text:
Delta lake error on DeltaTable.forName in k8s cluster mode   cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.sql.catalyst.expressions.ScalaUDF.f of type scala.Function1 in instance of org.apache.spark.sql.catalyst.expressions.ScalaUDF

Hey Folks,
I am trying to merge some data to delta table in a streaming application
getting the below error, But its works fine in k8s local mode and in my laptop
`ERROR MicroBatchExecution: Query [id = fd5c019f-05f7-4f94-8eb4-cf4427201d0f, runId = 3a37f986-54ec-43f2-a396-c702a7c83928] terminated with error
py4j.Py4JException: An exception was raised by the Python Proxy. Return Message: Traceback (most recent call last):
File "/opt/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/clientserver.py", line 617, in _call_proxy
return_value = getattr(self.pool[obj_id], method)(*params)
File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 272, in call
raise e
File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 269, in call
self.func(DataFrame(jdf, self.session), batch_id)
File "/app/ingest/jobs/process_stream.py", line 108, in merge
deltaTable = DeltaTable.forName(self.spark, "{}.{}".format(self.database_name,self.table_name))
File "/usr/local/lib/python3.9/dist-packages/delta/tables.py", line 404, in forName
jdt = jvm.io.delta.tables.DeltaTable.forName(jsparkSession, tableOrViewName)
File "/opt/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in call
return_value = get_return_value(
File "/opt/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 190, in deco
return f(*a, **kw)
File "/opt/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", line 326, in get_return_value
raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling z:io.delta.tables.DeltaTable.forName.
: java.util.concurrent.ExecutionException: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (192.168.15.215 executor 1): java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.sql.catalyst.expressions.ScalaUDF.f of type scala.Function1 in instance of org.apache.spark.sql.catalyst.expressions.ScalaUDF
at java.base/java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(Unknown Source)
at java.base/java.io.ObjectStreamClass$FieldReflector.checkObjectFieldValueTypes(Unknown Source)
at java.base/java.io.ObjectStreamClass.checkObjFieldValueTypes(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultCheckFieldValues(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.readArray(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.readArray(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.readArray(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.readArray(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.readArray(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject(Unknown Source)
at scala.collection.immutable.List$SerializationProxy.readObject(List.scala:527)
at jdk.internal.reflect.GeneratedMethodAccessor3.invoke(Unknown Source)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.base/java.lang.reflect.Method.invoke(Unknown Source)
at java.base/java.io.ObjectStreamClass.invokeReadObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.defaultReadFields(Unknown Source)
at java.base/java.io.ObjectInputStream.readSerialData(Unknown Source)
at java.base/java.io.ObjectInputStream.readOrdinaryObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject0(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject(Unknown Source)
at java.base/java.io.ObjectInputStream.readObject(Unknown Source)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:87)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:129)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:85)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:136)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.base/java.lang.Thread.run(Unknown Source)
Driver stacktrace:
at com.google.common.util.concurrent.AbstractFuture$Sync.getValue(AbstractFuture.java:306)
at com.google.common.util.concurrent.AbstractFuture$Sync.get(AbstractFuture.java:293)
at com.google.common.util.concurrent.AbstractFuture.get(AbstractFuture.java:116)
at com.google.common.util.concurrent.Uninterruptibles.getUninterruptibly(Uninterruptibles.java:135)
at com.google.common.cache.LocalCache$Segment.getAndRecordStats(LocalCache.java:2410)
at com.google.common.cache.LocalCache$Segment.loadSync(LocalCache.java:2380)
at com.google.common.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2342)
at com.google.common.cache.LocalCache$Segment.get(LocalCache.java:2257)
at com.google.common.cache.LocalCache.get(LocalCache.java:4000)
at com.google.common.cache.LocalCache$LocalManualCache.get(LocalCache.java:4789)
at org.apache.spark.sql.delta.DeltaLog$.getDeltaLogFromCache$1(DeltaLog.scala:604)
at org.apache.spark.sql.delta.DeltaLog$.apply(DeltaLog.scala:611)
at org.apache.spark.sql.delta.DeltaLog$.forTable(DeltaLog.scala:507)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.deltaLog$lzycompute(DeltaTableV2.scala:83)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.deltaLog(DeltaTableV2.scala:82)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.$anonfun$snapshot$3(DeltaTableV2.scala:113)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.snapshot$lzycompute(DeltaTableV2.scala:113)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.snapshot(DeltaTableV2.scala:101)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.tableSchema$lzycompute(DeltaTableV2.scala:119)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.tableSchema(DeltaTableV2.scala:117)
at org.apache.spark.sql.delta.catalog.DeltaTableV2.schema(DeltaTableV2.scala:121)
at org.apache.spark.sql.execution.datasources.v2.DataSourceV2Relation$.create(DataSourceV2Relation.scala:178)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.$anonfun$createRelation$1(Analyzer.scala:1184)
at scala.Option.map(Option.scala:230)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.createRelation(Analyzer.scala:1156)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.$anonfun$lookupRelation$3(Analyzer.scala:1207)
at scala.Option.orElse(Option.scala:447)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.$anonfun$lookupRelation$1(Analyzer.scala:1205)
at scala.Option.orElse(Option.scala:447)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveRelations$$lookupRelation(Analyzer.scala:1197)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$13.applyOrElse(Analyzer.scala:1068)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$13.applyOrElse(Analyzer.scala:1032)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUpWithPruning$3(AnalysisHelper.scala:138)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:176)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUpWithPruning$1(AnalysisHelper.scala:138)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:323)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUpWithPruning(AnalysisHelper.scala:134)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUpWithPruning$(AnalysisHelper.scala:130)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsUpWithPruning(LogicalPlan.scala:30)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:1032)
at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:991)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:211)
at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
at scala.collection.immutable.List.foldLeft(List.scala:91)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:208)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:200)
at scala.collection.immutable.List.foreach(List.scala:431)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:200)
at org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:227)
at org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$execute$1(Analyzer.scala:223)
at org.apache.spark.sql.catalyst.analysis.AnalysisContext$.withNewAnalysisContext(Analyzer.scala:172)
at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:223)
at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:187)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:179)
at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:179)
at org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$executeAndCheck$1(Analyzer.scala:208)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:330)
at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:207)
at org.apache.spark.sql.execution.QueryExecution.$anonfun$analyzed$1(QueryExecution.scala:76)
at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:185)
at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:510)
at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:185)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:184)
at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:76)
at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:74)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:66)
at org.apache.spark.sql.Dataset$.$anonfun$ofRows$1(Dataset.scala:91)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:89)
at org.apache.spark.sql.DataFrameReader.table(DataFrameReader.scala:607)
at org.apache.spark.sql.SparkSession.table(SparkSession.scala:600)
at io.delta.tables.DeltaTable$.forName(DeltaTable.scala:699)
at io.delta.tables.DeltaTable.forName(DeltaTable.scala)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.base/java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.ClientServerConnection.sendCommand(ClientServerConnection.java:244)
at py4j.CallbackClient.sendCommand(CallbackClient.java:384)
at py4j.CallbackClient.sendCommand(CallbackClient.java:356)
at py4j.reflection.PythonProxyHandler.invoke(PythonProxyHandler.java:106)
at com.sun.proxy.$Proxy42.call(Unknown Source)
at org.apache.spark.sql.execution.streaming.sources.PythonForeachBatchHelper$.$anonfun$callForeachBatch$1(ForeachBatchSink.scala:51)
at org.apache.spark.sql.execution.streaming.sources.PythonForeachBatchHelper$.$anonfun$callForeachBatch$1$adapted(ForeachBatchSink.scala:51)
at org.apache.spark.sql.execution.streaming.sources.ForeachBatchSink.addBatch(ForeachBatchSink.scala:32)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$17(MicroBatchExecution.scala:660)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:109)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$16(MicroBatchExecution.scala:658)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:68)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:658)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:255)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
at org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:68)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:218)
at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:67)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:212)
at org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:307)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:285)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:208)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (192.168.15.215 executor 1): java.lang.ClassCastException: cannot assign instance of java.lang.invoke.SerializedLambda to field org.apache.spark.sql.catalyst.expressions.ScalaUDF.f of type scala.Function1 in instance of org.apache.spark.sql.catalyst.expressions.ScalaUDF
...
`
DELTA LAKE 2.10
SPARK_VERSION_DEFAULT=3.3.0
HADOOP_VERSION_DEFAULT=3
HADOOP_AWS_VERSION_DEFAULT=3.3.1
AWS_SDK_BUNDLE_VERSION_DEFAULT=1.11.974

