media presence is crucial for any organization. For projects dealing with dynamic data, manual posting can quickly become overwhelming. This is where automated social media management systems shine. This article explores the architecture and implementation of a socialcontentmanager module, a robust system designed to automate content generation and posting across various social media platforms, with a focus on Facebook and X (formerly Twitter).

The Core Concept: Modular Content Generation

At the heart of our socialcontentmanager module is a highly modular approach to content generation. Instead of hardcoding specific post types, we leverage an interface-driven design. This allows us to define a contract for what a "social media content" should be, and then implement various content types as separate, independent classes. This approach promotes reusability, scalability, and maintainability.

The ISocialMediaContent Interface

The ISocialMediaContent interface defines the fundamental structure and behavior expected from any content type within our system. It ensures that each content class can provide the necessary information (text, image, comments) for a social media post.

Overview​

As election and political data expanded, performance bottlenecks became visible—especially on pages rendering historical trends and analytics. I adopted Redis-based caching with time-based expiry to ensure:

• Faster load times
• Reduced DB load
• Controlled freshness of data

This post details my approach using NestJS, Redis, and TTL strategies.

Overview​

Once data is live, platforms become conversations. In this post, I’ll explain how I created a resource-aware content and feedback engine where users can:

• Read and write multilingual content
• Rate political entities (parties, leaders, governments)
• Comment on historical events and scandals
• Attach feedback directly to any model in the system

The system is powered by polymorphic content linking, a unified comment engine, and approval metrics.

Design Goals​

Overview​

When building a platform that relies on statistical analysis and deep comparisons, response time can quickly become a bottleneck. In this article, I’ll walk through how I integrated Redis with NestJS to reduce computation time and database load on performance-heavy endpoints.

I implemented caching on frequently accessed data like:

• Party trends across elections
• Leader performance history
• Poll summaries
• Government composition data

Overview​

Polling seems simple on the surface—ask a question, tally responses—but in a public-facing, multilingual, political data platform, the requirements grow fast. I needed to build a polling system that was:

• Reusable and flexible (attach polls to leaders, parties, elections, etc.)
• Localized (bilingual support)
• Honest (no spam or duplicate votes)
• Insightful (results usable in trends and analytics)

This post covers how I approached it with NestJS, Prisma, and a clean frontend API.

Overview​

This post outlines the architectural foundation I laid for building a real-world fullstack platform from scratch. The goal was to support a growing, data-rich application while keeping development modular, testable, and extensible.

I chose a stack centered around NestJS and Next.js with Prisma ORM and MySQL, aiming for type safety across the stack and a clean separation between backend services and the frontend UI.

Why I Built This​

The platform was designed to serve as a public data explorer for civic and political datasets. It needed to:

• Display complex relationships (leaders, parties, elections, content)
• Scale across time (historical data, future updates)
• Be multilingual (English and Nepali)
• Allow feature layering (polls, ratings, approval metrics)
• Expose secure APIs for multiple clients

Rather than using off-the-shelf CMS tools, I opted to build a bespoke platform tailored to domain logic and long-term extensibility.

Key Concepts and Challenges​

1. Modular Backend Design (NestJS)​

NestJS made it easy to separate services by domain: elections, leaders, parties, polls, contents, and so on. I used feature modules, each with its own DTOs, services, and controller layer. This enabled:

• Independent testing and caching
• Cleaner route control
• Ability to extend domains (e.g. attach content to any resource)

2. Type-Safe Data Layer (Prisma + MySQL)​

The Prisma schema models were written to reflect real-world civic and political relationships:

• Polymorphic fields via resourceType + resourceId
• Soft deletes and timestamps
• Dual-language fields: name, nameLocal, titleLocal, etc.

3. Frontend and API Contracts​

The UI is powered by Next.js with Mantine + TailwindCSS. I ensured strong alignment between frontend and backend through shared types and predictable endpoints, like:

• /api/v1/parties/:id
• /api/v1/elections/:id
• /api/v1/polls/:id

4. Multi-Channel Architecture​

The platform is designed to serve:

• Static SSR frontend (Next.js)
• Admin dashboard (coming soon)
• Public API consumers (researchers, journalists)

Real Implementation Examples​

Prisma Example (Polymorphic Content)​

model Content {
  id           Int      @id @default(autoincrement())
  resourceType String   // LEADER, PARTY, ELECTION, etc.
  resourceId   Int
  title        String
  content      String
  titleLocal   String?
  contentLocal String?
  createdAt    DateTime @default(now())
}

NestJS Module Structure​

src/
  └── elections/
        ├── elections.service.ts
        ├── elections.controller.ts
        ├── dto/
        ├── elections.module.ts

Next.js + Mantine UI​

<Card>
  <Title>{party.name}</Title>
  <Text>{party.descriptionLocal}</Text>
</Card>

Lessons / Takeaways​

• Build around your data, not your UI. Data modeling upfront saved major refactoring.
• Invest in multilingual support early — it's harder to retrofit.
• NestJS with Prisma and Next.js offers a highly productive fullstack foundation.
• Use polymorphic content linking sparingly and deliberately.

This architecture has held up well as I’ve expanded the platform to include polls, ratings, scandal timelines, and trend visualizations.

More details on how I structured the Prisma models and handled localization coming in the next article.