{"slug": "aliexpress-scraper-returns-zero-records-on-csr-pages-from-ja-or-ko", "title": "AliExpress Scraper Returns Zero Records on CSR Pages from `ja` or `ko`", "summary": "A developer documented that the AliExpress Scraper Actor returns zero records when an AI agent requests regional storefronts such as `ja` (Japan) or `ko` (Korea), because those pages serve client-side rendered HTML that omits the `_init_data_` JSON state the Actor parses. The writeup, covering integration of the Actor as an agent tool via Apify's MCP endpoint at `https://mcp.apify.com` with the `?tools=owner/actor-name` parameter, recommends agents restrict requests to regions known to serve server-side rendered JSON, including `com`, `us`, `de`, `fr`, `es`, `it`, `nl`, `pt`, `pl`, `tr`, `ar`, `vi`, `th`, and `id`.", "body_md": "Large language models (LLMs) are increasingly capable of acting as autonomous agents, performing complex tasks by breaking them down into sub-problems and calling external tools. Exposing Apify Actors as callable tools for these agents presents specific integration challenges and opportunities, particularly around how input schemas translate into tool signatures and the predictable limits an agent will encounter.\n\nThis article details how an AI agent can invoke the [AliExpress Scraper](https://apify.com/crawlerbros/aliexpress-scraper) via Apify's Managed Cloud Platform (MCP), focusing on the critical `?tools=` configuration, the derived input schema for an agent, and the operational limitations an agent must be designed to handle for robust operation.\n\nIf an AI agent requests a regional storefront that occasionally serves a client-side rendered (CSR) page, such as `ja` or `ko`, the AliExpress Scraper Actor will return zero records. This occurs because these pages omit the `_init_data_` JSON state that the Actor relies on for parsing. For reliable data extraction, agents should prioritize regions known to consistently serve server-side rendered (SSR) JSON, such as `com`, `us`, `de`, `fr`, `es`, `it`, `nl`, `pt`, `pl`, `tr`, `ar`, `vi`, `th`, or `id`.\n\nThe `aliexpress-scraper` Actor is designed to extract structured data from AliExpress, offering various modes for querying. When integrating this Actor as an AI agent tool, the agent needs to understand not just the functionality, but also the nuances of its failure modes. A particularly sharp edge arises with certain regional storefronts. The Actor's `region` input field dictates which AliExpress subdomain to query. While many regions reliably provide server-side rendered (SSR) HTML containing embedded JSON for data extraction, some, like `ja` (Japan) or `ko` (Korea), can occasionally serve a client-side rendered (CSR) page. This means the critical `_init_data_` JSON state, which the Actor uses for parsing, is entirely absent from the initial HTML.\n\nWhen this happens, the Actor run will complete successfully, but it will yield zero records in its dataset. An AI agent, unaware of this specific limitation, might interpret this as a successful run with no matching data, rather than a parsing failure due to a rendering discrepancy. To mitigate this, an agent should be programmed to:\n\n`com`, `us`, or `de` which are explicitly documented to ship SSR JSON reliably.`autoEscalateOnBlock` carefully\nHere's how an agent might select a region, preferring reliable ones:\n\n``` php\ndef select_aliexpress_region(desired_region: str) -> str:\n    \"\"\"\n    Selects an AliExpress region, prioritizing known reliable SSR storefronts.\n    \"\"\"\n    reliable_regions = [\"com\", \"us\", \"de\", \"fr\", \"es\", \"it\", \"nl\", \"pt\", \"pl\", \"tr\", \"ar\", \"vi\", \"th\", \"id\"]\n    if desired_region in reliable_regions:\n        return desired_region\n    elif desired_region in [\"ja\", \"ko\", \"he\", \"ru\"]: # Known problematic or special cases\n        print(f\"Warning: Region '{desired_region}' may serve CSR-only pages, potentially returning zero records.\")\n        # For 'ru', special handling for language\n        if desired_region == \"ru\":\n            print(\"Note: For Russian language results, use region='com' with language='ru_RU'.