In the previous Python Tutorial, I walked you through how to create a youtube API key and scrape videos by search queries via python programming. Basically, the beauty of youtube video scraping is you don’t need to pay any fees to research potential YouTubers for your brand and eCommerce store product review, which is a super-efficient way.

But having said that for filtering the better YouTubers, it’s not sufficient for us to select just by those fetched videos, on the other hand, we also need to look into the video data, such as view, comments, likes, dislikes, etc, which can help us make a better candidate list. Also, by default Youtube data API v3 allows developers to scrape the top 50 pieces of videos, I would say it might be not enough because you might miss some secondary tier YouTubers whose videos might rank lower positions, but the content is pretty good and engaging.

As I haven’t talked about how to fetch those data above, so in this piece, I’ll continue to use the previous Youtube video scraping python script, and walk you through Youtube data API video data, how to write the codes to fetch the data, and scrape more than 50 pieces of videos from the search query result.

Previously we took Ring.com website as an example, and walked you through how to specify Ring product price data to scrape and save the bulk of data in local drive. Basically, the script code can scrape any general websites that are built and developed by CMS, such as WordPress, Shopify, etc. If you want to have a copy of the python script file, please contact us.

Being said that, not all the websites can be indexable and crawlable, because the data feed from some websites can be only accessible via API, such as Youtube, Facebook, Amazon, etc. Frankly if you just want to scrape these sites’ data by URL, I suggest you leverage Google Sheet importxml instead of Python, because it’s much easier (Time is money). On the other hand, automation and bulk amount of scraping data work are your regular work, for example, if you are a social media marketer, you need to recruit influencers, or KOLs, the following a series of articles can help relieve your stress and repeating manual work.

We would start with Youtube video scraping first, and by the end of this article, you can learn how to install Youtube API key, and what give methods you can use by Youtube API, how to scrape youtube videos, and video analytic data in bulk.

As mentioned in the last chapter about “How to Write, Parse, Read CSV Files with Scraped Data”, we would discuss how to specify web data to scrape, because this is one of the key purposes of why we like to learn Python as a digital marketer.

So in this python tutorial for digital marketers 4, I’ll walk you through a basic concept, and methods with using beautifulsoup and requests you need to know to specify web data and scrape. It’s better if you understand how to read HTML, CSS, javascript in this part, but it’s totally okay if you haven’t yet, because the purpose is to find the data located at the moment and learn some methods to scrape specific data for digital marketing purpose.

During the lesson, I’ll take Ring.com as an example to write codes and scrape all the latest offers and pricing. By the end of the lesson, you can master identify where your expected data locate on a target page and scrape it all in minutes.

In the previous Python Tutorial for digital marketers 2, we talked about how to install beautifulsoup4, requests, lxml, html5lib and sublime text, and then scraping web data by them. But the data is not saved in a file or a database yet, so it’s not convenient for you to use for your business purpose and work operation.

So in this Python Tutorial,we would talk about how to write Python scripts to parse and save the data into CSV files in local, and read the CSV files in a Python environment.

By the end of this Python Tutorial, you can master what CSV read, parse and write methods you can use to open and save CSV files in a readable format, although we are not going to deep dive into a specific scraping methods script writing which we would talk about in the next chapter of Python Tutorial.

In the previous Python tutorial for digital marketers 1, we discussed what a digital marketer can benefit from Python super power, why she or he needs it, and how to install and set up the latest Python version for Mac OS. As you might be aware, one of the most essential Python benefits to digital marketers is to scrape web data and update the data automatically. 

So in this article, I’ll talk about how to set up an environment to write python scripts for the purpose of scraping objective website data. This article doesn’t go into details regarding Python methods introduction, code writing and feeding the data to a spreadsheet or database. I’ll release other articles and videos to walk through. But the purpose of this article is to let you understand the big picture of what components are necessary and how it works.

By the end of this article, you can master the installation of beautifulsoup4, requests, lxml, html5lib and sublime text, and how to scrape web data by them.