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LocalFetch

LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.

Key Features:

  1. Amazon Link Integration:

    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.

  2. Database Integration (local_shops.db):

    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.

  3. Interactive Map Display:

    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.

  4. Item Comparison:

    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.

  5. Price Optimization:

    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.

  6. Smooth Animations with Gsap:

    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.

How It Works:

  1. Input Amazon Link:

    • Users provide an Amazon link for a specific product they are interested in purchasing.

  2. Database Query:

    • The application queries the local_shops.db database to identify nearby shops offering the same item.

  3. Map Visualization:

    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.

  4. Price Comparison:

    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.

  5. Detailed Information:

    • Users can view detailed information about each shop, including the available items, prices, and contact details.

Technologies Used:

  • Frontend:

    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.

  • Backend:

    • Python with Flask for server-side functionality.
    • SQLite3 for database management.

  • Mapping:

    • Folium for dynamic map generation.

Future Improvements:

  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.

How to Run Locally:

  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.

About

LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.

Resources

Readme
Activity

Stars

0 stars

Watchers

1 watching

Forks

0 forks
Report repository

Releases

Packages

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" + '

Skip to content
BranchesTags
Repository files navigation
LocalFetch
LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.
Key Features:
  1. Amazon Link Integration:
    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.
  2. Database Integration (local_shops.db):
    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.
  3. Interactive Map Display:
    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.
  4. Item Comparison:
    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.
  5. Price Optimization:
    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.
  6. Smooth Animations with Gsap:
    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.
How It Works:
  1. Input Amazon Link:
    • Users provide an Amazon link for a specific product they are interested in purchasing.
  2. Database Query:
    • The application queries the local_shops.db database to identify nearby shops offering the same item.
  3. Map Visualization:
    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.
  4. Price Comparison:
    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.
  5. Detailed Information:
    • Users can view detailed information about each shop, including the available items, prices, and contact details.
Technologies Used:
  • Frontend:
    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.
  • Backend:
    • Python with Flask for server-side functionality.
    • SQLite3 for database management.
  • Mapping:
    • Folium for dynamic map generation.
Future Improvements:
  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.
How to Run Locally:
  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.
About
LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
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
BranchesTags
Repository files navigation
LocalFetch
LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.
Key Features:
  1. Amazon Link Integration:
    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.
  2. Database Integration (local_shops.db):
    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.
  3. Interactive Map Display:
    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.
  4. Item Comparison:
    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.
  5. Price Optimization:
    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.
  6. Smooth Animations with Gsap:
    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.
How It Works:
  1. Input Amazon Link:
    • Users provide an Amazon link for a specific product they are interested in purchasing.
  2. Database Query:
    • The application queries the local_shops.db database to identify nearby shops offering the same item.
  3. Map Visualization:
    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.
  4. Price Comparison:
    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.
  5. Detailed Information:
    • Users can view detailed information about each shop, including the available items, prices, and contact details.
Technologies Used:
  • Frontend:
    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.
  • Backend:
    • Python with Flask for server-side functionality.
    • SQLite3 for database management.
  • Mapping:
    • Folium for dynamic map generation.
Future Improvements:
  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.
How to Run Locally:
  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.
About
LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
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
BranchesTags
Repository files navigation
LocalFetch
LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.
Key Features:
  1. Amazon Link Integration:
    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.
  2. Database Integration (local_shops.db):
    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.
  3. Interactive Map Display:
    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.
  4. Item Comparison:
    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.
  5. Price Optimization:
    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.
  6. Smooth Animations with Gsap:
    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.
How It Works:
  1. Input Amazon Link:
    • Users provide an Amazon link for a specific product they are interested in purchasing.
  2. Database Query:
    • The application queries the local_shops.db database to identify nearby shops offering the same item.
  3. Map Visualization:
    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.
  4. Price Comparison:
    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.
  5. Detailed Information:
    • Users can view detailed information about each shop, including the available items, prices, and contact details.
Technologies Used:
  • Frontend:
    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.
  • Backend:
    • Python with Flask for server-side functionality.
    • SQLite3 for database management.
  • Mapping:
    • Folium for dynamic map generation.
Future Improvements:
  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.
How to Run Locally:
  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.
About
LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
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
BranchesTags
Repository files navigation
LocalFetch
LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.
Key Features:
  1. Amazon Link Integration:
    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.
  2. Database Integration (local_shops.db):
    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.
  3. Interactive Map Display:
    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.
  4. Item Comparison:
    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.
  5. Price Optimization:
    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.
