### Impact undici's `interceptors.dump()` reads and discards response bodies up to a configurable `maxSize`. When a response declares a `Content-Length` that exceeds `maxSize`, the request is abor...

This feature release adds a maxSize option to weakMapMemoize to bound cache growth, adds a new development-mode check that warns when a selector's cache grows without bound, improves memoization pe...

I performed object-based methods to calculate a mean (zonal statistics) for connected pixels adapted from this guide: https://developers.google.com/earth-engine/guides/image_objects#label_objects Here is a sample of the code I used the get that final layer: var objectBased = changeLayer.select([0], ['change']) var objectId = objectBased.connectedComponents({ connectedness: ee.Kernel.plus(2), maxSize: 1024}); Map.addLayer(objectId.randomVisualizer(), null, 'Objects', false); test = changeLayerClass.addBands(objectId.select('labels')); var meanClass = test.reduceConnectedComponents({ reducer: ee.Reducer.mean(), labelBand: 'labels', maxSize: 1024 }); Map.addLayer(meanClass, {min:3, max:5, palette:['red', 'yellow']}, 'Mean Class', false) var disturbanceType = meanClass.select(0).gte(4) Map.addLayer(disturbanceType, {palette:['red', 'yellow']}, 'disturbance') Export.image.toAsset({ image: disturbanceType, description: 'objectBasedDisturbanceType', scale: 10, region: geometry, maxPixels:300000000 }); I don't encounter a problem when running the analysis, but when I export the end image. The objects that are large are not exported as the other smaller objects. Result of the object-based analysis Result when visualizing the exported image How I can fix this issue?

Generic immutable undo/redo ring for Dart. Type-safe CommandHistory~~with Command~~— maxSize cap, undo/redo labels, value equality, no Flutter dependency. Changelog excerpt: - **Command merging**— `Command~~`gains `mergeWith(Command~~next) → Command~~?`(default `null`). Override it to coalesce consecutive commands of the same type into a single undoable step (e.g. per-keystroke typing). When `execute`is called and the previous command returns a non-null merge result, the top of the undo stack is extended in-place instead of growing. Undo still reverses the entire merged batch in one step. - **Named checkpoints**— full history snapshots stored by name: - `check[...]~~~~~~~~~~

Proposed change The result of a template render is coerced into a Python value via ast.literal_eval, memoized with @lru_cache(maxsize=EVAL_CACHE_SIZE) in _cached_parse_result. However, lru_cache o...

A flaw was found in libsolv. This heap buffer overflow vulnerability occurs when a victim processes a specially crafted `.solv` file containing negative size values in the `repo_add_solv` function. This leads to an undersized memory allocation and a subsequent out-of-bounds write. An attacker could exploit this to cause a denial …

CVE-2026-9149: A flaw was found in libsolv. This heap buffer overflow vulnerability occurs when a victim processes a specially crafted `.solv` file containing negative size values in the `repo_add_solv` function. This leads to an undersized memory allocation and a subsequent o...

前回の記事 ではNiquestsに最近修正された深刻なバグがあることを紹介しましたが、それで HTTP/2 や HTTP/3 の利用を不安に思い HTTP/1.1 を使うことにしていました。そして HTTP/1.1 の場合に Requests と pool_maxsize の振る舞いが大きく異なることに気がつきました。 ちなみに pool_maxsize について初めて触れたのは Requests の設定についての記事でした。 urllib3 では PoolManager の maxsize で同時接続数を制限できてデフォルトで1なのですが、 requests ではこれを10に置き換えてしまっ…

fixes #923 const cachedSchema = v.cache(baseSchema, { maxSize: 100, duration: 5_000 }) Summary by CodeRabbit New Features Added caching functionality for schemas with configurable size and time-...

I performed object-based methods to calculate a mean (zonal statistics) for connected pixels adapted from this guide: https://developers.google.com/earth-engine/guides/image_objects#label_objects Here is a sample of the code I used the get that final layer: var objectBased = changeLayer.select([0], ['change']) var objectId = objectBased.connectedComponents({ connectedness: ee.Kernel.plus(2), maxSize: 1024}); Map.addLayer(objectId.randomVisualizer(), null, 'Objects', false); test = changeLayerClass.addBands(objectId.select('labels')); var meanClass = test.reduceConnectedComponents({ reducer: ee.Reducer.mean(), labelBand: 'labels', maxSize: 1024 }); Map.addLayer(meanClass, {min:3, max:5, palette:['red', 'yellow']}, 'Mean Class', false) var disturbanceType = meanClass.select(0).gte(4) Map.addLayer(disturbanceType, {palette:['red', 'yellow']}, 'disturbance') Export.image.toAsset({ image: disturbanceType, description: 'objectBasedDisturbanceType', scale: 10, region: geometry, maxPixels:300000000 }); I don't encounter a problem when running the analysis, but when I export the end image. The objects that are large are not exported as the other smaller objects. Result of the object-based analysis Result when visualizing the exported image How I can fix this issue?