Perl script monitors visitor statistics for YouTube movies
Chart Stormers

Hobby YouTuber Mike Schilli is interested in whether his videos go viral. What better way to check skyrocketing viewer numbers than letting a Perl script analyze the daily trends and watch for unexpected upswings?
When a hardware hacker like myself faces a seemingly unsolvable mechanical problem – for example, when a gadget resists warranty-invalidating opening – you can typically find a solution on YouTube. And, if you need to use a less-than-intuitive program like GIMP, you will typically find an expert screencast on YouTube to help you solve complex problems, even as a newbie.
Dreamship
When I recently managed to use GIMP's Scissor Select tool successfully, I decided to create a screencast. Then, I waited for this masterpiece of movie magic to hit the charts on YouTube. I initially set monthly reminder dates in Evernote to check the number of views by hand at regular intervals. However, that got old pretty quickly, so thanks to the CPAN WebService::GData::YouTube module, I managed to fully automate the process.
For this to happen, the YAML file in Listing 1 lists the IDs of the movies to monitor [1]. I simply extracted the hex numbers from my videos' YouTube URLs. For example, the _Cxu3-UP0G8
string for the GIMP video was simply cut and pasted from the URL line in the browser displayed in Figure 1.
Listing 1
youtube-watch.yml

The script in Listing 2 uses the CPAN YAML module to walk through the entries in the YAML file; it passes the movie ID to the get_video_by_id()
method in the WebService::GData::YouTube package on every iteration. The method in turn contacts the YouTube API server and receives a mess of metadata about the movie. Below the _feed
key, the script finds the yt$statistics
entry with the value for ViewCount
– you guessed it, the number of times the movie was requested by interested viewers.
Listing 2
youtube-viewcounts
Lines 23 and 24 quickly convert the output, with some help from the CPAN JSON module, to a machine-readable format; this allows for easier post-processing by a script like Listing 3. They set the pretty
option to make the output easier for human consumers to understand and canonical
to sort the hash keys alphabetically, which would otherwise be in random order in Perl. In the resulting array (@result
), each element contains the name
(movie title), count
(the view count added by line 17), and id
(the unique YouTube ID of the movie).
Listing 3
viewcounts-todb
Figure 2 shows the output from the script and reveals that my previously little-known sideline as a car mechanic working on 20-year-old Honda engines is one of the highlights of my oeuvre with no fewer than 56,000 views, whereas the GIMP screencast has a miserly 297 views to date.
Daily Tests
If you run Listing 1 once a day as a cronjob, the next logical thing to do is to archive and later evaluate the data. For this, Listing 3 employs a SQLite mini-database that stores its data in a single file but still supports SQL queries.
The database schema generated in Listing 4 contains fields for every movie's YouTube ID (video_id
), the number of views (views
) and the date stamp of the query (queried
). The command
Listing 4
viewcounts.sql
sqlite3 viewcounts.db <viewcounts.sql
tells SQLite to create a database in the new viewcounts.db
file. Listing 3 can then fire as a second stage in the command pipe
youtube-viewcounts | viewcounts-todb
to receive the JSON data generated by Listing 2 and create a database record for each array entry.
The script fills the table's date field for each new entry in line 16 of Listing 3 with CURRENT_TIMESTAMP
; SQLite replaces this in the database with the current date and time. This step gives you a database entry with a time stamp for each monitored movie and day, and you can easily retrieve the entries sorted by time.
Based on the database entries shown in Figure 3, Listing 5 now tries to find out whether the viewer figures are continually increasing or possibly skyrocketing. In this case, I want the script to alert me.
Listing 5
hit-detect
Hit or Miss?
How do you define skyrocketing, though? For a movie with 30,000 views, which increases by about 10 views a day, these 10 hits don't mean much. However, if you have a less successful movie that remains undiscovered for a long time, and then suddenly has 10 views, you might like to be notified.
Because I recently read an excellent book titled Machine Learning with R [2], which explains all kinds of statistical methods, I had the idea of determining unusual jumps in the viewing figures by means of linear regression [3]. This involves the CPAN Statistics::LineFit module used by Listing 5 trying to make a straight line out of flatlining or continually increasing historic viewing figures (Figure 4). The x axis denotes time from left to right, and the y axis represents the number of views for the current measuring point.

It doesn't matter that the straight line doesn't hit each measuring point precisely (in fact, it's not even possible in most cases), as long as the linear regression keeps the unavoidable errors to a minimum. The problem was solved by scientists back in the dark ages, and the CPAN module simply implements the algorithm to compute the a and b parameters from the linear formula y = b+ax. The b parameter expresses the y value at the origin of the x axis (intercept), and the a parameter gives you the gradient of the linear approximation (slope).
Buy this article as PDF
(incl. VAT)
Buy Linux Magazine
Direct Download
Read full article as PDF:
Price $2.95
Subscribe to our Linux Newsletters
Find Linux and Open Source Jobs
Subscribe to our ADMIN Newsletters
Find SysAdmin Jobs
News
-
KDE Plasma 5.27 Beta is Ready for Testing
The latest beta iteration of the KDE Plasma desktop is now available and includes some important additions and fixes.
-
Netrunner OS 23 Is Now Available
The latest version of this Linux distribution is now based on Debian Bullseye and is ready for installation and finally hits the KDE 5.20 branch of the desktop.
-
New Linux Distribution Built for Gamers
With a Gnome desktop that offers different layouts and a custom kernel, PikaOS is a great option for gamers of all types.
-
System76 Beefs Up Popular Pangolin Laptop
The darling of open-source-powered laptops and desktops will soon drop a new AMD Ryzen 7-powered version of their popular Pangolin laptop.
-
Nobara Project Is a Modified Version of Fedora with User-Friendly Fixes
If you're looking for a version of Fedora that includes third-party and proprietary packages, look no further than the Nobara Project.
-
Gnome 44 Now Has a Release Date
Gnome 44 will be officially released on March 22, 2023.
-
Nitrux 2.6 Available with Kernel 6.1 and a Major Change
The developers of Nitrux have officially released version 2.6 of their Linux distribution with plenty of new features to excite users.
-
Vanilla OS Initial Release Is Now Available
A stock GNOME experience with on-demand immutability finally sees its first production release.
-
Critical Linux Vulnerability Found to Impact SMB Servers
A Linux vulnerability with a CVSS score of 10 has been found to affect SMB servers and can lead to remote code execution.
-
Linux Mint 21.1 Now Available with Plenty of Look and Feel Changes
Vera has arrived and although it is still using kernel 5.15, there are plenty of improvements sure to please everyone.