Documentation.md

Building a GitHub Organization Leaderboard: A Deep Dive into recode hive's Implementation

Ever wondered how to build a live leaderboard that tracks contributions across an entire GitHub organization? Let me walk you through how we built ours at recode hive. This isn't your typical "fetch and display" tutorial - we're talking about handling rate limits, caching strategies, time-based filtering, and creating a smooth user experience that doesn't make the GitHub API cry.

What We're Building

Our leaderboard does a few things that make it interesting:

Aggregates merged PRs from all repositories in an organization
Calculates contributor rankings based on a simple point system
Supports time-based filtering (this week, month, year, or all time)
Shows detailed PR information for each contributor
Caches aggressively to avoid hitting API rate limits
Handles concurrent requests efficiently

The whole thing is built with React, TypeScript, and integrates with Docusaurus. But the concepts here work for any stack.

Architecture Overview

Here's how the pieces fit together: ┌─────────────────────────────────────────────────────────────┐ │ User Interface │ │ (LeaderBoard Component + PRListModal) │ └────────────────────────┬────────────────────────────────────┘ │ │ Consumes Context; ▼ ┌─────────────────────────────────────────────────────────────┐ │ CommunityStatsProvider │ │ • Manages state (contributors, stats, filters) │ │ • Handles caching (5-minute TTL) │ │ • Orchestrates data fetching │ └────────────────────────┬────────────────────────────────────┘ │ │ Makes API Calls ▼ ┌─────────────────────────────────────────────────────────────┐ │ GitHub REST API │ │ • Organization repos │ │ • Pull requests per repo │ │ • User information │ └─────────────────────────────────────────────────────────────┘

Data Flow: From API to UI

Phase 1: Data Collection

When the app loads, we kick off a multi-stage process:

Stage 1: Fetch All Organization Repositories

const fetchAllOrgRepos = async (headers: Record<string, string>) => {
  const repos: any[] = [];
  let page = 1;
  
  while (true) {
    const resp = await fetch(
      `https://api.github.com/orgs/${GITHUB_ORG}/repos?type=public&per_page=100&page=${page}`,
      { headers }
    );
    
    const data = await resp.json();
    repos.push(...data);
    
    if (data.length < 100) break; // Last page
    page++;
  }
  
  return repos;
};

This grabs every public repo in the organization. Simple pagination loop.

Stage 2: Fetch Merged PRs for Each Repository Here's where it gets interesting. We need PRs from potentially dozens of repos, and we can't just fire off 50 requests at once.

const fetchMergedPRsForRepo = async (repoName: string, headers: Record<string, string>) => {
  const mergedPRs: PullRequestItem[] = [];
  
  // Get first page to estimate total
  const firstResp = await fetch(
    `https://api.github.com/repos/${GITHUB_ORG}/${repoName}/pulls?state=closed&per_page=100&page=1`,
    { headers }
  );
  
  const firstPRs = await firstResp.json();
  const firstPageMerged = firstPRs.filter((pr) => Boolean(pr.merged_at));
  mergedPRs.push(...firstPageMerged);
  
  if (firstPRs.length < 100) return mergedPRs; // Only one page
  
  // Fetch remaining pages in parallel (with limit)
  const pagePromises: Promise<PullRequestItem[]>[] = [];
  const maxPages = Math.min(MAX_PAGES_PER_REPO, 10);
  
  for (let i = 2; i <= maxPages; i++) {
    pagePromises.push(
      fetch(
        `https://api.github.com/repos/${GITHUB_ORG}/${repoName}/pulls?state=closed&per_page=100&page=${i}`,
        { headers }
      )
      .then(async (resp) => {
        const prs = await resp.json();
        return prs.filter((pr) => Boolean(pr.merged_at));
      })
      .catch(() => [])
    );
  }
  
  const remainingPages = await Promise.all(pagePromises);
  remainingPages.forEach(pagePRs => {
    if (pagePRs.length > 0) mergedPRs.push(...pagePRs);
  });
  
  return mergedPRs;
};

Key optimization: we fetch the first page sequentially to see if there are more pages, then parallelize the remaining requests. This prevents unnecessary API calls for repos with few PRs.

