Parquet schema / data type for entire null object DataFrame columns

I'm writing some DataFrame to binary parquet format with one or more entire null object columns.
If I then load the parquet dataset with use_legacy_dataset=False
parquet_dataset = pq.ParquetDataset(root_path, use_legacy_dataset=False, **kwargs)
type(parquet)
pyarrow.parquet._ParquetDatasetV2

It returns an _ParquetDatasetV2 instance and when I check the schema.
type(parquet_dataset.schema)
pyarrow.lib.Schema

If I load the same file but with use_legacy_dataset=True
parquet_dataset2 = pq.ParquetDataset(root_path, use_legacy_dataset=True, **kwargs)

The schema for the file is an instance of ParquetSchema
type(parquet_dataset2.schema)
pyarrow._parquet.ParquetSchema

This is as I would expect and I'm aware that I can get the "arrow schema" like this.
arrow_schema = parquet_dataset2.schema.to_arrow_schema()
type(arrow_schema)
pyarrow.lib.Schema

i.e same format as when I use use_legacy_dataset=False
For an instance of ParquetSchema, I can get details of any column. e.g
parquet_dataset2.schema[13]

<ParquetColumnSchema>
  name: col13
  path: col13
  max_definition_level: 1
  max_repetition_level: 0
  physical_type: INT96
  logical_type: None
  converted_type (legacy): NONE

Here the "physical_type" for this column is INT96.
parquet.schema[13].physical_type
'INT32'

For an instance of pyarrow.lib.Schema, if I get the "data type" for the same column.
parquet_dataset.schema.field("col13").type
DataType(null)

i.e with no information about what the "data type" is supposed to be.
This information is available in the Parquet file. But how do I access it?
Is there way to convert instance of pyarrow.lib.Schema -> pyarrow._parquet.ParquetSchema?

I recreated the error with a simple test dataframe.
I think there is a bug on the  legacy datasets API.
Where is is getting the  INT32 physical type from?

Copying my question from the gist:
What is parquet_file.schema[0].logical_type? For me, if I do not specify a schema, it is Null (which is different than None). In your first snippet the logical type is None so I assume you are specifying the schema when writing.
Perhaps you have some files with Null logical type and some with None logical type? This could explain the behavior as the new datasets API infers the schema from a single file (picked more or less at random). So if it picked one of the null ones then you may end up with the behavior you are describing.

parquet_file.schema[0]

<ParquetColumnSchema>
  name: x
  path: x
  max_definition_level: 1
  max_repetition_level: 0
  physical_type: INT32
  logical_type: Null
  converted_type (legacy): NONE

Just incase there is some issue with my  data source .
Now I'm using df = pd.DataFrame(data={"x": [None, ]}) as input.

This is a null array represented in parquet:
<ParquetColumnSchema>
  name: x
  path: x
  max_definition_level: 1
  max_repetition_level: 0
  physical_type: INT32
  logical_type: Null
  converted_type (legacy): NONE

The original post was not a null array:
<ParquetColumnSchema>
  name: col13
  path: col13
  max_definition_level: 1
  max_repetition_level: 0
  physical_type: INT96
  logical_type: None
  converted_type (legacy): NONE

In particular the logical_type is different between the two.  I'm not actually sure what data type it is (maybe timestamp)?  What is different between how the data is generated?

Ignoring my initial code sample where I was using real parquet file as source.
This is fresh example using df = pd.DataFrame(data={"col1": [None, ], "col2": ["foo1", ]}) as starting point.
Where does pyarrow get INT32 as "physical_type" when the column completely empty (only null values)
import pandas as pd
import pyarrow as pa
import pyarrow.parquet as pq

df = pd.DataFrame(data={"col1": [None, ], "col2": ["foo1", ]})

table = pa.Table.from_pandas(df)

pq.write_table(table, '/tmp/data.parquet')

legacy_dataset = pq.ParquetDataset('/tmp/data.parquet', use_legacy_dataset=True)

dataset = pq.ParquetDataset('/tmp/data.parquet', use_legacy_dataset=False)

legacy_dataset.schema

<pyarrow._parquet.ParquetSchema object at 0x7efc1dc51a40>
required group field_id=-1 schema {
  optional int32 field_id=-1 col1 (Null);
  optional binary field_id=-1 col2 (String);
}

legacy_dataset.schema[0]

<ParquetColumnSchema>
  name: col1
  path: col1
  max_definition_level: 1
  max_repetition_level: 0
  physical_type: INT32
  logical_type: Null
  converted_type (legacy): NONE

dataset.schema[0].type

DataType(null)

Where does pyarrow get INT32 as "physical_type" when the column completely empty (only null values)

For Parquet, you need to distinguish the "physical_type" and "logical_type" (as shown in the output of the ParquetColumnSchema, this is "INT32" vs "Null" for this column of all nulls).
Parquet only has a limited set of physical types, see https://github.com/apache/parquet-format#types. And "Null" is not a physical type, but only a logical type. And a logical type always "annotates" some actual physical type.
So when Arrow saves a "null" column (in Arrow this is an actual, proper type) to Parquet, it can use a "Null" logical type, but it still needs to choose some physical type for the column in the Parquet file. And by default, Arrow uses INT32 for the physical type.
That explains where the "INT32" physical type is coming from. But in general, I think you don't need to care about this / you can ignore this. When reading the Parquet file to an Arrow table, we will correctly notice the "Null" logical type, and create a "null" column in the resulting Arrow table (basically ignoring the INT32 physical type of the Parquet field)

Ok. Thanks for the explanation.
I think I am going to change my code the use the v2 dataset API (use_legacy_dataset=False)
And then throw an error when field.type == pa.null() and ask the user to cast dataframe column with specific type.
e.g df['x'] = df['x'].astype('string')

still needs to choose some physical type for the column in the Parquet file. And by default, Arrow uses INT32 for the physical type.
@jorisvandenbossche can that default be changed in pyarrow ? I want to use STRING instead.
The issue we are facing is that when saving a dataset, i.e. multiple parquet files, with one file having a column coincidentally with all nulls whereas other files have some strings for that column. The result is different schema across the dataset (INT32 or STRING), which when reading with bigquery (for instance), raises errors.

It's currently not possible to customize this as a user (and I am not sure it is worth adding a new option for this ..).
If you want to use strings for all-null columns, you can also try to ensure your data have a proper string type when saving to parquet (this issue only happens if the data has the actual "null" arrow data type, not if your column contains all-null data but has some actual data type like "string").
Of course, it depends on your exact pipeline how easy it is to do (eg if you actually start with pandas data that gets converted to arrow while writing to parquet, you can currently only specify a full schema, not just the data type for one column were you want to override the inference).

@jorisvandenbossche you are right on, pandas is the source, and before that sql (query).
I could figure out how to retrieve sqltypes somewhere in pandas internals (or sqlalchemy) to map to the correct dtype for pa.null-type columns (I saw a long-time open issue on that) but for my use case, all such happen to be null-strings so the below just works fine:
schema = pa.Schema.from_pandas(df)
for i, col in enumerate(schema):
    if col.type == pa.null():
        schema = schema.set(i, pa.field(col.name, pa.string()))
table = pa.Table.from_pandas(df, schema=schema)


Update with kubebuilder go/v4

/help
It looks like we are eligible to upgrade our toolchain at somepoint using the latest kubebuilder variant with plugin go/v4. Of the listed upgrade reasons we meet the following criteria:
- If you are looking to have your project update with the latest version available
- if you are not targeting k8s versions < 1.16 and 1.20 if you are using webhooks
- If you are looking to work on with scaffolds which are compatible with k8s 1.25+

/priority important-longterm
However, we are not in a rush as we are not blocked by any of the other reasons, and this does require a tedious migration process involving regenerating some code as the directory structure totally changed. See the migration guide here if you are interested.

/assign

/assign


[Java] default output directory of SbeTool to CWD

The docs here say the output directory defaults to current : "sbe.output.dir: Target directory for output generation, defaults to current directory."
However it attempts to write to /packagename.
Small patch to fix that.

Thanks


Problem using Java library

I am running into issues using the or-tool library with Java bindings. We have one class and one test that uses MPSolver. When the test is run by itself everything works, but the VM crashes when run as part of the test suite. Through both stepping through with a debugger and by using print lines, I have determined that the JVM is crashing with a SIGILL when our code calls MPSolver.solve.
I am running this on OSX 10.11.6.  I am using the prebuilt libraries. But the only files I am including in the build are libjniortools.jnilib and the ortools jar. Is this correct set of files to include?
Intellij just gives me this error:
Process finished with exit code 132 (interrupted by signal 4: SIGILL)

But maven provides a bit more:
/bin/sh: line 1: 10427 Illegal instruction: 4  /Library/Java/JavaVirtualMachines/jdk1.8.0_102.jdk/Contents/Home/jre/bin/java -javaagent:/Users/adamcook/.m2/repository/org/jacoco/org.jacoco.agent/<IP_ADDRESS>505241946/org.jacoco.agent-<IP_ADDRESS>505241946-runtime.jar=destfile=/Users/adamcook/code/algorithm/target/jacoco.exec -jar /Users/adamcook/code/algorithm/target/surefire/surefirebooter7894310666470673198.jar /Users/adamcook/code/algorithm/target/surefire/surefire6683140905464024423tmp /Users/adamcook/code/algorithm/target/surefire/surefire_04135778575773710503tmp

Results :

Tests run: 201, Failures: 0, Errors: 0, Skipped: 1

[INFO] ------------------------------------------------------------------------
[INFO] BUILD FAILURE
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 01:35 min
[INFO] Finished at: 2016-11-14T16:54:22-08:00
[INFO] Final Memory: 28M/180M
[INFO] ------------------------------------------------------------------------
[ERROR] Failed to execute goal org.apache.maven.plugins:maven-surefire-plugin:2.12.4:test (default-test) on project foxtrot-algorithm: Execution default-test of goal org.apache.maven.plugins:maven-surefire-plugin:2.12.4:test failed: The forked VM terminated without saying properly goodbye. VM crash or System.exit called ? -> [Help 1]
org.apache.maven.lifecycle.LifecycleExecutionException: Failed to execute goal org.apache.maven.plugins:maven-surefire-plugin:2.12.4:test (default-test) on project foxtrot-algorithm: Execution default-test of goal org.apache.maven.plugins:maven-surefire-plugin:2.12.4:test failed: The forked VM terminated without saying properly goodbye. VM crash or System.exit called ?
	at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:224)
	at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:153)
	at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:145)
	at org.apache.maven.lifecycle.internal.LifecycleModuleBuilder.buildProject(LifecycleModuleBuilder.java:116)
	at org.apache.maven.lifecycle.internal.LifecycleModuleBuilder.buildProject(LifecycleModuleBuilder.java:80)
	at org.apache.maven.lifecycle.internal.builder.singlethreaded.SingleThreadedBuilder.build(SingleThreadedBuilder.java:51)
	at org.apache.maven.lifecycle.internal.LifecycleStarter.execute(LifecycleStarter.java:120)
	at org.apache.maven.DefaultMaven.doExecute(DefaultMaven.java:355)
	at org.apache.maven.DefaultMaven.execute(DefaultMaven.java:155)
	at org.apache.maven.cli.MavenCli.execute(MavenCli.java:584)
	at org.apache.maven.cli.MavenCli.doMain(MavenCli.java:216)
	at org.apache.maven.cli.MavenCli.main(MavenCli.java:160)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.codehaus.plexus.classworlds.launcher.Launcher.launchEnhanced(Launcher.java:289)
	at org.codehaus.plexus.classworlds.launcher.Launcher.launch(Launcher.java:229)
	at org.codehaus.plexus.classworlds.launcher.Launcher.mainWithExitCode(Launcher.java:415)
	at org.codehaus.plexus.classworlds.launcher.Launcher.main(Launcher.java:356)
Caused by: org.apache.maven.plugin.PluginExecutionException: Execution default-test of goal org.apache.maven.plugins:maven-surefire-plugin:2.12.4:test failed: The forked VM terminated without saying properly goodbye. VM crash or System.exit called ?
	at org.apache.maven.plugin.DefaultBuildPluginManager.executeMojo(DefaultBuildPluginManager.java:143)
	at org.apache.maven.lifecycle.internal.MojoExecutor.execute(MojoExecutor.java:208)
	... 19 more
Caused by: java.lang.RuntimeException: The forked VM terminated without saying properly goodbye. VM crash or System.exit called ?
	at org.apache.maven.plugin.surefire.booterclient.output.ForkClient.close(ForkClient.java:257)
	at org.apache.maven.plugin.surefire.booterclient.ForkStarter.fork(ForkStarter.java:301)
	at org.apache.maven.plugin.surefire.booterclient.ForkStarter.run(ForkStarter.java:116)
	at org.apache.maven.plugin.surefire.AbstractSurefireMojo.executeProvider(AbstractSurefireMojo.java:740)
	at org.apache.maven.plugin.surefire.AbstractSurefireMojo.executeAllProviders(AbstractSurefireMojo.java:682)
	at org.apache.maven.plugin.surefire.AbstractSurefireMojo.executeAfterPreconditionsChecked(AbstractSurefireMojo.java:648)
	at org.apache.maven.plugin.surefire.AbstractSurefireMojo.execute(AbstractSurefireMojo.java:586)
	at org.apache.maven.plugin.DefaultBuildPluginManager.executeMojo(DefaultBuildPluginManager.java:132)
	... 20 more
[ERROR]
[ERROR]
[ERROR] For more information about the errors and possible solutions, please read the following articles:
[ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/PluginExecutionException

Actually all of the .dynlib files are also in the same directory as the .jnilib file. But they aren't referenced from Java or maven in any way.

This issue appears to be limited to Cbc - using GLPK as our MIP solver sidestepped the issue. We're not sure if the problem originates in Cbc or or-tools, though I note we were able to solve some MIP problems with Cbc accessed via JuMP and Julia.

Did somebody find the source of the problem ?

Any update on this bug? I have the same issue!

This happens to me with less than 100% reliability. I get runs with SIGILL but no stacktrace, SIGILL with stacktrace, and some successful runs. My program is not using any threads, so if there is a race, it isn't in my code.

Same issue too. Just get "Process finished with exit code 132 (interrupted by signal 4: SIGILL)" when run "model.solve()". And I tried to re-install ortools and chose "Installing OR-Tools Java from Source". New library works.

I know.
I have no way to fix that. There is an incompatibility between Java and the CBC code (I believe when solving in parallel).

@roborobotheart can you explain how you solved? I've tried to build the sources from latest stable and then use what was inside lib in the classpath but i'm getting other errors. Which version is working for you?

I've updgraded from java 12 to java 13 and the problem is solved.


Cuboxi & adalightapa102

Hi,
I tried newest release from hyperion for cubox-i and it seams to miss adalightapa102 leddevice. Could it be a case? Is there anything specific to the raspberry pi that would prevent this leddevice to work with cubox-i? I've looked at the code and I don't see that.
Here is the output that I'm getting:
OpenELEC:~/.config # ../hyperion/bin/hyperiond.sh hyperion.config.json
Application build time: Sep  9 2015 21:54:50
QCoreApplication initialised
Selected configuration file: hyperion.config.json
ColorTransform 'leds' => [0; 259]
Device configuration:
{
"colorOrder" : "bgr",
"name" : "MyPi",
"output" : "/dev/ttyACM0",
"rate" : 500000,
"type" : "adalightapa102"
}
Unable to create device adalightapa102
Black border threshold set to 0.05 (13)
Creating linear smoothing
Created linear-smoothing(interval_ms=50;settlingTime_ms=100;updateDelay=0
Effect loaded: Knight rider
Effect loaded: Blue mood blobs
Effect loaded: Cold mood blobs
Effect loaded: Full color mood blobs
Effect loaded: Green mood blobs
Effect loaded: Red mood blobs
Effect loaded: Warm mood blobs
Effect loaded: Rainbow mood
Effect loaded: Rainbow swirl fast
Effect loaded: Rainbow swirl
Effect loaded: Snake
Effect loaded: Strobe blue
Effect loaded: Strobe Raspbmc
Effect loaded: Strobe white
Effect loaded: X-Mas
Initializing Python interpreter
Hyperion created and initialised
run effect Rainbow swirl fast on channel 0
Boot sequence(Rainbow swirl fast) created and started
Framebuffer opened with resolution: 1920x1080@32bit
Framebuffer grabber created and started
Json server created and started on port 19444
Proto server created and started on port 19445
Segmentation fault
OpenELEC:~/.config #
Thank you in advance!
Tomek.