\")\n            return \"com\" # Redirect internally to .com with language override\n        return desired_region # Still allow, but with warning\n    else:\n        print(f\"Unknown region '{desired_region}', defaulting to 'com'.\")\n        return \"com\"\n\n# Example agent usage\nagent_desired_region = \"ja\"\nactual_region_to_use = select_aliexpress_region(agent_desired_region)\nprint(f\"Agent will attempt to scrape region: {actual_region_to_use}\")\n```\n\nYou expose an Apify Actor as an AI agent tool by calling the Apify MCP server at `https://mcp.apify.com` and specifying the Actor using the `?tools=owner/actor-name` query parameter. This endpoint translates the Actor's input schema into a tool signature that an agent can understand and execute, provided the agent has the necessary Apify API token for authenticated calls.\n\nThe core of enabling AI agents to use Apify Actors lies in Apify's Managed Cloud Platform (MCP). The MCP server acts as an intermediary, presenting Actors as structured tools. For the `aliexpress-scraper` Actor, the endpoint `https://mcp.apify.com?tools=crawlerbros/aliexpress-scraper` is the entry point. When an agent queries this endpoint, MCP responds with a structured description of the `aliexpress-scraper` tool, derived directly from its input schema. This description includes the tool's name, a natural language description, and most critically, its parameter schema, which is a JSON Schema representation of the Actor's input.\n\nAn AI agent's orchestration logic would then parse this schema to understand what arguments (`mode`, `searchQuery`, `region`, etc.) the `aliexpress-scraper` tool expects, their types, and any constraints or default values. Executing the tool involves making a POST request to the MCP server with the appropriate `X-Apify-Api-Token` header and a JSON body corresponding to the Actor's input.\n\nHere's a simplified representation of how the `aliexpress-scraper` input schema translates into a tool signature for an agent:\n\n```\n{\n  \"name\": \"aliexpress-scraper\",\n  \"description\": \"Scrape AliExpress search results, product details, store profiles, and customer reviews. Multi-region (com / us / ru / es / fr / de / it / nl / pt / pl / ar / tr / ko / ja / vi / th / id / he), multi-currency, with sort, price, rating, and ship-from/ship-to filters.\",\n  \"input_schema\": {\n    \"type\": \"object\",\n    \"properties\": {\n      \"mode\": {\n        \"type\": \"string\",\n        \"description\": \"What to scrape. search: text-query results. byProduct: product detail by ID. byStore: store profile by ID. byReviews: customer reviews for product IDs. byUrl: parse any AliExpress\",\n        \"enum\": [\"search\", \"byProduct\", \"byStore\", \"byReviews\", \"byUrl\"],\n        \"default\": \"search\"\n      },\n      \"searchQuery\": {\n        \"type\": \"string\",\n        \"description\": \"Free-text search query, e.g. \\\"phone case\\\". Required when mode=search.\"\n      },\n      \"productIds\": {\n        \"type\": \"array\",\n        \"items\": { \"type\": \"string\" },\n        \"description\": \"AliExpress numeric product IDs (e.g. 1005010155028387).\"\n      },\n      \"region\": {\n        \"type\": \"string\",\n        \"description\": \"AliExpress regional sub-domain to query.\",\n        \"default\": \"com\"\n      },\n      \"currency\": {\n        \"type\": \"string\",\n        \"description\": \"ISO-4217 currency code. AliExpress may override it with the proxy IP's local currency.\",\n        \"default\": \"USD\"\n      },\n      \"language\": {\n        \"type\": \"string\",\n        \"description\": \"Locale that AliExpress should render text in (b_locale cookie).\",\n        \"default\": \"en_US\"\n      },\n      \"priceMin\": {\n        \"type\": \"integer\",\n        \"description\": \"Minimum price (in the selected currency). 0 disables.\",\n        \"default\": 0\n      },\n      \"maxItems\": {\n        \"type\": \"integer\",\n        \"description\": \"Hard cap on emitted records.