Need a parser for the online store https://www.lcsc.com/

Hello!

The task is clear: it is necessary to regularly collect all "In Stock" items from LCSC across all sections of the catalog and export them to XLSX in a clearly defined format.

What I can deliver:
— a stable parser for a large volume of data (~650,000 items) that goes through all categories;
— export to Excel with the required columns: section, MPN, Manufacturer, Availability, Description, Package, Pricing;
— a button to run or a schedule + the possibility for further refinement if the catalog structure changes.

… I work with Python, large parsing, Excel export, and maintaining such scripts, so I can create not just a one-time collection, but a working tool for regular use.

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Hello!

I have reviewed your technical specifications and the attached example file. The task is clear: I need a regular dump of the LCSC.com catalog (only "In Stock" items, about 650k positions) with the correct breakdown of the wholesale pricing grid (Quantity/Price up to 4 levels) in XLSX format.

I am a Python developer specializing in creating high-load parsers and working with data pipelines.

Many developers suggest parsing such sites through browser emulation (Selenium), but with a volume of 650,000 items, this would take days.

Here’s how I will implement this parser (Solution Architecture):
…
Direct work with the Backend API: LCSC.com dynamically loads products through hidden JSON API endpoints. I will write a script that will directly call these APIs. This will speed up data collection by 100 times.

Bypassing the limit of 5000 items: The platform does not allow scrolling through more than 50-100 pagination pages at a time. To extract all 650k, I will write a deep crawl algorithm that will recursively delve into subcategories and apply micro-filters to ensure each sample has fewer than 5000 items.

Speed and stability: I will build the script on an asynchronous engine (Aiohttp/Asyncio). We will implement proxy rotation (the proxy will be included in the budget) and a retry system. If LCSC temporarily blocks the IP, the parser will simply switch proxies, wait a few seconds, and continue from where it left off.

Generating XLSX: Dynamic parsing of the pricing tiers and writing in the format you need (8 columns for prices) using the pandas library. The file will not weigh gigabytes and will easily open in Excel.

The script will be equipped with a config and a detailed logger (so you can see what percentage of the catalog has already been collected). If the site structure changes (if they update the API), the code is easily scalable and modifiable, as I write in strict OOP style.

I am ready to start immediately. Message me privately, and I will show you exactly how we will extract the pricing matrix!

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Good afternoon. I can implement such a parser, as well as its monthly discussion (manual or automatic). However, we should discuss the details. Shall we chat in private messages?

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Hello!

I have extensive experience in developing solutions for parsing and processing data (various sources, protection against blocking, automation). I am ready to implement the assigned task in the shortest possible time.

I suggest discussing the details in private messages.

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Hello! Ready to collaborate. I have experience in creating parsers. I offer quality and fast work. Write to me)

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I can help with the execution, they also have an API that makes the work easier.

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Hello. I understand the task: a script is needed that, upon launch, traverses the entire catalog of lcsc.com across all sections, takes only In Stock items, about 650,000 positions, and exports them to XLSX with columns for section, MPN, manufacturer, availability, description, casing, and price pairs for quantity and price at four levels. It should run once a month or manually, plus the ability to adjust for changes in the catalog structure.

Regarding implementation: lcsc has an internal JSON API that provides the catalog page by page, so I would primarily look into working directly with these requests rather than parsing HTML. This is faster, more stable for a volume of half a million positions, and easier to fix when changes occur. If part of the data is closed or protected, I would add Selenium only to problematic areas.

With a volume of 650,000, stability is crucial, so I would implement resumption from the point of interruption, duplicate control by MPN, careful pauses, and retries against anti-bot measures, with proxies if necessary, plus progress logging so that the run can be restarted without losing collected data. The export to XLSX should be done via pandas or openpyxl with exactly the column structure specified in the technical specifications, including four pairs for quantity and price.

I have been creating parsers in Python with Selenium, BeautifulSoup, and pandas for a long time. To assess more accurately: are the price levels needed specifically those shown for retail quantities, or are all wholesale tiers from the product page important? This affects how many requests per position are needed. I am ready to start by analyzing the structure of their API in several sections to fix the export format and timeline.

