Parsing YML Feeds for Import into 1C-Bitrix

Parsing YML Feeds for Import into 1C-Bitrix

The supplier sent a YML file with 50,000 products — and you need to load them into Bitrix over the weekend. Standard tools fail: encoding issues, missing categories, offer duplicates, and image timeouts. We automate this process so you can forget about manual import. With 10+ years of Bitrix experience, we've processed over 500,000 products via YML feeds and have proven solutions that save up to 70% time on each import. Our company has been on the market for over 10 years, completed 50+ integrations, and helped clients save an average of $2,000 per month on manual labor.

Why YML is Better Than Excel for Import

Excel files from suppliers often contain merged cells, macros, non-standard date and currency formats. YML (Yandex Market Language specification) is a strict XML format, documented and easily parsed. It supports category hierarchy, multiple images, characteristics, and availability flags. Unlike Excel, YML requires no manual transformations and allows full automation of import.

Structure of a YML Feed

YML is an XML format for product feeds from Yandex. Suppliers often provide YML: the structure is documented, and the data is sufficient for a full import. It's simpler than parsing arbitrary Excel, but has its own nuances.

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE yml_catalog SYSTEM "shops.dtd">
<yml_catalog date="2025-03-15 10:30">
  <shop>
    <name>Shop Name</name>
    <currencies>
      <currency id="RUR" rate="1"/>
    </currencies>
    <categories>
      <category id="1">Electronics</category>
      <category id="2" parentId="1">Smartphones</category>
    </categories>
    <offers>
      <offer id="12345" available="true">
        <price>29990</price>
        <currencyId>RUR</currencyId>
        <categoryId>2</categoryId>
        <picture>https://example.com/img/12345.jpg</picture>
        <name>Samsung Galaxy A54 Smartphone</name>
        <vendor>Samsung</vendor>
        <vendorCode>SM-A546</vendorCode>
        <description>Product description</description>
        <param name="Color">Black</param>
        <param name="Storage">128 GB</param>
      </offer>
    </offers>
  </shop>
</yml_catalog>

Key elements: offer id — unique identifier (analogous to XML_ID in Bitrix), available — availability flag, categoryId — reference to category, param — arbitrary characteristics.

Parsing Categories and Building the Tree

Categories in YML form a hierarchy via the parentId attribute. During import, you need to create the corresponding section structure in the infoblock. Algorithm:

1. Load all categories into an associative array [id => ['name' => ..., 'parentId' => ...]].
2. Recursively build the tree.
3. For each category: find the section by XML_ID = 'yml_cat_{id}' or create a new one.
4. Save the mapping [yml_id => bitrix_section_id].

$sectionId = CIBlockSection::GetList(
    [],
    ['IBLOCK_ID' => $iblockId, 'XML_ID' => 'yml_cat_' . $cat['id']],
    false,
    ['ID']
)->Fetch()['ID'];

if (!$sectionId) {
    $bs = new CIBlockSection();
    $sectionId = $bs->Add([
        'IBLOCK_ID' => $iblockId,
        'XML_ID'    => 'yml_cat_' . $cat['id'],
        'NAME'      => $cat['name'],
        'IBLOCK_SECTION_ID' => $parentBitrixId,
        'ACTIVE'    => 'Y',
    ]);
}

Importing Products (Offers) and Working with Images

The main processing loop — iterating over all offers in the XML. For each, an infoblock element is created or updated. Special attention goes to image loading: with a feed of 10,000 products, that's 10,000 HTTP requests. We use URL hash checking and parallel loading via agents to reduce time by 3–5 times.

foreach ($xml->shop->offers->offer as $offer) {
    $xmlId = (string)$offer['id'];
    $available = (string)$offer['available'] === 'true';

    $params = [];
    foreach ($offer->param as $param) {
        $params[(string)$param['name']] = (string)$param;
    }

    $fields = [
        'IBLOCK_ID'         => $iblockId,
        'NAME'              => (string)$offer->name,
        'XML_ID'            => $xmlId,
        'ACTIVE'            => $available ? 'Y' : 'N',
        'IBLOCK_SECTION_ID' => $sectionMap[(string)$offer->categoryId] ?? null,
        'PROPERTY_VALUES'   => [
            'VENDOR'  => (string)$offer->vendor,
            'ARTICLE' => (string)$offer->vendorCode,
        ],
    ];

    $existId = getElementByXmlId($xmlId, $iblockId);
    $el = new CIBlockElement();
    if ($existId) {
        $el->Update($existId, $fields);
    } else {
        $el->Add($fields);
    }
    updatePrice($existId ?: $el->LAST_ID, (float)$offer->price);
}

What Offer Types Does YML Support?

