ivy repository URL String parsing broken with 8.3

Current Behavior
Before gradle 8.3 we could pass our ivy repository url definition like this:
repositories {
    // Cloud builds bundle some beats
    ivy {
      name = 'beats'
      url "file://${buildDir}/artifacts/"
      patternLayout {
          artifact '/[organisation]/[module]-[revision]-[classifier].[ext]'
      }
    }
}

this is broken with Gradle 8.3 as we have a '+' in our CI project path (eg.: /usr/jenkins/elasticsearch+7.10/) as the plus sign gets interpreted as space. That should not be the case in file urls I think.
Expected Behavior
The plus sign in a file url is not interpreted as a special character or as an escape of a space sign.
Context (optional)
Digging into the gradle sources I found a simple workaround by just passing a File object directly but I still think in general the change in behaviour was not intended and is wrong.
Steps to Reproduce
with a simple given build script:
repositories {
    // Cloud builds bundle some beats
    ivy {
      name = 'beats'
      url "/dev/jenkins/project+branch"
      println "repo url: $url"
      patternLayout {
          artifact '/[organisation]/[module]-[revision]-[classifier].[ext]'
      }
    }
}

if you run that with ./gradlew help will print "repo url: /dev/jenkins/project branch"
Gradle version
8.3
Gradle version that used to work
8.2
Build scan URL (optional)
No response
Your Environment (optional)
this issue is environment independant

Thank you for providing a valid report.
The issue is in the backlog of the relevant team, but the existence of a workaround makes it non-critical, so it might take a while before a fix is made.

I found a simple workaround by just passing a File object directly

Can you please detail the workaround. Thanks in advance!


How to write conditional rule in K

I'm trying to implement the condition statements of COBOL into K.
I've already implemented with success the logic of the IF [condition] THEN .. ELSE .. END-IF
Now i'm trying to implement the negated condition for this statement but i cannot figure how to do it..
 _ : E:Exp => E
but i'm not able to figure how to use with my case
Can someone give me a hint that allow me to write that rule?
I've searched in all tutorials and on the official site, but nothing.

hi @manueldallavalle, sorry for the late reply. did you figure out a solution?

@cos Yes, found a solution myself. Thanks anyway


Prettify stdlib param names

Standard library methods have ugly param + template-param names (typically __foo instead of foo, or _Foo instead of Foo) to guard against macros and such.
Can we prettify these in code completion, signature help, the index, hover, etc? Not sure if there's more to do than strip leading _s.

Param names show up in the middle of things things like printed return types too (e.g. returns decltype(__a+__b)). Maybe adding a flag on PrintingPolicy to strip underscores is OK.
(But it's probably not the end of the world to just fail to strip some cases inconsistently)


s3-ocr inspect-job job_id command

I found myself wanting to check the status of a specific job based on its job ID.

Documentation: https://github.com/simonw/s3-ocr/blob/2b415143c57cb880300123a41ea75598c50eadfa/README.md#inspecting-a-job


phoenix; RenderTexture; non-existent renderbuffer on iOS

The /tests/rendering/rendertexture project reproduces this issue. Here's the error and GL calls from Xcode:
Attempted present of non-existent renderbuffer (Issue) Renderbuffer #0 can not be presented as it is a non-existent renderbuffer