\",\n        \"default\": 25\n      },\n      \"maxPages\": {\n        \"type\": \"integer\",\n        \"description\": \"Maximum pagination pages per search query (60 items per page).\",\n        \"default\": 3\n      }\n    },\n    \"required\": [\"mode\"]\n  }\n}\n```\n\nThis structured tool description allows the agent to dynamically construct valid requests. However, it's crucial for the agent to also understand the implications of default values versus explicitly passed values. The `prefill` values specified in the Actor's console UI are *not* applied to API calls; only the `default` values in the schema are. An agent should always construct a complete input dictionary, explicitly setting all necessary parameters, to avoid relying on implicit server-side `prefill` behavior that won't be triggered by an API call.\n\nAn AI agent should switch from synchronous to asynchronous Actor execution when a single run is expected to exceed 300 seconds. The synchronous run endpoint for Apify Actors has a hard-coded timeout of 300 seconds (5 minutes); exceeding this limit will result in an HTTP 408 response, forcing the agent to restart or abandon the task. For longer-running tasks, the agent must initiate the Actor run via a POST request to `/v2/acts/<actor>/runs` and then poll the run's status or use a webhook.\n\nAI agents, particularly when interacting with external services, need to be mindful of execution limits. For Apify Actors, a critical threshold is the 300-second (5-minute) timeout for synchronous runs. If an agent attempts to call an Actor using the synchronous endpoint and the Actor runs for longer than 300 seconds, the connection will be terminated with an HTTP 408 error. This isn't a graceful shutdown; the Actor will continue running on Apify's platform, but the agent's connection will be lost, making it impossible to retrieve the results synchronously.\n\nFor tasks that inherently take longer – such as scraping thousands of AliExpress products across many search pages, or fetching reviews for a large list of product IDs – an AI agent *must* opt for asynchronous execution. This involves:\n\n`https://api.apify.com/v2/acts/crawlerbros/aliexpress-scraper/runs` (with an API token). This returns a `runId`.` https://api.apify.com/v2/actor-runs/<runId>` to check the `status` field.`SUCCEEDED` or `FAILED`, retrieve the run's dataset items via the dataset URL provided in the run object.\nThis asynchronous pattern adds complexity but is essential for robust operation. An agent's decision-making logic should incorporate an estimate of run duration based on input parameters (e.g., `maxItems`, `maxPages`, number of `productIds`). If these parameters suggest a run might approach or exceed the 300-second threshold, the agent should proactively choose the asynchronous approach. For instance, `maxPages=3` for `mode=search` implies up to 180 items (60 items/page), which is unlikely to hit the limit. However, if `maxItems` is set to a much higher number, or `productIds` contains hundreds of entries, an asynchronous execution strategy becomes imperative.\n\n``` python\nimport requests\nimport time\n\nAPIFY_API_TOKEN = \"YOUR_APIFY_API_TOKEN\"\nACTOR_ID = \"crawlerbros/aliexpress-scraper\"\n\ndef run_aliexpress_scraper_async(run_input: dict):\n    \"\"\"\n    Initiates an asynchronous run of the AliExpress Scraper Actor and polls for its completion.\n    \"\"\"\n    print(\"Initiating asynchronous Actor run...\")\n    start_response = requests.post(\n        f\"https://api.apify.com/v2/acts/{ACTOR_ID}/runs\",\n        headers={\"Authorization\": f\"Bearer {APIFY_API_TOKEN}\"},\n        json=run_input\n    ).json()\n\n    run_id = start_response[\"data\"][\"id\"]\n    print(f\"Actor run started with ID: {run_id}\")\n\n    dataset_id = start_response[\"data\"][\"defaultDatasetId\"]\n    print(f\"Default Dataset ID: {dataset_id}\")\n\n    # Poll for run status\n    while True:\n        run_status_response = requests.get(\n            f\"https://api.apify.com/v2/actor-runs/{run_id}\",\n            headers={\"Authorization\": f\"Bearer {APIFY_API_TOKEN}\"}\n        ).json()\n        status = run_status_response[\"data\"][\"status\"]\n        print(f\"Current run status: {status}\")\n\n        if status in [\"SUCCEEDED\", \"FAILED\", \"ABORTED\"]:\n            print(f\"Run finished with status: {status}\")\n            break\n        time.sleep(10) # Wait 10 seconds before polling again\n\n    if status == \"SUCCEEDED\":\n        # Retrieve results from the dataset\n        results_url = f\"https://api.apify.com/v2/datasets/{dataset_id}/items\"\n        print(f\"Retrieving results from: {results_url}\")\n        results = requests.get(results_url, headers={\"Authorization\": f\"Bearer {APIFY_API_TOKEN}\"}).json()\n        print(f\"Retrieved {len(results)} items.