Have you ever wondered how we can make text files smaller without losing any information? That’s what text compression is all about! There’s a cool tool called the Text Compression Widget that helps you learn how to compress text by finding patterns and using fewer bytes to represent the same information. Let’s dive into how it works and why it’s useful.
The main idea behind text compression is to replace repeating patterns in text with shorter symbols. This way, you can send or store the text using fewer bytes. For example, if a word like “pitter” appears multiple times in a text, you can replace it with a single symbol, like a sun. Similarly, “patter” can be replaced with an umbrella symbol. When you send the compressed text to someone, you also need to send a dictionary that explains what each symbol stands for, so they can reconstruct the original text.
The widget gives you a piece of text to compress. Your task is to find repeating words or patterns and replace them with symbols. For instance, in one example, the compressed version of a poem uses 53 bytes, and the dictionary uses 14 bytes. Together, that’s 67 bytes. The original text had 93 bytes, so you’ve saved 26 bytes, which is about 28% compression!
Looking for repeating words is a great start, but you can also find smaller patterns within words. For example, both “pitter” and “patter” contain the letters “t-t-e-r.” If you add “t-t-e-r” to the dictionary, you can replace it with a single symbol, saving even more space.
As you get better at finding patterns, you might notice that some patterns include symbols from the dictionary. For example, if “pitter” is now “p-i” with a sun symbol for “t-t-e-r,” and “p-i-sun” repeats, you can use that pattern for further compression. You can even reference earlier entries in the dictionary to create new patterns.
To get back to the original text, you need to start from the bottom of the dictionary and work your way up, replacing symbols with their original words or patterns. Be careful, though! Each dictionary entry can only reference symbols that came before it. If you try to reference a symbol that appears later, the widget will warn you and stop you from making that mistake.
Text compression is a fascinating way to make data smaller and more efficient. By practicing with the widget, you can become skilled at finding patterns and understanding how compression works. Have fun experimenting and see how much you can compress your text!
Explore a given text and identify repeating patterns or words. Use your creativity to replace these patterns with unique symbols. Share your compressed version with classmates and see who can achieve the highest compression rate!
Design a dictionary for a short story or poem. Assign symbols to frequently occurring words or patterns. Exchange your dictionary with a partner and try to decode each other’s compressed text. This will help you understand the importance of a well-structured dictionary.
Work in teams to compress a large piece of text. Each team member takes turns finding patterns and updating the dictionary. The goal is to achieve the maximum compression in the shortest time. Reflect on the strategies that worked best for your team.
Write a short story using symbols from a pre-defined dictionary. Share your story with the class and see if they can reconstruct the original text. This activity will enhance your understanding of how symbols can represent complex ideas.
Analyze a compressed text and its dictionary to reconstruct the original text. Pay attention to the order of symbols and dictionary entries. This will sharpen your skills in decoding and understanding the logic behind text compression.
Here’s a sanitized version of the provided YouTube transcript:
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This widget allows you to experiment with techniques for compressing text. Your goal is to represent the original text with as few bytes as possible. Let’s look at how the tool works. The widget presents you with a piece of text to compress. You can identify patterns that appear in the text. For now, let’s focus on words that repeat. As you type, a single symbol will be substituted.
In the example here, each occurrence of the word “pitter” has been replaced with a sun symbol, and “patter” has been replaced with an umbrella symbol. If you send the compressed version of the poem to someone, you’ll also need to send along the dictionary so the person can reconstruct the original text.
So the question is, is the total number of bytes in the compressed text plus the bytes in the dictionary less than the number of bytes in the original text? The answer is yes for our current example, and the widget shows you how it’s calculated. We assume that every character that needs to be sent takes one byte. The display shows that the current version of the poem with the symbols substituted in it has 53 bytes. It also shows the number of bytes in the dictionary as 14.
The characters for the text “pitter” and “patter” add up to 12, but we also need to include the sun and umbrella symbols in the count. This gives us a total of 67 bytes: 53 for the poem and 14 for the dictionary. We can see that the original plain text had 93 characters, so we’ve reduced the bytes needed to represent the poem by 26 bytes, which works out to almost 28 percent compression.
Looking for words that repeat is a good start on trying to compress a piece of text, but you can train yourself to look for other patterns of characters. For example, you may have noticed that “pitter” and “patter” both contain the characters “t-t-e-r.” If we include that in the dictionary, it’s beneficial because “t-t-e-r” repeats more frequently, allowing for a single character substitution for more parts of the poem.
Now, here’s where it gets interesting. You might begin to notice patterns that include dictionary symbols themselves. For example, the original word “pitter” is now represented as “p-i” with a sun symbol in place of “t-t-e-r,” but “p-i-sun” also repeats in the poem. Within the dictionary, you can actually reference earlier entries. You can do that by typing “p-i” and then copying and pasting the sun symbol from anywhere it appears on the page. You can also copy a pattern that you find directly from the poem text.
Let me do that for “p-a-sun.” And then I notice a pattern with umbrellas and snowmen. Let me copy that, too. Now the single comet symbol is standing in for a bunch of text, allowing for further compression.
To reconstruct the original, you have to work your way up from the bottom of the dictionary, substituting along the way. Remember, though, a line in the dictionary can only reference previous entries. This can catch you if you accidentally introduce a pattern later in the dictionary that invalidates a previous entry. The widget will give you a warning and prevent you from creating an entry that references something further down in the dictionary.
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This version maintains the original meaning while removing any informal language and ensuring clarity.
Text – Text refers to the written or printed words that are used in documents or displayed on screens. – Example sentence: When coding a website, you can change the color and size of the text to make it more appealing.
Compression – Compression is the process of reducing the size of a file or data to save space or make it easier to send over the internet. – Example sentence: We used compression to make the video file smaller so it could be uploaded faster.
Widget – A widget is a small application or tool that provides specific information or functionality on a computer screen or website. – Example sentence: The weather widget on my desktop shows the current temperature and forecast.
Patterns – Patterns in coding refer to repeated sequences or structures that can be used to solve problems or organize data efficiently. – Example sentence: Recognizing patterns in code can help programmers write more efficient algorithms.
Symbols – Symbols are characters or signs used in programming to perform operations or represent data. – Example sentence: In programming, symbols like + and – are used to perform mathematical operations.
Bytes – Bytes are units of digital information used to measure data size, typically consisting of eight bits. – Example sentence: A simple text file might only be a few bytes in size, while a video file could be several gigabytes.
Dictionary – In programming, a dictionary is a data structure that stores data in key-value pairs, allowing for fast retrieval. – Example sentence: We used a dictionary to store the names and scores of students in the coding competition.
Original – Original refers to the first or initial version of something before any changes or modifications are made. – Example sentence: Always keep a backup of the original code before making any major changes.
Data – Data refers to information processed or stored by a computer, which can be in the form of text, numbers, or other formats. – Example sentence: The program analyzes data from various sources to generate a report.
Efficient – Efficient means achieving maximum productivity with minimum wasted effort or resources, especially in coding or computing. – Example sentence: Writing efficient code can help programs run faster and use less memory.