#0 glClearColor(0.1019608, 0.1019608, 0.1019608, 1.0000000)
#1 glClear(GL_COLOR_BUFFER_BIT)
#2 glViewport(0, 0, 1536, 2048)
#3 glBindTexture(GL_TEXTURE_2D, 3)
#4 projectionMatrix <- glGetUniformLocation(6, "projectionMatrix")
#5 modelViewMatrix <- glGetUniformLocation(6, "modelViewMatrix")
#6 glUseProgram(6)
#7 glUniformMatrix4fv(modelViewMatrix, 1, 0, {1.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.0000000})
#8 glUniformMatrix4fv(projectionMatrix, 1, 0, {0.0013021, 0.0000000, 0.0000000, 0.0000000, 0.0000000, -0.0009766, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0010000, 0.0000000, -1.0000000, 1.0000000, 0.0000000, 1.0000000})
#9 glGenBuffers(1, {7})
#10 glGenBuffers(1, {8})
#11 glGenBuffers(1, {9})
#12 glBindBuffer(GL_ARRAY_BUFFER, 7)
#13 glVertexAttribPointer(0, 4, GL_FLOAT, 0, 0, NULL)
#14 glBufferData(GL_ARRAY_BUFFER, 96, <data>, GL_STREAM_DRAW)
#15 glBindBuffer(GL_ARRAY_BUFFER, 9)
#16 glVertexAttribPointer(1, 4, GL_FLOAT, 0, 0, NULL)
#17 glBufferData(GL_ARRAY_BUFFER, 96, <data>, GL_STREAM_DRAW)
#18 glBindBuffer(GL_ARRAY_BUFFER, 8)
#19 glVertexAttribPointer(2, 4, GL_FLOAT, 0, 0, NULL)
#20 glBufferData(GL_ARRAY_BUFFER, 96, <data>, GL_STREAM_DRAW)
#21 glDrawArrays(GL_TRIANGLES, 0, 6)
#22 glDeleteBuffers(1, {7})
#23 glDeleteBuffers(1, {8})
#24 glDeleteBuffers(1, {9})
#25 glBindTexture(GL_TEXTURE_2D, 0)
#26 glUseProgram(0)
#27 glBindFramebuffer(GL_FRAMEBUFFER, 2)
#28 glClearColor(1.0000000, 0.2941177, 0.0117647, 1.0000000)
#29 glClear(GL_COLOR_BUFFER_BIT)
#30 glViewport(0, 0, 512, 512)
#31 glBindTexture(GL_TEXTURE_2D, 2)
#32 projectionMatrix <- glGetUniformLocation(6, "projectionMatrix")
#33 modelViewMatrix <- glGetUniformLocation(6, "modelViewMatrix")
#34 glUseProgram(6)
#35 glUniformMatrix4fv(modelViewMatrix, 1, 0, {1.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.0000000})
#36 glUniformMatrix4fv(projectionMatrix, 1, 0, {0.0039062, 0.0000000, 0.0000000, 0.0000000, 0.0000000, -0.0039062, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0010000, 0.0000000, -1.0000000, 1.0000000, 0.0000000, 1.0000000})
#37 glGenBuffers(1, {7})
#38 glGenBuffers(1, {8})
#39 glGenBuffers(1, {9})
#40 glBindBuffer(GL_ARRAY_BUFFER, 7)
#41 glVertexAttribPointer(0, 4, GL_FLOAT, 0, 0, NULL)
#42 glBufferData(GL_ARRAY_BUFFER, 96, <data>, GL_STREAM_DRAW)
#43 glBindBuffer(GL_ARRAY_BUFFER, 9)
#44 glVertexAttribPointer(1, 4, GL_FLOAT, 0, 0, NULL)
#45 glBufferData(GL_ARRAY_BUFFER, 96, <data>, GL_STREAM_DRAW)
#46 glBindBuffer(GL_ARRAY_BUFFER, 8)
#47 glVertexAttribPointer(2, 4, GL_FLOAT, 0, 0, NULL)
#48 glBufferData(GL_ARRAY_BUFFER, 96, <data>, GL_STREAM_DRAW)
#49 glDrawArrays(GL_TRIANGLES, 0, 6)
#50 glDeleteBuffers(1, {7})
#51 glDeleteBuffers(1, {8})
#52 glDeleteBuffers(1, {9})
#53 glBindTexture(GL_TEXTURE_2D, 0)
#54 glUseProgram(0)
#55 glBindFramebuffer(GL_FRAMEBUFFER, 0)
#56 ["Context 1" presentRenderbuffer:GL_RENDERBUFFER]

could you specify which device (or simulator?), OS version etc as to narrow it down?  Thanks!