Could you please look into this issue

attaching the full log
error_log.log

Finally able to resolve this issue , issue was due to some reason dependant jars like delta, kafka are not available in executor , as per the below SO response
cannot assign instance of scala.collection.immutable.List$SerializationProxy to field org.apache.spark.sql.execution.datasources.v2.DataSourceRDD
i have added the jars in spark/jars folder using docker image and issue got resolved
but i have added all my dependant packages during spark submit command, then wondering why still its missing in executor

repo: delta-io/delta


text:
New Blog Ready for Publish: SageMaker Studio for ML on DL

How to Use Amazon SageMaker Studio for Machine Learning on Delta Lake by Vedant Jain is ready to be published to delta.io.
Please see the final draft here.
Thank you! @dennyglee @MrPowers

@dennyglee @MrPowers Hi Denny/Matthew - what's the status of the blog? Please share link if it's already published. Thanks!

source: gharchive/issue

authors: ari-in-media-res cakerly-lf

repo: delta-io/website

license_type: permissive

license_source: github-api


text:
adb模式激活冰箱后依然无法连接

使用adb模式激活冰箱后应用还是提示iceboxnotinstalled冰箱未安装

由于目前冰箱接口 Icebox-sdk 尚未适配 Android R
Amarok 的隐藏应用功能无法在 Android R 或以上版本使用。
(于 Amarok v0.6.1-beta，文件隐藏也因 Android R 隐私政策调整而不可使用，但已在 master 分支修复)
WIP: 使用 DSM 代替 Icebox-sdk 完成隐藏功能

已经在 v0.7.4a4 中加入 DSM 模式替代冰箱完成免 root 隐藏

authors: deltazefiro sandboxdream

repo: deltazefiro/Amarok-Hider


text:
Issue with "GetListRow" in @site/docs/reference/scripts/get-list-row.md

Describe the problem

Page: GetListRow
Source: https://github.com/demisto/content/blob/master//Packs/CommonScripts/Scripts/GetlistRow/README.md

Issue using get-list-row two get multiple values from a single row. have a list with the name of CS-FW-Level. The list contains two headers CSFWhostname,CSFWlevel. I can get the value of the first header CSFWhostname the second gets null as header is not found CSFWlevel has a space after it. The code below fixed the issue
Screenshots

Environment

OS: [e.g. Windows]
Browser: [e.g. chrome, safari, firefox..]
Browser Version:

Suggested fix
 and strip to the following def list_to_headers_and_lines(list_data, list_separator: str):
lines_and_headers = [line.strip().split(list_separator) for line in list_data.split('\n')]
headers = lines_and_headers[0]
return headers, lines_and_headers[1:]

Hey @neonizer70,
I couldn't reproduce the issue,
Also, from looking at the code it doesn't seem like a trailing space should affect the results that way.
Can you attach logs of execution before the fix where it failed for you using the debug-mode=true argument in the playground CLI?
Thanks in advance!

link to the Jira issue

I have not received a response from you in the last two weeks, so I'm closing the bug.
Thanks again.

repo: demisto/content-docs

license: MIT


text:
Feature use combined-unique index on connect

Hi
I found issue and implement behavior.
Problem
Throw error when create a record with connects via combined-unique index to already exists.
Fix
Look-up record by unique index with combined-key after single key look-up failed.
Tests

[x] postgress
[x] mock

Hi @Angeart thanks for your contribution

source: gharchive/pull-request

authors: Angeart stijnvanderlaan

repo: demonsters/prisma-mock


text:
Benchmarks for Alternative Implementations, Inline, and InlineIfLambda

Proposed Changes
Benchmarks for Alternative Implementations, Inline, and InlineIfLambda
Types of changes
What types of changes does your code introduce to MyLib.1?
Put an x in the boxes that apply

[ ] Bugfix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your code.

[ ] Build and tests pass locally
[ ] I have added tests that prove my fix is effective or that my feature works (if appropriate)
[ ] I have added necessary documentation (if appropriate)

Further comments
If this is a relatively large or complex change, kick off the discussion by explaining why you chose the solution you did and what alternatives you considered, etc...

