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Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

Forks

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Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
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This repository was archived by the owner on Apr 2, 2026. It is now read-only.

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Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content
This repository was archived by the owner on Apr 2, 2026. It is now read-only.

Repository files navigation

Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content
This repository was archived by the owner on Apr 2, 2026. It is now read-only.

Repository files navigation

Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content
This repository was archived by the owner on Apr 2, 2026. It is now read-only.

Repository files navigation

Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content
This repository was archived by the owner on Apr 2, 2026. It is now read-only.

Repository files navigation

Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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This repository was archived by the owner on Apr 2, 2026. It is now read-only.

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Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
Skip to content
This repository was archived by the owner on Apr 2, 2026. It is now read-only.

Repository files navigation

Huffman-coding-compression

Compression & decompression of text files using huffman coding.

Usage

To compress or decompress files, pass the paths to the files as parameters to the program. You can do that by simply dragging and dropping the selected files on the program, and Windows will automatically pass the paths to the files as arguments to the program.

When a file filename.txt is passed to the program, it is compressed and the bytes are written to a file filename.txt.comp, created in the same location as filename.txt is.

When a file filename.txt.comp is passed to the program, it is decompressed and the text is written to a file filename.txt, created in the same location is filename.txt.comp is.

Inner workings

Text encoding

Both compression and decompression uses ISO-8859-2 (/latin 2) encoding.

Compression method

Each character is assigned an alternative code (instead of the latin-2 8-bit one) using huffman coding. Higher occuring characters simply have shorter codes and less occuring characters longer codes, which most of the time results in smaller total amount of bits. This implementation operates on individual characters, it does not encode sections of text (which would give better compression results).

This specific implementation compresses files to about 70% of their initial size, saving 30% of space.

Storing of the tree

Informations about each character are stored as follows:

[bit indicating if the character was already encountered in the text],

if not: [length of the character's code], [the character's latin-2 representation], [the character's code]

if yes: [the character's code]

  • the character's code length is represented in 3-6 bits (which means that the maximal code length is 2^6 - 1 = 63 - so in this implementation there's a limit on the amount of different characters that can be present in the text - but it is very unlikely than any text would generate code larger than 63 bits). How does the decompressor know how many bits are representing the code's length? In the beginning of the file, the first two bytes indicate exactly that. 00 is for 3 bits, 01 for 4 bits, 10 for 5 bits and 11 for 6 bits.

  • Informations about each characters are not written at the beginning or the end of the file, but directly whenever the character is in the text (the only information written directly at the beginning of the file - even before the redundant zeros - is a two-bit indicator of in how many bits the codes lengths are stored).

  • The bits are stored in bytes, and each byte has 8 bits. If the amount of bits isn't divisible by 8 without a remainder, additional bits must be added. This implementation adds zeros at the beginning of the compressed text, and because the first information on each character is if it has (0) or has not (1) already been encountered, then the first bit on the first character must obviously always be 1. This allows the decompressor to safely recognize and ignore the redundant bits -> all zeros before the first non-zero character.

  • The only information added to a character that was already encountered is one bit (0), which indicates that it has already been encountered. Decompressor then starts reading from the first bit and gradually adds next, until it finds a match in whenever it stores already encountered codes and their latin-2 representations.

example:

letter | code | code length | latin-2 code |
R 1010 4 (0100) 01001010
  • if not already encountered: [1][0100][01001010][1010] (in the file written together, like this: 10100010010101010)
  • if already encountered: [0][1010] (in the file written together, like this: 01010)

To-do

  • Storing each bit (while compressing and mainly decompressing) as one character was an absolutely retarded idea. This way, representing one bit takes 2 bytes (the size of one character), which is unacceptable. It's needed to, for example, create a BitArray or BitList class, which will internally store a collection of bytes, and will write (and read) each bit to a byte. This way representing one bit will take 1/8 byte (+ the initial size of instantiating the class - the internal collection, fields etc.), which is a significant improvement.

  • Limit the amount of threads that are used to concurrently compress/decompress files (either set a limit based on the PC's processor, or use ThreadPool)

  • Optimize speed

license

MIT

About

Compression & decompression of text files using huffman coding.

Resources

Stars

1 star

Watchers

1 watching

Forks

Releases

Used by

Contributors

Languages