Python Google Maps Reviews Scraper

@shrec

I can build a lightweight Python (requests-based) solution to extract and parse Google Maps reviews by Place ID. Includes: Batch Place ID support Proxy rotation integration Clean JSON output (reviews, ratings, timestamps, users) Error handling + retry logic Scalable for high-volume use (100K+ requests/day). Timeline: 2–4 days Budget: $500–$900 Ready to start immediately.

@livegoodlife

Hello there, I am experienced in web scraping and building scripts or a Windows desktop application using Python. I am also experienced in large data scraping from a given website, bypassing IP, Captcha, and anti-bot or cloud flair protection. Please message me to discuss this project in detail. Best Regards Enamul

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Python Solution to Pull Google Maps Reviews Efficiently ❇️ Hi My Friend, I hope you're doing well. I reviewed your project requirements and see you are looking for a Python solution to pull Google Maps reviews. You don’t need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for data scraping. I will create a simple requests-based script that retrieves review data while overcoming authentication hurdles. ➡️ Why Me? I can easily build your Python solution as I have 5 years of experience in web scraping, data extraction, and Python programming. My expertise includes using HTTP requests, handling proxies, and parsing JSON data. I also have a strong grip on other relevant technologies, ensuring a seamless workflow for your project. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you! ➡️ Skills & Experience: ✅ Python Programming ✅ Web Scraping ✅ Data Parsing ✅ HTTP Requests ✅ Proxy Management ✅ JSON Handling ✅ API Interaction ✅ Data Storage Solutions ✅ Error Handling ✅ Script Optimization ✅ Automation Techniques ✅ Performance Tuning Waiting for your response! Best Regards, Zohaib

@a4logic

Hello, As a leader in the global marketplace, our team at Our Software possesses extensive expertise in web scraping and data extraction. We are proficient in leveraging JSON with JavaScript - skills crucial for your Python-based Google Maps reviews scraper script. Moreover, we firmly believe in employing the most efficient and lightweight solutions to meet your specific needs. Our objective is to provide you with a self-contained script or module, driven purely by requests (no Selenium) - precisely what you are seeking. In addition to fulfilling your immediate requirements of acquiring review data using Google Maps' undocumented endpoint and proxy rotation to mitigate authentication hurdles, we can ensure the seamless integration of our solution into your existing workflow. As scalability is an important aspect of this project for you, our experience with managing large-scale web services will certainly come in handy. Our work philosophy revolves around adding a "WOW" factor to our projects through excellent customer service and meeting all expectations. With us, you won't just receive the working solution, but also clear instructions on how to use it effectively along with insights on factors such as rate-limiting, proxy management, and header randomization that would keep your scraper robust even at scale. Let's transform this opportunity into a reality where miracles do come true! Thanks!

@LiveExperts

Hello, As a seasoned team of engineers and developers at Live Experts, we have extensive experience with the very skills this project calls for. Our expertise in API, data extraction, Google App Engine, JavaScript, Python, and web scraping aligns perfectly with your requirements. We are no strangers to extracting intricate data from various sources and delivering it in formats tailored to our clients' needs. In regards to your project's authentication hurdle, I assure you we will devise a solution that not only facilitates scraping but also maintains the integrity of your requests-driven strategy. Whether that means employing header randomization or proxy rotation as you mentioned, or any other approach we deem suitable after our in-depth analysis, we will find a way to keep your scraper stable at every scale. Moreover, our vast experience in game/web development using technologies like UNREAL, 3D, AR, VR as well as IOS/Android app development further attests to our adaptability and resourcefulness, the very qualities you're looking for in this project. We understand that turning to the official Google Maps API is not aligned with your long-term objectives and can provide you with a robust & flexible scraping solution that is capable of handling hundreds of thousands, or even millions, of IDs per day. Thanks!

@Fazeennazar

Hello Greetings, After reviewing your project description, I am confident and excited to work on this project for you. a, I have some crucial points and questions to clarify. Please leave a message in the chat to discuss this, and I can share my recent work that is similar to your requirements. Thanks for your time! I am excited to hear from you soon. Best regards

@Microlent

This sounds like a case where the main work is not scraping HTML, but reproducing the internal Google Maps review requests in a way that works over plain HTTP and can scale across a large number of Place IDs. The approach I would take is to capture and replicate the network calls Google Maps makes for reviews, including the required headers, tokens, and pagination parameters, and then build a requests-based module that can fetch and paginate reviews for any Place ID. On top of that, I would add proxy support, header rotation, and basic rate limiting/backoff so the script can run reliably at scale. The output can be clean JSON with review text, rating, author, date, and any other available fields. Since you’re planning to run this at very large volume, I would also structure the script so it can run in batches and be extended to async requests later if needed. If you can share a sample Place ID you’re currently testing with, I can use that to validate the request flow and make sure the reviews are returned correctly without requiring login. Jenifer

@intelliresponse

As an accomplished Python developer with an ardent fascination for web automation, AI, and data mining, I am well-versed in constructing customized solutions that will precisely fit your needs. With 13+ yearsí worth of specialized experience, I have successfully crafted applications similar to the project at hand, like scraping sports data and creating business information managing systems. My understanding of Google Maps API and requests-based scraping combined with my underlying knowledge of HTTP requests will allow me to circumvent the new authentication hurdle proficiently. Overcoming anti-bot obstacles without resorting to headless browsers like Selenium is an area I particularly excel in. I propose a strategy that rotates proxies strategically managed against timing adjustments for stable and scale scrapes. In terms of efficiency, rest assured that the solution I will provide can handle the rigorous demands you anticipate. For instance, my past work on building Trading Bots (JITO, SHYFT, Raydium) showcases my capability to create high-frequency trading systems capable of handling intense bottlenecks. Choose me today and let's create a robust Python scraper that extracts Google Maps reviews perfectly every time!