Benchmarks exploration (WIP)
Types of Implementations:

Normal

Reuse functions, for example, apply can be implemented in terms of bind

Alternative

Don't reuse functions, do the match implementation in the body

Variations for each:

inline

Which is known to give performance boosts

InlineIfLambda

new perfomance technique if F# 6.0

I've chosen a few functions, specifically eitherMap and map2 as they call into other functions typically and inlining all the match statements, using inline, and the new InlineIfLambda should give some interesting results.
And as I've benchmarked and done deep analysis, I've notices the composition operator >> creates a lot of code where as a lambda will produce a lot less.

Additional variations

No Composition Operator

Composition doesn't apply the Alt implementations so it leaves us with:

EitherMap

Result Normal EitherMap
Result Normal No Composition EitherMap
Result Normal Inline EitherMap
Result Normal Inline No Composition EitherMap
Result Normal InlineIfLambda EitherMap
Result Normal InlineIfLambda NoComposition EitherMap
Result Alt EitherMap
Result Alt Inline EitherMap
Result Alt InlineIfLambda EitherMap

Map2

Result Normal EitherMap
Result Normal No Composition EitherMap
Result Normal Inline EitherMap
Result Normal Inline No Composition EitherMap
Result Normal InlineIfLambda EitherMap
Result Normal InlineIfLambda No Composition EitherMap
Result Alt EitherMap
Result Alt Inline EitherMap
Result Alt InlineIfLambda EitherMap

I'm going to show the benchmarks first but then explore each of these in detail below by showing the F# Code, the decompiled code in C# and any interesting findings. I've included a SharpLab link for each so you can see the code for yourself.
Benchmark Results
EitherMap

Method
Mean
Error
StdDev
Ratio
RatioSD
Gen 0
Allocated

Result_Normal_EitherMap
19.833 ns
0.3458 ns
0.3235 ns
1.00
0.00
0.0057
48 B

Result_Normal__NoComposition_EitherMap
20.158 ns
0.1837 ns
0.1434 ns
1.01
0.02
0.0057
48 B

Result_Inlined_EitherMap
3.275 ns
0.0408 ns
0.0341 ns
0.16
0.00
-
-

Result_Inlined_NoComposition_EitherMap
3.237 ns
0.0957 ns
0.2402 ns
0.16
0.01
-
-

Result_InlinedLambda_EitherMap
3.003 ns
0.0472 ns
0.0441 ns
0.15
0.00
-
-

Result_Normal_InilnedLambda_NoComposition_EitherMap
3.449 ns
0.0953 ns
0.1904 ns
0.18
0.01
-
-

Result_Alt_EitherMap
3.301 ns
0.0908 ns
0.1637 ns
0.16
0.01
-
-

Result_Alt_Inilned_EitherMap
3.349 ns
0.0876 ns
0.1464 ns
0.17
0.01
-
-

Result_Alt_InilnedLambda_EitherMap
3.337 ns
0.0922 ns
0.1488 ns
0.17
0.01
-
-

Map2

Method
Mean
Error
StdDev
Ratio
RatioSD
Gen 0
Allocated

Result_Normal_Map2
56.549 ns
0.8351 ns
0.6974 ns
1.00
0.00
0.0172
144 B

Result_NoComposition_Map2
55.577 ns
0.6339 ns
0.5619 ns
0.98
0.02
0.0172
144 B

Result_Inlined_Map2
23.692 ns
0.2581 ns
0.2414 ns
0.42
0.01
0.0038
32 B

Result_Inlined_NoComposition_Map2
23.905 ns
0.2586 ns
0.2292 ns
0.42
0.01
0.0038
32 B

Result_InlinedLambda_Map2
11.263 ns
0.2560 ns
0.6327 ns
0.21
0.01
0.0038
32 B

Result_InlinedLambda_NoComposition_Map2
12.034 ns
0.1359 ns
0.1271 ns
0.21
0.00
0.0038
32 B

Result_Alt_Map2
6.182 ns
0.0666 ns
0.0623 ns
0.11
0.00
-
-

Result_Alt_Inlined_Map2
3.108 ns
0.0294 ns
0.0260 ns
0.06
0.00
-
-

Result_Alt_InlinedLambda_Map2
3.127 ns
0.0437 ns
0.0409 ns
0.06
0.00
-
-

Result_Alt_InlinedLambda2_Map2
3.080 ns
0.0250 ns
0.0221 ns
0.05
0.00
-
-

Result Normal EitherMap
This is base case implementation. It doesn't try to do anything fancy, in fact it tries to re-use existing functions so the implmentations don't vary. However as we can see, this seems to be leading to some performance issues.
Sharplab link
Interesting Findings (rnem)
I do find the C# decomplilation of the Example_EitherMap intersting as you can see it has many calls and classes it has to make to get to the actual matter at hand. By contrast in later variations, this will be less convoluted.
Result Normal No Composition EitherMap
This is removing the >> (composition operator) calls.
Sharplab link
Interesting Findings (rnncem)
Nothing really different from the Normal implementation.
Result Normal Inline EitherMap
This is only adding the inline keyword to all functions associated with eitherMap.
Sharplab link
Interesting Findings (rniem)
Example_EitherMap looks a lot less complicated and the performance represents that.
Result Normal Inline No Composition EitherMap
This is adding the inline keyword to all functions associated with eitherMap and removing the >> (composition operator) calls.
Sharplab link
Interesting findings (rnincem)
While there's no noticible performance gains, there's quite a bit less C# code by comparison.
Result Normal InlineIfLambda EitherMap
This is adding the InlineIfLambda attribute to the function parameters.
Sharplab link
Interesting findings (rniilem)
No performance differences from inline and the C# code doesn't look much different either.
Result Normal InlineIfLambda No Composition EitherMap
This is adding the inline keyword to all functions associated with eitherMap, adding the InlineIfLambda attribute to the function parameters and removing the >> (composition operator) calls.
Sharplab link
Interesting findings (rniilncem)
Again no noticible perfomance differences, however the C# code is greatly reduced and very readable compared to any of the previous variations. It doesn't seem to be generating classes and other static methods.
Result Alt EitherMap
Instead of writing this in terms of the either function, this will do the match statement in the body of the function.
Sharplab link
Interesting findings (raem)
Again no noticible perfomance differences, but is making classes again.
Result Alt Inline EitherMap
Same with the previous variation except it also includes the inline keyword.
Sharplab link
Interesting findings (raiem)
Again no noticible perfomance differences, but with like the [Result Normal InlineIfLambda NoComposition EitherMap], it produces simple C# code.
Result Alt InlineIfLambda EitherMap
Same with the previous variation except it also includes the InlineIfLambda attribute.
Sharplab link
Interesting findings (raiilem)
Again no noticible perfomance differences, but with like the [Result Normal InlineIfLambda NoComposition EitherMap], it produces simple C# code.

Given the Alt implementation and InlineIfLambda seems to give the best performance benefits, it's time to change the implementation of these functions.

After reading the docs on InlineIfLambda

An opt-in warning (/warnon:3517, off by default) can be turned on to indicate places in your code where InlineIfLambda arguments are not bound to lambda expressions at call sites. In normal situations, this warning should not be enabled. However, in certain kinds of high-performance programming, it can be useful to ensure all code is inlined and flattened.

Turning this on for the benchmarks.fsproj gives quite a few warnings. Going to keep digging at how to use this properly.

let inline map ([<InlineIfLambda>] mapper : 'ok -> 'ok2) value  =
    match value with
    | Ok x -> Ok(mapper x)
    | Error e -> Error e

let inline bind ([<InlineIfLambda>] binder: 'ok -> Result<'ok2, 'err>) value  =
    match value with
    | Ok x -> binder x
    | Error e -> Error e

warning FS3517: The value 'mapper' was marked 'InlineIfLambda' but was not determined to have a lambda value. This warning is for informational purposes only
warning FS3517: The value 'binder' was marked 'InlineIfLambda' but was not determined to have a lambda value. This warning is for informational purposes only.

Does this mean these implementations can't take advantage of this attribute? cc @baronfel @dsyme @mrange

@TheAngryByrd TBH I haven't looked closely on this but my guess is that you get this error message when you pass a function value that is not a lambda. Something like this:
bind x.MyBind v

x.MyBind is a function that matches the signature but is not a lambda and thus won't be inlined.
AFAICT if you provide a lambda it shouldn't give you the warning but I haven't tried.
bind (fun x -> doSomeStuff x) v

The warning seems to be generated here:
https://github.com/dotnet/fsharp/blob/edd4c3b902bb28af15460813a823346fb4c17ad3/src/fsharp/Optimizer.fs#L2754

This goes to show how big of a deal InlineIfLambda is. We get serious performance improvements while still writing clean, idiomatic F# code. Now there's even less need to resort to "imperative nonsense" :-).
Really nice work here.

authors: TheAngryByrd kerams mrange


text:
Grammar errors in readme

There are lots of annoying grammar errors in README, are you going to fix this?

There are lots of annoying grammar errors in README, are you going to fix this?

I've already fixed alot so nah

Maybe when everything will be release state


text:
Is it possible to hide the Menu's button?

Hi there,
Apologies if this has been answered elsewhere, but is it possible to hide the menu's hamburger button on an individual slide? I am giving a talk at a conference that has asked me to use a particular title slide - the idea being that all of the talks start with a uniform look-and-feel. Because of this, I would like to be able to hide the menu's button (on the title slide) and then have the button appear on all of the other slides.
I noticed that I can use the 'delayInit' configuration parameter to prevent the menu from initialising when the presentation loads. Then, once the user has advanced beyond the title slide, I can call 'initialiseMenu()' to start the menu plugin from that point onwards. This works fine, except that once the Menu has been initialised, if I go back to the title slide, the icon is present. Is there a good way to hide (and unhide) the menu's button?
Many thanks and take care,
Jim

My comment is 22 days late, so you've probably figured this out already.  My solution is to create a css class and javascript callback:
  <section class="hide-menu-button"> test slide 2 </section>

and this javascript:
    Reveal.on( 'slidetransitionend', event => {
      var menubutton = document.getElementsByClassName("slide-menu-button")[0]
      // store default display setting
      if (typeof(menubutton.__stored_display) == "undefined") {
          menubutton.__stored_display = menubutton.style.display;
      }
      if (event.currentSlide.classList.contains("hide-menu-button")) {
        console.log("current slide hide");
          menubutton.style.display = 'none';
      } else if (event.previousSlide.classList.contains("hide-menu-button")) {
        console.log("current slide show");
        menubutton.style.display = menubutton.__stored_display;
      }
    });

For the above, I wonder if it makes sense to add it to the reveal.js-menu as a default option?

authors: adgaudio jamespascoe

license: mit

license_source: bigquery


text:
Separate Search Bar for Location in Adm Service Page

Add a separate search bar to Adm Service Page so that admin shall be able to search services with an address keyword.

A second search bar to Adm Service Page for address search has been added.


text:
feat: gotouch should be able to create files in the current directory

Use case
I'd like to use gotouch not only to bootstrap complete projects but also to distribute common default files like:

.gitignore
.editorconfig
...

currently gotouch always creates a directory with the name of the module requiring the user to move the template file a level up and delete the created directory.
Possible solutions

introduce a flag to create files in specified directory instead of creating a new one
introduce some kind of 'project type' and differentiate between:

module template
file template

having different kinds of project types moves the control to the properties YAML author which sounds like from an author perspective and potentially annoying from a user perspective :smile:
Same as already mentioned in the previous issue, as soon as the details are settled I'd be happy to provide you with a PR as well!

We can add --inline bool flag when gotouch is executed. For example it will look like gotouch --inline -f path/to/file. What do you think?

Yeah! Initially I thought about something longer like --skip-module-directory- but --inline is nice and short!
Do you want to implement it yourself? Otherwise I'd see to implement it beginning next week?

You can implement it. When it is completed I can do the testing.

repo: denizgursoy/gotouch


text:
How I can apply batch normalization?

I read this paper: https://arxiv.org/abs/1502.03167 and I would to test in my model the technique.
I found the implementation for tensorflow 0.9 (function batch_norm(...)):
https://github.com/tensorflow/tensorflow/blob/r0.9/tensorflow/contrib/layers/python/layers/layers.py
but how I can apply this at the code?

