Keeta App Menu Scraper

@hirujiyu

⭕⭕ MOBILE APP DATA SCRAPING & AUTOMATION EXPERT ⭕ Hi there, ✔️ I see you need a reusable automation tool that can extract complete restaurant menu data including item names, variations, descriptions, prices and images and generate a structured Excel file for repeated use. I can build this as a maintainable Android automation/data-extraction workflow rather than a one-off scraper. ✍️ Questions to get started ? 1) Do you have an Android device/emulator environment already available, or should I prepare the complete setup as part of the project? 2) Should images be delivered as direct image URLs in Excel, or do you also need image filenames/metadata associated with each menu item? ✅ I would first validate the extraction against a representative restaurant and confirm that menu variations, pricing, descriptions and image references are captured correctly. Once the data structure is reliable, I’ll make the workflow reusable for additional restaurants and document the complete execution process. I can start immediately. For the requested sample, I can provide it from an authorised/test data source or after access to the agreed environment rather than claiming a sample I have not personally generated. Thank you.

@justmian876

As the leader of BN-Droids Digital Services, I can assure you that my experienced team and I have the exact skills you are seeking for your Keeta App Menu Scraper project. Our reputation in web scraping and data extraction work is well-established and we have a solid ability to bypass the kind of protections implemented in the Keeta app. We recently worked on a similar project where we successfully extracted menu items, variations, and prices from the Keeta app and saved them in an Excel spreadsheet.

@gotucat

Hi, I reviewed the request for a reusable Keeta app menu scraper that extracts menu items, descriptions, prices, and images, then saves everything into an .xlsx file for any restaurant. I’ll build the Web Scraping and Data Extraction pipeline around an automated Android emulator flow with Python plus Selenium/Appium, and also integrate API-style calls where available, so the script can reliably capture variations and map them into Excel columns including item name, variation, price, description, and image links. I’ll keep the code clean and fully documented with a step-by-step setup guide, producing a validation Excel sample to confirm output quality. Let’s discuss here now.

@denisSolution

Hi, I'm Denis. I've worked on similar scraping and automation projects where mobile app data needed to be extracted reliably while dealing with protections. From your description, the main challenge is bypassing the Keeta app's security to access menu data consistently. I can build a solution using packet inspection to identify the API endpoints or emulator-based flows with Appium to extract the structured data you need. The output will include item names, variations, prices, descriptions, and images in a clean Excel format. I'll provide documented Python code, a setup guide, and a sample file from a test run so you can verify the approach before we proceed. All dependencies will be open-source to ensure you can run and maintain the tool long-term. I can start working right away. Let's connect and discuss the details. Thanks, Denis.

@syphaxzen

Hi, I can build this as a reusable Python tool rather than a one-off scraper, with `.xlsx` output including item names, variations, descriptions, prices and images. I’m experienced with Python automation, reverse-engineering web/app data flows, Selenium and structured data extraction. I can also provide the source code, setup documentation and handover. I can first demonstrate the approach on a Keeta restaurant so you can verify the output before we discuss the full implementation. If this is still open, message me and I’ll explain exactly how I’d approach it.

@maxscender

I’ll build you a reusable Keeta scraper that works across restaurants by intercepting the app’s own API traffic, so you’re not relying on brittle UI automation or HTML scraping. The Python script will authenticate within your session, pull complete menu data—item names, descriptions, variations, prices, and image URLs—and write everything into a clean .xlsx file. It will be structured so you can swap in any restaurant ID and re-run the script to generate a fresh spreadsheet. The code will be fully documented, modular, and runnable from your local machine with a simple setup process. I hear your requirement for proof: I can provide a sample Excel file extracted from Keeta with item name, variation, and price before we move forward. Once that sample meets your standard, you’ll get the full source, setup guide, sample output, and a short walkthrough. All libraries used will be standard, open-source, and free for commercial purchase and resale.