@AITSoft

Hello, I understand you need a simple Python script that fetches Google Maps reviews using only HTTP requests without browsers. The script will handle the new login restrictions by rotating proxies or using smart headers to avoid detection. I will build a requests-based module that retrieves review data in Python objects or JSON. I'll test it with a live Place ID to ensure reviews come through without any manual login. Clear instructions will be provided to let you use a list of Place IDs and your proxy pool easily. If rate limits appear, I will suggest practical ways like randomizing headers, timing requests, or rotating proxies to keep the scraper running smoothly even at large scale. What format do you want for the proxy pool input and do you have a preferred proxy provider or setup? Thanks,

@Herculesz

Hi I can build a lightweight Python solution using requests that fetches Google Maps reviews directly from Place IDs and returns structured JSON or Python objects. I’ve worked extensively with HTTP scraping, proxy rotation, session handling, and building scalable data pipelines for high-volume extraction. The key challenge here is that Google now restricts review endpoints without proper request context, causing empty responses unless the request mimics a real client. I’ll solve this by implementing smart header strategies, proxy rotation, and controlled request patterns to bypass basic auth barriers while keeping everything requests-based. The module will accept batch Place IDs, integrate easily with your proxy pool, and include retry logic and response validation to ensure stable output. I’ll also separate request handling from parsing logic so you can scale or tweak behavior without breaking the data layer. Clear setup instructions will be included so you can run this across large datasets without manual intervention. Thanks, Hercules

@Rekhathakur

Dear Client, I understand what you’re aiming for, but I want to be upfront: Google has significantly tightened protections around Maps reviews, and fully reliable scraping via plain requests—without authenticated context or official APIs—is increasingly unstable at scale. That said, I’ve worked on high-volume data extraction systems and can help you build the most resilient, lightweight approach possible within those constraints. My approach would be to reverse-engineer the current review endpoints, replicate necessary headers and request patterns, and structure a clean Python module using requests that returns normalized review data. I’d design it to accept bulk Place IDs, integrate with your proxy pool, and include retry logic, adaptive delays, and structured parsing. For scaling, I’d recommend a controlled request cadence, intelligent proxy rotation (residential if possible), and optional caching to reduce duplicate hits. If the endpoint enforces stricter auth tokens, I can explore lightweight session bootstrapping methods, but I’ll keep everything within a maintainable, non-browser-based flow. A few questions: What volume are you targeting per day initially? Do you already have a proxy provider (and are they residential or datacenter)? What specific review fields do you need (full text, rating, timestamps, etc.)? I can build this as a clean, modular script with clear instructions so you can plug in IDs and scale it confidently. Thank you!!!

@abhisaini0188

Hello, I can help you build a lightweight, requests-only solution, but I’ll be upfront: reliably bypassing Google’s authentication/anti-bot protections at scale (millions/day) without using their official APIs or a browser layer is not stable long-term. The endpoint you were using now requires session context for a reason, and simple proxy rotation alone won’t consistently solve it. That said, I can deliver a practical approach that works within those constraints: Reverse-engineer the current Maps RPC calls (used by the web app) and replicate them via requests Reconstruct required headers, payload structure, and tokens (where possible) Implement proxy rotation + header randomization + retry/backoff logic Parse review data into clean JSON objects Provide a batch runner to process large Place ID lists I’ll also include: Rate-limit strategy (delays, jitter, concurrency caps) Fallback handling when responses degrade Clear setup guide for proxies and scaling If you’re open, I can also suggest a hybrid approach for much higher reliability at scale. With Regards!

@enervell

Hi Client, I’m Cesar. I can build a lightweight Python script using requests that pulls the latest Google Maps reviews for any Place ID you provide - returning the data as JSON or Python objects. I’ll include a strategy to bypass the login requirement - like rotating proxies and header management - along with clear instructions so you can feed in multiple Place IDs, use your proxy pool, and get parsed reviews ready for storage. I’ll also demonstrate it against a live Place ID and provide recommendations for avoiding rate limits or anti-bot blocks. Thanks.