There are many ways to achieve this, pointing one of those here.
in text_cnn.py replace following lines:
W = tf.Variable(tf.truncated_normal(filter_shape, stddev=0.1), name="W")
b = tf.Variable(tf.constant(0.1, shape=[num_filters]), name="b")
conv = tf.nn.conv2d(
                    self.embedded_chars_expanded,
                    W,
                    strides=[1, 1, 1, 1],
                    padding="VALID",
                    name="conv")
# Apply nonlinearity
h = tf.nn.relu(tf.nn.bias_add(conv, b), name="relu")

to this:
conv1 = tf.contrib.layers.convolution2d(
                self.embedded_chars_expanded,
                num_filters,
                [filter_size,embedding_size],
                padding='VALID',
                normalizer_fn=tf.contrib.layers.batch_norm,
                normalizer_params={'decay': 0.9},
                weights_regularizer=weight_decay)
# Apply nonlinearity
h=tf.nn.relu(conv1)

one has to add update ops to control dependencies as is the case when applying batch norm as a separate layer via tf.contrib.layers.batch_norm or not?

authors: Nitinsiwach dhwajraj fmaglia

repo: dennybritz/cnn-text-classification-tf


text:
For calling stored procedure, why does client.query() and client.execute() only return result of first query? (unlike nodejs mysql2 which gives result of all queries)

I wrote a very simple app in both node and deno. I'm calling same store procedure in both (which is just 2 select statement returning 2 rows each).
node mysql2 client.query() gives array containing 2 array result. But deno mysql client.query() and client.execute() both only give result for first select statement.
Any idea why this is happening?

Unfortunately, the Deno MySQL module does not have built-in support for handling multiple result sets from stored procedures. To work around this limitation, you can split your stored procedure into multiple procedures, each returning a single result set, and then call each of them sequentially in your code.

repo: denodrivers/mysql


text:
feat: prevent duplicate routes when generating manifest

closes https://github.com/denoland/fresh/issues/1378
Now if someone has e.g. routes/user.ts and routes/user.tsx we'll throw an error message when generating the manifest, instead of allowing people to shoot themselves in the foot and have massive confusion / pain.
I need some help with the test. It definitely asserts the functionality, but if the startup process doesn't error, the test hangs. Is there an easy way to tell Deno.Command to stop after X seconds?

The test becomes a little easier when you create a ./tests/fixture_my_test folder instead of creating a project from scratch with every run.
What do you mean the startup process doesn't error? Does it print the correct exit code or is that wrong too? Wondering if it's either not being teared down correctly or if the error message isn't flushed before the process aborts.

Ok, I can refactor it to introduce a new test folder. I have another PR planned after this in the same space, so maybe it's good to have a new fixture.
What I mean is the following. When I do:
const cliProcess = new Deno.Command(Deno.execPath(), {
  args: [
    "run",
    "-A",
    `tests/fixture_route_analysis/dev.ts`,
  ],
  stdin: "null",
  stdout: "piped",
  stderr: "piped",
});

and the project doesn't error (because I reverted my fix, in order to test that the test fails correctly), then the test just runs forever. Because the server successfully starts up.

In theory this is ready to review, but we've hit the flaky test on windows (noting the OS for record keeping).

LGTM, Re-ran the CI for now. Not sure why it was flaky

authors: deer marvinhagemeister

repo: denoland/fresh


text:
Fix showing bundler v1 deprecation warnings in PR message and logs

What are you trying to accomplish?
This PR ensures that deprecation warnings for bundler v1 are properly displayed in both the pull request message and the logs.
Anything you want to highlight for special attention from reviewers?
There are two key fixes in this PR:

PR Message Warning: The bundler v1 deprecation warning is now correctly displayed in the PR message without including the "Bumps rails..." message within the warning block.
Example of the fixed warning:

Logging Warning Consistency: In the log output, the second deprecation warning message ("Please upgrade to version v2.") should properly work under the updater thread.

Checklist
After fix:

[x] I have run the complete test suite to ensure all tests and linters pass.
[ ] I have thoroughly tested my code changes to ensure they work as expected, including adding additional tests for new functionality.
[x] I have written clear and descriptive commit messages.
[x] I have provided a detailed description of the changes in the pull request, including the problem it addresses, how it fixes the problem, and any relevant details about the implementation.
[x] I have ensured that the code is well-documented and easy to understand.

Tested in https://github.com/dsp-testing/dependabot-all-updates-test-grouped-10554-3
PR warning message is showing properly

Log is fixed.

CC: @Nishnha , @abdulapopoola

/report

repo: dependabot/dependabot-core


text:
Inline updater specs

🖼 Context
While trying to make changes to the updater logic, it's become apparent that our tests have become difficult to work with. This is a first pass at inlining setup so that tests can be reasoned about as individual units.
The approach here is generally:

Remove let statements which are not overridden
Stub calls to Dependabot.logger
Exract setup of job, service and updater objects into callable methods
Use :point_up: to bring setup into individual specs

I had a look at the FIXMEs about errors supposed to be raised, and they do seem correct to me?
The updater does not raise errors but reports them to Sentry/Backend instead and that's what the specs seem to be checking. The setup is a bit cumbersome through stubbing checker#can_update? to raise the different errors but I'd say it's working fine.

Ah, you're right! I had mistakenly thought that we were relying on this line to raise errors, and that was happening in a separate context. But it's happening in a before block via raise error.
I'll go ahead and remove those FIXMEs 😄

Separately, I left two FIXMEs because specs were failing due to the file mode being changed for me locally. That doesn't seem to affect CI. Do you know why that happens? I can remove those separately if it's expected behavior.


text:
DotArray Syntax in Deployer 4.0.0 not supported anymore?

Q
A

Issue Type
Question

Deployer Version
4.0.0

Local Machine OS
Gitlab CI Docker Container (Debian)

Remote Machine OS
Ubuntu 14.04

Description
I've just updated from Deployer version 3.3.0 to version 4.0.0 and I have a question regarding the DotArray Syntax.
In my deploy scripts I was using env('server.host') to obtain the defined server hostname.
I've changed it to get('server.host') for Deployer 4.0.0, but now I'm getting the following error message:
Configuration parameter `server.host` does not exists.

So, the question is: How can I obtain the server host via the environment variables with Deployer 4.0.0?

I can confirm with env('server.name') . My quick fix was:
get('server')['name'];

DotArray was deprecated in Deployer 4, but i think we can return some of it functionality back to Collection class.  So it will be possible to use dot notation. Btw @t33k solution correct.

@elfet There's a difference between deprecating and completely removing a feature. :)

@t33k: Thank you for the hint. get('server')['host'] did the trick for me. :)
@elfet: Although @mootari ist right, Deployer 4.0.0 was/is a major release, so removing features or breaking the API isn't a problem imo.
But it would have helped a lot to mention in the UPGRADE.md, that the DotArray syntax isn't supported anymore.

@tinogo: I'm totally fine with feature removal / changes, too. I merely wanted to point out that "deprecated" doesn't mean "removed" and might cause confusion if used that way.

Returned part of functionality back. Please, check master branch.

Fixed.

not working in v4.0.2 for me using serverList('servers.yml') and dep staging.foo
I do get:
[RuntimeException]
  Stage or server `staging.foo` was not found.