Stage 3: Process in Batches We don't process all repos at once. Instead, we batch them:

const processBatch = async (
  repos: any[],
  headers: Record<string, string>
): Promise<{ contributorMap: Map<string, FullContributor>; totalMergedPRs: number }> => {
  const contributorMap = new Map<string, FullContributor>();
  let totalMergedPRs = 0;

  // Process 8 repos at a time
  for (let i = 0; i < repos.length; i += MAX_CONCURRENT_REQUESTS) {
    const batch = repos.slice(i, i + MAX_CONCURRENT_REQUESTS);
    
    const promises = batch.map(async (repo) => {
      if (repo.archived) return { mergedPRs: [], repoName: repo.name };
      
      try {
        const mergedPRs = await fetchMergedPRsForRepo(repo.name, headers);
        return { mergedPRs, repoName: repo.name };
      } catch (error) {
        console.warn(`Skipping repo ${repo.name} due to error:`, error);
        return { mergedPRs: [], repoName:
BD91
 repo.name };
      }
    });

    const results = await Promise.all(promises);
    
    // Aggregate contributor data
    results.forEach(({ mergedPRs, repoName }) => {
      totalMergedPRs += mergedPRs.length;
      
      mergedPRs.forEach((pr) => {
        const username = pr.user.login;
        if (!contributorMap.has(username)) {
          contributorMap.set(username, {
            username,
            avatar: pr.user.avatar_url,
            profile: pr.user.html_url,
            points: 0,
            prs: 0,
            allPRDetails: [],
          });
        }
        
        const contributor = contributorMap.get(username)!;
        contributor.allPRDetails.push({
          title: pr.title,
          url: pr.html_url,
          mergedAt: pr.merged_at,
          repoName,
          number: pr.number,
        });
      });
    });
  }

  return { contributorMap, totalMergedPRs };
};

Why batches of 8? Trial and error. Too many concurrent requests = rate limits. Too few = slow load times. Eight was the sweet spot.

Phase 2: State Management & Filtering

Once we have all the data, we store it in a way that makes filtering fast. This is the secret sauce.

Data Structure

interface FullContributor {
  username: string;
  avatar: string;
  profile: string;
  allPRDetails: PRDetails[]; // ALL PRs ever, unfiltered
  points: number;             // Calculated based on current filter
  prs: number;                // Calculated based on current filter
}

Notice allPRDetails stores everything. We never refetch when users change the time filter.

Time Filtering Logic

const getTimeFilterDate = (filter: TimeFilter): Date | null => {
  const now = new Date();
  switch (filter) {
    case 'week':
      return new Date(now.getTime() - 7 * 24 * 60 * 60 * 1000);
    case 'month': {
      const lastMonth = new Date(now);
      lastMonth.setMonth(now.getMonth() - 1);
      return lastMonth;
    }
    case 'year':
      return new Date(now.getTime() - 365 * 24 * 60 * 60 * 1000);
    case 'all':
    default:
      return null;
  }
};

const isPRInTimeRange = (mergedAt: string, filter: TimeFilter): boolean => {
  if (filter === 'all') return true;
  
  const filterDate = getTimeFilterDate(filter);
  if (!filterDate) return true;
  
  const prDate = new Date(mergedAt);
  return prDate >= filterDate;
};
Computed Contributors
This is where React's useMemo shines:
typescriptconst contributors = useMemo(() => {
  if (!allContributors.length) return [];
  
  const filteredContributors = allContributors
    .map(contributor => {
      const filteredPRs = contributor.allPRDetails.filter(pr => 
        isPRInTimeRange(pr.mergedAt, currentTimeFilter)
      );
      
      return {
        username: contributor.username,
        avatar: contributor.avatar,
        profile: contributor.profile,
        points: filteredPRs.length * POINTS_PER_PR,
        prs: filteredPRs.length,
        prDetails: filteredPRs,
      };
    })
    .filter(contributor => contributor.prs > 0)
    .sort((a, b) => b.points - a.points || b.prs - a.prs);

  return filteredContributors;
}, [allContributors, currentTimeFilter]);

When the user changes the filter, this recalculates instantly. No API calls, no loading spinners. The Context Provider Pattern Everything runs through a Context Provider. This gives us a single source of truth and makes the data available anywhere in the component tree.