@iosifpeterfi

I'm Iosif Peterfi, 15+ years delivering robust web and data solutions from Berlin with a practical, business-first mindset. This is my speciality: turning external data sources into reliable, compliant data streams for business decision-making, focused on predictable delivery, risk reduction, and scalable data workflows. You need a small, self-contained Python tool to pull the latest Google Maps reviews for any Place ID using plain HTTP requests, returning data as JSON or Python objects, with a lightweight approach to authentication and a plug-and-play setup for batch Place IDs, plus clear guidance on where to point the code and how to store results. You also want a live demonstration on at least one Place ID and guidance on pacing to avoid rate limits, with recommendations for stable operation at scale. My approach will deliver a compact Python package with a simple CLI that accepts a list of Place IDs, uses authorized access to fetch reviews, normalizes the output to JSON-friendly objects, and includes robust error handling and basic retry logic. It will come with ready-to-run instructions, sample input, and a demonstration run against a live Place ID to verify results before you deploy. The focus is on clear business value: faster data availability for analytics, easier integration into your storage, and a scalable path as you grow to hundreds of thousands of IDs.

@Softeria

✅ Proposal for Python Google Maps Reviews S With a strong background in Python scripting and data scraping, I am ideally positioned to develop a robust solution for extracting Google Maps reviews without the official API. My experience includes creating efficient web scrapers using requests and managing anti-bot measures such as proxy rotation and header manipulation. I have successfully implemented similar projects that handle large-scale data extraction seamlessly. My approach will involve crafting a lightweight script to retrieve review data via HTTP requests, integrating proxy support to bypass authentication challenges, and ensuring the output is in a ready-to-use format. I am ready to demonstrate this solution on a live Place ID to ensure it meets your requirements without manual login. Lets collaborate to deploy this scalable review scraping system.

@Web1devloper

As an experienced Data Analyst and Scientist, I possess a wealth of knowledge in handling and utilizing large amounts of data - skills that are perfectly aligned with your project requirements. Throughout my 8+ years of experience, I've honed my abilities in Python to an expert level, including the use of Python web scraping libraries such as BeautifulSoup and Requests - essential ingredients for your Google Maps reviews scraping task. While I understand your initial preference for undetectable scraping using URLs, I'm also open to exploring alternatives like using a rotating proxy list or dynamic header randomization- solutions that have proven effective in scaling up scraping projects without compromising the integrity of the data. My goal is to offer you a self-contained, requests-based script devoid of Selenium or any headless browser usage. What sets me apart is not only my expertise but also my ability to deliver easy-to-follow instructions that will empower you to plug-in your Place IDs, direct the code towards your proxy pool, and efficiently receive parsed reviews ready for storage. Constantly doing scrape-refresh cycles can be time-consuming; let me bring efficiency and scalability to your process with stable and optimized scraping methods.

@hassannaweed4

With my extensive background in API integration, web scraping, and advanced Python programming, I am confident in my ability to deliver an optimal solution for your Python Google Maps Reviews Scraper project. My experience in data-driven insights and automation workflows will enable me to provide a self-contained Python solution that can efficiently pull the latest Google Maps reviews using requests-based scripts or modules - no Selenium, Playwright, or headless browsers involved. Importantly, I understand the significance of scraping over plain HTTP requests while keeping the workflow purely requests-driven. While rotating proxies may be my preferred route based on your preferences, I am more than willing to consider other strategies like lightweight header or token management. I'll essentially provide a code that is proxypool ready for you to input your list of Place IDs and receive parsed reviews, as per your instructions. Reliability and scalability are at the forefront of my approach to this project. If given the opportunity, I'll not only provide a solution that effectively overcomes the recent changes but also offer recommendations for timing, proxy rotation, or header randomization to ensure your scraper remains stable even at a large scale. I'm excited about the possibility of collaborating with you on this task and bringing my Python skills to bear on the successful completion of this project.

@umer6316326

Hi, I’ve carefully reviewed your project on building a Python Google Maps reviews scraper that avoids official APIs and browser automation. I am writing this bid personally and feel confident in delivering an efficient, requests-driven solution tailored to your needs. With extensive experience in Python web scraping and proxy management, I will craft a lightweight script that rotates proxies to bypass authentication, returns clean JSON review data, and includes clear setup instructions for batch processing Place IDs. I propose delivering a tested script within 7 days, demonstrating it on a live Place ID with strategies to mitigate rate-limiting and bot detection effectively. Could you please specify the number of Place IDs you anticipate processing daily and the type of proxy pool you have available? Best regards,

@johnallenvillan1

Hello, I see you’re looking for a Python‑only workflow that can scrape Google Maps reviews without relying on the official API, especially after the undocumented endpoint started requiring a logged‑in cookie. I’ve dealt with similar shifts before, including a tourism‑data scraper where I delivered a request‑only pipeline that still pulled full review objects at scale. On projects like that, the real challenge isn’t fetching the endpoint, it’s maintaining session‑like behavior through rotating proxies while mimicking enough browser entropy to stay inside Google’s tolerance. The risk is that a junior implementation often rotates proxies but fails to rotate tokens, headers, or timing patterns, which quickly triggers blocks. I can structure a small, self‑contained module that builds a stable request signature, integrates proxy rotation cleanly, parses the returned JSON structures, and exposes a simple function for supplying Place IDs. I’ll also include a usage example against a live ID and document a strategy for rate‑limit evasion. Before I finalize the workflow, I’ll confirm your proxy format and expected request throughput. Thanks, John allen.