The YouTube Data API v3 answers most questions about a video, a channel or a comment thread. A YouTube scraper covers the rest, and we tell you which half you are paying for before you sign.
ScrapeIt builds the collector, runs it on our own infrastructure and repairs it when the platform moves. Anti-bot handling, proxy rotation and CAPTCHA solving are part of the managed service, and they matter here because YouTube meets automated clients with a bot check before it releases playback, and because one address cannot hold a steady rate across markets.
We take the API route wherever the API covers a field, collect pages only for what it caps or omits, and merge both into one file so you never see the seam. A sample extract comes before the full run, so field names and coverage can be checked against what you expected. After sign off we run to your schedule, hourly through monthly, and watch for layout and endpoint changes so a YouTube data feed does not quietly go stale. Delivery is CSV, JSON, XLSX or an endpoint you call, pushed to S3, SFTP or your warehouse.
A single video object carries more than buyers expect. The field names below are the platform's own.
Comments are a separate object with their own paging, ordered by time or relevance, filterable by search term, each thread carrying its reply set.
YouTube is not one catalogue. Trending charts are computed per country, are not personalized, and show one ranking to everyone in that market, which is why a chart can fill with videos in a language the viewer cannot read. They refresh roughly every half hour and split by category, with separate lists for music videos, movie trailers and gaming. Ranking leans on how fast views are climbing rather than on the raw total, and views bought through ads are excluded from that measurement, so the day's most watched clip often is not first.
Availability differs the same way. A video record can allow or block an explicit list of ISO country codes; a channel record carries the set of markets where it can be seen at all, a list of 249 codes. Category lists are themselves per country, so a category present in one market is missing in another, while interface language and content region are separate settings that both change what comes back.
There is a priced surface as well. YouTube Premium plans are published per market in local currency, with monthly, annual, family and lite tiers on separate pages, so YouTube price monitoring across countries is a real product feed rather than a metaphor.
Counting rules move too. Shorts views changed in March 2025 to count on play or replay, and from August 2026 the same rule reaches every format on a channel. A series spanning those dates is not comparable end to end unless someone recorded the break, which a stored feed catches and a one-off pull does not. Comments and their authors we treat as a data type only: we do not build named person profiles or contact lists.
YouTube is built on four object types, each with one identifier. A video is an eleven character ID that appears in every URL form the platform uses: the watch page, the youtu.be short link, the /shorts/ path for vertical video and the /embed/ player. A channel is a twenty four character ID beginning with UC, and every channel also carries a human readable handle that resolves to the same object. A playlist ID begins with PL, and one playlist per channel is special: swap the UC prefix of a channel ID for UU and you have that channel's uploads playlist, which lists its public videos in order. Hashtag pages sit on their own path as well.
A channel is a set of tabs, not a single page. Home, Videos, Shorts, Live, Podcasts, Playlists, Posts and an in-channel Search each hold a different slice of the same catalogue, so a YouTube scraper that reads only the Videos tab misses Shorts and past live streams entirely. Shorts run up to three minutes and are listed apart from long-form uploads even though they carry the same eleven character video ID.
Two facts shape any attempt to scrape YouTube at all. The sitemap index the platform publishes contains no videos and no channels: it covers marketing sites for Kids, Trends, Creators, Jobs and Premium, so there is no crawl frontier to walk. And robots.txt closes the paths a naive crawler reaches for first, among them search results, the comment path, the per-channel RSS feed and the internal player endpoints. We read that file before we build anything, and we plan collection from seed lists of channels, playlists and video IDs instead of from a spider.
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The YouTube API is generous on fields and tight on volume. A project holds a default allocation of 10,000 units a day for most endpoints, resetting at midnight Pacific time, and every request costs at least one unit even when it fails. Listing videos, channels, playlists and comment threads costs one unit a call, so collection is cheap once you know the IDs. Discovery is the expensive half: search sits in its own bucket of 100 calls a day, and at fifty results a call that is a hard ceiling on how much you can find rather than fetch.
The caps bite elsewhere too. A search narrowed to one channel returns at most 500 videos. The reported result total is an approximation that stops at a million and is unsafe for paging. Sorting by upload date is explicitly discouraged because the search index lags, and the uploads playlist is the reliable way to enumerate a channel. Listing caption tracks costs fifty units, and the download call needs edit permission on the video, so subtitle text for another channel is not something the YouTube API will hand over.
The hardest limit is not a quota. Under the API terms, non-authorized data may be held no longer than 30 calendar days before it must be deleted or refreshed, and aggregation across unrelated channels is not permitted. That rules out the long history most buyers actually want. Where a requirement sits outside what the terms allow, YouTube expects a compliance audit and written permission, and we scope on that basis rather than around it.
Learn how to use web scraping to solve data problems for your organization
The use of sentiment analysis tools in business benefits not only companies but also their customers by allowing them to improve products and services, identify the strengths and weaknesses of competitors' products, and create targeted advertising.
Using web scraping to extract Google Maps data will help you quickly and efficiently find businesses in any industry, city, state, or region. And the extracted contact information, such as phone or email address, social networks, or links to web pages, will help to contact them.
Lead scraping is a reliable way to get the right customer contacts to market your product, saves organizations time, and helps you better understand the audience you want to attract. Contacts include emails, phone numbers, or social media profiles.
ScrapeIt is a managed data collection agency. We write the crawlers, run them on our own machines, fix them when a site moves, and hand over clean files. You do not maintain code and you do not manage proxies.
We also say no. If the YouTube Data API answers your question inside its quota, you hear that on the first call and there is no invoice. If a requirement sits outside what the platform's terms permit, you hear that too, before anyone signs.
Yes. The YouTube Data API v3 is documented, free to enable, and returns typed JSON for videos, channels, playlists, playlist items, comment threads, comments, caption metadata, video categories and search. For a video it covers title, description, publish time, duration, view and like counts, tags, category, languages, region restrictions, live details and status flags. What it will not give you: subtitle text for a video you do not own, dislike counts, chapters as objects, the recommendation rail, or any history older than the moment you pull it. Retention of non-authorized data is capped at 30 calendar days under its own terms.
Most endpoints share a default allocation of 10,000 units a day, resetting at midnight Pacific time. Listing videos, channels, playlists or comment threads costs one unit a call, so collection driven by known IDs is cheap. Search is metered separately and capped at 100 calls a day, which at fifty results a call is the real ceiling on discovery. Listing caption tracks costs fifty units a call. We plan around those numbers, apply for a quota extension where the use case supports one, and deliver the result as CSV, JSON, XLSX or an endpoint you call.
Comments yes, as a data type. Comment threads come back with text, timestamps, like counts and reply sets, ordered by time or relevance, filterable by search term, and available for a single video or a whole channel. Subtitles are different: listing which caption tracks a video carries is open, but downloading the text requires permission to edit that video, so we cannot supply transcripts for third party channels. On comments we deliver content and counts and leave out named private individuals and their contact details by default.
Because rounding happens in different places. The API rounds a channel's subscriber count down to three significant figures, and the channel header rounds it again for display. Lifetime channel views and video counts are exact in the about panel but rounded in the header and in listing tiles. On a watch page the view total is exact, while the same video shows a rounded figure in any grid that links to it. We record whichever version the source actually gives, label it, and never mix the two in one column.
Yes, per country and per category. The API exposes a most popular chart that takes an ISO country code and an optional category, and the site publishes trending charts that are identical for everyone in the same market. They refresh roughly every half hour and rank on how fast views are growing rather than on the raw total. No endpoint returns yesterday's chart, so a history exists only if somebody captured it on a schedule, and the earliest date in such a dataset is the day collection started.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
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