Hi
I'm having the same problem: OSMC + hyperion master. Could you please advise what to do?

@tomaszszczerba

I tried newest release from hyperion for cubox-i
Which one? hyperion_imx6.tar.gz?

I used hyperion installator (a standard one). It has a logic that will install tar.gz that you mentioned on cuboxi.

Try this one to update and report back
https://github.com/tvdzwan/hyperion/issues/493
Thank you

@tomaszszczerba
Any news on this?

yes, I got my cuboxi a few days ago, I'll check on that.
Right now I tested your script on rpi3 (but you know that one works). Sorry about the wetek - I don't have this one anymore, but will try to test on my friends.

I tested your problem on rpi3
i don´t get the Unable to create device adalightapa102
message in the log. So i am sure it is working with the latest images.
Also i added the AdalightAPA102 device to HyperCon.
Will be published soon

Is it ok if i close this?

Yes, I did that too and works beautifully. Thank you for this!


Getting error while running az login --identity in ML compute: ImportError: cannot import name 'PersistenceError' from 'msal_extensions.persistence'

This is autogenerated. Please review and update as needed.
Describe the bug
Getting error while running az login --identity in ML compute
As advised in following Github issue link: https://github.com/Azure/azure-cli/issues/22325
We tried upgrading azure identity version from 1.7.0 to 1.12.0. But still it is not working.
Command Name
az login --identity
Errors:
ImportError: cannot import name 'PersistenceError' from 'msal_extensions.persistence' (/anaconda/envs/azureml_py38/lib/python3.8/site-packages/msal_extensions/persistence.py)

To Reproduce:
Steps to reproduce the behavior. Note that argument values have been redacted, as they may contain sensitive information.

Put any pre-requisite steps here...
az login --identity

Expected Behavior
Environment Summary
Linux-5.15.0-1035-azure-x86_64-with-glibc2.10, Ubuntu 20.04.6 LTS
Python 3.8.5
Installer: PIP

azure-cli 2.47.0
azure identity 1.12.0

Extensions:
azure-cli-ml 1.41.0
ml 2.5.0

Dependencies:
msal 1.21.0
azure-mgmt-resource 21.2.1

Additional Context

In additional to https://github.com/Azure/azure-cli/issues/22325#issuecomment-1371717240, downgrading azure-identity will downgrade msal-extensions because azure-identity has an upper bound for msal-extensions. On the contrary, upgrading azure-identity won't affect msal-extensions since new azure-identity is compatible with old versions of msal-extensions.
Could you try to upgrade msal-extensions to the latest version as well?

@jiasli Could you please provide an update on the issue or any other suggestions to try.

It is likely you are not installing into Azure CLI's env: /anaconda/envs/azureml_py38/lib/python3.8/site-packages. You may run pip list -v to confirm. If Azure CLI's environment has been corrupted, you need to use the pip of that environment to fix it.
@azureml-github, please help take a look, as installing Azure CLI into a custom python environment is not officially supported.


Replace Travis with CircleCI and add auto deploy to staging

This is the result of two discussions on our research board. The first was to replace Travis with CircleCI:
https://trello.com/c/Se4mELMh/199-hosted-ci-for-continuous-deployment
A few reasons we've enjoyed using Circle:

Faster builds due to parallel builds
Built in bundle caching
Easy deployment
Really easy setup
The ability to ssh into the CI server during a test run. This has been great when debugging a test failure. It's not something you use a lot but it is so great when you need it.
A free plan for private repos that supports small MVPS

This also adds automatic deployment to staging when the build passes. This is the result of this discussion:
https://trello.com/c/Se4mELMh/199-hosted-ci-for-continuous-deployment
A few reasons for those who don't have access to the trello card:

Part of the CI now is whether or not you can actually deploy successfully. If you merge to master, it will automatically try and deploy to staging. If that fails, your build will actually fail. This should be treated with the same urgency that any other failing build on master would be treated.
Staging is always up to date. No options. This makes it really nice for verifying stories for clients.
Automate more things!

LGTM.

Thanks @tute and @gabebw

We don't want to set up the project with bin/setup on CI?

We don't want to set up the project with bin/setup on CI?

I also liked that we used the same bin/setup locally and on CI.


node 10 install issue

I am running Manjaro/Arch Linux:
community/zeromq 4.2.2-2 [installed]  Fast messaging system built on sockets. C and C++ bindings. aka 0MQ, ZMQ.
community/node-gyp 3.6.2-1 [installed]
    Node.js native addon build tool
community/nodejs 10.4.0-1 [installed]
    Evented I/O for V8 javascript

Now I just tried to install the npm package zmq, but it failed.
gyp ERR! node -v v10.4.0
gyp ERR! node-gyp -v v3.6.2
npm ERR<EMAIL_ADDRESS>install: `node-gyp rebuild`
136 verbose stack Exit status 1
136 verbose stack     at EventEmitter.<anonymous> (/usr/lib/node_modules/npm/node_modules/npm-lifecycle/index.js:304:16)
136 verbose stack     at EventEmitter.emit (events.js:182:13)
136 verbose stack     at ChildProcess.<anonymous> (/usr/lib/node_modules/npm/node_modules/npm-lifecycle/lib/spawn.js:55:14)
136 verbose stack     at ChildProcess.emit (events.js:182:13)
136 verbose stack     at maybeClose (internal/child_process.js:961:16)
136 verbose stack     at Process.ChildProcess._handle.onexit (internal/child_process.js:248:5)

I think it is due to the new version 10 of node.
On my computer that runs an older version all is fine.

Same problem with node 10.16.3. It is still working fine on 8.x


Consider supporting *.mysql file type for import-db

What happened (or feature request):
Rick noted with a ddev demo that an import of a backup-migrate module backup failed.  For example, ddev import-db --src=APLVDatabaseBackup-2017-10-23T06-30-32.mysql.gz:
Failed to import database for aplv: no .sql files found to import

The issue here is that backup-migrate uses the very nonstandard ".mysql" file type inside the gzip file, and ddev recognizes only the more-likely ".sql" filetype.
backup-migrate has gzip files like APLVDatabaseBackup-2017-10-23T06-30-32.mysql.gz containing a file like APLVDatabaseBackup-2017-10-23T06-30-32.mysql. If you gunzip and give the .mysql file to ddev import-db, it imports just fine.
It shouldn't be hard to expand our vision to looking for *.mysql as equivalent to *.sql

We can re-open if anyone else trips up on this.

As a frequent user of backup_migrate for its one-click downloads of remote databases (and I can't be the only one) this would be a big help.

Please open a new issue with your request, thanks!

Done https://github.com/drud/ddev/issues/1483


add test coverage

What I have done:

visit this website and setup the codecov for this repo, https://app.codecov.io/gh
make this repo public (otherwise this service is hard to setup)
add the badge and codecov commands in CI (check the Files changed of this PR).

@maddiecain

Codecov Report

:exclamation: No coverage uploaded for pull request base (main@ecd931c). Click here to learn what that means.
The diff coverage is n/a.

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  Coverage        ?   88.00%
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  Branches        ?        0
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  Misses          ?       30
  Partials        ?        0

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Everything looks good to me!


parameter to start another job after after job is finished

for example, if I want to start the full backup job after index optimizing I could just add
@startjob = 'Full Backup - USER DATABASES'
I could replace all schedules but the first one.

Why not just create one job with multiple steps?

primarily for running it as a command or if there are other jobs that are not necessarily related to the maintenance jobs but I want to run them anyway after update statistics for example...
you could do it by adding another step with the sp_start_job proc, but I thought it would be more efficient doing it in the same step with one command.


Test scroll position when page invalidated

Related: #63 and https://github.com/turbolinks/turbolinks/issues/181

Seems fixed now! 🎉

Seems fixed now! 🎉


Reduce SQL panel overhead

The existing SQLPanel.generate_stats() method can be rather expensive if there are a lot of SQL queries.  This PR defers that expense by moving that code to a new generate_context() method, which only gets called if the panel's .content attribute is accessed.  Thus requests in which the user does not need to see the SQL Panel content get faster.
It also moves some code from the NormalCursorWrapper._record() function to the SQLPanel.generate_context() method to reduce the runtime overhead of recording SQL queries.

Thus requests in which the user does not need to see the SQL Panel content get faster.

How do we determine which requests the user doesn't need to see the SQL Panel content for?

How do we determine which requests the user doesn't need to see the SQL Panel content for?

We don't have to.  All the information is still there, but the heavy computations are deferred until the the first time the render_panel() view is called, which actually displays the panel content.

There are a lot of good things in this PR that aren't all related to the performance improvements. I'd be happy to merge those in separate PRs.
Regarding the performance improvements: which part(s) of generate_stats are expensive? Can we move those out to something that occurs on render? The concern is that the SQLPanel won't have the same flow as the other panels. This makes maintenance a bit more cumbersome and would impact any third party panels that inherit from SQLPanel. I'm currently a 0 on this. I'd be a 1 if we stuck to record_stats storing the information that's then used by the overridden content property / a new render function which would do the expensive computations.
@matthiask what are your thoughts?

Thanks for the feedback.  I've had some thoughts on the design so I'm planning to rework this PR a little bit and then hopefully post an updated version for review this week.
Regarding the overall performance of .generate_stats(), I have not done any profiling to see what parts are expensive, but was rather trying to defer the cost until it was actually needed.  But trying to improve the overall performance is probably something worth looking into in addition to deferring unnecessary work until rendering the content.  I do know that prettifying the SQL can be expensive, especially for queries with large numbers of terms.  I have posted PRs to fix a couple of instances of quadratic behavior in sqlparse, but they have not yet been merged.  I suspect that sqlparse isn't the only contributor to the rendering cost, but without doing some profiling work I cannot say definitively.

Superseeded by changes which have been merged in the meantime. Thanks!


Revert "Packaging: adjust dependecy requirements #1203"

This reverts commit 97d1cbada4b7b600f85484055f31862d1a42c737.
OVS on RHEL is in a different repo than nmstate, thus Recommends
should be used.
Signed-off-by: Antonio Cardace<EMAIL_ADDRESS>

The specfile is actually correct, closing this.


Gallery

Hello! I'm trying to use the hugo-shortcode-gallery together with this theme, but I seem to be running into the same issue as https://github.com/mfg92/hugo-shortcode-gallery/issues/19 which seems to point to a theme incompatibility.
The error I'm getting is gallery.justifiedgallery is not a function
Sadly I'm quite new to the whole hugo-thing so I'm not exactly sure what the fix would be in this case. Any pointers?

I think we should go with https://photoswipe.com = https://github.com/dimsemenov/photoswipe
since they have enough features and compatible license

What about https://hugocodex.org/add-ons/slider-carousel/
I used the  lightbox https://hugocodex.org/add-ons/lightbox/
When you add hyperlinks to the source file of  an image this works out of the box
But now i run into the issue that each image is displayed with full page/content width. and I cant make it display smaller images side by side.

@jonas37 Thanks for suggestion, looks ok, but it is a little different use case. A separate feature I would say. We can have both Gallery option and carousel option. Feel free to
I can see they also have https://hugocodex.org/add-ons/image-gallery/ , but it seems pretty basic (not even left/right keys working)

@jonas37 Thanks for suggestion, looks ok, but it is a little different use case. A separate feature I would say. We can have both Gallery option and carousel option.
I can see they also have hugocodex.org/add-ons/image-gallery , but it seems pretty basic (not even left/right keys working)

any idea how you would integrate photoswipe then? image-gallery is really basic indeed. Doesnt this repo also work with sub modules? Im using the https://github.com/gethugothemes/hugo-modules/tree/master/gallery-slider in a different project. Ill test how it works as shortcode.


Logout does not properly end the session

🐛 Bug Report

[ ] I am including my log files in zip format.
[x] I have looked for similar issues among all the former issues including closed ones.

What Operating system and version is LibrePhotos running on:
Debian/Docker
What architecture is LibrePhotos running on:
x64
How is LibrePhotos installed:
Docker - using dev tag
If running via Docker or Kubernetes please list version including docker-compose:
version: '3.8'
services:
  proxy:
    image: reallibrephotos/librephotos-proxy:${tag}
    restart: always
    volumes:
    # - /home/docker/librephotos/photos:/data
      - nas-images:/data
      - librephotos-protected:/protected_media
    ports:
      - ${httpPort}:80
    depends_on:
      - backend
      - frontend

  frontend:
    image: reallibrephotos/librephotos-frontend:${tag}
    restart: always
    depends_on:
      - backend

  backend:
    image: reallibrephotos/librephotos:${tag}
    restart: always
    volumes:
      - nas-images:/data
      - librephotos-protected:/protected_media
      - ${logLocation}:/logs
      - ${cachedir}:/root/.cache

    environment:
      - SECRET_KEY=${shhhhKey}
      - BACKEND_HOST=backend
      - ADMIN_EMAIL=${adminEmail}
      - ADMIN_USERNAME=${userName}
      - ADMIN_PASSWORD=${userPass}
      - DB_BACKEND=postgresql
      - DB_NAME=${dbName}
      - DB_USER=${dbUser}
      - DB_PASS=${dbPass}
      - DB_HOST=database.triplusnet.home
      - DB_PORT=5432
      - REDIS_HOST=redis
      - REDIS_PORT=6379
      - MAPBOX_API_KEY=${mapApiKey}
      - TIME_ZONE=${timeZone}
      - WEB_CONCURRENCY=${gunniWorkers}
      #- SKIP_PATTERNS=${skipPatterns}
      - DEBUG=0
      - HEAVYWEIGHT_PROCESS=${HEAVYWEIGHT_PROCESS}

  redis:
    image: redis:6
    restart: always

volumes:
  nas-images:
    driver: local
    driver_opts:
      type: cifs
      o: "username=librepho,password=xxx,rw"
      device: "//<IP_ADDRESS>/Photos"
  librephotos-protected:
    driver: local
    driver_opts:
      type: cifs
      o: "username=librepho,password=xxx,rw"
      device: "//<IP_ADDRESS>/librephotos-work"

Are you running LibrePhotos on a virtual machine if so please list:
Proxmox VM running docker
How is you picture library mounted on the host (or in the virtual machine):
Local file system (Type), NFS, or SMB
SMB
Description of issue:
When logging out of one user and logging in on another user, the photos of the first user are still shown.
In my example:

Login with admin user (for me, this one has no pictures ect.)
Logout on admin user
Login with a different user
Observe that there are no photos displayed (so the admin photos probably)
Press crtl+f5 and the correct photos are visible.

How can we reproduce it:
see above
Additional Information:

Include a ZIP file containing your log files.
Provide pictures or links to videos that clearly demonstrate the issue.

Duplicate of #453

You are correct - I will close this so it can be tracked in the original ticket.
"logout" & "session" were not the correct search terms it seems ;)

Thanks for checking out Librephotos!


Do not draw strokes unless a stroke color, pattern, or gradient is sp…

…ecified
Noticed this when checking a SVG that renders correctly in flutter_svg.
flutter_svg had a bug like this at some point that I fixed and didn't think applied to this package, but it does.
The overdraw optimizer test had to be updated because it doesn't do optimization if there's a stroke, but it can now do the optimization on the sample SVG because there is a stroke property that doesn't result in drawing strokes there. Added another test that actually does draw a stroke to test both behaviors.

We should probably wait to land this until google3 is caught up to head to make sure if it breaks goldens we know why.

Ahh ok optimizers will get rolled in separately anyway. I'll land and kick a roll and we can see.


Implement Component for Hex

This should be hidden behind a feature flag to avoid pulling in bevy_ecs as a dependency. Storing the position of an effect, unit or tile directly on the entity is a common and clear pattern.

Having Hex as a Component is definetely possible but wouldn't that go against the whole point of the Component trait ?
It's like putting a IVec2 as a component, it could mean many things


feat: add tailwind-converter

what is this
currently a tailwind to CSS-in-JS converter
in the future it could :

keep the theme token values

atm: bg-slate-100  -> background: "#12345"
future: bg-slate-100 -> background: "slate.100" (given slate.100 is defined in the theme.colors)

also convert the tailwind config to the panda config equivalent
atm it extracts (using box-extractor) class/className jsx attributes but in the future there could be a Combobox or some kind of inputs to specify which fn args to extract (think cx, clsx, cn, etc etc)

how does it work
using tailwind internals (1) we can directly use their config + function to convert to postcss AST and then walk this AST to convert to a CSS-in-JS object
// (1)
import { resolveMatches as resolveMatchesRaw } from 'tailwindcss/lib/lib/generateRules'
import { createContext as createContextRaw } from 'tailwindcss/lib/lib/setupContextUtils'

rough implementation is in tailwind-converter/src/converter/tw.ts

as a side note, the current tailwind-converter directory was ported from a local PoC vite repo so some eslint/ts lint rules may throw, some logs might still be commented out, in summary this is not clean yet

@segunadebayo @astahmer
Did this get closed because there's going to be a tailwind preset instead?
Seems like a killer feature to be able to just copy and paste tailwind examples from the net into a panda project.


Removing OperationName

Question
Is it possible to not pass OperationName to the backend? I would like to just pass variables and query

You can customize the HTTP request using the HttpRequestComposer API:
  object myHttpRequestComposer : HttpRequestComposer {
    override fun <D : Operation.Data> compose(apolloRequest: ApolloRequest<D>): HttpRequest {
      val postData = buildJsonString {
        writeObject {
          name("query")
          value(apolloRequest.operation.document())
          name("variables")
          apolloRequest.operation.serializeVariables(this, apolloRequest.executionContext[CustomScalarAdapters]!!, false)
        }
      }.encodeUtf8()

      return HttpRequest.Builder(HttpMethod.Post, "https://example.com/graphqls")
          .body(object : HttpBody {
            override val contentType: String
              get() = "application/Json"
            override val contentLength: Long
              get() = postData.size.toLong()

            override fun writeTo(bufferedSink: BufferedSink) {
              bufferedSink.write(postData)
            }
          })
          .build()
    }
  }

And then use it when building your ApolloClient:
    val apolloClient = ApolloClient.Builder()
        .networkTransport(
            HttpNetworkTransport.Builder()
                .httpRequestComposer(myHttpRequestComposer)
                .build()
        )
        .build()

Thanks for the quick replying. Could I use this along with okHttpClient?

@Provides
    @Singleton
    @Named("apollo")
    fun okhttpClientForApollo(): OkHttpClient {
        val logging = HttpLoggingInterceptor()
            .apply { level = HttpLoggingInterceptor.Level.BODY }
        return OkHttpClient().newBuilder()
            .connectTimeout(BFF_OK_HTTP_CONNECT_TIMEOUT_IN_SECONDS, TimeUnit.SECONDS)
            .readTimeout(BFF_OK_HTTP_READ_TIMEOUT_IN_SECONDS, TimeUnit.SECONDS)
            .writeTimeout(BFF_OK_HTTP_WRITE_TIMEOUT_IN_SECONDS, TimeUnit.SECONDS)
            .addInterceptor(GraphqlAuthInterceptor())
            .addInterceptor(logging)
            .build()
    }

@Provides
    @Singleton
    fun provideApollo(
        @Named("apollo") client: OkHttpClient
    ): ApolloClient {
        return ApolloClient.Builder()
            .okHttpClient(client)
            .build()
    }

Sure, just set the OkHttpClient on the HttpNetworkTransport:
    val client = ApolloClient.Builder()
        .networkTransport(
            HttpNetworkTransport.Builder()
                .okHttpClient(yourOkHttpClient)
                .httpRequestComposer(myHttpRequestComposer)
                .build()
        )
        .build()

This is what ApolloClient.Builder.okHttpClient() is doing under the hood

Getting a Nesting problem error now. Previously it was working as expected.
Error getting live orders Nesting problem. : java.lang.IllegalStateException: Nesting problem.
	at com.apollographql.apollo3.api.json.BufferedSinkJsonWriter.name(BufferedSinkJsonWriter.kt:119)
	at com.doordash.smartshelf.adapter.GetLiveOrdersQuery_VariablesAdapter.toJson(GetLiveOrdersQuery_VariablesAdapter.kt:32)
	at com.doordash.smartshelf.GetLiveOrdersQuery.serializeVariables(GetLiveOrdersQuery.kt:40)
	at com.doordash.smartshelf.network.ApiModule$apolloHttpRequestComposer.compose(ApiModule.kt:404)
	at com.apollographql.apollo3.network.http.HttpNetworkTransport.execute(HttpNetworkTransport.kt:50)
	at com.apollographql.apollo3.interceptor.NetworkInterceptor.intercept(NetworkInterceptor.kt:22)
	at com.apollographql.apollo3.interceptor.DefaultInterceptorChain.proceed(ApolloInterceptor.kt:23)
	at com.apollographql.apollo3.ApolloClient.executeAsFlow$apollo_runtime(ApolloClient.kt:187)
	at com.apollographql.apollo3.ApolloCall.toFlow(ApolloCall.kt:120)
	at com.apollographql.apollo3.ApolloCall.execute(ApolloCall.kt:129)

I'm using Apollo3 (3.8.2) and noticed that apolloRequest.operation.serializeVariables() doesn't have a 3rd parameter so I wonder if there's a version missmatch

My bad, I forgot to wrap the variables in writeObject:
          writeObject {
            apolloRequest.operation.serializeVariables(this, apolloRequest.executionContext[CustomScalarAdapters]!!, false)
          }

I have edited the code above to account for that

worked perfectly. Thank you very much!!!


KeyError: 'PROJ_LIB'

it seems that we don'r have the patch available if we have installed the developer environment by
$ conda create -n mssdev python=3 mamba
$ conda activate mssdev
(mssdev)$ mamba install mss --only-deps

This shows up as failure when e.g. the server is started now
WARNING:root:Couldn't import mscolab_settings (ImportError:'No module named 'mscolab_settings''), using dummy config.
Traceback (most recent call last):
  File "/home/user/PycharmProjects/mss/mslib/mscolab/server.py", line 44, in <module>
    from mslib.utils import conditional_decorator
  File "/home/user/PycharmProjects/mss/mslib/utils.py", line 42, in <module>
    import mpl_toolkits.basemap.pyproj as pyproj
  File "/home/user/miniconda3/envs/mssdev2/lib/python3.9/site-packages/mpl_toolkits/basemap/__init__.py", line 152, in <module>
    pyproj_datadir = os.environ['PROJ_LIB']
  File "/home/user/miniconda3/envs/mssdev2/lib/python3.9/os.py", line 679, in __getitem__
    raise KeyError(key) from None
KeyError: 'PROJ_LIB'

setting this var seems to be all needed
export PROJ_LIB=$CONDA_PREFIX/share/proj

setting this var seems to be all needed
export PROJ_LIB=$CONDA_PREFIX/share/proj

that maybe also a difference for mamba?

that maybe also a difference for mamba?

verified
(mssdev)$ conda install mss --only-deps
creates the env var but replaced by mamba not
But I also found an easy solution, The env var is enabled on restarting the env.
conda deactivate
conda activate mssdev

verified
(mssdev)$ conda install mss --only-deps
creates the env var but replaced by mamba not
But I also found an easy solution, The env var is enabled on restarting the env.
conda deactivate
conda activate mssdev

documentation fixed and upwards reported

documentation fixed and upwards reported


Unable to parse git-upload-pack payload

How to reproduce
# Setup server
git clone https://github.com/sluongng/git-cache/
git checkout 07f1136c7d09c8281e4e0d8a8b96e3816dffbdac
go run .

# Setup client
# This should clone git.git from Github through the simple golang proxy
git -c http.extraHeader='GIT-CACHE-UPSTREAM: https://github.com' clone -vvv http://<IP_ADDRESS>:8080/git/git.git

Expected result
The middleware layer in https://github.com/sluongng/git-cache/commit/07f1136c7d09c8281e4e0d8a8b96e3816dffbdac#diff-0eb779b9e49d8e44b0f36923fdb8d87d5ee024f886eefc45deec4ec88380a087R56 should be able to parse the request body into ProtocolV2RequestChunk and serialize the Chunks as JSON and log them out.
Actual result
ls-ref command seems to work fine, but the one next git-upload-pack command failed to be parse by gitprotocolio
Unable to scan request: strconv.ParseUint: parsing "\x1f\x8b\b\x00": invalid syntax

Which most likely coming from https://github.com/google/gitprotocolio/blob/b5a56823ae5213a598e042c567d5f0015213150b/token.go#L179

I am using latest Git version compiled from master of https://github.com/git/git/commit/670b81a890
~> git version
git version <IP_ADDRESS>.g670b81a890

Do you have full pkt-lines on the request? It seems to me that you've read the entire request body, so it should be easy to dump that.

After a bit of tinkering, it seems like the body of the fetch command was in gzip and need to be wrapped with a gzip.NewReader() before passing to gitprotocolio.
I am closing this issue for now. We can consider adding support for native gzip handling in this lib in a separate discussion (or if it's even needed)

To give future folks some context on how I fixed my issue: https://github.com/sluongng/git-cache/commit/02eca505f9405845a85e53425b50165a008f1a2c


Pytorch Profiler autocomplete

Environment data

Language Server version: 2021.3.2
OS and version: Linux Ubuntu 18.04
Python version (& distribution if applicable, e.g. Anaconda): 3.7.9
Pytorch version: 1.9.0.dev20210317

Expected behaviour
expected intellisense to pickup profiler methods
Actual behaviour

[Info  - 4:49:16 PM] Pylance language server 2021.3.2 (pyright 85309906) starting
[Info  - 4:49:16 PM] Server root directory: /home/azureuser/.vscode-server-insiders/extensions/ms-python.vscode-pylance-2021.3.2/dist
[Info  - 4:49:16 PM] No configuration file found.
[Info  - 4:49:16 PM] Setting pythonPath for service "pyprofiler": "/anaconda/envs/py37_default/bin/python"
Search paths found for configured python interpreter:
  /anaconda/envs/py37_default/lib/python3.7
  /anaconda/envs/py37_default/lib/python3.7/lib-dynload
  /anaconda/envs/py37_default/lib/python3.7/site-packages
  /anaconda/envs/py37_default/lib/python3.7/site-packages/dlib-19.18.0-py3.7-linux-x86_64.egg
  /anaconda/envs/py37_default/lib/python3.7/site-packages/xgboost-0.90-py3.7.egg
[Error - 4:49:16 PM] stubPath /home/azureuser/pyprofiler/typings is not a valid directory.
[Info  - 4:49:16 PM] Assuming Python version 3.7
[Info  - 4:49:16 PM] Assuming Python platform Linux
[Info  - 4:49:16 PM] Searching for source files
[Info  - 4:49:16 PM] Found 1 source file
[FG] parsing: /home/azureuser/pyprofiler/resnet50.py (68ms)
[FG] parsing: /home/azureuser/.vscode-server-insiders/extensions/ms-python.vscode-pylance-2021.3.2/dist/typeshed-fallback/stdlib/builtins.pyi [fs read 3ms] (111ms)
[FG] binding: /home/azureuser/.vscode-server-insiders/extensions/ms-python.vscode-pylance-2021.3.2/dist/typeshed-fallback/stdlib/builtins.pyi (43ms)
[FG] binding: /home/azureuser/pyprofiler/resnet50.py (3ms)
[Info  - 4:49:16 PM] Background analysis(1) root directory: /home/azureuser/.vscode-server-insiders/extensions/ms-python.vscode-pylance-2021.3.2/dist
[Info  - 4:49:16 PM] Background analysis(1) started
Background analysis message: setConfigOptions
Background analysis message: setTrackedFiles
Background analysis message: markAllFilesDirty
Background analysis message: ensurePartialStubPackages
Background analysis message: setFileOpened
Background analysis message: getDiagnosticsForRange
Background analysis message: getSemanticTokens full
[BG(1)] getSemanticTokens full at /home/azureuser/pyprofiler/resnet50.py ...
[BG(1)]   parsing: /home/azureuser/pyprofiler/resnet50.py (67ms)
[BG(1)]   parsing: /home/azureuser/.vscode-server-insiders/extensions/ms-python.vscode-pylance-2021.3.2/dist/typeshed-fallback/stdlib/builtins.pyi [fs read 2ms] (104ms)
[BG(1)]   binding: /home/azureuser/.vscode-server-insiders/extensions/ms-python.vscode-pylance-2021.3.2/dist/typeshed-fallback/stdlib/builtins.pyi (39ms)
[BG(1)]   binding: /home/azureuser/pyprofiler/resnet50.py (3ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/__init__.py [fs read 2ms] (77ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/__init__.py ...
[BG(1)]     parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/_C/__init__.pyi [fs read 1ms] (102ms)
[BG(1)]     binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/_C/__init__.pyi (50ms)
[BG(1)]     parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/_C/_VariableFunctions.pyi [fs read 1ms] (85ms)
[BG(1)]     binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/_C/_VariableFunctions.pyi (55ms)
[BG(1)]     parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/functional.py [fs read 1ms] (27ms)
[BG(1)]     binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/functional.py (7ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/__init__.py (335ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/nn/parallel/__init__.pyi [fs read 0ms] (1ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/nn/parallel/__init__.pyi (0ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/optim/__init__.pyi [fs read 0ms] (1ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/optim/__init__.pyi (0ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/utils/data/__init__.py [fs read 0ms] (11ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/utils/data/__init__.py (0ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/profiler/__init__.py [fs read 0ms] (2ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/profiler/__init__.py (0ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/nn/__init__.py [fs read 1ms] (2ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/nn/__init__.py ...
[BG(1)]     parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/nn/modules/__init__.py [fs read 0ms] (3ms)
[BG(1)]     binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/nn/modules/__init__.py (2ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/nn/__init__.py (6ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/backends/cudnn/__init__.py [fs read 0ms] (5ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torch/backends/cudnn/__init__.py (3ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/__init__.py [fs read 0ms] (0ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/__init__.py (1ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/transforms/__init__.py [fs read 0ms] (0ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/transforms/__init__.py ...
[BG(1)]     parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/transforms/transforms.py [fs read 0ms] (39ms)
[BG(1)]     binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/transforms/transforms.py (7ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/transforms/__init__.py (47ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/datasets/__init__.py [fs read 0ms] (3ms)
[BG(1)]   binding: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/datasets/__init__.py (0ms)
[BG(1)]   parsing: /anaconda/envs/py37_default/lib/python3.7/site-packages/torchvision/models/__init__.py [fs read 0ms] (1ms)
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[BG(1)] getSemanticTokens delta previousResultId:1616604575662 at /home/azureuser/pyprofiler/resnet50.py (10ms)
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[BG(1)] getSemanticTokens delta previousResultId:1616604578583 at /home/azureuser/pyprofiler/resnet50.py ...
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[BG(1)] getSemanticTokens delta previousResultId:1616604578583 at /home/azureuser/pyprofiler/resnet50.py (89ms)
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Code Snippet / Additional information
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim
import torch.utils.data
import torchvision
import torchvision.transforms as T
import torchvision.datasets as datasets
import torchvision.models as models

import torch.profiler

with torch.profiler.record_function("backward_pass"):

Looking at the torch package, there are two profiler submodules included: torch.autograd.profiler and torch.cuda.profiler. Based on the type information provided in the package, neither of these submodules is exported from the top-level torch module, so import torch.profiler isn't a valid symbol. It looks like you are interested in the autograd profiler, which you can access using import torch.autograd.profiler.
If you think that profiler should be exported from the top-level torch module, then this could be a bug in the type information provided in the package, and I recommend that you file a bug (or submit a PR) to the pytorch repo.