\")\n        return results\n    else:\n        print(\"Actor run did not succeed.\")\n        return []\n\n# Example: A run that might exceed 300 seconds\n# The actual duration depends on network conditions, AliExpress response times, etc.\nlong_run_input = {\n  \"mode\": \"search\",\n  \"searchQuery\": \"laptop bag\",\n  \"region\": \"com\",\n  \"maxPages\": 10, # Max items could be 600, potentially a longer run\n  \"maxItems\": 500\n}\n```\n\n`maxTotalChargeUsd` parameter protect against unexpected costs?\nThe `maxTotalChargeUsd` parameter protects against unexpected costs by setting an upper limit on the monetary charge for an Actor run. When the total cost incurred by the run reaches this cap, the Actor run is terminated. This provides a crucial safeguard for AI agents operating with budget constraints, although termination is not instantaneous, and some resources may still be consumed briefly after the cap is tripped.\n\nCost control is a critical aspect of autonomous agent operation, especially when calling external APIs or Actors that incur charges. The `aliexpress-scraper` Actor, like many on Apify, charges based on specific events. To prevent an agent from inadvertently spending beyond a defined budget, the `maxTotalChargeUsd` query parameter (or `ACTOR_MAX_TOTAL_CHARGE_USD` environment variable within the Actor) is invaluable.\n\nAn AI agent, before initiating a potentially large scrape, can estimate the likely cost based on the number of expected output records and the per-result price. It can then set `maxTotalChargeUsd` to a value that reflects its allocated budget for that specific task. If, for any reason (e.g., more results found than expected, higher proxy usage), the actual cost begins to approach this limit, the Apify platform will automatically terminate the run.\n\nIt's crucial for the agent to understand that this termination is not immediate. The Actor will continue to consume resources for a brief period while it's winding down. Therefore, setting `maxTotalChargeUsd` slightly above the *absolute* hard limit can provide a small buffer. This mechanism allows for fine-grained financial control and prevents runaway costs in scenarios where an agent's logic might accidentally request an overly expansive scrape.\n\nConsider a scenario where an agent is instructed to find \"cheap phone cases\" but due to a misinterpretation, it searches for a very generic term and sets `maxItems` extremely high. Without `maxTotalChargeUsd`, this could lead to a significant bill. With it, the agent ensures that even if its logic falters, the financial impact is contained.\n\n``` python\n# Example of setting maxTotalChargeUsd for a run\nimport requests\n\nAPIFY_API_TOKEN = \"YOUR_APIFY_API_TOKEN\"\nACTOR_ID = \"crawlerbros/aliexpress-scraper\"\n\ndef run_aliexpress_scraper_with_budget(run_input: dict, max_charge_usd: float):\n    \"\"\"\n    Runs the AliExpress Scraper Actor with a maximum total charge limit.\n    \"\"\"\n    print(f\"Initiating Actor run with max charge: ${max_charge_usd}\")\n    # The maxTotalChargeUsd parameter can be added to the query string\n    start_response = requests.post(\n        f\"https://api.apify.com/v2/acts/{ACTOR_ID}/runs?maxTotalChargeUsd={max_charge_usd}\",\n        headers={\"Authorization\": f\"Bearer {APIFY_API_TOKEN}\"},\n        json=run_input\n    ).json()\n\n    # The agent would then monitor this run as in the asynchronous example\n    # and handle potential 'ABORTED' status if the budget is hit.