Context Definition

interface ICommunityStatsContext {
  // Organization stats
  githubStarCount: number;
  githubContributorsCount: number;
  githubForksCount: number;
  githubReposCount: number;
  
  // Leaderboard data
  contributors: Contributor[];
  stats: Stats | null;
  
  // Time filtering
  currentTimeFilter: TimeFilter;
  setTimeFilter: (filter: TimeFilter) => void;
  getFilteredPRsForContributor: (username: string) => PRDetails[];
  
  // Meta
  loading: boolean;
  error: string | null;
  refetch: (signal: AbortSignal) => Promise<void>;
  clearCache: () => void;
}

Using the Context

export const useCommunityStatsContext = (): ICommunityStatsContext => {
  const context = useContext(CommunityStatsContext);
  if (context === undefined) {
    throw new Error("useCommunityStatsContext must be used within a CommunityStatsProvider");
  }
  return context;
};

Any component can now access the leaderboard data:

const { contributors, currentTimeFilter, setTimeFilter } = useCommunityStatsContext();
### Caching Strategy
GitHub API has rate limits. We cache everything for 5 minutes:
```typescript
const CACHE_DURATION = 5 * 60 * 1000; // 5 minutes

const [cache, setCache] = useState<{
  data: { contributors: FullContributor[]; rawStats: { totalPRs: number } } | null;
  timestamp: number;
}>({ data: null, timestamp: 0 });

// In fetchAllStats
const now = Date.now();
if (cache.data && (now - cache.timestamp) < CACHE_DURATION) {
  setAllContributors(cache.data.contributors);
  setLoading(false);
  return;
}

Simple but effective. On subsequent visits within 5 minutes, users see data instantly.

UI Components

The Main Leaderboard The leaderboard component is pretty straightforward once you have the data:

export default function LeaderBoard(): JSX.Element {
  const { 
    contributors, 
    stats, 
    loading, 
    error, 
    currentTimeFilter, 
    setTimeFilter 
  } = useCommunityStatsContext();
  
  const [searchQuery, setSearchQuery] = useState("");
  const [currentPage, setCurrentPage] = useState(1);
  
  // Filter by search
  const filteredContributors = contributors.filter((contributor) =>
    contributor.username.toLowerCase().includes(searchQuery.toLowerCase())
  );
  
  // Pagination
  const itemsPerPage = 10;
  const totalPages = Math.ceil(filteredContributors.length / itemsPerPage);
  const currentItems = filteredContributors.slice(
    (currentPage - 1) * itemsPerPage,
    currentPage * itemsPerPage
  );
  
  // Render...
}

Time Filter Dropdown

<select
  value={currentTimeFilter}
  onChange={(e) => {
    setTimeFilter(e.target.value as TimeFilter);
    setCurrentPage(1); // Reset to first page
  }}
  className="time-filter-select"
>
  <option value="all">🏆 All Time</option>
  <option value="year">📅 This Year</option>
  <option value="month">📆 This Month</option>
  <option value="week">📊 This Week</option>
</select>

Top 3 Performers We show the top 3 in a special layout:

  <div className="top-performers-grid">
    <TopPerformerCard contributor={filteredContributors[1]} rank={2} />
    <TopPerformerCard contributor={filteredContributors[0]} rank={1} />
    <TopPerformerCard contributor={filteredContributors[2]} rank={3} />
  </div>
)}

Notice rank 2, then 1, then 3? Creates a podium effect in the layout.

Contributor Rows

{currentItems.map((contributor, index) => (
  <div key={contributor.username} className="contributor-row">
    <div className="rank-cell">
      <div className={`rank-badge ${getRankClass(index)}`}>
        {filteredContributors.indexOf(contributor) + 1}
      </div>
    </div>
    <div className="avatar-cell">
      <img src={contributor.avatar} alt={contributor.username} />
    </div>
    <div className="username-cell">
      <a href={contributor.profile} target="_blank" rel="noreferrer">
        {contributor.username}
      </a>
    </div>
    <div className="prs-cell">
      <Badge 
        count={contributor.prs} 
        label="PRs" 
        onClick={() => handlePRClick(contributor)}
        clickable={true}
      />
    </div>
    <div className="points-cell">
      <Badge count={contributor.points} label="Points" />
    </div>
  </div>
))}

PR Details Modal When users click on a contributor's PR count, we show a modal with all their PRs:

