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Repository Overview (README excerpt)
Crawler viewiplist-youtube An attempt to list all IPs that YouTube uses. This list attempts to keep all ipv4 and ipv6 addresses used by YouTube. We use DNS Lookups to achieve this and the lists are automatically updated approximately every 5 minutes. The project is currently **STABLE BETA.** So, not all IPs might be available. At present, it has a collection of **30449** YouTube IPs. Lists • ipv4.txt • ipv6.txt • cidr4.txt • cidr6.txt • routeros.rsc ***NEW!*** • routerosv4.rsc ***NEW!*** • routerosv6.rsc ***NEW!*** Used open source lists: • https://github.com/nickspaargaren/no-google/blob/master/categories/youtubeparsed How to make the lists manually. There are two scripts in the repository root, and . Running any of these scripts should generate two files with a list of **IPv4** and **IPv6** addresses with the filenames and . Note that the is recommended although should run better. This is because the uses an underlining tool called which is a troubleshooting tool not intended to be used for production purposes. It has a little chance of listing some wrong **IPs** In some cases. With a warning or error. To use the file run these commands in the folder containing the files. If this doesn't work, run the following before using it. It should only be necessary once. For the file, you need to install dependencies. This is only necessary once. Then run: If this doesn't work, try: ***New!*** To generate CIDR lists use Important Notes Using any of these scripts once is not enough. This is because **IPs** returned by DNS Queries are not consistent. They are changed at fixed or unfixed intervals. Although all **IPs** are not returned at the same time, all have the same purpose. And different computers use different **IPs** at the same time. And so, running the scripts, again and again, is a necessity. If you run the scripts more **IPs** should be automatic. Personally recommend running the scripts at least **100** times at the interval of **5** minutes or **300** seconds (Google's TTL). For reasonable performance, run it **1000** times before using it for production. I use such Cron jobs to populate the lists.