Dumping
$deployer = Deployer::get();
var_dump($deployer->servers);

I can see 'staging.foo' does exist.
From reading the code the error is logic. In Collection the DotArray is implemented by exploding the lookup key and searching for some nested values. However I do see that in ServersCollection::collection the key is just used "as is" with the dot.
Changing private to protected for  ::collection in Collection() and overriding get() and  has()  in ServerColleciton does fix the problem for me. PR to follow.

Created PR https://github.com/deployphp/deployer/pull/913

authors: elfet mootari pniederlag t33k tinogo

repo: deployphp/deployer


text:
🛑 Derailed Home is down

In 0085fc5, Derailed Home (https://derailed.one) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Derailed Home is back up in b4b745d.

repo: derailed-org/derailed-oss-status


text:
Missing measurements in PDF export file

App version
1.8.2
Bug Description
I am having a problem with exporting measurements to PDF, especially in the table containing the data. Some of these are missing from the output file, in particular I notice that this happens when you have to move to the next page. Between the measurement of the previous page and the one immediately after, some measurements are not printed.
Steps to Reproduce
No response
Details (Screenshots, Debug Info, Configurations)
Attachments

Thanks, I can reproduce between 1-2 measurements missing at page transitions (tmp.pdf)
Code to reproduce

final List<FullEntry> measurements = [
  for (int sys = 1; sys < 2000; sys++)
    (BloodPressureRecord(
      time: DateTime.now().add(Duration(minutes: sys)),
      sys: Pressure.mmHg(sys),
      dia: null,
      pul: null
    ), Note(time: DateTime.now().add(Duration(minutes: sys))), []),
];
final pdf = await PdfConverter(
  PdfExportSettings(),
  await AppLocalizations.delegate.load(const Locale('en')),
  Settings(),
  ExportColumnsManager(),
).create(measurements);
File('tmp.pdf').writeAsBytesSync(pdf);

authors: Intranox derdilla

repo: derdilla/blood-pressure-monitor-fl


text:
Allow the use of the Arduino Leonardo

The Arduino Leonardo (atmega32u4) does not have an UART0 but only UART1.
I have used the same syntax has the official Arduino IDE.
Another solution is to change it inside the method like here

I chose the other solution, see commits 152751f9715ce5fd6f272c0f9ce2c8aeab7dbbe9 and 08f085379f8cc53c7104d0d180dae48d2df8c5bb, they should fix your issue.

Ok, nice approach, so it should work on atmega8 that have a single uart and use TXEN register.

authors: descampsa romainreignier

repo: descampsa/ardyno


text:
Added Target props and some other important props.

I created this pull request to solve the issue when TS throws an error when we try to use the target prop on the patched link component. I also added other useful props one may need when working with this link element.

That looks like it did it. Thanks again!
Jay
------ Original Message ------
From "Abdulrahim2567" @.>
To "designly1/nextjs13-progress" @.>
Cc "Subscribed" @.***>
Date 5/25/2024 4:22:06 AM
Subject [designly1/nextjs13-progress] Added Target props and some other
important props. (PR #6)

I created this pull request to solve the issue when TS throws an error
when we try to use the target prop on the patched link component. I
also added other useful props one may need when working with this link
element.

You can view, comment on, or merge this pull request online at:
https://github.com/designly1/nextjs13-progress/pull/6
Commit Summary
f4cad5f
https://github.com/designly1/nextjs13-progress/pull/6/commits/f4cad5f45c330b79f286c5314d906d10546ef0aa
have added the target prop as well as other useful link props
b8bb0fa
https://github.com/designly1/nextjs13-progress/pull/6/commits/b8bb0fa4632436ce7d55be259eb6c46668945779
modified props
File Changes
(1 file https://github.com/designly1/nextjs13-progress/pull/6/files)
Msrc/lib/router-events/patch-router/link.tsx
https://github.com/designly1/nextjs13-progress/pull/6/files#diff-841f34336d720abfe5f0ba1ebfbfc73f64b5c42cb1b778b80c718d56f19cbb23
(13)
Patch Links:
https://github.com/designly1/nextjs13-progress/pull/6.patch
https://github.com/designly1/nextjs13-progress/pull/6.diff
—
Reply to this email directly, view it on GitHub
https://github.com/designly1/nextjs13-progress/pull/6, or unsubscribe
https://github.com/notifications/unsubscribe-auth/ALHCNZCMAVDCVGVUFF67Q5LZEBJ35AVCNFSM6AAAAABIIX2GE6VHI2DSMVQWIX3LMV43ASLTON2WKOZSGMYTMOBWG4YDSMQ.
You are receiving this because you are subscribed to this
thread.Message ID: @.***>

My pleasure!


text:
Remove line separator detection logic

This is now fully handled by the IntelliJ components in the embeddable compiler.
Waiting on merge of:

#7235
#7237
#7238
#7240
#7250

@3flex is this ready for review?

I messed up from mobile and I can move it back to draft

authors: 3flex BraisGabin cortinico

repo: detekt/detekt


text:
border offset specified window name

I have a problem with matlab, xborders cant get the proper window size from it, is it possible to add a window offset just for matlab?

Fixed by the new versions

license: Unlicense


text:
Failed to generate additional resources

Running OS_hardening module throws the following error,
Error: /Stage[main]/Os_hardening::Minimize_access/File[/usr/bin]: Failed to generate additional resources using 'eval_generate': Too many levels of symbolic links @ rb_file_s_stat - /usr/bin/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/X11/lzcat

OS_hardening is at version 1.1.2 on patched Debian Jessie. I'm instantiating the module with these parameters,
class spacex_os_hardening_rules {
  class { "os_hardening":
    system_environment        => "default",
    desktop_enabled           => false,
    enable_ipv4_forwarding    => false,
    enable_ipv6_forwarding    => false,
    enable_ipv6               => false,
    arp_restricted            => true,
    extra_user_paths          => [],
    umask                     => "027",
    password_max_age          => 182,
    password_min_age          => 7,
    auth_retries              => 5,
    auth_lockout_time         => 300,
    login_timeout             => 60,
    allow_login_without_home  => true,
    passwdqc_enabled          => false,
    # passwdqc_options          => "",
    allow_change_user         => true,
    enable_module_loading     => true,
    load_modules              => [],
    enable_sysrq              => false,
    enable_core_dump          => false,
    enable_stack_protection   => true,
    # cpu_vendor                => 'intel'
    root_ttys                 => ["console","tty1","tty2","tty3","tty4","tty5","tty6","ttyS0","ttyS1"],
    # whitelist                 => [],
    # blacklist                 => [],
    # remove_from_unknown       => false,
    # dry_run_on_unknown        => false,
  }
}

This bug was due to a erroneous symlink, originally created by X11.
ls -alh /usr/bin | grep X11
lrwxrwxrwx  1 root   root       1 May  6  2013 X11 -> .