const getFilteredPRsForContributor = useCallback((username: string): PRDetails[] => { const contributor = allContributors.find(c => c.username === username); if (!contributor) return []; return contributor.allPRDetails .filter(pr => isPRInTimeRange(pr.mergedAt, currentTimeFilter)) .sort((a, b) => new Date(b.mergedAt).getTime() - new Date(a.mergedAt).getTime()); }, [allContributors, currentTimeFilter]);

This function is exposed through the context, so the modal can call it:

export default function PRListModal({ contributor, isOpen, onClose }: PRListModalProps) { const { getFilteredPRsForContributor, currentTimeFilter } = useCommunityStatsContext(); const filteredPRs = getFilteredPRsForContributor(contributor.username); return ( <AnimatePresence> {isOpen && ( <motion.div className="pr-modal-backdrop" onClick={handleBackdropClick}> <motion.div className="pr-modal-container"> <div className="pr-modal-header"> <h2>{contributor.username}'s Pull Requests</h2> <p> {filteredPRs.length} merged PR{filteredPRs.length !== 1 ? 's' : ''} • {filteredPRs.length * 10} points </p> </div> <div className="pr-modal-body"> {filteredPRs.map((pr) => ( <div key={`${pr.repoName}-${pr.number}`} className="pr-item"> <h3>{pr.title}</h3> <div className="pr-item-meta"> <span><FaGithub /> {pr.repoName}</span> <span>#{pr.number}</span> <span>Merged on {formatDate(pr.mergedAt)}</span> </div> <a href={pr.url} target="_blank" rel="noopener noreferrer"> <FaExternalLinkAlt /> </a> </div> ))} </div> </motion.div> </motion.div> )} </AnimatePresence> ); }

GitHub API Reference

Endpoints We Use

List Organization Repositories GET https://api.github.com/orgs/{org}/repos Parameters:

type (query): Repository type filter. We use public

per_page (query): Results per page. Max 100

page (query): Page number for pagination

Request Example:

curl -H "Authorization: token YOUR_TOKEN" \ -H "Accept: application/vnd.github.v3+json" \ "https://api.github.com/orgs/recodehive/repos?type=public&per_page=100&page=1" Response Example: ```json[ { "id": 123456, "name": "awesome-project", "full_name": "recodehive/awesome-project", "private": false, "archived": false, "html_url": "https://github.com/recodehive/awesome-project", "description": "An awesome project", "fork": false, "created_at": "2024-01-15T10:30:00Z", "updated_at": "2024-12-20T15:45:00Z" } ]

Rate Limit: 5000 requests per hour (authenticated)

List Pull Requests GET https://api.github.com/repos/{owner}/{repo}/pulls

Parameters:

state (query): PR state. We use closed to get merged PRs

per_page (query): Results per page. Max 100

page (query): Page number

sort (query, optional): Sort by created, updated, popularity, long-running

direction (query, optional): Sort direction asc or desc

Request Example:

curl -H "Authorization: token YOUR_TOKEN" \ -H "Accept: application/vnd.github.v3+json" \ "https://api.github.com/repos/recodehive/awesome-project/pulls?state=closed&per_page=100&page=1" ```json [ { "id": 789012, "number": 42, "state": "closed", "title": "Add new feature", "user": { "login": "johndoe", "id": 12345, "avatar_url": "https://avatars.githubusercontent.com/u/12345?v=4", "html_url": "https://github.com/johndoe" }, "body": "This PR adds a new feature...", "created_at": "2024-11-01T09:00:00Z", "updated_at": "2024-11-05T14:30:00Z", "closed_at": "2024-11-05T14:30:00Z", "merged_at": "2024-11-05T14:30:00Z", "merge_commit_sha": "abc123def456", "html_url": "https://github.com/recodehive/awesome-project/pull/42", "commits": 5, "additions": 150, "deletions": 30, "changed_files": 8 } ]

Key Fields:

merged_at: If not null, PR was merged (this is what we check)

user: Contains contributor info (username, avatar, profile URL)

number: PR number for the repo

title: PR title

html_url: Link to the PR

Rate Limit: Same as above

Get Organization Stats GET https://api.github.com/orgs/{org}

Request Example:

curl -H "Authorization: token YOUR_TOKEN" \ -H "Accept: application/vnd.github.v3+json" \ "https://api.github.com/orgs/recodehive" Response Example: ```json { "login": "recodehive", "id": 98765, "url": "https://api.github.com/orgs/recodehive", "repos_url": "https://api.github.com/orgs/recodehive/repos", "avatar_url": "https://avatars.githubusercontent.com/u/98765?v=4", "description": "Community-driven open source projects", "name": "recode hive", "company": null, "blog": "https://recodehive.com", "location": "Worldwide", "email": null, "public_repos": 25, "public_gists": 0, "followers": 150, "following": 0, "html_url": "https://github.com/recodehive", "created_at": "2023-06-15T08:00:00Z", "updated_at": "2024-12-01T12:00:00Z", "type": "Organization" }