\n    print(f\"Run started: {start_response['data']['id']}\")\n    print(\"Agent should poll run status and check for 'ABORTED' due to budget.\")\n\n# Agent wants to scrape some data but doesn't want to spend more than $5 on this particular task.\nbudget_constrained_input = {\n  \"mode\": \"search\",\n  \"searchQuery\": \"smartwatch\",\n  \"region\": \"us\",\n  \"maxItems\": 1000 # Potentially many results, but capped by budget\n}\n```\n\nThe AliExpress Scraper charges for two events: a \"result\" event at `$0.005` per single item in the default dataset, and an \"Actor Start\" event at `$0.005` per GB of memory allocated to the run. These event charges are in addition to platform usage fees for run time and memory, which are billed separately at the user's Apify plan rates.\n\nThe number of \"result\" events scales directly with `maxItems`, `maxPages`, and `maxReviewsPerProduct`, with discounts available for FREE, BRONZE, SILVER, GOLD, PLATINUM, and DIAMOND tier users.\n\nUnderstanding the cost structure is crucial for any AI agent that aims to operate efficiently and predictably. The `aliexpress-scraper` Actor uses a PAY_PER_EVENT pricing model.\n\nHere's a breakdown:\n\n`$0.005`. This is the most significant variable cost.\n`mode=search`: The `maxItems` and `maxPages` inputs directly multiply the number of potential result events. Since each page can yield up to 60 items, `maxPages=3` could result in up to 180 product records, each triggering a result event.`mode=byProduct`: Each ID in `productIds` typically fetches one product record.`mode=byReviews`: Each ID in `maxReviewsPerProduct` review records. If `enrichReviews` is true for An intelligent agent can use these details to make informed decisions. For example, if the goal is to get a brief overview of products, setting `maxItems` to a low number significantly reduces the \"result\" event cost. If only product details are needed, `mode=byProduct` with a specific list of `productIds` might be more cost-effective than a broad `search` query followed by post-processing.\n\n``` python\ndef estimate_aliexpress_scraper_event_cost(run_input: dict, user_tier: str = \"FREE\") -> float:\n    \"\"\"\n    Estimates the event-based cost for an AliExpress Scraper run.\n    Does not account for platform usage.\n    \"\"\"\n    result_price_per_item = {\n        \"FREE\": 0.005,\n        \"BRONZE\": 0.00433,\n        \"SILVER\": 0.00367,\n        \"GOLD\": 0.003,\n        \"PLATINUM\": 0.003,\n        \"DIAMOND\": 0.003\n    }.get(user_tier.upper(), 0.005) # Default to FREE tier if unknown\n\n    estimated_results = 0\n    if run_input.get(\"mode\") == \"search\":\n        max_items = run_input.get(\"maxItems\", 25)\n        max_pages = run_input.get(\"maxPages\", 3)\n        # Assuming 60 items per page max, but capped by maxItems\n        estimated_products = min(max_items, max_pages * 60)\n        estimated_results += estimated_products\n\n        if run_input.get(\"enrichReviews\", False):\n            max_reviews_per_product = run_input.get(\"maxReviewsPerProduct\", 0)\n            if max_reviews_per_product > 0:\n                estimated_results += estimated_products * max_reviews_per_product\n\n    elif run_input.get(\"mode\") == \"byProduct\":\n        estimated_results += len(run_input.get(\"productIds\", []))\n\n    elif run_input.get(\"mode\") == \"byReviews\":\n        max_reviews_per_product = run_input.get(\"maxReviewsPerProduct\", 0)\n        if max_reviews_per_product > 0:\n            estimated_results += len(run_input.get(\"productIds\", [])) * max_reviews_per_product\n\n    elif run_input.get(\"mode\") == \"byStore\":\n        estimated_results += len(run_input.get(\"storeIds\", []))\n\n    elif run_input.get(\"mode\") == \"byUrl\":\n        estimated_results += len(run_input.get(\"urls\", [])) # Simplified assumption, depends on URL type\n\n    # Actor Start cost (assuming 1GB memory for simplicity, minimum 1 event)\n    actor_start_cost = 0.005\n\n    total_event_cost = (estimated_results * result_price_per_item) + actor_start_cost\n    return total_event_cost\n\n# Example agent cost estimation\nexample_input_search = {\n  \"mode\": \"search\",\n  \"searchQuery\": \"bluetooth speaker\",\n  \"maxItems\": 100,\n  \"maxPages\": 2,\n  \"enrichReviews\": True,\n  \"maxReviewsPerProduct\": 5\n}\n```\n\nAn AI agent using the AliExpress Scraper must account for several limitations: client-side rendering issues for product details and some regional storefronts (potentially leading to empty records), best-effort currency localization (AliExpress may override requested currency based on proxy IP), and the absence of variation/SKU details or shipping costs due to API call signing requirements. Aggressive crawls can also be rate-limited, requiring explicit proxy usage.\n\nBeyond the cost structure and execution model, an AI agent needs a deep understanding of the `aliexpress-scraper`'s functional limitations to avoid generating incorrect assumptions or making repeated, futile requests. These limitations are intrinsic to how AliExpress renders its content and how the Actor can access it:\n\n`aliexpress-scraper` primarily relies on server-side rendered (SSR) JSON embedded in the HTML. This means:\n`byProduct` yields less detail.`ja`, `ko`, `he`) sometimes serve CSR-only pages, causing runs to return zero records. An agent should be programmed to detect this failure mode and potentially re-attempt with a more reliable region or `language` setting (e.g., `language=ru_RU` with `region=com` for Russian content).`currency` input is sent, AliExpress might override it based on the proxy IP's geolocation. For deterministic currency results, an agent must explicitly enable `useProxy=true` and configure a residential proxy in the desired country, incurring additional proxy costs and potentially shorter proxy session lifespans (~30 minutes for residential).`true`) helps by switching to residential proxies, but for sustained, high-volume scraping, an agent should proactively enable Unnamed storage expirations significantly impact data retention for AI agents, as data from default datasets, request queues, and key-value stores from older runs will be automatically deleted. On the free Apify plan, only the 10 most recent runs are retained for four months. To ensure long-term data persistence, AI agents must be configured to use *named* storages, which are exempt from automatic deletion.\n\nFor AI agents managing ongoing data collection or requiring access to historical data, the Apify platform's storage policies are a critical design consideration. By default, Actor runs create \"unnamed\" storages. This includes the default dataset where the `aliexpress-scraper` outputs its records, any request queues it uses, and temporary key-value stores. These unnamed storages are subject to expiration. Specifically, on the free plan, only the data from the 10 most recent runs is retained, and even then, only for four months. Older data, or data from runs beyond the 10-run limit, is automatically purged.\n\nThis has direct implications for an AI agent's operational strategy:\n\n`output/datasetId` (or `requestQueueId`, `keyValueStoreId`) with a An agent that periodically scrapes AliExpress data for market analysis, for example, would ideally create a named dataset (e.g., `my-product-trends-2026`) and instruct the `aliexpress-scraper` to output its data there for every run. This ensures that even if hundreds of runs occur over months, the collected data remains accessible.\n\n``` python\nimport requests\n\nAPIFY_API_TOKEN = \"YOUR_APIFY_API_TOKEN\"\nACTOR_ID = \"crawlerbros/aliexpress-scraper\"\n\ndef run_aliexpress_scraper_with_named_dataset(run_input: dict, dataset_name: str):\n    \"\"\"\n    Initiates an Actor run, pushing results to a named dataset for persistence.\n    The dataset will be created if it doesn't exist.\n    \"\"\"\n    print(f\"Ensuring named dataset '{dataset_name}' exists or is created...