SolriXML: Rays of light in the dark forest of XML data

In the era of big data, working with huge XML files often becomes a real challenge for developers and analysts. Imagine a giant XML file containing thousands or even millions of records about the products of your online store. This file includes everything: from names and prices to detailed descriptions and characteristics of each product. Processing such a volume of data manually is not only laborious but also fraught with errors.

In this article, I will tell you how SolriXML automates the processing of XML files, transforming complex data structures into user-friendly formats. When it comes to huge volumes of data in XML, processing efficiency becomes a key success factor in the world of e-commerce.

To split such files into parts, traditional processing tools may be ineffective, and operations are almost always labor-intensive and resource-intensive. Often, a developer may need not only to split the file into parts but also to convert its content into another format, such as CSV. SolriXML offers a solution to these problems, providing fast and efficient processing of large XML files.

🛒 Meeting with e-commerce giants

Working for large marketplaces, I often encountered problems with data implementation in their systems. This usually meant working with tabular data - CSV files with delimiters.

But here's what's interesting: many companies, especially from the small and medium business sector, sent their feeds as links to XML files. And, you know, for them, it turned out to be a fairly quick and convenient way to transfer information. Especially when working with large databases seemed too difficult a task.

Why XML?

1. Data transfer speed

2. Convenience for small companies

3. Flexibility in structuring information

However, this created certain difficulties. Imagine: on one side we have marketplaces expecting neat CSV tables, and on the other - suppliers with their XML files.

My task was to establish effective "communication" between these two formats. It was necessary to ensure a smooth flow of data while preserving all important information.

This situation prompted me to create a tool capable of effectively converting XML to CSV, taking into account all the nuances of both formats.
This experience showed me how important it is to be able to adapt to different data formats in the world of e-commerce. And, more importantly, how the right approach to data processing can significantly simplify the lives of both marketplaces and their suppliers.

However, this approach creates a number of additional difficulties:

🚧 The problem of large XML data

Traditional methods of processing XML files face a number of problems when working with large amounts of data:

1. 🧠 High memory consumption: Loading the entire XML file into memory can lead to its overflow.

2. 🐢 Slow processing: Parsing large XML files takes a lot of time.

3. 🔍 Data extraction complexity: Extracting specific information from a huge XML can be challenging.

4. 🔀 Formatting difficulties: Converting XML to other formats, such as CSV, for further analysis can be a complex process.

🌟 SolriXML: Solution for efficient XML processing

SolriXML offers an innovative approach to solving these problems. Our tool allows:

• 📊 Splitting large XML files into manageable parts: This reduces memory load and speeds up processing. SolriXML uses smart algorithms for data segmentation, ensuring efficient use of resources even when working with gigantic XML files.

• 🔄 Automatically convert XML to CSV: Simplifies further data analysis in popular tools such as Excel or Python pandas. Our system maintains the data structure, ensuring ease of use in various analytical platforms.

• ⚡ Asynchronously process data: Increases the speed of working with large volumes of information. SolriXML uses multithreading and asynchronous operations, which allows for maximum efficient use of computing resources and significantly reduces processing time.

• 🎯 Extract specific data: Allows you to select only the necessary elements from the XML structure. This is especially useful when you need only part of the information from a large XML file, saving time and resources on processing unnecessary data.

• 🔍 Intelligent search and filtering: SolriXML provides powerful tools for searching and filtering data within XML structures, allowing you to quickly find the information you need without having to load the entire file into memory.

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• 📈 Performance optimization: Our solution is constantly being improved to achieve maximum efficiency. We use advanced optimization techniques to ensure high performance even when working with the most complex and voluminous XML data.

SolriXML not only solves the problems of processing large XML files, but also opens up new opportunities for working with data, increasing the efficiency and productivity of your team.

💼 Practical Application

Suppose you have an XML file with information about thousands of products. With SolriXML, you can easily process this data:

1. 🔗 Specify the XML link:
   Just paste the URL of your XML file into the input field.