  6. Smooth Animations with Gsap:
    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.
How It Works:
  1. Input Amazon Link:
    • Users provide an Amazon link for a specific product they are interested in purchasing.
  2. Database Query:
    • The application queries the local_shops.db database to identify nearby shops offering the same item.
  3. Map Visualization:
    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.
  4. Price Comparison:
    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.
  5. Detailed Information:
    • Users can view detailed information about each shop, including the available items, prices, and contact details.
Technologies Used:
  • Frontend:
    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.
  • Backend:
    • Python with Flask for server-side functionality.
    • SQLite3 for database management.
  • Mapping:
    • Folium for dynamic map generation.
Future Improvements:
  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.
How to Run Locally:
  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.
About
LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
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
BranchesTags
Repository files navigation
LocalFetch
LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.
Key Features:
  1. Amazon Link Integration:
    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.
  2. Database Integration (local_shops.db):
    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.
  3. Interactive Map Display:
    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.
  4. Item Comparison:
    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.
  5. Price Optimization:
    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.
  6. Smooth Animations with Gsap:
    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.
How It Works:
  1. Input Amazon Link:
    • Users provide an Amazon link for a specific product they are interested in purchasing.
  2. Database Query:
    • The application queries the local_shops.db database to identify nearby shops offering the same item.
  3. Map Visualization:
    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.
  4. Price Comparison:
    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.
  5. Detailed Information:
    • Users can view detailed information about each shop, including the available items, prices, and contact details.
Technologies Used:
  • Frontend:
    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.
  • Backend:
    • Python with Flask for server-side functionality.
    • SQLite3 for database management.
  • Mapping:
    • Folium for dynamic map generation.
Future Improvements:
  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.
How to Run Locally:
  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.
About
LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
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
BranchesTags
Repository files navigation
LocalFetch
LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.
Key Features:
  1. Amazon Link Integration:
    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.
  2. Database Integration (local_shops.db):
    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.
  3. Interactive Map Display:
    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.
  4. Item Comparison:
    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.
  5. Price Optimization:
    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.
  6. Smooth Animations with Gsap:
    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.
How It Works:
  1. Input Amazon Link:
    • Users provide an Amazon link for a specific product they are interested in purchasing.
  2. Database Query:
    • The application queries the local_shops.db database to identify nearby shops offering the same item.
  3. Map Visualization:
    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.
  4. Price Comparison:
    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.
  5. Detailed Information:
    • Users can view detailed information about each shop, including the available items, prices, and contact details.
Technologies Used:
  • Frontend:
    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.
  • Backend:
    • Python with Flask for server-side functionality.
    • SQLite3 for database management.
  • Mapping:
    • Folium for dynamic map generation.
Future Improvements:
  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.
How to Run Locally:
  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.
About
LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.
Resources
Readme
Activity
Stars
0 stars
Watchers
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, '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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LocalFetch
LocalFetch is a comprehensive web application developed to facilitate users in finding local shops that offer the same products available on Amazon, along with detailed information about the items and their prices. The project seamlessly integrates HTML, CSS, JavaScript, Gsap, Lenis, Python, Flask, Folium, and SQLite3 to provide a user-friendly and efficient experience.
Key Features:
  1. Amazon Link Integration:
    • Users can input an Amazon product link, initiating a search for local shops carrying the same item.
  2. Database Integration (local_shops.db):
    • Utilizes SQLite3 to store and manage data about nearby shops, their available items, and corresponding prices.
  3. Interactive Map Display:
    • Presents the search results on an interactive map using Folium, offering a visual representation of nearby shops with the desired product.
  4. Item Comparison:
    • Highlights shops on the map that carry the same item, making it easy for users to compare prices and offerings.
  5. Price Optimization:
    • Identifies the shop with the lowest price for the searched item, marked with a distinctive green marker for quick identification.
  6. Smooth Animations with Gsap:
    • Incorporates Gsap for smooth and visually appealing animations, enhancing the overall user experience.
How It Works:
  1. Input Amazon Link:
    • Users provide an Amazon link for a specific product they are interested in purchasing.
  2. Database Query:
    • The application queries the local_shops.db database to identify nearby shops offering the same item.
  3. Map Visualization:
    • Results are dynamically displayed on an interactive map, making it easy for users to explore and assess their options.
  4. Price Comparison:
    • Shops with the same item are highlighted, and the shop with the lowest price is distinguished by a green marker.
  5. Detailed Information:
    • Users can view detailed information about each shop, including the available items, prices, and contact details.
Technologies Used:
  • Frontend:
    • HTML, CSS for the user interface.
    • JavaScript for interactive features.
    • Gsap for smooth animations.
  • Backend:
    • Python with Flask for server-side functionality.
    • SQLite3 for database management.
  • Mapping:
    • Folium for dynamic map generation.
Future Improvements:
  • Implement user authentication for personalized experiences.
  • Expand the database to include a wider range of products and shops.
  • Enhance the user interface for a more polished look.
How to Run Locally:
  1. Clone the repository.
  2. Install required dependencies using pip install -r requirements.txt.
  3. Run the Flask application using python app.py.
About
LocalFetch connects Amazon products to nearby stores. It maps shops, compares prices, and simplifies local shopping. Find deals effortlessly and support local businesses.
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