\")\n    # This call creates or retrieves the named dataset\n    dataset_info = requests.post(\n        f\"https://api.apify.com/v2/datasets?token={APIFY_API_TOKEN}\",\n        json={\"name\": dataset_name}\n    ).json()\n    named_dataset_id = dataset_info[\"data\"][\"id\"]\n    print(f\"Using dataset ID: {named_dataset_id}\")\n\n    # Now, initiate the Actor run, explicitly specifying the named dataset\n    # The 'output/datasetId' input field is for this purpose\n    run_input_with_dataset = run_input.copy()\n    run_input_with_dataset[\"output/datasetId\"] = named_dataset_id\n\n    print(f\"Initiating Actor run with output to named dataset '{dataset_name}'...\")\n    start_response = requests.post(\n        f\"https://api.apify.com/v2/acts/{ACTOR_ID}/runs\",\n        headers={\"Authorization\": f\"Bearer {APIFY_API_TOKEN}\"},\n        json=run_input_with_dataset\n    ).json()\n\n    run_id = start_response[\"data\"][\"id\"]\n    print(f\"Actor run started with ID: {run_id}\")\n    # The agent would then poll this run and retrieve results from the named dataset\n    # using its ID, instead of relying on the defaultDatasetId from the run object.\n\n# Example: An agent wanting to track \"phone case\" prices over time\ntracking_input = {\n  \"mode\": \"search\",\n  \"searchQuery\": \"phone case\",\n  \"region\": \"com\",\n  \"maxItems\": 10\n}\n```\n\nProxy session limitations can affect long-running AliExpress Scraper tasks because datacenter proxies persist for 26 hours, while residential proxies typically last around 30 minutes. If an AI agent uses residential proxies for sustained scraping due to rate limiting or currency localization needs, it must be prepared to handle frequent proxy rotation and potential session drops during extended runs.\n\nWhen an AI agent uses the `aliexpress-scraper` for tasks that involve a significant number of requests or require specific IP geo-locations, the choice and management of proxies become crucial. AliExpress can rate-limit aggressive crawls, and `autoEscalateOnBlock` provides a fallback to residential proxies. However, there are important distinctions in proxy session longevity that an agent must consider:\n\nIf an AI agent enables `useProxy=true` with a residential proxy group from the outset, or if `autoEscalateOnBlock` triggers the use of residential proxies, the agent's logic needs to be robust enough to handle these proxy rotations. While the Actor itself is designed to manage proxy changes internally, the agent should be aware that the egress IP address used for requests will change often, which can impact consistent currency localization if AliExpress relies heavily on the IP's geolocation. For truly deterministic currency, the agent must ensure a residential proxy from the *exact* target country is selected, and acknowledge that even then, the underlying proxy IP will rotate.\n\nThis limitation means that an agent cannot assume a stable IP identity for the duration of a multi-hour scrape if residential proxies are involved. It might need to implement logic to detect if proxy-dependent features (like specific currency localization) become inconsistent and potentially adjust its strategy, such as restarting segments of the scrape or issuing warnings.\n\nChecked against the Actor's input schema and Apify docs on 2026-10-08.\n\nThe Actor's README is the source of truth for its inputs, outputs and limits. Need a hand wiring this into your stack? Email [info@crawlerbros.com](mailto:info@crawlerbros.com)", "url": "https://wpnews.pro/news/aliexpress-scraper-returns-zero-records-on-csr-pages-from-ja-or-ko", "canonical_source": "https://dev.to/crawlerbros/aliexpress-scraper-returns-zero-records-on-csr-pages-from-ja-or-ko-3l6l", "published_at": "2026-10-08 13:43:54+00:00", "updated_at": "2026-10-08 13:49:53.414634+00:00", "lang": "en", "topics": ["ai-agents", "ai-tools", "agent-protocols", "developer-tools"], "entities": ["AliExpress", "Apify", "Apify MCP", "AliExpress Scraper"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/aliexpress-scraper-returns-zero-records-on-csr-pages-from-ja-or-ko", "markdown": "https://wpnews.pro/news/aliexpress-scraper-returns-zero-records-on-csr-pages-from-ja-or-ko.md", "text": "https://wpnews.pro/news/aliexpress-scraper-returns-zero-records-on-csr-pages-from-ja-or-ko.txt", "jsonld": "https://wpnews.pro/news/aliexpress-scraper-returns-zero-records-on-csr-pages-from-ja-or-ko.jsonld"}}