@mayankinnovative

I'm not able to help with this one. Building a tool specifically to bypass Keeta's app protections - MITM interception, reverse-engineered private APIs, or automated emulator flows meant to circumvent access controls - falls under unauthorized access to a system's protected data, regardless of the intended end use being a personal spreadsheet. That's true even framed as a "permanent tool for my own use" rather than a one-off scrape. If there's a legitimate underlying need here, there are a couple of paths that don't involve circumventing app protections: if Keeta or its restaurant partners publish an official public API or partner data feed for menu access, that's fair game and I'd be glad to help build against it. Separately, if you specifically need to catalog menu data for restaurants you personally own or have written permission to access, that's a very different and workable scope. Would either of those describe your actual situation?

@TeraByte26

Hi mohamedplatt I will deliver a reusable Python script that extracts every menu item, description, price and image from any Keeta restaurant into an .xlsx file, with full source, setup guide, sample Excel and a hand‑over walkthrough. I can have a working demo ready within 2 days. I’ll send a sample Excel now—shall I use the default emulator? Waiting for your response in chat! Best Regards.

@muneeb6767

I can build a reusable Python/Appium-based workflow to collect Keeta restaurant menus, including item names, variations, descriptions, prices, and publicly available images, then export clean XLSX files with documentation and repeatable setup. I can work with permitted app/API flows, but I can’t provide or claim a pre-extracted Keeta sample without actually having access to the app data.

@mzdesmag

Hello sir, Did go through your job description and glad to share that I have enormous experience in working with Keeta App Menu Scraper I'm a seasoned programmer and Engineer with quality experience in Flutter, React, Node.JS, SpringBoot, Frontend and Backend Development, Python, Matlab, R studio, C, C++, C#, OpenCV, OpenGL, Tesseract OCR, google vision, Statisticaal programming/R progamming data analysis Computing for Data Analysis Time Series & Econometric, Machine learning, AI, Deep learning, Matlab and Mathematica, 3D modeling, CAD/CAM,AutoCAD, 2D, Architectural Engineering, SolidWorks, Unity 3D, AutoCAD, 2D drawing, 2D draftingPCB, Electronics, Arduino, Embedded Systems Automation, Embedded and Firmware , IOT, Electrical/Mechanical Engineering I am a TOP Rated Freelancer, and you can check my reviews here as well: https://www.freelancer.com/u/mzdesmag. Looking forward to potentially working together on this project. Thanks and Best regards, Adekunle.

@mahads31

With my extensive skills in automation and data processing, coupled with a mastery of Python, I am well-equipped to create the reusable script you need for your Keeta application menu scraper. I have successfully developed similar tools for several clients, including automated scraping with MITM, packet capture, reverse-engineered API, or automated Android emulator flows using Python + Selenium/Appium. I understand that this isn't just a one-off scrape but a permanent tool you need for your own use. Rest assured, the code I develop for you will be fully documented and come with a step-by-step setup/run guide so that you can repeat the scrape for any restaurant any time you want. My dedication to efficient results has always enabled me to deliver on or before ASAP deadlines without sacrificing quality. Additionally, my knack for building systems designed for lasting success aligns perfectly with what you desire in terms of output format (xlsx) and deliverables like fully-documented source code, dependencies, along with brief hand-over sessions should you require further guidance. In partnering with me on this project, you'll not only be acquiring the code outright but also receiving long-term support to ensure its continued utility as your requirements evolve.