2. 📤 Upload the file (optional):
   If the XML file is on your device, you can upload it directly through the upload form.

3. ⚙️ Configure processing:
   Select the preferred CSV delimiter from the dropdown menu.

4. ▶️ Start processing:
   Click the "Process" button to start parsing the XML and converting it to CSV.

5. 📥 Get the result:
   After processing is complete, you will receive a CSV file for download with all the extracted data.

This optimized process not only saves you time, but also significantly simplifies further work with the data, whether it is importing into a database, analyzing in spreadsheets, or processing with scripts.

🚀 Additional features:

• The tool automatically processes category hierarchies, creating a full category path for each product.

• It removes HTML tags from descriptions, providing you with clean, readable text.

• The resulting CSV includes all product parameters (characteristics), making it complete and ready for analysis.

• API for integration with other systems and process automation.

Using SolriXML, you can quickly convert complex product XML feeds into easily manageable CSV files, making your data processing tasks much more efficient.

💡 Tip: Using SolriXML is especially effective for regular processing of large XML files, such as weekly product catalog updates.

Code example:

import os
import aiohttp
import asyncio
import chardet

### Asynchronous function to fetch and decode data from URL
async def fetch_url(link_url):
    async with aiohttp.ClientSession() as session:
        async with session.get(link_url) as response:
            response.raise_for_status()  ### Check for successful request
            raw_data = await response.read()
            detected_encoding = chardet.detect(raw_data)['encoding']  ### Determine encoding
            return raw_data.decode(detected_encoding)

### Asynchronous function to split XML into parts
async def split_xml(xml_data, chunk_size):
    root = ET.fromstring(xml_data)
    offers = root.findall('.//offer')

    for i in range(0, len(offers), chunk_size):
        chunked_offers = offers[i:i + chunk_size]
        chunk_root = ET.Element(root.tag, root.attrib)
        shop = ET.SubElement(chunk_root, 'shop')
        for offer in chunked_offers:
            shop.append(offer)
        yield ET.tostring(chunk_root, encoding='unicode', method='xml')

### Asynchronous function to process link and save data to CSV
async def process_link(link_url):
    try:
        xml_data = await fetch_url(link_url)  ### Fetch XML data
        chunk_size = 100
        tasks = []

        async for chunk in split_xml(xml_data, chunk_size):
            task = process_chunk(chunk)  ### Process each part
            tasks.append(task)

        results = await asyncio.gather(*tasks)  ### Asynchronous processing of all parts
        combined_data = {"offers": [], "categories": {}, "category_parents": {}}

        for result in results:
            if result:
                combined_data["offers"].extend(result["offers"])
                combined_data["categories"].update(result["categories"])
                combined_data["category_parents"].update(result["category_parents"])

        ### Save combined data to CSV file
        save_path = "data_files"
        os.makedirs(save_path, exist_ok=True)
        domain_name = urlparse(link_url).netloc.replace("www.", "")
        safe_filename = domain_name.replace(".", "_")
        unique_filename = f"{safe_filename}.csv"
        file_path = os.path.join(save_path, unique_filename)

        category_names = set()
        for row in combined_data["offers"]:
            category_names.update(row.keys())

        with open(file_path, 'w', newline='', encoding='utf-8-sig') as file:
            writer = csv.DictWriter(file, fieldnames=sorted(category_names), delimiter=';')
            writer.writeheader()
            for offer in combined_data["offers"]:
                writer.writerow(offer)

        return file_path  ### Return path to saved file
    except Exception as e:
        print(f"An error occurred: {str(e)}")
        return None

🔗 Integration with your systems via API

SolriXML provides a powerful API that allows you to easily integrate XML processing functionality into your existing systems and workflows. Here are some examples of how you can use the SolriXML API:

1. 🔄 Automatic processing of XML feeds: Set up your systems to automatically send XML files for processing via the SolriXML API. This is especially useful for regularly updated product catalogs or data.

2. ⚡ Real-time results: Use the API to track the processing status and get results immediately after the conversion is complete.