YML distinguishes several types, each with its own mandatory fields:

In practice, 80% of suppliers use the simple type. Specific types require additional property mapping.

How to Speed Up Import of Products with Images?

Images are the biggest bottleneck. Our approach: before downloading, compare the URL hash with the previous import (stored in a property). If the URL hasn't changed, skip download. For new products — background agents with a limit of 5 concurrent threads. This saves up to 70% time on a batch of 50,000 products.

Typical Errors in Parsing and How to Avoid Them

• Encoding problems — YML comes in UTF-8, but Bitrix may expect windows-1251. Solution: convert using iconv() before parsing.
• Missing categories — when YML specifies a categoryId that doesn't exist in the category block. Solution: create missing categories with a note "Temporary".
• Offer duplicates — multiple records with the same id. Solution: use XML_ID and check existence before adding.

Case Study

One of our clients, an electronics online store with 30,000 products from 5 suppliers, faced the main problem: different category schemas (one had 2-level nesting, another 4-level). We solved it with an intermediate mapping: a dictionary table in an HL-block. In 4 days, we developed a universal wrapper that now updates the catalog daily via Cron. The client saved $2,500 monthly on manual data entry.

What's Included

Development Timelines

We develop both simple integrations and complex multi-feeds. Want to set up YML parsing for your store? Contact us — we'll evaluate your project in 1 day. We guarantee quality and deadlines. Order YML parsing — and forget about manual import forever.

CommerceML: Why Standard Exchange Is Both a Lifesaver and a Trap

Standard exchange via CommerceML 2.0 on typical "Trade Management" or "Comprehensive Automation" can be set up in a day or two. Products, prices, stock, orders—all via XML files on a schedule. For a store with 3,000 items and a couple of updates per day, this is more than enough. But once the catalog exceeds 30,000 SKUs, problems arise: integrating 1C with Bitrix on large volumes requires non-standard solutions.

Why does CommerceML slow down with catalogs over 100,000 items?

bitrix_1c_exchange.php generates XML on the Bitrix side, and 1C retrieves and parses it. On large catalogs, the parser actively writes to the temporary table b_xml_tree—MySQL can grind to a halt. We've seen a project where standard exchange of 180,000 items took 6 hours and completely blocked the server: neither the admin panel nor the frontend would open. The solution is incremental exchange. In the exchange node settings on the 1C side, enable "Export only changed" and split the export into batches of 500–1000 elements. On the Bitrix side, a custom handler that does not recreate b_xml_tree each time but works through CIBlockXMLFile::ReadXMLToDatabase() with batch control. A catalog of 200,000 SKUs updates in 8–12 minutes.

Another pitfall is EXTERNAL_ID. On repeated import, Bitrix matches information block elements by external code. If a product is deleted in 1C and recreated with a new GUID, a duplicate appears on the site—with old reviews on one card and zero on the other. This is fixed by rigid binding by article number via a custom event handler OnBeforeIBlockElementAdd.

How to avoid duplicates during repeated import?

We bind products not by GUID but by article number. Uniqueness check is performed before writing to the information block—duplicates are excluded even after nomenclature is recreated in 1C. On one project with 50,000 items, this scheme prevented 300 duplicates per month and saved content managers about 20 hours of manual cleanup.

Custom 1C Configurations: When CommerceML Falls Short

"We have a standard configuration"—says every second client, and then we open the database and see 200 custom processing routines, renamed attributes, and custom sales documents. CommerceML works with a fixed XML structure. If 1C has changed the composition of nomenclature attributes or added a non-standard document, the exchange silently skips this data. Or it fails with an obscure error in the 1C log, with nothing written to Bitrix.

In such cases, we implement custom export. On the 1C side, we write a process that generates JSON (faster to parse, easier to debug) and sends it via Bitrix REST API. Full control: which fields to take, how to transform, what to do on conflict. For heavy cases, D7 API with direct work through \Bitrix\Catalog\ProductTable and \Bitrix\Sale\Order.

What are the key steps to set up 1C integration?