Duplicate of #484. I've already fixed this upstream, so whenever pytorch releases again it'll be fixed.
https://github.com/pytorch/pytorch/blob/f9ca0d87a7cd2afb3ae5866acf7a77af54c5ab91/torch/__init__.py#L671

@lenisha I heard you were testing with the 1.8.1 release candidate; do you know how I can test with it to verify my fix? We had previously gone and tested with a nightly build, but if the RC doesn't work then that's not good.

In a fresh environment with:
pip install --pre -U torch torchvision  -f https://download.pytorch.org/whl/test/cu102/torch_test.html

This is an issue upstream, here: https://github.com/pytorch/pytorch/blob/master/torch/profiler/init.py
That module doesn't explicitly reexport these values (even though the library is py.typed). More of the same and needs to be fixed upstream eventually.


MusicBot Error I want to know how to fix

Please tick all applicable boxes.

[/ ] I am using Python 3.5.3 or higher (run python --version on the command line)
[ /] I have followed the official guides to install the bot for my system
[ /] I have updated my dependencies to the latest version using the appropriate update script

Which version are you using?

[ /] The latest master version (release-260819)
[ ] The latest review version

What type of issue are you creating?

[ ] Bug
[ ] Feature request
[ /] Question

Description of issue
Steps to reproduce

Log file
Please attach your MusicBot log file (located at logs/musicbot.log) to this issue. You can do so by dragging and dropping the file here. If you do not include your log file, you WILL b
musicbot.log
e asked to provide one.
Before, I was able to use bots without problems. But today, there is a problem as listed below.
[INFO] launcher: Starting sanity checks
[INFO] launcher: Checking for Python 3.5+
[INFO] launcher: Checking console encoding
[INFO] launcher: Setting console encoding to UTF-8
[INFO] launcher: Ensuring we're in the right environment
[INFO] launcher: Adding local bins/ folder to path
[INFO] launcher: Required checks passed.
[INFO] launcher: Optional checks passed.
[INFO] launcher: Moving old musicbot log
Starting MusicBot release-260819-5-gc87dc05
Loaded autoplaylist with 67 entries
[ERROR] launcher: Error starting bot
Traceback (most recent call last):
File "run.py", line 373, in main
m.run()
File "C:\Users\AzIToB\Desktop\MusicBot\musicbot\bot.py", line 902, in run
self.loop.run_until_complete(self.start(*self.config.auth))
File "C:\Users\AzIToB\AppData\Local\Programs\Python\Python37-32\lib\asyncio\base_events.py", line 568, in run_until_complete
return future.result()
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\client.py", line 543, in start
await self.connect(reconnect=reconnect)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\client.py", line 457, in connect
await self._connect()
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\client.py", line 421, in _connect
await self.ws.poll_event()
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\gateway.py", line 469, in poll_event
await self.received_message(msg)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\gateway.py", line 423, in received_message
func(data)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\state.py", line 663, in parse_guild_create
guild = self._get_create_guild(data)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\state.py", line 638, in _get_create_guild
guild._from_data(data)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\guild.py", line 391, in _from_data
self._sync(guild)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\guild.py", line 420, in _sync
self._add_channel(VoiceChannel(guild=self, data=c, state=self._state))
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\channel.py", line 504, in init
self._update(guild, data)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\channel.py", line 535, in _update
self._fill_overwrites(data)
File "C:\Users\AzIToB\AppData\Roaming\Python\Python37\site-packages\discord\abc.py", line 271, in _fill_overwrites
self._overwrites.append(_Overwrites(id=overridden_id, **overridden))
TypeError: new() got an unexpected keyword argument 'deny_new'
[INFO] launcher: All done.
C:\Users\AzIToB\Desktop\MusicBot>
//Thank you for all your help.//

#2107

#2110

Fixed in review

Fixed in review


Kindly request the inclusion

Thank you for this great repo! I would be delighted if our work could also be included.

Title: GuardBench: A Large-Scale Benchmark for Guardrail Models
Venue: EMNLP 2024
Paper: https://aclanthology.org/2024.emnlp-main.1022.pdf
Code: https://github.com/AmenRa/guardbench
Classification: toolkit
Model: guardrail models
Tags: guardrail models, safety, benchmark, evaluation

Hi!
Congrats on your excellent work!
We have included this paper into toolkit of our list, please check it!
Best,
LM-SSP Team

Great, thanks! :)


Disable plugin during SSR

I have a problem with the plugin during SSR.
The plugin injects code with a window inside and this doesn't work in the node. The error is:
ReferenceError: window is not defined
    at cov_16v5xmsk37 (/src/entry-server.js:3:184)
    at eval (/src/entry-server.js:4:75)
    at instantiateModule (file:///Users/ed/Projects/github/vite/packages/vite/dist/node/chunks/dep-161621a1.js:55599:15)

I can't simply turn it off, because I need this plugin to work during middleware transformation(app.use(vite.middlewares)). So the issue only with modules handled during vite.ssrLoadModule(...).
Vite passes ssr flag inside plugin transform function. It feels that it makes sense to skip all transformations during ssr.
To reproduce the issue:
1.git clone git@github.com:vitejs/vite.git - Clone vite repo
2.cd vite + pnpm i + pnpm run build - Install deps
3.cd playground/ssr-vue + pnpm i vite-plugin-istanbul - Go to the playground and install the plugin
4. Add plugin to vite.config.js

5. pnpm run dev - start server and open the browser
Maybe I'm wrong and this issue can be handled in a different way. Thank you!

Hello @edikdeisling, thanks for the issue!
Absolutely i've not used the plugin on an SSR project before so this is something I've completely overlooked.
I'll look into adding the ssr check within the transform and send out a fix for it when it's ready.

hey any update on this? Or is there any workaround in the meantime? I'm using a Nuxt3 project and getting the same error for the window object.

@rathorevaibhav you can wrap the plugin that way and use the wrapper. It works for me
import { Plugin } from 'vite';
import istanbulPlugin from 'vite-plugin-istanbul';

// TODO: remove this wrapper after issue would be done
// https://github.com/iFaxity/vite-plugin-istanbul/issues/50
export function istanbul(): Plugin {
  const plugin = istanbulPlugin({
    ...
  });

  return {
    ...plugin,
    transform(code, id, options) {
      if (options?.ssr) {
        return;
      }

      // @ts-ignore
      return plugin.transform.call(this, code, id, options);
    },
  };
}

hey @edikdeisling @iFaxity
My understanding of options.ssr is that it's a global property, meaning it will return true if I've enabled SSR in my application. If that's the case, I don't think it will transform any files right, because options.ssr will be true for all. Doesn't that contradict the very purpose of this plugin to instrument the code?
Or maybe my understanding of options.ssr is incomplete. Let me know!
The Nuxt3 app where I'm trying to implement this plugin compiles all the files into two versions, one for the client side and one for the SSR server side. I only want the server copies to NOT have instrumented code. The client copies should have the coverage function defined.

@rathorevaibhav I think that it will work as you want. When you serve SSR application through Vite you have client-side components and server-side components(which loading through vite.ssrLoadModule). So SSR=true will be only for server-side components.
The same story for a build. You build server-side and client-side applications independently. So ssr=true will be for server-part only

@rathorevaibhav It is as @edikdeisling, i think you are mixing ssr from config and the options that are passed to the transform.
In a Vite plugin the transform has 3 parameters, link to typings.
The last parameter here are options passed to the transform. This gets set to { ssr: true } if Vite is bundling a file that is executed by the server. So as long as the option that is passed into the transform is checked and not the one defined in Vite config it should be good.

@iFaxity yeah, I meant exactly that) We'll have ssr in the transform hook only for server-proceed files

@edikdeisling thanks. Though I'm getting options.ssr value as both true & false for different files, it does seems like something related to Nuxt. I'll try checking in the Nuxt3 community.


