Add Noon & Extra Scrapers

@adeelpirzada

Hi, I am Adeel. I build automation around Apify style scraping APIs regularly, including provider integrations feeding Flask and SQLite backends similar to your amazon_provider setup. For this I would compare the working amazon_provider call shape against the Noon and Extra actor input schemas directly in Apify Console, fix the payload and parsing to match, then run the iphone 15 test until both return 20+ products. I can start right away and push fixes with screenshots as proof once each provider passes the test. Are the Apify actor input schemas documented anywhere, or do I need to reverse engineer them from the console?

@Badhan685

Hi, I have read the job description and now ready to start. I will provide 100% quality. Please send me a message for discussion. Let's discuss the project. Thanks

@emanz03

Since both Actors work in Apify Console, I’ll compare those successful inputs with the Python payloads and check run completion, dataset retrieval and result mapping against your working Amazon provider. I’ll fix both providers, test “iphone 15”, capture product-count screenshots and push the changes to GitHub. Can you share the two files and successful Console input JSONs?

@TheSecondSource

Hey! We are a team of 62 professionals specializing in Python backend development with 9+ years of experience integrating APIs, scrapers, and production services. Here’s how we can help: * Fix Noon and Extra provider API input mappings * Match both providers against the working Amazon implementation * Verify 20+ products for each test search * Push tested fixes to GitHub with proof screenshots Could you clarify whether both Apify Actors already have fixed input schemas, or should I inspect their current configurations first? Also, are there any provider-specific fields beyond product data that the Flask application expects from Noon and Extra?

@manishashree12

Hello, I’ve carefully read your project requirements and I'm confident I can deliver exactly what you need. I have a strong portfolio showcasing my work in Python, Data Processing, Data Entry, SQLite, Data Scraping, Flask, Data Integration, Database Management, Data Collection, Data Annotation and Python, Data Entry, Data Annotation, Data Processing, Data Scraping, Database Management, Flask, SQLite. Please check my profile for examples relevant to Add Noon & Extra Scrapers. Lets connect in chat so that We discuss further. Regards, Manisha

@albert1025dev

Hi, Albert here, from Philippines. Building your add noon and extra scrapers with 20+ products comes down to one thing: clean, complete data that keeps arriving when the site changes. I'm a senior software developer with 10+ years of experience working with Python, Data Processing and Data Scraping. For your add noon and extra scrapers, the real challenge is layout changes and blocking. A common issue: no monitoring, so when the site changes the scraper returns empty data and nobody notices. My plan: first, map the pages, fields and blocking rules of the target site. Then, build the scraper with retries, rate limits and data cleaning. Finally, add monitoring and alerts, then run it on a full sample. I'd start with the main target pages as phase one. I've done scraping work in Python. A few questions to better understand the scope: 1. Should an empty run alert you right away? Sites change without notice, so I add alerts. 2. Save only changed records on each run? I'd recommend it, you get a clear change history. 3. Is the data compared across several sites? Then names and units get normalized across sources. I can start right away. I'm on CET, so our working hours overlap. Happy to go over the details here in chat and suggest the best approach. Looking forward to hearing from you, Albert

@adriank06

The main issue is likely not the scrapers themselves, but the mismatch between Apify Actor input schemas and the Flask provider integration layer. I can fix the Noon and Extra providers by aligning API calls with the working Amazon provider pattern and validating real product output. I will review the existing provider structure, update the request/response handling, and test the `"iphone 15"` case to confirm 20+ returned products. I can handle Python API integration, debugging, validation, and clean Git-based delivery. I will provide the updated provider files, test proof, and clear changes for future maintenance. Please share the repository access and Apify API configuration details so I can review the current implementation and start the fix.

@jeremyc121

Hi there, I hope this can be my first project with you. I’d be really happy to work together! I understand the issue: the Noon and Extra Actors already work correctly inside Apify Console, but the Flask-side Python calls are sending inputs that don’t match what those Actors expect. I’d focus on the integration rather than rewriting anything unnecessarily. I’ll inspect the existing scraper functions, compare their payloads with the tested Actor inputs, correct the Apify API calls, and verify that an “iphone 15” search returns 20+ products from both providers. I’ll also make sure the returned data fits your existing application flow, provide screenshot proof for both results, and push the final changes to GitHub as requested. Could you share the current scraper files and the working reference implementation mentioned in the project description? Also, are both Actors being called through `apify-client`, or are you using direct HTTP API requests? I can start directly with the two failing integrations. Best regards, Jeremy

@kafupeople

Hi I've fixed Python/Apify integrations where an Actor worked correctly in the Apify Console but failed from application code because the API payload didn't match the Actor's input schema. I'll correct the Noon and Extra calls without disturbing the working Flask flow, then test both with "iphone 15" and verify each returns 20+ products. I'll also make sure the returned data is handled consistently with your existing scraper implementation rather than just making the Actor run. I'll deliver the two fixed files, screenshot proof for both tests, and push the changes to GitHub. Thanks, Belal

@nicolasarmandoc

Hi, The main issue here is matching the Python provider payload exactly to the input schema expected by each Apify Actor, while keeping the existing response format consistent with the working Amazon provider. I’d inspect the Noon and Extra Actor input definitions, compare them with the current API calls, then update both providers without changing the surrounding Flask integration unnecessarily. I’d test each provider with “iphone 15”, verify that both return 20+ products, and check the returned fields for missing or malformed data. I’d also run the tests against the existing environment before pushing the corrected files to GitHub, with screenshots showing the successful results. One question: can you provide access to the current repository and Apify API credentials for testing? I’m available to make the fixes and verify both scrapers end to end. Nicolas