Custom REST is justified when:

• Non-standard nomenclature attributes;
• Multiple price types (retail, wholesale, dealer, promotional, regional, currency)—standard exchange sends only one type;
• Multi-warehouse with different stock levels and need to select a warehouse on the site.

Prices, Stock, and Multi-Warehouse

Standard exchange can transfer one price type. In reality, there may be 15: each with its own buyer group and priority. Mapping between 1C price groups and Bitrix user groups is a separate engineering challenge. Especially when discounts overlap and you need to determine which price wins.

Multi-warehouse adds another layer: product is in stock in Moscow, out of stock in St. Petersburg, and "on order" in Novosibirsk. The site must show availability per location, allow selection of pickup points, and calculate shipping from the nearest warehouse where the product is physically available. The standard Bitrix warehouse module (catalog.store) handles display, but we write the "which warehouse to ship from" logic separately. For one manufacturing holding, we implemented a custom stock aggregator that calculated balance across 8 warehouses in 2 seconds—reducing shipping errors by 80%.

Orders and Document Flow

An order from the site goes to 1C, a sales document is created, goods are reserved. Statuses come back. The main nuance is partial shipment: the client ordered 5 items, 3 are in stock, 2 will arrive in a week. 1C creates two sales documents. Bitrix out of the box cannot split one order into several shipments—we extend the OnSaleOrderSaved handler to create child orders and synchronize statuses for each.

Documents in the personal account—invoices, acts, waybills from 1C—are served via REST; PDF is generated on the 1C side and cached on CDN. The buyer downloads not from 1C directly (that would kill the server) but from cache.

Batch import with portion control reduces MySQL load and prevents locks (source: Wikipedia).

Monitoring: Not "Set and Forget"

Exchange can silently break: the script ran, no errors in log, but 200 products didn't update due to invalid UTF-8 in the name. Or 1C changed the date format in an update—all prices came in as zero.

Minimum set we install on every project:

• Telegram alert if exchange time increases 3+ times from average.
• Stock discrepancy check: script compares b_catalog_product.QUANTITY with what 1C provides, and alerts when delta exceeds 5%.
• Dashboard: last sync, number of processed items, queue, errors.

For high-load projects, we add async queues on Redis or RabbitMQ. Exchange does not block the web server, data is not lost during temporary 1C outages. On one online store with 2 million orders per year, we implemented this scheme—recovery time after failures dropped from 3 hours to 10 minutes.

Linking with Bitrix24 for Document Flow Automation

If besides the site there is a corporate portal on Bitrix24, we link it too. Counterparties from CRM go to 1C, invoices from 1C appear in deal cards. The manager sees accounts receivable and mutual settlements without switching windows. Deal closed—documents generated automatically.

Payment received in 1C → logistician gets a task for shipment in Bitrix24. Goods shipped → manager sees notification. Automatic tasks based on events from 1C—via Bitrix24 REST API webhooks. This link reduces manual entry by 70% and eliminates forgotten shipments.

How We Set Up Integration: Step-by-Step Process

1. Audit of 1C Configuration. Review the structure of directories, documents, attributes. Identify custom modifications. Assess data volume (number of SKUs, orders, warehouses).
2. Design Exchange Schema. Agree on data set: products, prices, stock, orders, documents. Determine sync interval and mechanism—CommerceML or custom REST.
3. Configure Standard Exchange. Set up CommerceML, batch mode, binding by article. Verify data transfer correctness on a test catalog.
4. Extended Integration. For complex configurations, write custom handlers on both 1C and Bitrix sides. Incorporate multi-warehouse, multiple prices, partial shipment.
5. Monitoring and Warranty. Set up alerts, dashboard, documentation. Train operators. After launch, warranty support.

Timelines and What's Included

Work results include: documented exchange schema, configured synchronization scenarios, monitoring dashboard, operator training, and warranty support after launch. Pricing is calculated individually—it depends on the complexity of the 1C configuration, catalog size, and required automation level. We'll evaluate your project in 1 day—write to us, let's discuss. Order integration and get stable exchange in 1–2 weeks.

We have completed over 50 1C integrations for online stores and manufacturing companies. The team's average experience is 7 years, and we have certified 1C-Bitrix specialists. Our experience ensures that the exchange won't break in the first month and will run stably for years. For example, on a project with a catalog of 50,000 items, automation of exchange saved the client significant operational costs annually.

Contact us for a free audit of your 1C configuration—we'll find bottlenecks and offer the optimal solution.