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Good day. I am ready to complete this project; I have extensive experience in developing various applications.

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ready to complete your task, write to discuss the details..........................

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Good afternoon.

I looked at the example file — the structure is clear, the task is straightforward.

I propose a Python script with two modes of operation:

1. Through the LCSC API — if access is available:
— Batch requests of 100–200 products at a time
— 650,000 products — about 1–2 hours
…
2. Through Playwright (browser parsing) — if the API is unavailable:
— Page by page, bypassing anti-bot protection
— 650,000 products — 8–12 hours, I recommend running on a VPS

What will be included in both cases:
— Crawling all sections, filter "In Stock"
— Exporting 14 columns in the format of your example
— Saving progress (checkpoint) — if the script is interrupted, it continues from where it left off
— Documentation and the ability to edit if the website structure changes

Cost: 8,000 – 12,000 UAH. Deadline: 5–7 days.

Please clarify: do you have access to the LCSC API?

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Hello.
I have extensive experience in parsing, including products from online stores, not just XML exports.
I have also parsed auto and motorcycle parts and clothing from several sources where there is a huge number of products.
I even have experience in parsing databases of CIS websites.
In general, I have enough experience to complete your task efficiently and in the shortest time.
The task is clear, and I can start right now.

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Good day, I am interested in your project, let's discuss the details in the chat.

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Good evening, I am ready to complete your order and would be happy to collaborate further. Message me here in private, and I will send you examples of my work. I can also send you a link to my portfolio.)

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Hello.

I am developing parsers in NodeJS. I am ready to take it on. Write to me, and we will discuss.

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I write parsers in Python for various needs, feel free to contact me, we will get it done.

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Ready to take it on.
Need to clarify the order details, write to me!
I use python, uv, github, docker.

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I have already made a script in Python. There are millions of products. It will be necessary to split them into files. And to make pauses between requests to the site, otherwise they will block us. I can show you the finished file with 800 products. Contact me for clarification on the final result.

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Good day, I have been in web programming for over 9 years. I work with REST APIs, frameworks, and CMS such as Django, Laravel, Yii2, WP, OpenCart, CodeIgniter, etc. I am ready to complete the task. Reviews: Freelancehunt

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Hello, I am ready to take on the project, I have experience, waiting for a response.

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Good day! I specialize in developing parsers and automation. I am ready to implement a parser for LCSC.com in Python for regular collection of current "In Stock" products in XLSX, with the possibility of further support. I have experience with web scraping and large volumes of data.

Please write to me in private messages, and we will clarify the details.

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Hello!

I have reviewed your task and looked at the attached example CSV file. The task is completely clear — you need a parser for the site lcsc.com that will gather the necessary data on components and accurately reproduce the table structure you require.

Here’s how I will implement it:
I will write a reliable script in Python. If the site uses dynamic loading or protection, I will use tools to simulate a real browser to avoid blocks. The script will automatically go through categories/links, collect item numbers, prices, and other characteristics, and then generate a ready file (CSV/Excel) exactly according to your template.

The code will be clean and documented so that you can run it independently in the future. If needed, I can package everything in Docker.

… Clarifying question:
Is the parsing needed once (just to gather the database for now), or should this script run regularly to update stock and prices?

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Good day. I have familiarized myself with the website. I can write a parser that will put the data you need into an Excel table.

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Good afternoon. I can write a console program for parsing these products in Python. The attached file for some reason does not open - could you resend it in a private message?

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Hello. I have extensive experience in developing parsers. I am ready for collaboration.

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I will write a parser, host it on my resources with ongoing support. To collect such a quantity, proxies are needed, which will be included in the support. Also, the site returns no more than 5000 products at a time, so filtering is required. Please write to discuss the details.

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Hello! I will write a script tailored to your needs that will go through the pagination pages of all sections and retrieve information about the availability and prices of products.

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Hello, I am a Python developer with experience in developing parsers of varying complexity. I can complete your project quickly and efficiently. Write to me - we will discuss the details. I am ready to start working today.

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Good day, I can create a program and deliver it to you, or I can collect data upon your request. Write to me, and we will discuss.

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Hello! I have carefully studied your project and am ready to start its implementation. Let's discuss the details for the best execution.

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