That X11 symlink points to it's own parent directory, and thus the OS Hardening module recurses on it. The issue was solved by having Puppet delete that file before applying the hardening module.
http://ubuntuforums.org/showthread.php?t=829402

repo: dev-sec/puppet-os-hardening


text:
When creating a new tile, the tile border is left on screen, even after moving the tile.

See the video.
https://user-images.githubusercontent.com/30846057/153761498-7fd9f7f6-9f57-4b91-88bd-c9056e6a4972.mp4
I've used FindTheCulprit to narrow it down to Perfect Vision, and disabled all modules other than perfect vision to confirm.
Environment:
Foundry VTT 9.249
DnD5e System 1.5.7
PerfectVision 3.6.13
Please let me know if you need other information.
Thanks!

Oh, refreshing eliminates the left-over border, so it appears to be temporary. Also, it's not interactive; can't click on it or move it, so it appears to be just a graphics glitch.

Thanks for the report! Turns out it's actually caused by a core Foundry bug (I reported it). I included a fix for this issue in the latest PV release.

You know, I kinda figured it had to be something in core. Made no sense
that PV should be affecting tile placement like that. Thanks for letting me
know and for the fix.
On Sun, Feb 13, 2022 at 11:28 AM dev7355608 @.***>
wrote:

Thanks for the report! Turns out it's actually caused by a core Foundry
bug (I reported it). I included a fix for this issue in the latest PV
release.
—
Reply to this email directly, view it on GitHub
https://github.com/dev7355608/perfect-vision/issues/214#issuecomment-1038281253,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AHLKY2PQE6OSWOHZNKO7UJTU27S3PANCNFSM5OJHGOZA
.
Triage notifications on the go with GitHub Mobile for iOS
https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675
or Android
https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.
You are receiving this because you authored the thread.Message ID:
@.***>


text:
Autoreplay feature

Can you add autoReplay features or input number of replay as needed

you can use any macro software to config a simple combination in order to click on play button each 35 seconds
exemple :

repo: devbutlazy/Blum-AutoClicker


text:
[Docker-in-Docker] Missing option to restart docker from inside the devcontainer

Using default devcontainer setup:
"name": "Docker in Docker",
// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
"image": "mcr.microsoft.com/devcontainers/base:bullseye",

"features": {
	"ghcr.io/devcontainers/features/docker-in-docker:2": {
		"version": "latest",
		"enableNonRootDocker": "true",
		"moby": "true"
	}
}

The problem I experienced is, when I have changed my MTU on my host docker to e.g. 1332 I get connection disconnects inside the containers in my devcontainer environment. This is due to mismachting MTU values. Resetting my MTU on my host to 1500 resolves this problem.
So far this is no problem. Adjusting the MTUs accordingly should solve my issues, but I have to restart the docker daemon inside the devcontainer for that. Trying systemctl restart docker yields following message:

"systemd" is not running in this container due to its overhead.
Use the "service" command to start services instead. e.g.:
service --status-all

Executing  service --status-all yields:

[ ? ]  hwclock.sh
[ - ]  procps
[ - ]  rsync
[ - ]  sudo

It's also necesscary to be able to enable IPv6 for Docker ;)

Implemented missing scripts in #358

Thanks for putting up the PR (will take a peek).  Alternatively, executing the entrypoint script would start docker again (/usr/local/share/docker-init.sh)

repo: devcontainers/features


text:
[Req]: Color Conversion Tool

Contact Details
No response
Explain the proposed feature
Tool for converting colors between Hex/RGB/HSL/etc. A color picker would also be nice.
Explain the possible use cases for the feature
No response
Any other details you would like to provide?
No response

Hi! I think I can do this, could I get it assigned and I'll give it a shot :)

@kubahasek Awesome! Feel free to reach out if you have questions

@dlford
Hi, as much as I hate to annoy you, I am having some issues making the tool. I have gotten it to work with a color picker and as well as when you enter the HEX value, but I cannot get it to react to any other inputs properly at least.
Could you please take a look at https://github.com/kubahasek/developertools.tech/tree/color-tool and possibly point me to what's wrong? Thanks a lot

@kubahasek of course, not a problem at all! I'll take a look soon and get back to you.

@kubahasek great job on this so far!
Looks like we aren't catching the errors here - https://github.com/kubahasek/developertools.tech/blob/color-tool/pages/colors.tsx#L88
I think a better approach would be to set up all the onChange calls to just assign the value for that input and use a useEffect hook to update the others based on which input was changed, or show the user error if the input is not valid.
Alternatively you could use defaultValue instead of value on the inputs so their values will change when typed into, and just catch the errors.
Here's an example of a similar approach - https://github.com/developertools-tech/developertools.tech/blob/main/components/base64/Base64InputOutput.tsx#L38-L75
Feel free to reach out if you need more information!

@dlford
Hello! I have reshuffled the logic a little bit, but I am still having issues.
LINK The main problem is with this line (only there to demonstrate). If I use value, it works properly when the others change but it's practically impossible to change what's in the input because it holds the structure set out in the value (h, s, l).
I have tried different approaches, but if I use default value then the inputs aren't obviously reacting to the others changing.

@kubahasek I see, I'll take a look and see what I can figure out.

@kubahasek You're on the right track, just use value instead of  defaultValue since you're now handling the errors and still setting the value on change.
I think all that's left is to update the color picker when the text inputs change, and add tests.

@dlford I know that, but I will need to do some more digging. As soon as I set value={r, g, b} it becomes impossible to change the values in the inputs properly, so I need to look into that
As for tests, I will do my best, but I've never written them 😅

@kubahasek Ah I see, let me know if you still need help! As for the tests have a look at some of the other tests, I think you'll find it's easier than you might think, but I'm happy to help with that too if needed 😁

@dlford
I think I've exhausted all my options to try and make it work properly. The code should now be in the state where everything works properly apart from the editing really, which still acts all funky whenever you try to manually input a color.
As for tests, I haven't yet started those, as I assume that should be done after the page is actually done.

@kubahasek you are correct about the tests, go ahead and submit a PR if you haven't yet and mark it as a draft, I'll take a look and see what I can figure out.

authors: dlford kubahasek


text:
Thoughts on TypeScript support?

First of all, great project. The simplicity is beautiful.
I am curious on your thoughts on adding typings in some form to this repo from a maintainer perspective. I am happy to do the work here, but don't want to create a maintenance burden.
In order of personal preference:

Rewrite/convert the package with TypeScript, using your microbundle package?
Add .d.ts files to the current implementation?
Create a definitely typed package for @types/vhtml?

For my project, I cheated by pulling in Preact's type definitions.
I have a modules.d.ts in my project directory that looks like this:
declare module "vhtml" {
  function h(name: string, attrs?: Record<string, any>): string;

  // Let's borrow JSX types from Preact
  import { JSX } from "preact";
  namespace JSX {
    export import IntrinsicElements = JSX.IntrinsicElements;
    export type Element = string;
  }
}

Obviously very hacky, needs much improvement, and not recommended for professional setups.

I wrote some type definitions and made a PR to [DefinitelyTyped](https://github.com/DefinitelyTyped/DefinitelyTyped/pull/50147#issuecomment-746236878. If you need the typings right now, you might want to look at [my repository](https://github.com/ pastelmind/vhtml-types) instead.

@types/vhtml is now public. I think we can close this issue.

Nice work @pastelmind

authors: AndrewLeedham pastelmind

repo: developit/vhtml


text:
Addlikes

Hello, I hope you're doing well! I have completed the initial implementation of the Add likes of the ES6-Capstone project and I would greatly appreciate your code review. I've opened a pull request with the changes in a feature branch called test.
In this pull request, you will find the entire codebase for the ES6-Capstone project committed as a single chunk of code. As we discussed, please focus on reviewing the code for issues related to best practices and clean code rules.
I kindly request you to review the code and provide your valuable feedback. Feel free to comment directly on the pull request or raise any concerns you may have. Your input will greatly contribute to enhancing the quality and functionality of the project.
Thank you for taking the time to review my code. I'm looking forward to your feedback!


text:
Can't start successfully

Problem description

When I type docker compose up, there is something wrong.
Extra information
[+] Building 1.3s (11/11) FINISHED
=> [docker-elk_logstash internal] load build definition from Dockerfile                                                           0.0s
=> => transferring dockerfile: 32B                                                                                0.0s
=> [docker-elk_elasticsearch internal] load build definition from Dockerfile                                                      0.0s
=> => transferring dockerfile: 32B                                                                                0.0s
=> [docker-elk_setup internal] load build definition from Dockerfile                                                              0.0s
=> => transferring dockerfile: 32B                                                                                0.0s
=> [docker-elk_kibana internal] load build definition from Dockerfile                                                             0.0s
=> => transferring dockerfile: 32B                                                                                0.0s
=> [docker-elk_logstash internal] load .dockerignore                                                                              0.0s
=> => transferring context: 34B                                                                                0.0s
=> [docker-elk_elasticsearch internal] load .dockerignore                                                                         0.0s
=> => transferring context: 34B                                                                                0.0s
=> [docker-elk_setup internal] load .dockerignore                                                                                0.0s
=> => transferring context: 35B                                                                                0.0s
=> [docker-elk_kibana internal] load .dockerignore                                                                                0.0s
=> => transferring context: 34B                                                                                0.0s
=> CANCELED [docker-elk_logstash internal] load metadata for docker.elastic.co/logstash/logstash:8.3.1                            1.1s
=> ERROR [docker-elk_setup internal] load metadata for docker.elastic.co/elasticsearch/elasticsearch:8.3.1                        1.0s
=> CANCELED [docker-elk_kibana internal] load metadata for docker.elastic.co/kibana/kibana:8.3.1                                  1.0s

[docker-elk_setup internal] load metadata for docker.elastic.co/elasticsearch/elasticsearch:8.3.1:

failed to solve: rpc error: code = Unknown desc = failed to solve with frontend dockerfile.v0: failed to create LLB definition: rpc error: code = Unknown desc = error getting credentials - err: exec: "docker-credential-desktop": executable file not found in $PATH, out: ``
Stack configuration

Nothing changed. I cloned and cd docker-elk and type docker compose up
Docker setup

$ docker version

[OUTPUT HERE]
Client: Docker Engine - Community
 Version:           20.10.17
 API version:       1.41
 Go version:        go1.17.11
 Git commit:        100c701
 Built:             Mon Jun  6 23:03:17 2022
 OS/Arch:           linux/amd64
 Context:           default
 Experimental:      true

Server: Docker Engine - Community
 Engine:
  Version:          20.10.17
  API version:      1.41 (minimum version 1.12)
  Go version:       go1.17.11
  Git commit:       a89b842
  Built:            Mon Jun  6 23:01:23 2022
  OS/Arch:          linux/amd64
  Experimental:     false
 containerd:
  Version:          1.6.6
  GitCommit:        10c12954828e7c7c9b6e0ea9b0c02b01407d3ae1
 runc:
  Version:          1.1.2
  GitCommit:        v1.1.2-0-ga916309
 docker-init:
  Version:          0.19.0
  GitCommit:        de40ad0

$ docker-compose version

[OUTPUT HERE]
docker-compose version 1.25.0, build unknown
docker-py version: 4.1.0
CPython version: 3.9.2
OpenSSL version: OpenSSL 1.1.1n  15 Mar 2022

Container logs

$ docker-compose logs

[OUTPUT HERE]
Attaching to

First of all, beware that Compose version 1.25.0 isn't supported, as per the README.
Here the actual error is "docker-credential-desktop": executable file not found in $PATH. It seems like you are using Docker Desktop on Linux, so Docker is trying to authenticate with the registry via the docker-credential-desktop executable, but this executable doesn't exist.
The error isn't specific to docker-elk, chances are that you would get the same error running any Compose file.
Please check your installation, as well as your $HOME/.docker/config.json file.

First of all, beware that Compose version 1.25.0 isn't supported, as per the README.
Here the actual error is "docker-credential-desktop": executable file not found in $PATH. It seems like you are using Docker Desktop on Linux, so Docker is trying to authenticate with the registry via the docker-credential-desktop executable, but this executable doesn't exist.
The error isn't specific to docker-elk, chances are that you would get the same error running any Compose file. Please check your installation, as well as your $HOME/.docker/config.json file.

Thank you for solving my problem. After  rm $HOME/.docker/config.json, now everything works well.

repo: deviantony/docker-elk