@ianb65

Hi there, Keeta menu extraction with item names, variations, prices, descriptions, and images is exactly the kind of data-processing and web scraping problem I solve. I can build a reusable Python tool with a clean software architecture, then automate extraction through the most reliable path available, normalize the menu data, and export everything to a structured Excel workbook with documented setup and repeatable execution. Best regards, Ian

@abdulhamidh2

Hello I understand you need a reusable Python script that extracts full menu details from any Keeta restaurant app listing, bypassing protections like MITM or API restrictions, and outputs everything in an Excel file. I have hands-on experience with Android automation using Appium and Selenium combined with packet capture methods to reliably access protected app data. My approach would be to build a robust scraper automating the Keeta app via an Android emulator, capturing menu items, descriptions, prices, and images, then organizing all data neatly into .xlsx format. I’ll provide fully documented code, clear setup instructions, and a sample Excel file from a test scrape for your validation. Could you share which environment you prefer for running the script—local machine or cloud? Looking forward to your reply. Best regards, AbdulHamid

@pasion0128

★•══•★ Hi client ★•══•★ I’ve got solid experience with scraping mobile apps using Python and tools like Appium or Selenium to handle tricky protections like MITM or reverse-engineered APIs. I focus on making scripts that are easy to reuse and maintain, with clear documentation so you can run them anytime without hassle. I’ll deliver a clean Excel file including item names, variations, prices, descriptions, and images exactly as you need. Plus, I’ll include a step-by-step guide and a quick walkthrough session to get you fully comfortable running it yourself. Could you share a test restaurant name so I can prepare a sample Excel for you to check? Looking forward to showing you it works smoothly. Best regards, Rico

@dataspro

Nice to talk you , After reading in detail the requirements of your project and concluding that they match my areas of knowledge and skills, I would like to introduce myself. My name is Anthony Muñoz and I am the lead engineer for DS Pro IT agency. I have worked for over 10 years in Backend and software development and have successfully done multiple jobs. It will be a pleasure to work together to make your project a reality. Please feel free to contact me. I´m looking forward to working with you. I really appreciate your time and remain attentive to any request or question. Greetings

@ayesha86664

Freelancer Proposal Hi there! Your main challenge is creating a reusable Keeta menu extraction tool that can reliably collect complete item details, variations, prices, descriptions, and images into Excel. It also needs to remain practical for repeated use rather than being a one-time scraper. I have relevant experience with Python, data extraction, Selenium, Android automation, data processing, Excel generation, and automation workflows. I can build a structured solution that handles menu data consistently and produces clean .xlsx files. I will first assess the available app data flow and choose the most reliable extraction approach that complies with the applicable access rules. The script will organize item names, variations, descriptions, prices, and image references into a clean Excel format. I will provide documented source code, dependencies, setup instructions, and a simple handover so you can run it repeatedly. check our work https://www.freelancer.com/u/ayesha86664 Can you provide a sample restaurant or specific Keeta app version you want supported first? Let me know if you’re interested & we can discuss it. Best Regards Ayesha

@AndrewJSMAN

I've reverse-engineered Keeta's API for menu data extraction before, so this is right in my wheelhouse. I'll use Frida for runtime hooking to dump the internal API endpoints, then parse the JSON responses with Python's `requests` and `pandas`. Output will be structured in `.xlsx` with columns for item name, variation, price, description, and image URLs using `openpyxl`. The script will handle pagination and rate limiting automatically, with logging for failed requests. All dependencies are open-source (MIT-licensed). Thanks, Andrii.

@longngoc2307

Hi - Truong here >>>>>>>>>> "KEETA MENU DATA EXTRACTION" — you need a reusable scraper that produces clean restaurant menu data, not a one-time export. I will build a repeatable Python-based extraction workflow with structured output for items, descriptions, variations, prices, and images. I’ll first validate the available data source and build the tool around a stable approach rather than a fragile manual scrape. The final script will include setup steps, dependencies, Excel export, and a clear handover so you can run it for future restaurants. Can you provide one example Keeta restaurant link or ID, and confirm whether you need this tool for public app data only or also logged-in account data? Looking forward to working with you.

@mdabu38

I can build this as a reusable Keeta menu extraction tool, not a one-off scrape. I’ll first analyze the app/API flow, identify the most reliable data source, then automate extraction of item name, variation, description, price, and image into a clean .xlsx. I’ll also include open-source dependencies, setup/run documentation, and a sample Excel from the working extractor so you can verify the output before moving forward.