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@Mikolaj-A-KowalskiMikolaj-A-Kowalski commented Jun 16, 2025

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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all
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(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
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;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
Script to track performance regression by Mikolaj-A-Kowalski · Pull Request #36 · DEMENT-Model/DEMENTpy · GitHub
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@Mikolaj-A-KowalskiMikolaj-A-Kowalski commented Jun 16, 2025

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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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@Mikolaj-A-KowalskiMikolaj-A-Kowalski commented Jun 16, 2025

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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' Script to track performance regression by Mikolaj-A-Kowalski · Pull Request #36 · DEMENT-Model/DEMENTpy · GitHub
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@Mikolaj-A-KowalskiMikolaj-A-Kowalski commented Jun 16, 2025

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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' Script to track performance regression by Mikolaj-A-Kowalski · Pull Request #36 · DEMENT-Model/DEMENTpy · GitHub
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@Mikolaj-A-KowalskiMikolaj-A-Kowalski commented Jun 16, 2025

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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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@Mikolaj-A-KowalskiMikolaj-A-Kowalski commented Jun 16, 2025

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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' Script to track performance regression by Mikolaj-A-Kowalski · Pull Request #36 · DEMENT-Model/DEMENTpy · GitHub
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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })(); Script to track performance regression by Mikolaj-A-Kowalski · Pull Request #36 · DEMENT-Model/DEMENTpy · GitHub
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@Mikolaj-A-KowalskiMikolaj-A-Kowalski commented Jun 16, 2025

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Builds on top of #34

Related to #22

Adapts the performance regression inspection script of pyrealm. Some modifications were necessary to make it run with DEMENTpy, but following them the script runs and is capable to generate the report.

No documentation is provided yet. To run it one just needs to follow instructions from the pyrealm doc.

At the moment its usefulness seems to be limited I'm afraid. In the tests on my machine the profile entries seem to have a really high variance in the range of 15% so two profiling runes of the identical code do produce the disagreement with the default threshold value of 5%. Below is the example result of the comparison of the two consecutive runs without any code modification:

plot

At the moment I am not sure where does the variance comes from. Need to double check if the runs are seeded correctly and are reproducible. (EDIT: They are)

sjavisand others added 4 commits June 6, 2025 18:07
Adapted from pyrealm. Allows to compare two profiled runs of the code
and highlights which functions performance dropped below a threshold.
Note that at the memonet DEMENTpy exhibits high variance in runtime
of individual functions (observed up to 15%) so the check with default
settings (5% tolerance) will likley fail for the same code versions.
@Mikolaj-A-KowalskiMikolaj-A-Kowalski mentioned this pull request Jun 17, 2025
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