3. 🔗 Integration with CRM and ERP systems: Automate the import of processed data into your CRM or ERP systems, ensuring the relevance of product information.

4. 🖥️ Creating custom dashboards: Develop your own interfaces to manage the XML processing process using the SolriXML API.

5. 📚 Mass file processing: Use the API to process multiple XML files at once, which is ideal for large catalogs or multiple data sources.

🔒 Security and Privacy

When using SolriXML, the security of your data is our top priority. We ensure:

1. Data encryption

   • In transit: All data transmitted between your device and our servers is protected by TLS 1.3, ensuring maximum security during transport.

   • At rest: We use AES-256 to encrypt data at rest, ensuring that even in the event of unauthorized access to the servers, your information remains protected.

🚀 Future plans: Revolutionizing data processing for marketplaces

💡 Imagine: a system that not only processes data but anticipates business needs!

When I think about the future of SolriXML, I see something much more than just a tool for processing XML files. In my vision, SolriXML evolves into a fully automated data processing ecosystem.

Intelligent categorization and adaptation of products

My goal is to develop a system capable of:

1. Automation on a new level
   Imagine a system where the role of humans is minimized. Operators only set key parameters on an intuitive control panel, and the system does the rest.

2. Optimization of human resources
   Currently, dozens of employees are often involved in data processing. In the future, with SolriXML, these people will be able to become operators of a highly efficient system, directing their skills to more strategic tasks.

3. Scalability and flexibility
   The ecosystem will be able to process huge volumes of data, easily adapting to various formats and structures without requiring constant developer intervention.

4. Intelligent processing
   The implementation of machine learning elements will allow the system to independently optimize data processing processes, learn from past experiences, and anticipate potential problems.

💡 This is an ambitious vision, but I am confident that it is achievable!

🔬 Technologies that make this possible

Our system is based on advanced natural language processing technologies:

TF-IDF (Term Frequency-Inverse Document Frequency)

This technology allows determining the importance of words in the context of product descriptions, which is critical for accurate categorization and matching of products.

Learn more about TF-IDF

Cosine Similarity

It is used to determine the semantic proximity between products and categories, ensuring accurate matching even with differences in wording.

Learn more about cosine similarity

SpaCy

This natural language processing library helps us analyze the structure and meaning of product descriptions, which is critical for generating high-quality and relevant texts.

Official SpaCy documentation

These technologies, combined with our expertise and innovative approach, allow us to create truly revolutionary solutions for data processing in the e-commerce sector.

Current Status and Challenges

I have already achieved significant progress:

• The full data processing cycle has been implemented in test versions.

• The algorithms show high accuracy in matching and generating descriptions.

However, I face a serious challenge: processing large volumes of data requires significant computational resources. Currently, this limits the ability to provide full functionality in the web version of SolriXML.

I am actively working on optimizing algorithms and looking for opportunities to scale the infrastructure to make these advanced capabilities available to all SolriXML users in the near future.

🎉 Conclusion

I sincerely thank you for taking the time to read this article about SolriXML. Your interest in the project inspires me to further develop and improve this tool.

I created SolriXML with those in mind who face the challenges of processing large amounts of data for marketplaces daily. I hope this web service will become a reliable assistant in your work, significantly simplifying and speeding up processes that previously took a lot of time and resources.

It is important to note: At the moment, you can process files completely free of charge without any restrictions! This gives you the opportunity to fully appreciate the capabilities of SolriXML and understand how useful it can be in your activities.

If you find that SolriXML really helps you and your business, and if you care about the fate of this project, I would be extremely grateful for any support.

Your contribution, no matter how modest, will help me continue to work on improving the service, expanding its capabilities, and ensuring its availability to everyone who needs it.
You can support the development of the project here:
🤝 Support the project

P.S.
Your opinion and feedback are extremely important to me. If you have any questions about the service, ideas for improving functionality, or encounter any problems, please do not hesitate to contact me. I am always open to dialogue and ready to listen to your suggestions. Your experience with SolriXML can help make it even better!