Neo.ClientError.Procedure.ProcedureNotFound

I have successfully kept neo4j-versioner jar file in my plugins folder and try to run the following query.
CALL graph.versioner.init('Element', {name:"Neo4j"}, {status:'Initialized'}, 'Ready')
YIELD node
RETURN node

When I am running it I got this error
There is no procedure with the name graph.versioner.init registered for this database instance. Please ensure you've spelled the procedure name correctly and that the procedure is properly deployed.
I am using neo4j instance with version 3.5.24 in AWS platform.
Please help me to resolve this issue.
Thanks in advance!

Hi @Rajeswara-Rao , have you tried reproducing this issue on a local Neo4j db?

Hi @Rajeswara-Rao , I guess there's an issue when you "deploy" our versioner into your remote Neo4j on AWS.
That error shows that the init procedure is not registered, so somehow that instance can't "see" that you've deployed our library.

Hello @mfalcier  , While creating Neo4j instance I had mapped to wrong plugins folder which created this issue. Now it is working fine.
Thanks for your support!!


Improve code quality

Use 2 spaces for indents everywhere.
Use MaybeT if applicable.

@teggotic is there a way to have a formatter and CI check for this?

@extsoft This is a good question. stylish-haskell is not that strict, but has some good defaults for my tastes.
I'd check if there are any formatters that I like.


fix: getDeviceId was not working. Added an example on how to use it a…

fix: getDeviceId was not working. Added an example on how to use it additionally

Be aware that this is a breaking change, you change a callback to a promise so this must be informed in the documention.
Other than that this is approved by me.

LGTM


rocketMq will support master/slave switch when master is broke down in fuature version

in current version，a broker cluster include 3 master-slave brokers，when use order message，one broker down will cause message send to other broker，so during the switch order message will not keep order。
so i just ask will feature version support master/slave switch automatic

we will create another solution for HA. BTW, please ask the question as our template instruction.


Changed the way widgets are initialized.

This fixes initialization in inlines and also fixes multiple sets of
static files inserted with every HTMLField instance
This also changes the way initialization of the widget works in a major way though
Fixes https://github.com/divio/djangocms-text-ckeditor/issues/465

Coverage increased (+0.2%) to 78.207% when pulling f0ad8de5e5c266a1623c471dc1898c2248ff3580 on vxsx:bugfix/inlines into 67f550dc4eaad2f562a1da6559ead09fb6e5b0d8 on divio:master.

Coverage increased (+0.2%) to 78.207% when pulling f0ad8de5e5c266a1623c471dc1898c2248ff3580 on vxsx:bugfix/inlines into 67f550dc4eaad2f562a1da6559ead09fb6e5b0d8 on divio:master.

Coverage increased (+0.2%) to 78.207% when pulling f0ad8de5e5c266a1623c471dc1898c2248ff3580 on vxsx:bugfix/inlines into 67f550dc4eaad2f562a1da6559ead09fb6e5b0d8 on divio:master.

Coverage increased (+0.2%) to 78.207% when pulling f0ad8de5e5c266a1623c471dc1898c2248ff3580 on vxsx:bugfix/inlines into 67f550dc4eaad2f562a1da6559ead09fb6e5b0d8 on divio:master.

@czpython added. I will also add some integration tests, but in a separate PR


[TASK] Integrate back-end on Participants Table on Service Details page

Description
Fetch participants' address, idenity, socials likes. This can be done by both GraphQL and storage but GraphQL most likely will be better options here. Using storage will cause a huge amount of redundant data being fetched

The validators and their identities might already be cached. If they aren't, I would still suggest using a batch Polkadot API query.


[CORE] Simplify TransformSupport

What changes were proposed in this pull request?

Removes unused methods getBuildPlans and getStreamedLeafPlan
Add new triat LeafTransformSupport and UnaryTransformSupport to simplify columnarInputRDDs
Pull out doExecute and supportsColumnar to TransformSupport
remove COLUMNAR_ITERATOR_ENABLED config

How was this patch tested?
Pass CI

Run Gluten Clickhouse CI

Run Gluten Clickhouse CI

/Benchmark Velox

CC @JkSelf

===== Performance report for TPCH SF2000 with Velox backend, for reference only ====

query
log/native_3426_time.csv
log/native_master_10_18_2023_4dbb181cc_time.csv
difference
percentage

q1
40.82
43.58
2.764
106.77%

q2
24.70
24.34
-0.358
98.55%

q3
40.85
35.79
-5.060
87.61%

q4
33.90
41.52
7.622
122.49%

q5
69.91
70.78
0.876
101.25%

q6
8.68
5.74
-2.946
66.07%

q7
102.76
86.23
-16.533
83.91%

q8
101.52
80.16
-21.358
78.96%

q9
161.65
117.35
-44.300
72.59%

q10
76.15
47.73
-28.428
62.67%

q11
23.98
20.15
-3.836
84.01%

q12
39.86
25.94
-13.923
65.07%

q13
70.79
49.65
-21.133
70.15%

q14
23.43
15.32
-8.111
65.38%

q15
46.30
27.13
-19.169
58.60%

q16
24.69
16.07
-8.621
65.08%

q17
107.19
122.53
15.334
114.31%

q18
217.15
163.25
-53.904
75.18%

q19
25.83
13.15
-12.680
50.91%

q20
40.40
25.17
-15.231
62.30%

q21
335.14
235.27
-99.877
70.20%

q22
16.48
15.49
-0.984
94.03%

total
1632.17
1282.32
-349.858
78.56%


puzzle on training speed

I train the model on a Tesla M40 GPU. However, I could only train 40 steps within 1 minute. I admit that Titan Xp is faster than M40, so is multi-GPU training feasible?

Yes. I think multi-gpu is possible. We use only common modules, which should be easy to put on multi-gpu.
But the current codes need to be modified to use multi-gpu.

How to modify the code to meet multi-gpu training


[Suggestion] Coordinate selector.

If coordinate selector is installed in the rocket, u can select coordinates for next landing on the planet. And randomize button. This button select random coordinates.

Something like that already exists

Yes, this niche is filled by the


Adding Form_Wave_Animation Project

Related Issue
Closes: #592
Describe the changes you've made
I Have created an Awesome JavaScript Project : Form_Wave_Animation which will be useful to create Login and Signup forms.
Checklist:

[x] Added gif in assets/GIFs/Form_Wave_Animation.gif
[x] I have performed a self-review of my own code.
[x] Added JSON in script.js
[x] Opened an issue for this PR

Screenshots

Hey ! I have Recently made a new project and would like to add it to yours as well . Please assign it to me under GSSOC '21 and add the label of GSSOC '21 and level label as well. And Please Merge also 😄. Thank you.

Hey any updates??


Addon metadata isn't merged by the build

I tried adding metadata for a new function in source/codegen/metadata/nidcpower/functions_addon.py but nothing changed in the generated folder.
I finally tried adding it directly into the source/codegen/metadata/nidcpower/functions.py and the function was added to the generated files.
This seems like a clear sign that the addon metadata isn't being merged by the build.
AB#2456232

Closing out. If other products need the merge functionality then the code for those products can be updated during that time.


Explicit "Token expired" error message

Hey friends,
thank you for your recent changes on hapi-now-auth and passing through error messages.
Is there a chance the explicitly know if a token is expired?
I’d like to tell users that they have to renew the token. The current error message is this: Invalid JWT: key or signature is invalid.
The current error message is correct. I’m just looking for a detailed error message besides the general "is invalid" for expired tokens.
Do you think there’s a chance to add that?

@marcuspoehls this shouldn't be an issue at all. Give me a little bit of time and I'll return token expiration


modified starting page as per wireframes

Description
This PR is change the existing root page to the one in wireframes
Fixes # (issue)
How to test?
Tested in chrome browser of local machines
Checklist

[x] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[ ] This PR is ready to be merged and not breaking any other functionality

Hello @AnilMula  could you please add the issue number or link to the issue, because it help someone who going to review this PR to know more about the issue you resolved.

Hi @claudion3 there is no issue for that.

This PR is not necessary - will close it and delete it.