The above calls are from an iPad mini 2 running 9.3.1. I think I see the same issue (black screen) on the simulator (iPhone 6, iPad 2), but as far as I know it is not possible to launch the GPU debugger on the simulator to confirm. I believe @nslottow has seen the same issue on his iPhone 6 presumably running 9.0+. for what it's worth, those same devices are able to run the same project via the web target.

Thanks, I'll have a look later. I don't think much if anything changed there, so it seems to be rather odd. (I've been working on the new renderer, phoenix is going away soon enough, but I'll be sure to test both anyway)

iOS never had framebuffer 0. Every app is rendered into its own framebuffer, which is configured with system API, instead of being preallocated by system. This is one of the differences from standard OpenGL. When using third-party libs to create GL context (SDL, GLFW or other) you don't have handle to that frameuffer, as it stays inside the lib. Usually there is a library function, that binds the screen framebuffer, but i can't find one for SDL. You can get handle of screen framebuffer by using glGetInteger after you create and bind SDL context, like SDL itself does for some reason.

Yes this is not the issue, this has worked all along. This is anomalous.

@kneeko thanks for the report, it's been fixed. Update linc_opengl (using snowfall or directly) should solve it.


Single numpy array

I would doublecheck this. I see outputs for everything, but a lot did change with the shape and output of flowveldepth. I was also curious about whether or not I should try to reshape the flowveldepth_data into the same kind of NumPy array for this?

It looks like you need to do the same thing for the csv write as you did for the netcdf write:
flowveldepth[current_segment][:, time_index]

That was the magic we needed. I just pushed the change.
On Tue, Sep 1, 2020 at 11:55 AM jameshalgren<EMAIL_ADDRESS>wrote:

It looks like you need to do the same thing for the csv write as you did
for the netcdf write:
flowveldepth[current_segment][:, time_index]
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aya:35b-23-f16 erro

What is the issue?
ollama run aya:35b-23-f16
Error: llama runner process has terminated: signal: aborted (core dumped) error:failed to create context with model '/home/ais/.ollama/models/blobs/sha256-6f800f35270cacdcbdd43e2b96991c7974907b859ab0efa0a91b1523724b7e43'
OS
Linux
GPU
Nvidia
CPU
Intel
Ollama version
0.1.38 and 0.1.41

Hi @lymanzhao that's a really big model to run at f16 precision (70GB+ of VRAM required) - do you know if you have that much memory between your GPU and system memory? Sorry about the error. I'll merge this with https://github.com/ollama/ollama/issues/4955


Variable substitution in tasks file

Would be good to, within a tasks file, be able to support variable substitution.
Variables would always we resolved in the context of the Account/Region a task is being executed (this can be multiple targets, which means in the context of any target the variables will resolve to different values.
Syntax support:

!Ref logicalName
!GetAtt logicalName.attr
!Sub 'my-${reference.attr}
`!Sub

'my-${var}
{ var: reference.attr }`

Attribute support (task file attributes where variables can be substituted):
update-cdk

CustomDeployCommand
CustomRemoveCommand
Parameters

update-serverless.com

CustomDeployCommand
CustomRemoveCommand
Parameters

copy-to-s3

RemotePath
LocalPath

update-stacks

Parameters
StackDescription

Variable support (substitutions that can be made):

all Organization resources e.g. !Ref Account, !GetAtt Account.Id, !GetAtt Account.Alias  described here
${TASK::Parameters} for update-cdk and update-sls, to be used in CustomXxxxCommand
${AWS::AccountId}, ${AWS::Region} while we are at it.

released as part of v0.9.5


Added the shell meteor command

Pretty straight forward actually. This is useful when you use meteorite for a custom meteor fork.

Published as 0.9.3 Good stuff @gsuess


Minor spelling error corrections

Minor changes to correct spelling errors and remove unwanted spaces.

