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Workflow Automation

Simulate Real-life Events in Python Using SimPy

As a restaurant manager, you want to approximate how much food your restaurant needs to prepare for tomorrow. You know how many customers come to your restaurant per day and the average time it takes to serve one customer.
However, it is challenging to put all of these variables into one calculation. Wouldn’t it be great if you can simulate this event using Python?
That is when SimPy comes in handy. In my latest article, you will learn how to use SimPy to simulate a restaurant.
Link to the article.
Link to the source code.
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notion-py: Access and Edit your Notion App Using Python

Notion is a popular tool for note-taking. Wouldn’t it be nice if you can access Notion using Python? One of the applications is to write Python scripts to automate some processes such as daily updates.
Luckily, there is a Python library for Notion called notion-py. notion-py makes it easy to access and change the information in your Notion.
The code above shows how to use notion-py.
Link to notion-py.
How to find your Notion token.
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github-to-sqlite: Download the Data of your Starred GitHub Repositories in One Command Line

Have you ever interested in downloading and analyzing the data of your starred GitHub repositories? If so, try github-to-sqlite.
The code above shows how to use github-to-sqlite to download your starred repositories and save them at starred_repo.json.
Link to github-to-sqlite.
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top-github-scraper: Scrape Top Github Users and Repositories Based On a Keyword in One Line of Code

There are over 56 million developers in GitHub. This means just by exploring GitHub, you can potentially find your software’s partners or your next employee. Why don’t we utilize this platform to find interesting people?
That’s why I created a Python package called top-github-scraper. Top-github-scraper allows you to get top Github users, contributors, and repositories based on a certain keyword in ONE line of code.
In my latest article, you will learn how to use top-github-scraper and how to create a map to search for top GitHub users in your area of interest.

Links to Article and Scraper
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Extract series data from various Internet sources directly into a pandas DataFrame

Have you wanted to extract series data from various Internet sources directly into a pandas DataFrame? That is when pandas_reader comes in handy.
Above is the snippet to extract daily data of AD indicator from 2008 to 2018. All you need is one line of code to extract the data and it is Pythonic!
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    Work with Khuyen Tran

    Work with Khuyen Tran