Authentication

All requests require a GitHub Personal Access Token:

const headers: Record<string, string> = { Authorization: `token ${YOUR_GITHUB_TOKEN}`, Accept: "application/vnd.github.v3+json", }; #### Getting a Token: Go to GitHub Settings → Developer settings → Personal access tokens → Tokens (classic) Generate new token Select scopes: public_repo, read:org Copy the token (you won't see it again!) #### Storing the Token: In Docusaurus, we store it in docusaurus.config.js: ```javascript module.exports = { customFields: { gitToken: process.env.GITHUB_TOKEN || '', }, // ... };

Then access it:

const { siteConfig: { customFields }, } = useDocusaurusContext(); const token = customFields?.gitToken || "";

Error Handling

Rate Limit Exceeded (403)

{ "message": "API rate limit exceeded for user ID 12345.", "documentation_url": "https://docs.github.com/rest/overview/resources-in-the-rest-api#rate-limiting" }

How we handle it:

try { const resp = await fetch(url, { headers }); if (!resp.ok) { if (resp.status === 403) { throw new Error("Rate limit exceeded. Please try again later."); } throw new Error(`API error: ${resp.status} ${resp.statusText}`); } return await resp.json(); } catch (error) { console.error("Error fetching data:", error); // Fallback to cached data or show error message }

Not Found (404) Repository doesn't exist or is private:

{ "message": "Not Found", "documentation_url": "https://docs.github.com/rest/reference/repos#get-a-repository" }

Unauthorized (401) Invalid or expired token:

{ "message": "Bad credentials", "documentation_url": "https://docs.github.com/rest" }

Performance Optimizations

Concurrent Request Batching Processing 50 repos sequentially takes forever. Processing them all at once hits rate limits. Solution: batches.

const MAX_CONCURRENT_REQUESTS = 8; for (let i = 0; i < repos.length; i += MAX_CONCURRENT_REQUESTS) { const batch = repos.slice(i, i + MAX_CONCURRENT_REQUESTS); const promises = batch.map(repo => fetchMergedPRsForRepo(repo.name, headers)); await Promise.all(promises); }

Early Pagination Termination If a repo has 15 PRs, don't fetch 10 pages:

const firstResp = await fetch(`${url}?page=1&per_page=100`, { headers }); const firstPRs = await firstResp.json(); if (firstPRs.length < 100) { return firstPRs.filter(pr => pr.merged_at); // Only one page } // Otherwise, fetch more pages

Memoization Filter calculations are expensive when you have 200+ contributors:

const contributors = useMemo(() => { return allContributors .map(c => ({ ...c, prs: c.allPRDetails.filter(pr => isPRInTimeRange(pr.mergedAt, filter)).length })) .filter(c => c.prs > 0) .sort((a, b) => b.prs - a.prs); }, [allContributors, currentTimeFilter]);

Only recalculates when allContributors or currentTimeFilter changes. 4. Abort Controllers Clean up pending requests when component unmounts:

useEffect(() => { const abortController = new AbortController(); fetchAllStats(abortController.signal); return () => { abortController.abort(); // Cancel pending requests }; }, [fetchAllStats]);

Best Practices

Security Considerations

Never Expose Tokens Client-Side:

Our implementation runs in the browser, but the token is injected at build time and never exposed in the bundle: In production, this gets baked into the static build. The token never appears in client-side code.

Alternative: Backend Proxy

For more sensitive applications, proxy GitHub API calls through your backend: Client → Your API → GitHub API This way, tokens stay on the server.

Token Scopes

Use the minimum required scopes:

public_repo (read access to public repos)

read:org (read org data)

repo (full access - not needed)

admin:org (admin access - definitely not needed)

Scalability Considerations

Caching Strategy

5-minute cache works for us, but adjust based on your needs:

const CACHE_DURATION = 5 * 60 * 1000; // 5 minutes // For very large orgs (100+ repos), 4E2F increase to 15 minutes: const CACHE_DURATION = 15 * 60 * 1000; // For real-time requirements, decrease to 1 minute: const CACHE_DURATION = 1 * 60 * 1000;

Deployment Checklist

Before going live:

Token Security: Ensure GitHub token is in environment variables, not hardcoded

Rate Limits: Monitor API usage and adjust cache duration if needed

Error Handling: All API calls wrapped in try-catch with user-friendly messages

