One day, I was preparing for the SAT, specifically the vocabulary. I wanted to memorize several hundred words (500 to be exact). However, a majority of the words I don’t know the meanings of, not even the roots of the words. But, when I tried to find the definitions, I had to look for the menings of the words one by one. To look for the meaning of words a hundred times by searching up the words a hundred times is very tedious. The general process is that I have to search up a word, click a link to a website, copy the definition and input it back to excel. Then I have to repeat the process all over again. If I can automate it, I can do it for as many as words as possible So, I had an idea. Why not put all the words in excel, input all those words into a python program, and the program will output the definitions of those words all at once? With this in mind, I created a function that takes a list of words, extracts the definitions, and puts all the definitions back into excel (Explained in more depth below). I encourage you to use this program or you can modify it as well.
A basic Python Dictionary in JupyterLab that can take multiple words and output the definitions of those words at once.
The dictionary was created using python pandas, the BeautifulSoup library, and the website: www.dictionary.com. The code webscrapes a modified url using the word parameter of the function ggl_search(). From html of the url, the function extracts the first definition typed in the website and outputs it as a string.
The dictionary can also output multiple single-definitions of several words at once using lists. The words can come from a csv file (like in this repository) or they can come from a simple python list.
In both cases, the dictionary outputs the word and definition in a DataFrame. Below is the DataFrame output if the code in the repository is run.
There are two ways to use the source code. The desktop version (full use of features) and web version (limited use of features).
-
Desktop (RECOMMENDED):
a. Search up Anaconda Navigator and download the app.
b. Open Jupyter Lab and upload the .ipynb file.
c. Run the code.
-
Web Version:
a. Go to this link: https://jupyterlite.readthedocs.io/en/latest/_static/lab/index.html.
b. Download the .ipynb file in the source code, and upload it to the workspace in the link.
Note: Sometimes the dictionary may not include a word or the class with which the definition is in may be different. It's also possible that the word inputted is not a word at all (for example, the number 0). Therefore, when running the code with that type of word, it may output an error called 'NoneType' object has no attribute 'text'. If this error pops up, check the wrod you inputted into the function and change it. However, this happens rarely.