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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

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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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

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('^' + ".*" + '
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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

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('^' + ".*" + '
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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

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

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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

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

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NameName
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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

Contributors

Languages

, '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('^' + ".*" + '
Skip to content

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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

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); } })(); })();
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Portuguese Version 🇧🇷

Table of Contents

Introduction - Huffman Algorithm

Implementation of Compression Huffman Algorithm in C++

Huffman's algorithm uses a file compression method based on the probability of occurrence of characters in text.

Features

In this implementation the Huffman Algorithm is defined by the concept of digital search, described by Digital Search Tree, which will allow the compression and decompression of text files (.txt).

This code will receive a input file, a .txt file which will be compressed, and generates two files as output:

  • encoded.txt: represents the compressed file, in binary. This file is the result of running Huffman's algorithm on the input file.
  • decoded.txt: represents the decoded file. This file is the result of applying Huffman's algorithm on the encoded.txt file. In other words, it's decompression. This file works as a validation, because if the algorithm performed the compression/decompression process correctly, this file must be exactly equal to the file used as input for compression.

How to use

To run code just compile the files contained in src folder. To do this, perform the following simple steps

Compiling files

  • Clone repository

    git clone git@github.com:ViniciusMarchi/huffman-algorithm.git
  • Go to project folder

    cd huffman-algorithm
  • Compile the file contained in src directory using g++ with the following command:

    g++ -o compilled src/*.cpp

Run algorithm

After compiling, just run the compiled file, passing as a parameter the .txt input file to be compressed, for example.

./compilled input.txt

Releases

Packages

Contributors

Languages