Loading States: Skeleton loaders in place for all async operations

Mobile Responsive: Test on various screen sizes

Accessibility: Keyboard navigation, screen reader support, ARIA labels

Performance: Check bundle size, lazy load components if needed

Analytics: Track usage patterns (filter changes, PR modal opens, etc.)

Monitoring: Set up alerts for API failures or performance degradation

Documentation: Update README with setup instructions

Complete Flow

Here's what the complete flow looks like in action:

flowchart TD A[User visits leaderboard] --> B[CommunityStatsProvider initializes] B --> C[Check cache] C -->|Cache empty - first visit| D[Fetch org repos - 1 API call] C -->|Cache hit| J[Render leaderboard from cache] D --> E[Process repos in batches of 8] E --> F[Fetch closed PRs for each repo] F --> G[Filter merged PRs only] G --> H[Build contributor map] H --> I[Calculate points and rankings] I --> K[Cache results with timestamp] K --> J[Render leaderboard]

Loading

User changes filter to "This Month":

flowchart TD A["setTimeFilter('month') called"] --> B["useMemo recalculates contributors"] B --> C["Filters allPRDetails by date"] C --> D["Recalculates points for each contributor"] D --> E["Re-sorts contributors"] E --> F["UI updates instantly (no API calls)"]

Loading

User clicks PR badge:

flowchart TD A["handlePRClick sets selected contributor"] --> B["Modal opens with animation"] B --> C["getFilteredPRsForContributor called"] C --> D["Returns PRs matching current time filter"] D --> E["Modal displays list with details"]

Loading

User comes back 10 minutes later:

flowchart TD A["CommunityStatsProvider checks cache"] --> B["Cache expired (10min > 5min TTL)"] B --> C["Fetches fresh data"] C --> D["Updates cache"] D --> E["Shows new leaderboard"]

Loading

Wrapping Up

Building a leaderboard like this taught us a few things:

Cache aggressively - The GitHub API is fast, but not hitting it is faster

Batch intelligently - Too much concurrency = rate limits, too little = slow

Store everything - Fetch once, filter client-side for instant updates

Handle failures gracefully - One bad repo shouldn't break the whole leaderboard

Optimize for perception - Show something immediately, even if incomplete

The architecture here scales pretty well. We handle 10+ repos with 200+ contributors and the initial load takes about 8-10 seconds. After that, everything is instant because filtering happens in-memory. If you're building something similar, start simple. Fetch all the data, display it, then add features. We started with just a list of contributors and added time filters, PR details, and search later. The complete code is in our repo at recodehive check it out, steal liberally, and let us know if you build something cool with it.

Got questions? Open an issue on our repo or ping us on Discord. Happy coding!

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Building a GitHub Organization Leaderboard: A Deep Dive into recode hive's Implementation

What We're Building

Architecture Overview

Data Flow: From API to UI

Phase 1: Data Collection

Phase 2: State Management & Filtering

Data Structure

UI Components

Time Filter Dropdown

GitHub API Reference

Request Example:

Request Example:

Request Example:

Authentication

Error Handling

How we handle it:

Performance Optimizations

Best Practices

Security Considerations

Never Expose Tokens Client-Side:

Alternative: Backend Proxy

Token Scopes

Use the minimum required scopes:

Scalability Considerations

Caching Strategy

Deployment Checklist

Complete Flow

Wrapping Up

FilesExpand file tree

Documentation.md

Latest commit

History

Documentation.md

File metadata and controls

Building a GitHub Organization Leaderboard: A Deep Dive into recode hive's Implementation

What We're Building

Architecture Overview

Data Flow: From API to UI

Phase 1: Data Collection

Phase 2: State Management & Filtering

Data Structure

UI Components

Time Filter Dropdown

GitHub API Reference

Request Example:

Request Example:

Request Example:

Authentication

Error Handling

How we handle it:

Performance Optimizations

Best Practices

Security Considerations

Never Expose Tokens Client-Side:

Alternative: Backend Proxy

Token Scopes

Use the minimum required scopes:

Scalability Considerations

Caching Strategy

Deployment Checklist

Complete Flow

Wrapping Up