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The ipc Package

Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.

There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:

  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.

Installation

To install the latest version from CRAN run:

install.packages("ipc")

To install the latest development version from the github repo run:

# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources

To run an example application locally use:

library(ipc)
shinyExample()

Development

Development Practices and Policies for Contributers

About

Tools for message passing between processes

Resources

Readme
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54 stars

Watchers

3 watching

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2 forks
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, '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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The ipc Package
Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.
There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:
  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.
Installation
To install the latest version from CRAN
run:
install.packages("ipc")

To install the latest development version from the github repo run:
# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources
To run an example application locally use:
library(ipc)
shinyExample()

Development
Development Practices and Policies for Contributers
About
Tools for message passing between processes
Resources
Readme
Activity
Custom properties
Stars
54 stars
Watchers
3 watching
Forks
2 forks
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, '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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The ipc Package
Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.
There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:
  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.
Installation
To install the latest version from CRAN
run:
install.packages("ipc")

To install the latest development version from the github repo run:
# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources
To run an example application locally use:
library(ipc)
shinyExample()

Development
Development Practices and Policies for Contributers
About
Tools for message passing between processes
Resources
Readme
Activity
Custom properties
Stars
54 stars
Watchers
3 watching
Forks
2 forks
Report repository
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('^' + ".*" + '

Skip to content
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The ipc Package
Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.
There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:
  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.
Installation
To install the latest version from CRAN
run:
install.packages("ipc")

To install the latest development version from the github repo run:
# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources
To run an example application locally use:
library(ipc)
shinyExample()

Development
Development Practices and Policies for Contributers
About
Tools for message passing between processes
Resources
Readme
Activity
Custom properties
Stars
54 stars
Watchers
3 watching
Forks
2 forks
Report repository
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
BranchesTags
Repository files navigation
The ipc Package
Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.
There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:
  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.
Installation
To install the latest version from CRAN
run:
install.packages("ipc")

To install the latest development version from the github repo run:
# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources
To run an example application locally use:
library(ipc)
shinyExample()

Development
Development Practices and Policies for Contributers
About
Tools for message passing between processes
Resources
Readme
Activity
Custom properties
Stars
54 stars
Watchers
3 watching
Forks
2 forks
Report repository
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
BranchesTags
Repository files navigation
The ipc Package
Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.
There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:
  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.
Installation
To install the latest version from CRAN
run:
install.packages("ipc")

To install the latest development version from the github repo run:
# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources
To run an example application locally use:
library(ipc)
shinyExample()

Development
Development Practices and Policies for Contributers
About
Tools for message passing between processes
Resources
Readme
Activity
Custom properties
Stars
54 stars
Watchers
3 watching
Forks
2 forks
Report repository
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
BranchesTags
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The ipc Package
Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.
There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:
  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.
Installation
To install the latest version from CRAN
run:
install.packages("ipc")

To install the latest development version from the github repo run:
# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources
To run an example application locally use:
library(ipc)
shinyExample()

Development
Development Practices and Policies for Contributers
About
Tools for message passing between processes
Resources
Readme
Activity
Custom properties
Stars
54 stars
Watchers
3 watching
Forks
2 forks
Report repository
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); }
})();
})();

Skip to content
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The ipc Package
Asynchronous processing is critical for performing a wide array of tasks, from high performance computing to web services. Communication between these disparate asynchronous processes is often required. Currently the statistical computing language R provides no built in features to handle interprocess communication between R processes while they are performing computations. Several packages have been written to handle the passing of text or binary data between processes (e.g. txtq, liteq, and zmq). ipc allows you to easily pass R objects between processes along with an associated signal, and have handler functions automatically execute them in the receiving process.
There is particular focus on supporting asynchronous evaluation in Shiny applications. Examples are included in the package showing how to perform useful tasks such as:
  • Updating reactive values from within future
  • Progress bars for long running async tasks
  • Interrupting async tasks based on user input.
Installation
To install the latest version from CRAN
run:
install.packages("ipc")

To install the latest development version from the github repo run:
# If devtools is not installed:
# install.packages("devtools")
devtools::install_github("fellstat/ipc")

Resources
To run an example application locally use:
library(ipc)
shinyExample()

Development
Development Practices and Policies for Contributers
About
Tools for message passing between processes
Resources
Readme
Activity
Custom properties
Stars
54 stars
Watchers
3 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages