No checkpoints found

I am trying to run the inference with some checkpoints I downloaded from the PseudoLidar repository. The files are:

pyramid_cars_with_aug_example_scratch_300_val-00120000.data-00000-of-00001
pyramid_cars_with_aug_example_scratch_300_val-00120000.index
pyramid_cars_with_aug_example_scratch_300_val-00120000.meta

I put them into:

AVOD/avod/data/outputs/pyramid_cars_with_aug_example_scratch_300_val-00120000/checkpoints

And placed the pyramid_cars_with_aug_example_scratch_300_val-00120000.config into the folder with the same name. The file name matches the checkpoint_name inside the config
Then used the next line:

python avod/experiments/run_inference.py --checkpoint_name='pyramid_cars_with_aug_example_scratch_300_val-00120000' --data_split='test' --ckpt_indices=120 --device='1'

This is the output:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:458: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:459: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:460: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint16 = np.dtype([("qint16", np.int16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:461: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:462: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  _np_qint32 = np.dtype([("qint32", np.int32, 1)])
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:465: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
  np_resource = np.dtype([("resource", np.ubyte, 1)])
/content/AVOD/avod/data/outputs/pyramid_cars_with_aug_example_scratch_300_val-00120000/pyramid_cars_with_aug_example_scratch_300_val-00120000.config
2020-01-10 22:31:11.976810: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2020-01-10 22:31:11.976906: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2020-01-10 22:31:11.976919: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2020-01-10 22:31:11.976944: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2020-01-10 22:31:11.976954: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
No checkpoints found
Traceback (most recent call last):
  File "avod/experiments/run_inference.py", line 136, in <module>
    tf.app.run()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/platform/app.py", line 48, in run
    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
  File "avod/experiments/run_inference.py", line 132, in main
    args.ckpt_indices)
  File "avod/experiments/run_inference.py", line 71, in inference
    model_evaluator.run_latest_checkpoints()
  File "/content/AVOD/avod/core/evaluator.py", line 373, in run_latest_checkpoints
    checkpoint_to_restore = self._saver.last_checkpoints[ckpt_idx]
IndexError: list index out of range

Working on Google Colab with python 3 and tensorflow 1.3
What am I doing wrong? Thank you for your help

Hello. Were you able to solve this issue?

No, I have been stucked with this error for over 2 months :/

Hello. Were you able to solve this issue?

I think I solved this problem. I'm also using some downloaded pretrained weights in the three files you mentioned.
At first, I had the same issue in #132 , so I manually set this line to num_checkpoints = 1
Then I had the same issue as yours. So I manually set this line as "PATH_TO_CKPT/checkpoint name". The checkpoint name in your case should be pyramid_cars_with_aug_example_scratch_300_val-00120000 without any extension, and PATH_TO_CKPT should be the path you put these three files in.
Then I'm able to load the checkpoint and run evaluations.

I think I solved this problem. I'm also using some downloaded pretrained weights in the three files you mentioned.
At first, I had the same issue in #132 , so I manually set this line to num_checkpoints = 1
Then I had the same issue as yours. So I manually set this line as "PATH_TO_CKPT/checkpoint_name". The checkpoint_name in your case should be pyramid_cars_with_aug_example_scratch_300_val-00120000 without any extension, and PATH_TO_CKPT should be the path you put these three files in.
Then I'm able to load the checkpoint and run evaluations.
Updates: well, I saw that your error is on a different line, but I think these two things are the same. You just manually set the path to your checkpoints.

Work!

PseudoLidar repository.

Hi! I wonder where you download these checkpoints from.


UART of Auvidea J120 with TX2

maybe it's not suitable to raise an issue here. but really i cannot find another place to discuss J120+TX2. I want to use the UART of Auvidea J120 and TX2. but i don't know physically where is the uart port on J120. besides, i see /dev/ttyTHS1, /dev/ttyTHS2, /dev/ttyTHS3. don't know which port could I use? thanks so much if anyone could give a hint.

You are welcome to ask questions here, we'll try to help.
As for UART on J120 you may check out the following documents:

J120 Manual from Auvidea. In particular, look at page 6 - you will see the location of UART 0/2 (which is J7 connector). One thing to keep in mind is our build was tested with J120 Rev 4. In Rev 6 there were some changes to this port - make sure to read page 19 for details. If possible, I would recommend using Rev 2-5 or 7. If you still have questions or concerns then I recommend contacting Auvidea support.
Relevant parts of our assembly guides:

TBS Discovery
IRIS+

If everything is wired properly, UART port will be mapped to /dev/ttyTHS1 by default.

thanks so much! sadly still not work. i guess there's something with my carrier board. thank you alexey

thanks so much! sadly still not work. i guess there's something with my carrier board. thank you alexey

If you suspect something is wrong with J120 then you can try using Jetson DevKit board UART port (J17) - we documented it here. This will allow you to test Pixhawk - Jetson connectivity. If it works with dev board and does not work with J120 then you probably should contact Auvidea support.


The component is not rerendered when the value becomes empty again

Hi. I have this case:
I fill in the wrong code. Next, I have code validation.
If the pin code is incorrect, I write value = "" to state and pass it to ReactCodeInput.
But ReactCodeInput is not rerender. Fields are also filled with incorrect code.
You can see my example here:
https://codesandbox.io/s/react-code-input-example-td82z?file=/src/App.js

I have a similar issue with redux-form. Resetting or destroying form, removes the value from redux but values are still showing in the input fields.

Any news on this? Or workaround?

https://github.com/40818419/react-code-input/issues/69#issuecomment-506657412

# 69 (комментарий)

Is it worked for you?
I tried it. In my case, the input value is overwritten in the state, but the rerendering does not occur.

If that's the case, you can always force a render ;)
const [render, setRender] = React.useState(true)

setRender(v => !v) // This will force you component to re-render

I use this technique whenever I need to force re-rendering (after updating a ref, or an internal state)

If that's the case, you can always force a render ;)
const [render, setRender] = React.useState(true)

setRender(v => !v) // This will force you component to re-render

I use this technique whenever I need to force re-rendering (after updating a ref, or an internal state)

It is worked. Thank you!)


Automated Stress Tests, Multiple Keyspaces, many fixes

This is unfortunately a big PR with multiple features dumped into one branch.    The overview:

Addition of a new "stress" submodule, with several stress tests designed to be run either locally or in a cluster:  an ingestion stress test, a streaming/reading stress test, and an in-memory querying stress test.
Ability to read from or write to a dataset in any keyspace, using the "database" option in both Spark and the CLI.  Internally, revamped stuff everywhere to refer to a DatasetRef instead of just a string Dataset name.

the metadata tables dataset and columns are presently stored in each keyspace as well.  However, in the future all the datasets and columns will be stored in a "FiloDB system" keyspace.

Fix CLI bug where delete command only deleted the metadata.  Now it drops the chunks and chunkrowmap data tables as well.
Added a new CLI truncate command to truncate datasets
Fixed issue #84 with ingestion in Spark 1.5 after sort
More CLI fixes, esp for creating a dataset on a dataset that already exists
Enabled Akka message tracing / debug logging
Started an internal "client" Scala API to abstract interfacing with the NodeCoordinatorActor
Ingestion no longer flushes at the end of each partition write, but flushes at the end of entire ingestion command

NOTES:

Discovered that in cluster mode the flushing wasn't really working properly.  This will be fixed in a subsequent PR.  For now there might be more unwritten data staying in memtables.

I can confirm the issue 84 of tungsten sorting in spark fixed in this PR.

Yong, many thanks!   Great to hear that.

On Apr 14, 2016, at 7:32 AM, Yong Zhang<EMAIL_ADDRESS>wrote:
I can confirm the issue 84 of tungsten sorting in spark fixed in this PR.
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Reply to this email directly or view it on GitHub https://github.com/tuplejump/FiloDB/pull/91#issuecomment-209971916

hm, even this PR works with tungsten sort, but when ingesting data into same C* as tested before, I got following new error:
java.lang.NoSuchMethodError: com.datastax.driver.core.Session.newSimpleStatement(Ljava/lang/String;)Lcom/datastax/driver/core/SimpleStatement;
at com.websudos.phantom.builder.query.ExecutableStatement$class.statement(ExecutableQuery.scala:54)
at com.websudos.phantom.builder.query.Query.statement(Query.scala:69)
at com.websudos.phantom.builder.query.ExecutableStatement$class.future(ExecutableQuery.scala:58)
at com.websudos.phantom.builder.query.Query.future(Query.scala:69)
at com.websudos.phantom.builder.query.ExecutableQuery$class.singleFetch(ExecutableQuery.scala:116)
at com.websudos.phantom.builder.query.SelectQuery.singleFetch(SelectQuery.scala:48)
at com.websudos.phantom.builder.query.SelectQuery.one(SelectQuery.scala:212)
at filodb.cassandra.metastore.DatasetTable$$anonfun$getProjection$1.apply(DatasetTable.scala:90)
It looks like FiloDB fat jar in this PR includes "com.datastax.driver.core.Session" class. In our cluster, we always already includes "spark connector" jar released by datastax. The version is 1.5.0.
The compatible check can be found here:
https://github.com/datastax/spark-cassandra-connector
So it comes with the Cassandra Java driver 2.1
If I checked the version of the class, it looks like the method newSimpleStatement was NOT in version 2.1 and 3.0:
https://github.com/datastax/java-driver/blob/2.1/driver-core/src/main/java/com/datastax/driver/core/Session.java
The only version include this method is in version 2.2:
https://github.com/datastax/java-driver/blob/2.2/driver-core/src/main/java/com/datastax/driver/core/Session.java
But version 2.2 is never depended on in Spark Cassandra Connector.
In your sbt file, do you depend on Spark Cassandra connector? What version you depend on? Why C* Java Driver 2.2 being linked, and this cause some problem in our cluster environment.
In addition to that, I tried to start the spark-shell using following conf:
--conf spark.driver.userClassPathFirst=true --conf spark.executor.userClassPathFirst=true
Hope to use "filodb-spark-assembly-0.2.1-SNAPSHOT.jar" generated in this PR to override the classpath, but I still got the same error when I tried to do "save()" method.

Yong,
Nope we don’t depend on the Cass Connector.
One option is to downgrade the version of Phantom to use the older java driver.  If you look in the dse-4.8 branch, you will see the older version of Phantom which uses the C* Java driver 2.1…
-Evan

On Apr 14, 2016, at 8:53 AM, Yong Zhang<EMAIL_ADDRESS>wrote:
hm, even this PR works with tungsten sort, but when ingesting data into same C* as tested before, I got following new error:
java.lang.NoSuchMethodError: com.datastax.driver.core.Session.newSimpleStatement(Ljava/lang/String;)Lcom/datastax/driver/core/SimpleStatement;
at com.websudos.phantom.builder.query.ExecutableStatement$class.statement(ExecutableQuery.scala:54)
at com.websudos.phantom.builder.query.Query.statement(Query.scala:69)
at com.websudos.phantom.builder.query.ExecutableStatement$class.future(ExecutableQuery.scala:58)
at com.websudos.phantom.builder.query.Query.future(Query.scala:69)
at com.websudos.phantom.builder.query.ExecutableQuery$class.singleFetch(ExecutableQuery.scala:116)
at com.websudos.phantom.builder.query.SelectQuery.singleFetch(SelectQuery.scala:48)
at com.websudos.phantom.builder.query.SelectQuery.one(SelectQuery.scala:212)
at filodb.cassandra.metastore.DatasetTable$$anonfun$getProjection$1.apply(DatasetTable.scala:90)
It looks like FiloDB fat jar in this PR includes "com.datastax.driver.core.Session" class. In our cluster, we always already includes "spark connector" jar released by datastax. The version is 1.5.0.
The compatible check can be found here:
https://github.com/datastax/spark-cassandra-connector https://github.com/datastax/spark-cassandra-connector
So it comes with the Cassandra Java driver 2.1
If I checked the version of the class, it looks like the method newSimpleStatement was NOT in version 2.1 and 3.0:
https://github.com/datastax/java-driver/blob/2.1/driver-core/src/main/java/com/datastax/driver/core/Session.java https://github.com/datastax/java-driver/blob/2.1/driver-core/src/main/java/com/datastax/driver/core/Session.java
The only version include this method is in version 2.2:
https://github.com/datastax/java-driver/blob/2.2/driver-core/src/main/java/com/datastax/driver/core/Session.java https://github.com/datastax/java-driver/blob/2.2/driver-core/src/main/java/com/datastax/driver/core/Session.java
But version 2.2 is never depended on in Spark Cassandra Connector.
In your sbt file, do you depend on Spark Cassandra connector? What version you depend on? Why C* Java Driver 2.2 being linked, and this cause some problem in our cluster environment.
In addition to that, I tried to start the spark-shell using following conf:
--conf spark.driver.userClassPathFirst=true --conf spark.executor.userClassPathFirst=true
Hope to use "filodb-spark-assembly-0.2.1-SNAPSHOT.jar" generated in this PR to override the classpath, but I still got the same error when I tried to do "save()" method.
—
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Reply to this email directly or view it on GitHub https://github.com/tuplejump/FiloDB/pull/91#issuecomment-210014427

The above error happens in the Driver side, now it is gone.
But on the spark executor side, I got the following error:
16/04/15 14:40:20 ERROR executor.Executor: Exception in task 3.3 in stage 4.0 (TID 131)
java.lang.ClassCastException: cannot assign instance of com.typesafe.config.impl.SimpleConfig to field filodb.spark.FiloContext$$anonfun$insertIntoFilo$extension$1.filoConfig$1 of type com.typesafe.config.Config in instance of filodb.spark.FiloContext$$anonfun$insertIntoFilo$extension$1
at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Is this due to our environment, or something else?

Weird.  What distro of spark u running?  The version of Datastax driver, Typesafe config has not changed.  Must be a conflict somewhere.  The JVM really needs dependency isolation. Sigh.
-Evan
"Never doubt that a small group of thoughtful, committed citizens can change the world" - M. Mead

On Apr 15, 2016, at 11:47 AM, Yong Zhang<EMAIL_ADDRESS>wrote:
The above error happens in the Driver side, now it is gone.
But on the spark executor side, I got the following error:
16/04/15 14:40:20 ERROR executor.Executor: Exception in task 3.3 in stage 4.0 (TID 131)
java.lang.ClassCastException: cannot assign instance of com.typesafe.config.impl.SimpleConfig to field filodb.spark.FiloContext$$anonfun$insertIntoFilo$extension$1.filoConfig$1 of type com.typesafe.config.Config in instance of filodb.spark.FiloContext$$anonfun$insertIntoFilo$extension$1
at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2133)
at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1305)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Is this due to our environment, or something else?
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It is maybe our environment causing this. Let me dig it a little more.

@java8964 and others:  going to merge this PR to master.

Hi, Evan:
How to change the log level? I still try to find out more about losing update. I can produce it in-memory with 1M data on my laptop. I saw you add more "debug" level information, and I want to dump them when I test on my laptop. But I am kind of new of scala logging.
What I did is to start Spark locally on my laptop with following:
--conf spark.filodb.store=in-memory --conf spark.sql.shuffle.partitions=2 --packages com.databricks:spark-csv_2.10:1.4.0 --conf "spark.driver.extraJavaOptions=-Dlog.leve=debug"
But when I run the "save()", I didn't see any debug level logging from FiloDB in the console. But I don't see any logback.xml (is that the config file for scala slf4j?) in the classpath or jar. How do I change log level in scala in this case?
Thanks

You just configure spark logging.  In spark distro, log4j.properties.  Btw can you tell me how to repro on in-memory on laptop, I'll try it.  I added an ingestion stress test.
-Evan
"Never doubt that a small group of thoughtful, committed citizens can change the world" - M. Mead

On Apr 20, 2016, at 11:43 AM, Yong Zhang<EMAIL_ADDRESS>wrote:
Hi, Evan:
How to change the log level? I still try to find out more about losing update. I can produce it in-memory with 1M data on my laptop. I saw you add more "debug" level information, and I want to dump them when I test on my laptop. But I am kind of new of scala logging.
What I did is to start Spark locally on my laptop with following:
--conf spark.filodb.store=in-memory --conf spark.sql.shuffle.partitions=2 --packages com.databricks:spark-csv_2.10:1.4.0 --conf "spark.driver.extraJavaOptions=-Dlog.leve=debug"
But when I run the "save()", I didn't see any debug level logging from FiloDB in the console. But I don't see any logback.xml (is that the config file for scala slf4j?) in the classpath or jar. How do I change log level in scala in this case?
Thanks
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I cannot consistently reproduce it, but got very good chance (almost 1 in 3). The following test is done on pull-91.
I start my spark 1.5.2 like following:
spark-shell --jars /home/yzhang/java8964/FiloDB/spark/target/scala-2.10/filodb-spark-assembly-0.2.1-SNAPSHOT.jar --conf spark.filodb.store=in-memory --conf spark.sql.shuffle.partitions=2 --packages com.databricks:spark-csv_2.10:1.4.0 --driver-memory 3G --master local[2]
scala> import org.apache.spark.sql.SaveMode
import org.apache.spark.sql.SaveMode
scala> val csvDF = sqlContext.read.format("com.databricks.spark.csv").option("header", "true").option("inferSchema", "true").load("/home/yzhang/data/emails_1m.csv")
csvDF: org.apache.spark.sql.DataFrame = [Email: string, Domain: string, GlobalStop: int, RestrictedAddress: int, RestrictedDomain: int, RoleAddress: int, Active: int]
scala> val df = csvDF.withColumn("PartId", substring($"Email",0,2)).sort($"PartId").drop("PartId")
df: org.apache.spark.sql.DataFrame = [Email: string, Domain: string, GlobalStop: int, RestrictedAddress: int, RestrictedDomain: int, RoleAddress: int, Active: int]
scala>
scala> df.write.format("filodb.spark").option("dataset", "poc1").option("row_keys", "Email").option("segment_key", "Domain").option("partition_keys", ":stringPrefix Email 2").mode(SaveMode.Overwrite).save()
scala> val poc1 = sqlContext.read.format("filodb.spark").option("dataset", "poc1").load()
poc1: org.apache.spark.sql.DataFrame = [RestrictedDomain: int, RestrictedAddress: int, Email: string, GlobalStop: int, RoleAddress: int, Domain: string, Active: int]
scala> csvDF.count
res2: Long = 1000000
scala> poc1.count
res1: Long = 971397
So I just lost data in this case. Sometimes I will get 1,000,000, but if I run
"df.write.format("filodb.spark").option("dataset", "poc1").option("row_keys", "Email").option("segment_key", "Domain").option("partition_keys", ":stringPrefix Email 2").mode(SaveMode.Overwrite).save()" again in the same Spark shell, then load the poc1 again, I will lost data too.
I can reproduce this if I run the Spark-shell again 1 in 3. That's why I want to dump the debug log, to see if I can see any difference between runs.
If it helps, I attached the emails_1m.csv file in my test.
emails_1m.csv.gz

Thanks. Actually the current head of pull-91 will probably leak records, because of a change in how the flush is done.  it’s actually merged to master, but I’m working on a fix on a new branch.  Will let you know when it’s available.
Can you verify something?  At the end of the ingestion, if this is all on your laptop, do the following in Spark shell:
import filodb.core.DatasetRef
filodb.spark.FiloSetup.client.ingestionStats(DatasetRef(dataset), 0)
(where dataset is the name of your dataset, like poc1)
The code above will print out how many rows remain in your memtable, which has not been flushed to the column store.

On Apr 20, 2016, at 2:23 PM, Yong Zhang<EMAIL_ADDRESS>wrote:
I cannot consistently reproduce it, but got very good chance (almost 1 in 3). The following test is done on pull-91.
I start my spark 1.5.2 like following:
spark-shell --jars /home/yzhang/java8964/FiloDB/spark/target/scala-2.10/filodb-spark-assembly-0.2.1-SNAPSHOT.jar --conf spark.filodb.store=in-memory --conf spark.sql.shuffle.partitions=2 --packages com.databricks:spark-csv_2.10:1.4.0 --driver-memory 3G --master local[2]
scala> import org.apache.spark.sql.SaveMode
import org.apache.spark.sql.SaveMode
scala> val csvDF = sqlContext.read.format("com.databricks.spark.csv").option("header", "true").option("inferSchema", "true").load("/home/yzhang/data/emails_1m.csv")
csvDF: org.apache.spark.sql.DataFrame = [Email: string, Domain: string, GlobalStop: int, RestrictedAddress: int, RestrictedDomain: int, RoleAddress: int, Active: int]
scala> val df = csvDF.withColumn("PartId", substring($"Email",0,2)).sort($"PartId").drop("PartId")
df: org.apache.spark.sql.DataFrame = [Email: string, Domain: string, GlobalStop: int, RestrictedAddress: int, RestrictedDomain: int, RoleAddress: int, Active: int]
scala>
scala> df.write.format("filodb.spark").option("dataset", "poc1").option("row_keys", "Email").option("segment_key", "Domain").option("partition_keys", ":stringPrefix Email 2").mode(SaveMode.Overwrite).save()
scala> val poc1 = sqlContext.read.format("filodb.spark").option("dataset", "poc1").load()
poc1: org.apache.spark.sql.DataFrame = [RestrictedDomain: int, RestrictedAddress: int, Email: string, GlobalStop: int, RoleAddress: int, Domain: string, Active: int]
scala> csvDF.count
res2: Long = 1000000
scala> poc1.count
res1: Long = 971397
So I just lost data in this case. Sometimes I will get 1,000,000, but if I run
"df.write.format("filodb.spark").option("dataset", "poc1").option("row_keys", "Email").option("segment_key", "Domain").option("partition_keys", ":stringPrefix Email 2").mode(SaveMode.Overwrite).save()" again in the same Spark shell, then load the poc1 again, I will lost data too.
I can reproduce this if I run the Spark-shell again 1 in 3. That's why I want to dump the debug log, to see if I can see any difference between runs.
If it helps, I attached the emails_1m.csv file in my test.
emails_1m.csv.gz https://github.com/tuplejump/FiloDB/files/228834/emails_1m.csv.gz
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I created a new issue (92) with the debug logging enabled. Let me know if it helps.
Thanks

Here is the output:
scala> poc1.count
res3: Long = 997672
scala> import filodb.core.DatasetRef
import filodb.core.DatasetRef
scala> filodb.spark.FiloSetup.client.ingestionStats(DatasetRef("poc1"),0)
res4: filodb.coordinator.DatasetCoordinatorActor.Stats = Stats(19,19,0,3312,-1)
I expect poc1.count should be 1M, but only get 997672, so there is 2328 not matching in the count. Is the output matching with what you expect?

Hm thanks, not quite.  997672 + 3312 > 1M, so something is weird.  I'll try to reproduce, while at the same time adding instrumentation.


Fix DOCKER_VERSION for String type

should wrap ".
because if not wrap, recognizes to a decimal type.
actual occur bellow error.
https://github.com/momosetkn/liquibase-kotlin-docs/actions/runs/11216729220/job/31176668278

Thanks for the suggestion. I just updated the readme in a separate commit, the env var values now have quotes. Will close this PR.

Thanks for the suggestion. I just updated the readme in a separate commit, the env var values now have quotes. Will close this PR.

Thanks @azhebel! Just for your information, the README still contains some version declarations without the quotes.

@azhebel
I confirmed that it was fixed. Thanks for you.


“Error! Server responded with: Error: Error status: 409” by usage of IDTA 02006-2-0_Template_Digital Nameplate

Hello,
when we, the energy informatics group of the Fraunhofer IOSB-AST, built an AASX file together with a project partner, based on the IDTA 02006-2-0_Template_Digital Nameplate given via http://smt-repo.admin-shell-io.com/, we get the error “Error! Server responded with: Error: Error status: 409”, even though there is guaranteed no network issue, as it works with different files at any given time. We reviewed the generated files multiple times via different programs like the Package Explorer. The errors seems to based on some serialization error, even though all the needed concept descriptions are given.
This stops us from using BaSyx as our AAS framework for the continuous development of an energy market data space. We could also review the files individually.

Hello @MartinRudolph96,
I have tried to reproduce the problem you describe. I assume that the error you see is caused by an inconsistent state of the BaSyx infrastructure caused by a problem that occurred earlier.
The error 409 means that there is a conflict, probably caused by trying to insert a data element (AAS) that already exists in the repository.
The actual error happens before when trying to insert an AAS including creating it's descriptor for the AAS registry when a templateId is set. The actual bug is described in issue #525.
When you try to insert the AAS for the first time, you will get an error 500 because of the actual bug. In this case, the AAS is probably added to the repository, but not to the registry. That's why you can't see it in the BaSyx UI. If you try to add the same AAS again you will get error 409 because the AAS already exists in the AAS repository.
Assuming that this is the case, please update to the newest Docker images (delete the old snapshot images and do a fresh download). The newest images include a fix that prevents this inconsistent state of the infrastructure.
Nevertheless, we will inform you once the actual bug described in issue #525 has been solved.

It seems that the new image mostly resolved the issues in fact, thanks!
Also, please keep me updated on the related issue. :)


OKHTTP version 3.12.2 sets retryOnConnectionFailure to false, but will still automatically retry after failure

OKHTTP version 3.12.2 sets retryOnConnectionFailure to false, but will still automatically retry after failure

3.x is not actively supported https://square.github.io/okhttp/security/security/


Document new unexpected behavior due to logging changes

Context

With the new logging framework, by default, tasks with no generated logs do not show up in the console.  A side-effect of this is the following:
$ gradle build --dry-run

BUILD SUCCESSFUL in 1s
$

The output from previous versions of Gradle can still be captured via --console=plain:
$ gradle build --dry-run --console plain
:compileJava SKIPPED
:processResources SKIPPED
:classes SKIPPED
:jar SKIPPED
:startScripts SKIPPED
:distTar SKIPPED
:distZip SKIPPED
:assemble SKIPPED
:compileTestJava SKIPPED
:processTestResources SKIPPED
:testClasses SKIPPED
:test SKIPPED
:check SKIPPED
:build SKIPPED

BUILD SUCCESSFUL in 1s
$

Contributor Checklist

[x] Update User Guide, DSL Reference, and Javadoc for public-facing changes

Gradle Core Team Checklist

[ ] Verify documentation including proper use of @since and @Incubating annotations for all public APIs

Why don't we just fix the issue?

We're going to fix this instead, so closing this.


Update connector metadata generation with resource functions

Purpose
Update connector metadata generation with resource functions
Check List

[x] Read the Contributing Guide
[ ] Updated Change Log
[ ] Checked Tooling Support (#)
[x] Added necessary tests

[x] Unit Tests
[ ] Spec Conformance Tests
[ ] Integration Tests
[ ] Ballerina By Example Tests

[ ] Increased Test Coverage
[ ] Added necessary documentation

[ ] API documentation
[ ] Module documentation in Module.md files
[ ] Ballerina By Examples

Opened new PR https://github.com/ballerina-platform/ballerina-lang/pull/39701


fix LICENSE.md checksum

libmetal_2018.04's license.md file converted SPDX-tag version.
I fixed cheksum value.

Please signed the patches
Please change the title "fix LICENSE.md checksum" to "fix libmetal 2018.04 license file checksum"

ok, i try signed patches pull request.


added-react-svg

React svg updated

Hello,
I tried to upload the React icon for a second time. Did it still not work?
Thank you for your help.
On Fri, Oct 8, 2021 at 12:50 PM Terence Eden @.***>
wrote:

Can you please let us know what you're trying to do?
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Last Week in Pony - April 10, 2022

Audio from the April 5th, 2022 Pony development sync is available:
https://sync-recordings.ponylang.io/r/2022_04_05.m4a


Don't forget Plex-Meta-Manager

Another amazing tool... check it out! https://metamanager.wiki/en/latest/

Added!


interrupt properly each run through channel (and side effect fix compilation error and works on windows)

fix for #63

@ldemailly I'm using Mac and can't verify that it indeed fixed the compilation error on Windows

@ymesika welcome back ! it's not as much about windows than about per run channel now, PTAL

/lgtm
/approve


chore(docs): update vite example and remove alias in tsconfig

The alias is not doing what i thought it would.

:tada: This PR is included in version 1.0.5-alpha.5 :tada:
The release is available on:

npm package (@alpha dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

:tada: This PR is included in version 1.0.5 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


feat: adding ext-wap entity for meraki devices

Relevant information
adding new entity type for Meraki Wireless Access Points
NOTE: this entity should end up the Network section of the Explorer UI
Checklist

[x] I've read the guidelines and understand the acceptance criteria.
[x] The value of the attribute marked as identifier will be unique and valid.
[x] I've confirmed that my entity type wasn't already defined. If it is I'm providing an
explanation above.

I'll do a task to create the manual parts


Building a conda recipe with tests that send SIGINT to children fails with mambabuild but succeeds with conda build

Recently a conda-forge build of a python library failed and I traced it down to an issue with mambabuild.
The conda recipe contains tests and some tests fail with conda mambabuild but succeed with conda build. I stripped down to failing test to this (it sends SIGINT to a child process):
import os
import time
import signal
from multiprocessing import Queue
from multiprocessing import Process

def task(queue):
    try:
        time.sleep(10)
    except KeyboardInterrupt:
        queue.put(True)
        return
    queue.put(False)

def test_mambabuild():
    queue = Queue()
    proc = Process(target=task, args=(queue,))
    proc.start()
    time.sleep(1)
    os.kill(proc.pid, signal.SIGINT)
    proc.join()
    assert queue.get_nowait()

The recipe that fails (branch includes the stripped down test above)
{% set name = "pypushflow" %}
{% set version = "0.4.0" %}

package:
  name: {{ name|lower }}
  version: {{ version }}

source:
  git_url: https://gitlab.esrf.fr/workflow/pypushflow.git
  git_rev: fix_tests_on_conda_forge

build:
  noarch: python
  script: {{ PYTHON }} -m pip install . -vv
  number: 0

requirements:
  host:
    - python >=3.6,<3.9
    - pip
  run:
    - python >=3.6,<3.9

test:
  imports:
    - pypushflow
  commands:
    - pip check
    - pytest --pyargs pypushflow.tests.test_mambabuild
  requires:
    - pip
    - pytest >=7
    - pytest-subtests >=0.4
    - psutil >=5.8
    - mongita >=1

outputs:
  - name: pypushflow

about:
  home: https://gitlab.esrf.fr/workflow/pypushflow
  summary: A task scheduler for cyclic and acyclic graphs
  license: MIT
  license_file: LICENSE.md

extra:
  recipe-maintainers:
    - woutdenolf
    - olofsvensson
    - payno

My environment:
conda create --name=testbuild

conda activate testbuild

mamba install --update-specs --yes --quiet --channel conda-forge conda-build boa

# This fails:
conda mambabuild .

# This succeeds:
conda build .


[Bug]:  font is not visible in small device

Description
hello @os-code-community,
I found an issue in your website "oscode" which is not responsible for the moblie and tablets please check it .
I want to work on this issue .....please assign me
Expected Behavior
it is not good for user
Show us the trouble with screenshots
it is in large device

it is in small device

Which browsers are affected?
Firefox
Which OS are affected?
linux
Enter the version of your web browser
115.0
Device?
Mobile
Record

[X] I agree to follow this project's Code of Conduct
[ ] I'm a GSSoC'23 contributor
[X] I want to work on this issue

hello @Vaishnavi-Patil2211  ,
I want to work on this issue please assign me


VSCode: ERB file false positive problems

Description
Description
The latest Ruby LSP VSCode extension (v0.7.11) generates numerous code problems for ERB files which should not be indicated as problems. The issue does not occur with v0.7.10. I've attached two screenshots - one of the code:

and another of the 'Problems' output:

I think I narrowed it down to it only occurring when the solargraph gem is installed from my Gemfile, but the odd behavior occurs whether the VSCode "castwide.solargraph" extension is enabled or not (even occurs with the solargraph gem present when the "castwide.solargraph" extension has been fully uninstalled).
To Reproduce

Create a new empty directory with the following files:

.ruby-version containing an rbenv ruby version (3.2.2 in my case)
Gemfile containing only gem "solargraph", require: false
A dummy test.html.erb file with any valid HTML

run bundle install and then open VSCode in that directory
Notice the problems in the test.html.erb file once the LSP extension starts the language server

@vinistock, thank you for your suggestion. 👍
Yes, downgrading the extension to v0.7.10 works.

Found this issue after running into the same issue with erb file. Reverting to an older version worked. The file is listed as erb and my settings don't have any associations for *.erb
settings
{
  "[javascript]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },
  "[markdown]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode",
    "editor.formatOnSave": true
  },
  "[yaml]": {},
  "deno.enable": false,
  "workbench.startupEditor": "newUntitledFile",
  "files.trimTrailingWhitespace": true,
  "editor.tabSize": 2,
  "files.insertFinalNewline": true,
  "extensions.ignoreRecommendations": false,
  "gitlens.currentLine.enabled": false,
  "gitlens.hovers.currentLine.over": "line",
  "gitlens.codeLens.enabled": false,
  "editor.rulers": [80, 120],
  "terraform.indexing": {
    "enabled": false,
    "liveIndexing": false,
    "delay": 500,
    "exclude": [".terraform/**/*", "**/.terraform/**/*"]
  },
  "gitlens.advanced.messages": {
    "suppressLineUncommittedWarning": true
  },
  "[rust]": {
    "editor.defaultFormatter": "matklad.rust-analyzer"
  },
  "editor.formatOnSave": true,
  "editor.renderWhitespace": "boundary",
  "rust-client.disableRustup": true,
  "search.useGlobalIgnoreFiles": true,
  "[json]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },
  "javascript.updateImportsOnFileMove.enabled": "always",
  "rust-analyzer.diagnostics.disabled": ["missing-unsafe"],
  "[javascriptreact]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },
  "[jsonc]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },
  "workbench.editorAssociations": {
    "*.ipynb": "jupyter.notebook.ipynb"
  },
  "[sql]": {
    "editor.defaultFormatter": "adpyke.vscode-sql-formatter"
  },
  "window.restoreWindows": "none",
  "[nix]": {
    "editor.defaultFormatter": "jnoortheen.nix-ide"
  },
  "nix.serverPath": "nil",
  "files.associations": {
    "COMMIT_EDITMSG": "git-commit"
  },
  "[typescript]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },
  "[html]": {
    "editor.defaultFormatter": "vscode.html-language-features"
  },
  "files.maxMemoryForLargeFilesMB": 8192,
  "terraform.languageServer.enable": true,
  "redhat.telemetry.enabled": false,
  "nix.serverSettings": {},
  "workbench.editor.empty.hint": "hidden",
  "[typescriptreact]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },
  "rubyLsp.rubyVersionManager": {
    "identifier": "none"
  },
  "window.zoomLevel": 1,
  "git.enableCommitSigning": true,
  "rubyLsp.enableExperimentalFeatures": true,
  "[css]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },
  "[scss]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  }
}

@vinistock I did have craigmaslowski.erb and aliariff.vscode-erb-beautify, but even after disabling them & restarting VSCode completely, I still get the highlighting issue with 0.7.11 (though now my language shows erb just like in https://github.com/Shopify/ruby-lsp/issues/2282#issuecomment-2221211980). I don't define that files.associations *.erb key anywhere.

If you turn on verbose tracing for the server:
// Settings.json
{
  "ruby lsp.trace.server": "verbose"
}

All requests and their parameters get printed to the Ruby LSP channel in the Output tab. When you open an ERB file, the textDocument/didOpen request should have the languageId parameter set to erb.
If that's not the case, something is changing the language ID of ERB files. It could be a user setting, a workspace setting (.vscode/setings.json), a different extension. We need to understand what is changing the language ID.

2024-07-10 15:33:44.818 [info] (project) [Trace - 3:33:44 PM] Sending notification 'textDocument/didOpen'.
2024-07-10 15:33:44.818 [info] (project) Params: {
    "textDocument": {
        "uri": "file:///Users/<REDACTED>file.html.erb",
        "languageId": "erb",
        "version": 1,
        "text": "<REDACTED>"
    }
}

So, the language ID is correct. Oh, maybe the server is outdated? If you do

CMD + SHIFT + P
Update language server gem

Does that fix the issue?

@vinistock I ran that server gem update VSCode command, but that didn't fix the issue either, unfortunately.

If you click on the language status item (the {} next to Ruby here), what server version are you on?

Okay. That makes sense, the server isn't able to handle ERB files.
Usually, when it fails to upgrade, it's because your project is locked to an older version of prism or sorbet-runtime, which then stops Bundler from updating the LSP.
You can try it on the terminal with
BUNDLE_GEMFILE=.ruby-lsp/Gemfile bundle update ruby-lsp

humm, Bundler attempted to update ruby-lsp but its version stayed the same. I had to manually add gem "ruby-lsp", "0.17.6" to my project Gemfile (not ideal, but it worked) in order to update to the latest version, and then erb mode works. I'd rather not pin the ruby-lsp version in my Gemfile, it's weird that it wouldn't update when I ran the command even in the basic Gemfile reproduction setup (with only solargraph listed).

It could be the rbs dependency that is restricting it as well. Solargraph also depends on RBS, so if it's locked to anything older than 3, the Ruby LSP won't update.

Thank you @vinistock! Deleted my suggestion to avoid confusion.
For me it was indeed rbs, required by solargraph.

Ran into this issue tonight,I noticed I still had an old version of solargraph listed in my development group despite not using that extension anymore:
  gem 'solargraph', '~> 0.49.0'

Removing this gem worked -- not a great solution if you use solargraph but if you don't and have the gem just remove it to resolve the issue.

Removing solargraph also solved this for me.

Thanks for suggestion @vinistock Downgrading to v0.7.10 worked for me. Hope this gets fixed 🤞

What are your reasons for keeping solargraph around still? With https://gist.github.com/castwide/28b349566a223dfb439a337aea29713e and the solargraph-rails extension it does still offer better rails support (I think), just has better insight into the metaprogramming. I'm curious if that is part of your reasoning, or if its something else. The fix from the solargraph side would be https://github.com/castwide/solargraph/pull/662.

FWIW, my problem was that I'm getting ruby-lsp via the ruby-lsp-rails gem (ruby-lsp-rails is the only thing my Gemfile), so trying to bundle update ruby-lsp was not getting me to the latest version. Had to bundle update ruby-lsp-rails to unjam the bundles.

@andyw8 Ok that's helpful, thanks!

@nikasvan I don't believe downgrading is an optimal solution. I suggested that while we were still understanding the issue. But it goes beyond not having errors for ERB files.
If you are unable to upgrade the server gem, you will not have access to any new features we ship. Almost all features in a language server are implemented in the server and not on the client side.
For example, if you can't upgrade past v0.17.2, you are currently missing out on:

Support for method aliases
Support for Ruby core declarations through RBS
Proper constant resolution (thanks to the work for ancestor linearization)
Singleton context handling, which translates to go to definition, completion, hover and signature help for singleton methods, class instance variables and constants defined inside a singleton block
Quickfixes for contextual RuboCop violations
The super type hierarchy visualization feature
ERB features
Completion for locals
Support for super in go to definition and hover

Plus whatever we ship in the next versions until the constraint is lifted and you can successfully upgrade the ruby-lsp gem.
Even if we came up with a way to avoid the errors for ERB, being unable to upgrade the language server gem is incompatible with delivering a good developer experience. We need to be able to get new features into the hands of developers. Bugfixes. Performance improvements. And the quicker we can do that, the better.

Thanks for digging into this @vinistock and everybody else.
For our project, it's another gem prawn-manual_builder that is locking the version of prism at 0.22.0. I'll raise the issue with them.

I was having the same issue and, after reading this issue start to finish, these were the steps:

Removing solargraph and ruby-lsp-rails from gemfile;
Running bundle;
Uninstalling Ruby Solargraph extension;
Activating the command palette and running Ruby LSP: update language server gem;
Clicking on the { } icon in the bottom right corner of vscode and confirming Ruby LSP server is version >= 0.17.7

This solved the ERB issue and the code navigation kept working!
Thanks a lot for the work on this great DX tool.

Alternatively, we could also just print a warning linking to this issue and explaining what's wrong, but not automatically restart the client - but then the ERB issues will not go away.

This seems preferable to me, since it gives more of an opportunity to explain the problem to users.

I really disliked the double-launch approach, so we ended up providing the ability to disable ERB support through a setting https://github.com/Shopify/ruby-lsp/pull/2311.
For users who find this issue in the future:
I'm having trouble with ERB files
The reason is because another dependency's constraints are blocking updates for the ruby-lsp gem. You should look for other gems that depend on rbs, prism or sorbet-runtime and try to ensure they are up to date.
Not being able to upgrade the language server is troublesome and the optimal solution is to figure out why the upgrades are failing and then fix it. Read the rest of the issue for more context.
How to avoid the issues temporarily
Turn off ERB support until you are able to upgrade the ruby-lsp gem.
// Your VS Code settings
{
  "rubyLsp.erbSupport": false
}

Note: this setting is a temporary escape hatch. We will not support old versions of the language server indefinitely. After a few months of allowing users to turn off ERB support, we will remove the setting and go back to turning on support for all users.

Updated to the latest version and added "rubyLsp.erbSupport": false but I still have the issue.

We haven't cut a release that includes the PR adding the setting yet.

I removed Gemfile.lock and ran bundle install again. Only then did it disappear for me.

"rubyLsp.erbSupport": false, worked for me!

Updating ruby-lsp gem to 0.17.17 and prism to 1.0.0 worked for me

I had the same issue. Removed rufo & solargraph from Gemfile, bundle install. Problem solved, thanks for hints

I had the same issue. Removed rufo & solargraph from Gemfile, bundle install. Problem solved, thanks for hints

Yes, that was all I needed to do. I didn't have rufo in my Gemfile, but I did have Solargraph. I removed it, did bundle i and now that formatting madness has gone away!


[Improvement][solution] Document Dolphin schemes for ordinary users on Linux OS and run with ordinary permissions

Describe the question
Document Dolphin schemes for ordinary users on Linux OS and run with ordinary permissions
Cluster deployment - The third step is to create the sudo non-secret configuration in the deployment users and hosts mapping step
echo 'dolphinscheduler  ALL=(userA,userB,userC)  NOPASSWD: NOPASSWD: ALL' >> /etc/sudoers

Where the userA,userB, and userC representatives are Linux OS users, they are used for multi-tenancy to submit jobs to the big data cluster.
With the addition of new tenants, it added sudo configuration permission control to the machine where dolphin Worker node submitted the operation application, which also realized the use permission control of machine OS users.
Resolving the Sudo issue, Dolphin is fully capable of running with normal Linux OS users and normal permissions.
For more information, see:
https://mp.weixin.qq.com/s/vpFCordtJE0G9bCNYg-Qgw

描述问题
记录Dolphin在Linux OS普通用户并使用普通权限运行的方案
官网文档集群部署-第三步创建部署用户和hosts映射步骤中sudo免密配置
echo 'dolphinscheduler  ALL=(userA,userB,userC)  NOPASSWD: NOPASSWD: ALL' >> /etc/sudoers

其中userA,userB,userC代表是linux OS用户，用于多租户向大数据集群提交作业。
后面有新增租户，提交运营申请dolphin worker节点所在机器新增sudo配置权限控制，也实现了机器OS用户使用权限控制。
解决了sudo问题，dolphin完全可以使用Linux OS普通用户和普通权限运行。
详细信息可以看：
https://mp.weixin.qq.com/s/vpFCordtJE0G9bCNYg-Qgw

hi, chong, great suggestion, can you send it to the dev mailing list, I think it is better to discuss this matter in the mail

hi, chong, great suggestion, can you send it to the dev mailing list, I think it is better to discuss this matter in the mail

https://lists.apache.org/thread.html/r69e990bf41bc651477c69031638af2ff211d0ecab6871c0f8b3f7d5d%40<dev.dolphinscheduler.apache.org>


Add support for default version of registry resources

FHIRRegistryResource.getResource(String url) currently parses the url parameter as a canonical url (<url>|<version>). If the version is not present, then it will look for all versions with the given url across all registry resource providers. It will then dedup/sort this list and return the "latest version". In addition to "latest version" there is a notion of "default version". The "default version" may be designated by an implementation (see TerminologyCapabilities.codeSystem.version.isDefault for an example of this).
We should make the following changes to support the idea of a "default version".

Add a defaultVersion field to the FHIRRegistryResource class along with constructor(s) that include defaultVersion as a parameter and an isDefaultVersion method
Add factory methods that create FHIRRegistryResource instances and allow for a defaultVersion to be specified
Add unit tests to test "default version" and "latest version" behavior
Update FHIRRegistry, PackageRegistryResourceProvider and ServerRegistryResourceProvider to use "default version" when a version is not specified

If no version is designated as the "default version", then the logic falls back to "latest version" based on sort order. If multiple versions are designated as the "default version" then the first one encountered will be used.
We also discussed the potential for supporting a defaultVersion field in the .index.json NPM package format we use to load resources for a PackageRegistryResourceProvider but decided it was lower priority.
We may want to consider an extension that allows a client to specify that a particular definitional resource (e.g CodeSystem, StructureDefinition, etc.) has a business version that is intended to be the default version. We could then update FHIRRegistryResource.from method to use that extension (if it exists).

I verified in my dev workspace that if the FHIRRegistryResource.from method sets default to true for a CodeSystem version, then the <base>/metadata?mode=terminology API shows isDefault: true for that CodeSystem version. More complete QA of the functionality can be done when there is a way for a client to indicate the default version of definitional resource via an extension is implemented in the future.


remove unnessary status judge

In Table::Open function, we already judge status just after Decode footer, so the status judge before read index block is duplicate and unnessary,  we can remove it.

@googlebot I signed it!

is the mac clang configuration have some error?

And to answer the question above.. the CI was fixed recently. Rebasing on top of master would've given you a green check here.
At this point, however, it's better to leave this PR as-is. Messing with it may confuse the bot.


Release 4.1.0

We will need a maintainer to create and push the tag for 4.1.0, and we missed that on 4.0.0 so it would be good if that could happen at the same time. I had to create a tag locally for 4.0.0 to get the release script to behave

This will supercede #81 since we have another commit to include now

I think we need to get another fix in before being able to release this since CI is complaining:
error: use of deprecated method `tokio::runtime::RuntimeMetrics::injection_queue_depth`: Renamed to global_queue_depth
  --> foundations/src/telemetry/tokio_runtime_metrics/runtime_handle.rs:57:26
   |
57 |             .set(metrics.injection_queue_depth() as u64);
   |                          ^^^^^^^^^^^^^^^^^^^^^
   |
   = note: `-D deprecated` implied by `-D warnings`
   = help: to override `-D warnings` add `#[allow(deprecated)]`


OpenAPI 3.0.0 schema fix: Parameter Object must contain 'schema' or 'content'

See the Fixed Fields section of the specs, towards the end:

A parameter MUST contain either a schema property, or a content property, but not both.

Adding the oneOf constraint requiring either content or schema fixes this issue.
The same issue applies to all objects that refer to Parameter Objects as their basis, such as e.g. Header Objects. I will add to this branch until I've adjusted all of those, and notify when this is done.

Actually, it seems as if Parameter and Header objects are it. So this should do the trick.

The build failure appears to be due to pyflakes:
../../../virtualenv/python3.3.6/lib/python3.3/site-packages/pyflakes/checker.py:1198: in LAMBDA
    args.append(wildcard if PY2 else wildcard.arg)
E   AttributeError: 'str' object has no attribute 'arg'

@jfinkhaeuser thank you for the contribution.


sqlite3_go18.go:49: undefined: driver.TxOptions

sqlite3_go18.go:49: undefined: driver.TxOptions

please upgrade go

I'm using go1.8 beta1 on darwin, and this still happens. osx10.11.6.

please upgrade go.
https://github.com/golang/go/blob/d0501f1da9c54a8053940feeb86e1644ffaae522/src/database/sql/driver/driver.go#L180-L183

I update golang to 1.7.3 ，now, I don‘t have the bug


Splitter refactor

Description
Refactor text splitters
Breaking changes

Set SentenceSplitter as default text splitter
no longer populate start_char_idx and end_char_idx in Node and Document classes
text splitter does not return additional metadata
text splitter does not account for metadata string length (revising)

Details

Simplify TextSplitter interface

remove split_text_with_overlaps method
remove TextSplit class

Rewrote TokenTextSplitter

Misc

Add a streamlit based splitter playground

@Disiok Is it possible to merge this into logan/migrate_default_llm_v2 instead? Then we can land all these defaults changes in the same PR?


Add support for snapshot debugging behind Traefik

This adds support for snapshot debugging behind Traefik as suggested in #1702. This closes #1702

@freddydk I've based of master but targeted dev, I think that's why all the dev merges show up. And there seems to be some whitespace weirdness, if you look at the changes without whitespaces (https://github.com/microsoft/navcontainerhelper/pull/1711/files?diff=unified&w=1) it looks good

Thanks @tfenster


Refresh the whole docs site

[x] Added a readme to the docs site
[x] Cleaned up random unnecessary stuff
[x] Set the theme back to being from a cdn
[x] Make the site pull readme files from the other devcade repos
[x] Improve the "Edit on Github" button
[X] Replace current logo with the one that has text
[x] Enable auto table of contents
[x] Enable auto2top
[x] Remove old library page now that it gets pulled directly from the repo
[x] Add info to the home page
[x] Update contribution guide
[ ] Fill or remove any empty pages
[x] Remove sections that are now redundant
[ ] Restructure sidebar / site
[x] Add links to all repos (beyond the edit button)
[ ] Add the docs site readme to the docs site
[ ] Review all content to ensure accuracy and sufficient detail
[ ] Add links between pages where appropriate
[ ] Confirm all links are working

Specific changes to make

[ ] Add more detail to the "Making your first devcade game" page
[ ] Update content of the onboard readme (it is comically out of date)
[ ] Fix the link to (and possibly update content of) the "Using the Game Template" page
[ ] Add more detail to the hardware overview page
[ ] Add content to or remove the "Cabinet" page
[ ] Add content to or remove the "Gamepad" page
[ ] Add headings to the "Installing DCU" page
[ ] Update all links in the "Internals" section
[ ] Possibly add more detail to the "API" page
[ ] Possibly add more detail to the "Monogame Game Template" page
[ ] Possibly add more detail to the "Flatpakify" page

@esoccoli Some notes on the new install guide:
In addition to adding headers as you mentioned above, I would like to see it formatted more like a walk through or guide like the old one was.
Similarly, I've been trying to format the docs site with general information for anyone that might in the future want to make their own Devcade. To this point I would like to avoid specifying details specific to our instance of Devcade such as the dcu.csh.rit.edu hostname or referencing RTPs/Devcade Admins. These belong better on our wiki I think.
Do we need to specify mary's fork of flatpak still? or have the changes we need trickled down to the standard package yet?
We include an openbox config with the onboard, we could just add the volume control config to that... Or maybe as a separate PR.

@esoccoli Thoughts on not having the using-template page and instead just including that info in the readme of the template itself?

Id be fine with that. Most of the content is kinda just a repeat of what is in the readme of the template anyway

What I will say is that i can't guarantee that the onboard will actually launch after you finish following the instructions in the install guide. I was trying to test that, and it kept giving me errors, and I couldn't figure out why, and didn't really have the time to look into it too much.


Investigate whether parallel searching via different match window sizes wins performance.

This is a follow on from #35.
The binary search through match window sizes is efficient, and when it moves upwards in size due to having found suboptimal matches, the size estimation process is more often than not bang on the money, leading directly to the optimal match.
Where things could be improved is for downward moves in size - there is a crude heuristic that guides what size to choose, but it is essentially bisecting and hoping for the best. At large window sizes, this can lead to misses, followed by further downward moves and at large window sizes this is problematic if there are lots of undiscovered optimal matches of varying size greater than the bisected size - that can confuse the size estimation process.
Would executing alternate downward moves in parallel yield any benefit?

Tried a spike on this; performance is terrible. Looking at over 4 to 5 minutes for the example merge from #35.
Running the automated test CodeMotionAnalysisTest.matchingSectionsAreFound alos shows a marked drop in throughput.
CPU usage is definitely up, so work is taking place in concurrent threads, but it doesn't yield any benefit whatsover.

Abandoning this as wontfix.


Add us keymap and print ASCII chars

Added external crate for keymaps and for conversion of scancode to ASCII values.

oops! there is already a pull request for this so closing this!

Ah this still might be useful though! I like the idea of using an external crate; my PR has a very incomplete map, for example.

I am going to take this, and drop my other implementation. Thanks a ton!


Add support for the Leap Motion Unity Modules version 4.5.1

Overview

Adds support for Leap Motion Unity Modules version 4.5.1
Removes support for the leap motion 4.4.0 core assets as they are over two years old
Updated the documentation to reflect the changes
Updated the example scene
Added helper method to the AssemblyDefinition class

Updated the Leap Integration Process:

Added three menu items

Initialize on Load has been removed and the steps are now:

Import Leap Modules into the project
Select the Connect Leap Motion Unity Modules menu

Changes

Fixes: #8337

/azp run

/azp run

/azp run

/azp run


Query : not able to get existing options & modify them for maxTime and readPreference

We have a library which takes in org.mongodb.morphia.query.Query as the input parameter.

In the application, they set following on query object

query.order(sortyBy)

Library gets the query object and internally based on configuration needs to set
maxTime
readPreference
Query itself does not have setters for this, which means have to create new options object in step 2 and the values set in step 1 is lost.

Instead if i get the options from step 1 and then add other options in step 2, that would work.
But how do i get the options from query object?
Thanks in advance.

When methods which take options as a parameter get called ( such as public List asList(final FindOptions options) { )
shouldn't it merge the options already set in its private member variable (options) with the method parameter options
Or
provide a getter to access options member variable

2.0 cleans up this API (because I agree it's terribly awkward) so I'm going to close this one.  I'm hoping for 2.0 alpha/beta releases soon.  If that API still needs some work, please file an issue against 2.0.


Could I use the models you provide to retrain my data set directly?

Excuse me,I want to use the method of transfer learning to retrain the model you provided.Should I divide my dataset to 4 parts because there are 4 views?I don't know how to do before retrain the models.Could you give me some advice?
Thank you!
Looking forward to your reply!

Hi Alice,
If you only have one image per example (as opposed to four), you should only use one column from our network.


Refactoring again

No breaking anything this time, but:

better management of status
remove more things from main.nf script to put in the config file
code polishing
some channels are simplified

Succeed preprocessing, realign and skipPreprocessing
Seems to work with HaplotypeCaller, MuTect1, MuTect2, VarDictandAscatStill a few problems withStrelkaandManta`
But will fix soon


Revert "fix: "dependency_version_2": true"

Reverts terraform-ibm-modules/terraform-ibm-observability-da#230

/run pipeline

:tada: This PR is included in version 2.4.3 :tada:
The release is available on:

GitHub release
v2.4.3

Your semantic-release bot :package::rocket:


wip: Compress anchor event

Compress anchor event
Closes #997
Signed-off-by: Sandra Vrtikapa<EMAIL_ADDRESS>

The final solution was to compress attachments within anchor event instead whole anchor event.


"No published analyzer available for language version 2.12.0".   |   This requires the 'non-nullable' language feature to be enabled.

my   pub spec.yaml
environment:
sdk: ">=2.7.0 <3.0.0"
dependencies:
flutter:
sdk: flutter
flutter_localizations:
sdk: flutter
cupertino_icons: ^1.0.0
built_collection: '>=2.0.0 <5.0.0'
built_value: ^7.0.2
json_serializable: ^3.5.0
dev_dependencies:
flutter_test:
sdk: flutter
build_runner: ^1.0.0
built_value_generator: ^7.1.0
pedantic: ^1.4.0
quiver: '>=0.21.0 <3.0.0'
flutter_launcher_icons: ^0.8.1
I'm using both built_value & json_serializable in my app
and when I run:
flutter pub run build_runner build
I get this error:
flutter/bin/cache/pkg/sky_engine/lib/ui/channel_buffers.dart:166:25 - This requires the 'non-nullable' language feature to be enabled.
Here's a screen shot

Any help?

Seeing the same issue on latest Master branch.

This looks like a dupe of #44421, though I guess this one was technically filed first.

I was able to make build_runner work again with this dependency override in my pubspec.yaml:
dependency_overrides:
  analyzer: ^0.41.1

I was able to make build_runner work again with this dependency override in my pubspec.yaml:
dependency_overrides:
  analyzer: ^0.41.1

An analyzer version has since been published.


fix(tooltip): fix some issues in new tooltip.

Brief Information
This pull request is in the type of:

[x] bug fixing
[ ] new feature
[x] others

What does this PR do?

(1) [fix] transform may not be working in IE. (add vendor prefixes)
(2) [feat] disable transition after a long-time hide
(3) [feat] use opacity to fade out but not hide directly and add opacity transition
(3) reduce unnecessary imports.
I've made these changes to the new tooltip according to some personal ideas, please feel free to leave your comment.
Thank you!
@pissang @100pah @susiwen8 @Ovilia
Fixed issues
N/A.
Details
Before: What was the problem?

After: How is it fixed in this PR?

Usage
Are there any API changes?

[ ] The API has been changed.

Related test cases or examples to use the new APIs
please refer to test/new-tooltip.html
Others
Merging options

[ ] Please squash the commits into a single one when merge.

Other information

The result looks good. I've left my comment.


Store all local models in /models folder, with overridable model path

We should make sure that all models stored by llama, whisper, embedding, etc all get stored in a /models folder that is easy to find and clean. This way the repo doesn't get huge and locating models isn't messy.
Here are the steps:

Look for all services where models are being loaded, including llama, fastembed, whisper, etc
Change all paths to be eliza/models
Add a path checker if that doesn't exist with some sane defaults to handle any case
Add a model path override to functions so the packaged version doesn't go somewhere weird.

Shouldn't we just make it an environment variable so users might have their models stored at some different directory for any other purpose and they can easily point to that directory? and or Downloading model happens to that particular path?
For example like the follow one.
in .env
#LlamaLocal Configuration LLAMALOCAL_PATH=                      # Default: "" which is the current directory in plugin-node/dist/ which gets destroyed and recreated on every build
then in llama.ts line no 188,
 this.modelPath = path.join(process.env.LLAMALOCAL_PATH, modelName);


no build instructions?

How is this built?

Hello Mark,
This was a short term project that I started working on when I came back to start programming after 2 years and just uploaded the code without any relevant instructions. The project in itself is very suboptimal and needs a lot of work and polish in its very architecture, right now everything is contained under the file CheckValidCommand.java, just compile the file to generate the relevant .class file.
Regards,
Tridib.


Spectral Clustering

Some notes:

Main script is spectral.py in the src/clustering directory
Concept is rooted in graph theory but it essentially is a clustering algorithm, so I found it best to include it in clustering instead of graph + it can also use common clustering algorithms like k-means, DBSCAN so it's convenient to group them together
Demo notebook is in example/clustering/spectral along with example data; added a requirements.txt file but not sure if this is needed and just for formality?

Important:

Modified the TOML file to add matplotlib and scikit-learn as dependencies. Former is ok, but latter is unfortunately needed for a preprocessing step in the spectral clustering algo (not enough resources to implement from scratch correctly).

Let me know if I need to change/rearrange some things, particularly with regards to the dependencies. Thanks!

I'll add my second algorithm after this has been merged already


[Bug]: BASE_PATH Doesn't Seem To Work

Describe the bug
I'm trying to set the base path variable per the instructions for my reverse proxy.  If properly functioning, I should be able to access it locally at <IP_ADDRESS>:8008/pnut.  However, no matter how I set this variable I seem to get a 404 error served out by PeaNUT itself when navigating via the base path.  The guide doesn't have any actual examples on how to use it.  I've tried all of the following formatting in my Docker run command:
-e BASE_PATH=/pnut
-e BASE_PATH=/pnut/
-e BASE_PATH="/pnut"
-e BASE_PATH="/pnut/"
-e BASE_PATH=pnut
-e BASE_PATH="pnut"

Is the feature broken, or are the instructions to use it just missing important context?
Debug Output
N/A
Steps to reproduce

Use the docker run command and set the BASE_PATH environment variable to anything.

Device Type
Debian x86
UPS Device
TrippLite Smart1300CLDt
Last Working Version
No response

I've personally never used it myself, but I've heard from others that it's working for them. Not sure if this helps, but here are some resources.
https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://nextjs.org/docs/app/api-reference/next-config-js/basePath&ved=2ahUKEwjvkYD2i4uHAxWxFlkFHUfrAe4QFnoECAgQAQ&usg=AOvVaw3Gav0NLNi7JXw0I050D492
https://github.com/Brandawg93/PeaNUT/blob/main/next.config.js#L9

Closing as stale.

That's good to know. So users may need to compile from source for the time being until I can look into it again.


The train problem

Hello,I want to use the siamrpn_r50_l234_dwxcorr_8gpu for train,and I only use the COCO,

Then I use the commend like
python -m torch.distributed.launch --nproc_per_node=1  --master_port=2334 tools/train.py --cfg experiments/siamrpn_r50_l234_dwxcorr_8gpu/config.yaml
but it shows subprocess.CalledProcessError,returned non-zero exit status 1 and ValueError: Type mismatch (<class 'str'> vs. <class 'NoneType'>) with values ( vs. None) for config key: BACKBONE.PRETRAINED

Can you help me ,Thanks!

Maybe you haven't download the pretained backbone model.

It seems your config file was not properly configured.

Since no further question is asked, I'm closing it for now.
Please reopen it or create a new issue if you have further question.


[FEA] Fall back to CPU for more Delta Lake queries

Is your feature request related to a problem? Please describe.
The following Delta Table operations result in queries that are largely unsupported on GPU so we should detect these and fall back to CPU:

merge
history

(there are probably more and I am in the process of testing all the supported features)
Describe the solution you'd like
As above
Describe alternatives you've considered
None
Additional context
None

Note that merge involves a full outer join, so I'm not sure it's clear that we want to fallback in all cases there.  As far as history is concerned, I believe that's already been addressed by #7022.  Merge will be handled by #7007.


invenio 3.3 and KVSessions

If I try to install invenio 3.3.0 I get following error:

We have to install flask_kvsession or
we have to import KVSessionExtension from flask_kvsession_invenio?

Build web assets: collect
Traceback (most recent call last):
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/bin/invenio", line 11, in
sys.exit(cli())
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/click/core.py", line 829, in call
return self.main(*args, **kwargs)
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/flask/cli.py", line 586, in main
return super(FlaskGroup, self).main(*args, **kwargs)
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/click/core.py", line 782, in main
rv = self.invoke(ctx)
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/click/core.py", line 1254, in invoke
cmd_name, cmd, args = self.resolve_command(ctx, args)
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/click/core.py", line 1297, in resolve_command
cmd = self.get_command(ctx, cmd_name)
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/flask/cli.py", line 527, in get_command
self._load_plugin_commands()
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/flask/cli.py", line 523, in _load_plugin_commands
self.add_command(ep.load(), ep.name)
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/pkg_resources/init.py", line 2346, in load
return self.resolve()
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/pkg_resources/init.py", line 2352, in resolve
module = import(self.module_name, fromlist=['name'], level=0)
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/invenio_oauth2server/init.py", line 117, in
from .decorators import require_api_auth, require_oauth_scopes  # noqa isort:skip
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/invenio_oauth2server/decorators.py", line 19, in
from .provider import oauth2
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/invenio_oauth2server/provider.py", line 21, in
from .models import Client, Token
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/invenio_oauth2server/models.py", line 17, in
from invenio_accounts.models import User
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/invenio_accounts/init.py", line 38, in
from .ext import InvenioAccounts, InvenioAccountsREST, InvenioAccountsUI
File "/Users/wep/devel/virtualenvs/rero-ebooks-MevsRTH6-py3.6/lib/python3.6/site-packages/invenio_accounts/ext.py", line 18, in
from flask_kvsession import KVSessionExtension
ImportError: cannot import name 'KVSessionExtension'

Hi @rerowep since flask-kvsessions is unmaintained, Invenio now uses its own fork of it: https://pypi.org/project/Flask-KVSession-Invenio/
Which is the one that comes with invenio-accounts v1.3.0.
Was this error produced in a clean cookiecutted instance? Or during migration? Could you pip freeze and send the output?


Dep add zstd static explicitly

I tried this locally a while ago, but it doesn’t install the static library as desired. Didn’t investigate further


[ADD] GGolfz.codes

Add GGolfz.codes
I write this pull request for adding my website to this webring.
Position of Webring
The position of the webring logo is on the footer of my site as you can see in the below image

Mobile Display

Desktop Display

@GGolfz Thanks, and welcome to the webring!

@GGolfz Thanks, and welcome to the webring!


Seeing dev-friendly, readable JS output

Describe the problem
Transparency is important. Svelte has readable and informative JS output, seen e.g. in the REPL (JS output tab, next the to Result tab); however, there's currently no way I'm aware of to read this output when build with SvelteKit. There's an unreabable minimized version you get in .svelte-kit/output when using svelte-kit build, but the dev version seems to only ever exist on the fly.
Describe the proposed solution
I'd like a way to read and explore the dev-friendly, compiled JS output as run when using svelte-kit dev. I don't understand enough of how svelte-kit dev works to know whether the best way of implementing this is just writing it to the FS as part of svelte-kit dev, a special flag on svelte-kit build, or whatever else.
In any case, this is a significant step down in transparency and clarity of what's happening under the hood from plain Svelte.
Alternatives considered
No response
Importance
would make my life easier
Additional Information
No response

SvelteKit components are just regular Svelte components, so you can

past them into the Repl and look at the output (doesn't always work if you have more components set up)
use the "show compiled code" command from the vs code extension

I'm not sure if this is something that SvelteKit can/should offer.

Are you familiar with how to view them in Chrome? I'm not sure what the benefit is of viewing them on the filesystem instead of in the browser

@dummdidumm This works on a per-component basis, but even then completely misses out on e.g. routing stuff and <script context=module>. However,
@benmccann This completely skipped my mind and (of course) works perfectly and contains everything. Thanks a bunch!


terraform, gcp: configure user_project_override to avoid error

When @GeorgianaElena planned terraform work, there was an issue as outlined below when trying terraform plan -var-file=projects/pilot-hubs.tfvars from terraform/gcp. We couldn't understand why well, but this did the trick. But - maybe it has negative sideeffects? I can't say I understand this very well at all.
...
google_container_node_pool.dask_worker["worker"]: Refreshing state... [id=projects/two-eye-two-see/locations/us-central1-b/clusters/pilot-hubs-cluster/nodePools/dask-worker]
google_container_node_pool.notebook["user"]: Refreshing state... [id=projects/two-eye-two-see/locations/us-central1-b/clusters/pilot-hubs-cluster/nodePools/nb-user]
google_container_node_pool.core: Refreshing state... [id=projects/two-eye-two-see/locations/us-central1-b/clusters/pilot-hubs-cluster/nodePools/core-pool]
╷
│ Error: Error when reading or editing BillingBudget "billingAccounts/censored/budgets/censored": googleapi: Error 403: Your application has authenticated using end user credentials from the Google Cloud SDK or Google Cloud Shell which are not supported by the billingbudgets.googleapis.com. We recommend configuring the billing/quota_project setting in gcloud or using a service account through the auth/impersonate_service_account setting. For more information about service accounts and how to use them in your application, see https://cloud.google.com/docs/authentication/. If you are getting this error with curl or similar tools, you may need to specify 'X-Goog-User-Project' HTTP header for quota and billing purposes. For more information regarding 'X-Goog-User-Project' header, please check https://cloud.google.com/apis/docs/system-parameters.
│ Details:
│ [
│   {
│     "@type": "type.googleapis.com/google.rpc.ErrorInfo",
│     "domain": "googleapis.com",
│     "metadata": {
│       "consumer": "projects/32555940559",
│       "service": "billingbudgets.googleapis.com"
│     },
│     "reason": "SERVICE_DISABLED"
│   }
│ ]

I think the issue may relate to making a change to the node pools, which somehow couples with billing alerts that has been handled outside of terraform. In practice, when applying the addition of node pools the following showed up as resources to be destroyed.
  # google_billing_budget.budget[0] will be destroyed
  # (because google_billing_budget.budget is not in configuration)
  - resource "google_billing_budget" "budget" {
      - billing_account = "0157F7-E3EA8C-25AC3C" -> null
      - display_name    = "Billing alert" -> null
      - id              = "billingAccounts/0157F7-E3EA8C-25AC3C/budgets/1bf2106a-0b81-4a70-ab09-bcd568d80e13" -> null
      - name            = "1bf2106a-0b81-4a70-ab09-bcd568d80e13" -> null

      - all_updates_rule {
          - disable_default_iam_recipients   = true -> null
          - monitoring_notification_channels = [
              - "projects/two-eye-two-see/notificationChannels/10693994760737431897",
            ] -> null
          - schema_version                   = "1.0" -> null
        }

      - amount {
          - last_period_amount = false -> null

          - specified_amount {
              - currency_code = "USD" -> null
              - nanos         = 0 -> null
              - units         = "2500" -> null
            }
        }

      - budget_filter {
          - calendar_period        = "MONTH" -> null
          - credit_types           = [] -> null
          - credit_types_treatment = "INCLUDE_ALL_CREDITS" -> null
          - labels                 = {} -> null
          - projects               = [
              - "projects/350668521154",
            ] -> null
          - services               = [] -> null
          - subaccounts            = [] -> null
        }

      - threshold_rules {
          - spend_basis       = "CURRENT_SPEND" -> null
          - threshold_percent = 1 -> null
        }
      - threshold_rules {
          - spend_basis       = "FORECASTED_SPEND" -> null
          - threshold_percent = 1.01 -> null
        }
    }

  # google_monitoring_notification_channel.support_email[0] will be destroyed
  # (because google_monitoring_notification_channel.support_email is not in configuration)
  - resource "google_monitoring_notification_channel" "support_email" {
      - display_name =<EMAIL_ADDRESS>email" -> null
      - enabled      = true -> null
      - force_delete = false -> null
      - id           = "projects/two-eye-two-see/notificationChannels/10693994760737431897" -> null
      - labels       = {
          - "email_address" =<EMAIL_ADDRESS>        } -> null
      - name         = "projects/two-eye-two-see/notificationChannels/10693994760737431897" -> null
      - project      = "two-eye-two-see" -> null
      - type         = "email" -> null
      - user_labels  = {} -> null
    }

(Merged during a video meet with @GeorgianaElena)


Double buffering

Implement it.
Draw scene to buffer
Copy buffer to video memory
Repeat

Figure out how to allocate RAM

Done, malloc works, I was just missing a library.
NOW I CAN USE FGET! :D


InfluxDB v3(IOx) binary size too large

Describe the issue
I use RUSTFLAGS="-C linker=x86_64-linux-gnu-gcc" cargo build --release to build the latest InfluxDB v3 on main branch. I noticed that the generated binary size has reached an astonishing 1.7 GB. Even setting opt-level = "z" and lto = "thin" in Cargo.toml, the binary size remains 992.9 MB. It still too large in my situation.
Environment
OS: x86_64 linux
Toolchain: x86_64-linux-gnu-gcc
Here are my questions:

Does the above build method include optional features of InfluxDB v3? How to disable it?
What is the performance impact of InfluxDB v3 when using opt-level = "z" and lto = "thin"?
Does InfluxDB v3 support dynamic linking instead of static linking?

By the way, I noticed that metrico/iox-community provides release binaries only 31.1 MB. This seems to be a reasonable size. Does anyone know the differences in the build process that lead to such a contrast in binary size?

This is likely because by deafult the binary is built with debug symbols: https://github.com/influxdata/influxdb/blob/acfef87659c9a8c4c49e4628264369569e04cad1/Cargo.toml#L142-L145
Removing the debug=true or running strip on the resulting binary will likely make is much smaller

After using strip = "symbols" and codegen-units = 1
The binary size is about 81M
That helps me a lot, thank you @alamb

We have since changed the release profile in Cargo.toml which no longer includes debug symbols, and the binary sizes we are seeing are around 99 MB, so I closed this one out for now.


[fluentd-elasticsearch] add missing release label

The release label is required to select the right service

/assign @seanknox

Chart version needs to be 0.6.2.

And now 0.6.3 😁

And now 0.6.4 :O
/assign unguiculus
/assign @scottrigby

/lgtm

/lgtm


fix(nuxt): island components with number prefix

🔗 Linked issue

https://stackblitz.com/edit/nuxt-starter-xchkk1?file=app.vue
❓ Type of change

[ ] 📖 Documentation (updates to the documentation, readme or JSdoc annotations)
[x] 🐞 Bug fix (a non-breaking change that fixes an issue)
[ ] 👌 Enhancement (improving an existing functionality like performance)
[ ] ✨ New feature (a non-breaking change that adds functionality)
[ ] 🧹 Chore (updates to the build process or auxiliary tools and libraries)
[ ] ⚠ Breaking change (fix or feature that would cause existing functionality to change)

📚 Description

Using an island component that starts with a number completely breaks the island renderer, this is because it will introduce a syntax error within the template used to load the component.
import { defineAsyncComponent } from 'vue'
export const 2Foo = defineAsyncComponent(() => import("/home/harlan/packages/nuxt/playground/components/2Foo.island.vue" /* webpackChunkName: "components/2-foo-server" */).then(c => c.default || c))

To fix this I've just copied the convention used for the global components template.
📝 Checklist

[ ] I have linked an issue or discussion.
[ ] I have updated the documentation accordingly.

Not really sure what's going on with these failed tests, any ideas? Seems cache related

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

:exclamation: No coverage uploaded for pull request base (main@e3b8b84). Click here to learn what that means.

Additional details and impacted files
@@           Coverage Diff           @@
##             main   #24469   +/-   ##
=======================================
  Coverage        ?   58.65%
=======================================
  Files           ?        5
  Lines           ?      861
  Branches        ?       46
=======================================
  Hits            ?      505
  Misses          ?      356
  Partials        ?        0

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

Oh right! thanks @danielroe :bowing_man:


Added a quick reference section with quick links to issue trackers an…

…d downloads

Merged in 85f4b17e8461b54561d007150634d95be9cad84a..63459c49a5ec7d35bf007b116ba61dc90c94c891.


Add node lifecycle APIs and commands

Specifically:

remove node
lame-duck node
evacuate node

Partial fix in https://github.com/shakenfist/shakenfist/pull/1376 and https://github.com/shakenfist/client-python/pull/177.


Outline Client has stopped working after updating Windows 11, 21H2 to Windows 11, 22H2

Hi,
After updating my windows 11, version 21H2 to windows 11, version 22H2, I faced this error:
"Sorry, an unexpected error occurred. Quitting and restarting may help. If this happens again, please submit feedback."
I tried to uninstall outline and even delete its adapter and reinstall it again, but I still got this error.
Could anyone please help me to solve that issue?

Thanks, @jyyi1,
There's no error in the event log:

and the service is running :

But as you can see I still get the same error:
Sorry, an unexpected error occurred. Quitting and restarting may help. If this happens again, please submit feedback.
An interesting thing is I don't have this problem with the Outline android version on my phone.

Thanks @mamaly12 for the information, then I think we need to get the logs from the client. If you are using PowerShell (which should be the default Terminal in Windows 11), please restart Outline client using the following PowerShell commands (typically the outline installation path is C:\Program Files (x86)\Outline):
PS C:\....> cd "<your outline installation path>"
PS C:\....\Outline> $Env:OUTLINE_DEBUG="true"
PS C:\....\Outline> .\Outline.exe

Then try to connect to the server again, there should be some errors printed to PowerShell. If you want, you can also get some UI logs by clicking menu item "Developer" -> "Toggle Developer Tools".

@jyyi1 I got this error :

@mamaly12 This is expected, please try to connect to the server.

exactly, I created the connection_store folder manually and I tried to connect to the server:

@jyyi1

Thanks @mamaly12 , ah i see. This should be the same issue as #1449 , which occurs in a new component we introduced in this release. We will try to fix it ASAP, but for now I think the workaround would be using an old version (1.7.0 should be good). Again, sorry about the inconvenience.


enable browsing s3 via jupyter-fs

@tinaok this adds an S3 browser to the JupyterLab sidebar:

@yuvipanda this is what I mentioned to you yesterday. It seems to work fine with JupyterLab 4, but I had to do some shenanigans to work around https://github.com/PyFilesystem/s3fs/issues/70 because our files are not created with S3FS (they are created with s3fs), and S3FS makes some hard assumptions that it's created everything it might read (namely that an empty Object exists representing each directory level, which is not true in general). I did the definitely-totally-fine thing of catching the error that raises when a directory lacks a corresponding Object and making those empty objects if they are missing.

our files are not created with S3FS (they are created with s3fs)

this is beautiful haha

Hmm, so this just doesn't recognize 'directories' unless a specific empty object exists? So it probably won't work for readonly data buckets that don't do that?

So it probably won't work for readonly data buckets that don't do that?

My exact workaround won't, though you could do a read-only version of my workaround where it returns a fake Info model as if it were a real one instead of creating the object and trying again. The advantage of my version is it will only take the fallback path one time for any given missing directory, and will do the 'right' thing forever after.

This one appears to work for read-only:
import fs.errors
from fs.info import Info, ResourceType
from fs_s3fs import S3FS

class EnsureDirS3FS(S3FS):
    def getinfo(self, path, namespaces=None):
        try:
            return super().getinfo(path, namespaces)
        except fs.errors.ResourceNotFound as e:
            # workaround https://github.com/PyFilesystem/s3fs/issues/70
            # check if it's a directory with no corresponding Object (not created by S3FS)
            # scandir/getinfo don't work on missing directories, but listdir does
            # if it's really a directory, return stub Info instead of failing
            try:
                self.listdir(path)
            except fs.errors.ResourceNotFound:
                raise e from None
            else:
                # return fake Info
                # based on S3FS.getinfo handling of root (`/`)
                name = path.rstrip("/").rsplit("/", 1)[-1]
                return Info(
                    {
                        "basic": {
                            "name": name,
                            "is_dir": True,
                        },
                        "details": {"type": int(ResourceType.directory)},
                    }
                )

@minrk this is great!
How do you control the list of buckets that show up here?

We're only working with one bucket. I think you need to explicitly list each bucket you want to mount in the resources config.
Ours is here. The bucket name (or arbitrary subdir) is in the mount.

Interesting! Was https://github.com/destination-earth/DestinE_ESA_GFTS/pull/13/files#diff-96599d676c72313e9986285fd7ab9d14b18d8bec6167a33056b85ad4d2529435R101 needed as well, even if you only want the sidebar to show up?

Yes, the listing requests use the contents API at subdirectories. A default FileContentsManager still serves the "root" so there's no noticeable effect on regular file UI. I think you can still specify the root contents manager class if you need to.
I'm not 100% sure why this is implemented by overriding ContentsManager rather than replicating the API on a different endpoint.


Fix city name reference

Fix city normalisation from JSON to ruby object.
It was setting the full object { "name": "Acrelândia", "code": "1200013" }. Change to set only the name.

thanks for catching that <3


[2.2] fix: #10207 and #10206 admin search endpoint fixed

Info
Link: #10207 and #10206

Checked and found that the issue has been fixed. Please check the video for reference.
Grouped Product
https://github.com/user-attachments/assets/a3c037cb-b424-4e86-a6b5-220be5dca418
Bundled Product
https://github.com/user-attachments/assets/5cd2d06f-d4b8-48ac-87e1-c01066d7d16e


For a large api response, karate throws an error and stops schema validation in between

My feature file used
Feature: Test GET all locations and validate response object
Background:
    *  def result =  callonce read('../03_Locations/sender-interface/get-all-locations/GetLocations.feature')

Scenario: Validate Location object schema for mandatory and optional parameters

    * def locationData = $result
    * print locationData
    * match locationData.response contains {data: '#array'}
    * match locationData.response.data != []
    * match locationData.response.status_code == 1000
    * match locationData.response contains {timestamp: '#string', status_message: '#string'}
    * def givenTimestamp = locationData.response.timestamp

The error message I'm getting :
node:internal/errors:541
throw error;
^
TypeError [ERR_INVALID_ARG_TYPE]: The "code" argument must be of type number. Received type string ('ERR_CHILD_PROCESS_STDIO_M...')
at process.set [as exitCode] (node:internal/bootstrap/node:123:9)
at /home/user/Documents/test/node_modules/shelljs/src/exec-child.js:25:22
at ChildProcess.exithandler (node:child_process:430:5)
at ChildProcess.emit (node:events:519:28)
at maybeClose (node:internal/child_process:1105:16)
at ChildProcess._handle.onexit (node:internal/child_process:305:5) {
code: 'ERR_INVALID_ARG_TYPE'
}
Node.js v20.14.0
/home/user/Documents/test/node_modules/@jbangdev/jbang/jbang.js:28
throw err;
^
Error: The command failed: 'jbang  -Dkarate.config.dir=/home/anushabr/Documents/roaminghub-test-suite/src/test-scripts com.intuit.karate:karate-core:LATEST:all src/test-scripts/emsp_as_ocpi_api/13_Location_Tariff_Verification/LocationAndTariffExistsCheck.feature'. Code: 1
at jbang.exec (/home/user/Documents/test/node_modules/@jbangdev/jbang/jbang.js:24:15)
at karate.exec (/home/user/Documents/test/node_modules/@karatelabs/karate/karate.js:13:8)
at Object. (/home/user/Documents/test/test.js:4:8)
at Module._compile (node:internal/modules/cjs/loader:1358:14)
at Module._extensions..js (node:internal/modules/cjs/loader:1416:10)
at Module.load (node:internal/modules/cjs/loader:1208:32)
at Module._load (node:internal/modules/cjs/loader:1024:12)
at Function.executeUserEntryPoint [as runMain] (node:internal/modules/run_main:174:12)
at node:internal/main/run_main_module:28:49 {
code: 1,
cause: ''
}
Node.js v20.14.0

@anusha-br sorry, you have to help us replicate this. follow this process: https://github.com/karatelabs/karate/wiki/How-to-Submit-an-Issue
see if you can run this directly via java + the command-line also, and take the help of someone who knows how to set the JVM memory: https://github.com/karatelabs/karate/wiki/Get-Started:-Other-Runtime-Options
also see if this helps: https://stackoverflow.com/a/67245228/143475