@shreyasbapat

@DumbMachine It takes efforts to find out these typos! Thanks!
Rebase(and if possible squash), then it's a go!

@shreyasbapat LGTM :) squash n merge this.

Aah! We don't follow commits regulation until too necessary. I am rebasing this.


Xiaomi accessories to hue Bridge?

So are you saying all these xiaomi sensors can be paired with the Hue Bridge then? Without the Xiaomi gateway? How did you find that out and how to pull it off?

I believe they require the Deconz Zigbee hub. This is kind of a Hue/Deconz plug-in, not just Hue.

Ah, good to know, thanks for the info.


MOE not being detected.

I am having trouble getting osprey to detect moe even though it was working before. I already did the conda install moe and ipython seems to pick it up just fine. Any ideas how to go about debugging this? Already tried rebuilding osprey and reinstalling moe.
$ ipython
Python 2.7.9 |Continuum Analytics, Inc.| (default, Dec 15 2014, 10:33:51)
Type "copyright", "credits" or "license" for more information.

IPython 2.0.0 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]: import moe

In [2]: moe.__version__
Out[2]: '0.2.1'

In [3]:

It's hard to say. Are you sure you're using the same python interpreter in both cases?

I think so. I can show this to you offline tomorrow.
msultan@icme-gpu1 ~/research/kinase/fyn_kinase/2014-6_to_12/fah_water_traj/osprey_models
$ which python
alias python='/home/msultan/software/miniconda/bin/python2.7'
	~/software/miniconda/bin/python2.7

msultan@icme-gpu1 ~/research/kinase/fyn_kinase/2014-6_to_12/fah_water_traj/osprey_models
$ python
Python 2.7.9 |Continuum Analytics, Inc.| (default, Dec 15 2014, 10:33:51)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
Anaconda is brought to you by Continuum Analytics.
Please check out: http://continuum.io/thanks and https://binstar.org
>>> import moe
>>> moe.__version__
'0.2.1'
>>> import osprey
>>> osprey.__version__
'0.4-13-g0c4b067'
>>>

The import is here.
Try running this line in your ipython notebook: from moe.views.rest.gp_next_points_epi import GpNextPointsEpi

It cant find the boost libraries perhaps because the clusters are at currently at version /usr/lib64/libboost_python.so.5 instead of libboost_python.so.1.55.0 or it could be that I have some environment variable incorrectly setup.

In [5]: from moe.views.rest.gp_next_points_epi import GpNextPointsEpi
---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-5-ac59ed7470cd> in <module>()
----> 1 from moe.views.rest.gp_next_points_epi import GpNextPointsEpi

/home/msultan/software/miniconda/lib/python2.7/site-packages/moe/views/rest/gp_next_points_epi.py in <module>()
     11 from moe.optimal_learning.python.constant import OPTIMIZER_TYPE_AND_OBJECTIVE_TO_DEFAULT_PARAMETERS, EI_COMPUTE_TYPE_ANALYTIC, EI_COMPUTE_TYPE_MONTE_CARLO, ENDPOINT_TO_DEFAULT_OPTIMIZER_TYPE, SINGLE_POINT_EI, MULTI_POINT_EI, GRADIENT_DESCENT_OPTIMIZER, L_BFGS_B_OPTIMIZER
     12 from moe.views.constant import GP_NEXT_POINTS_EPI_ROUTE_NAME, GP_NEXT_POINTS_EPI_PRETTY_ROUTE_NAME, GP_NEXT_POINTS_EPI_OPTIMIZER_METHOD_NAME
---> 13 from moe.views.gp_next_points_pretty_view import GpNextPointsPrettyView
     14 from moe.views.pretty_view import PRETTY_RENDERER
     15

/home/msultan/software/miniconda/lib/python2.7/site-packages/moe/views/gp_next_points_pretty_view.py in <module>()
      9 import numpy
     10
---> 11 import moe.optimal_learning.python.cpp_wrappers.expected_improvement
     12 from moe.optimal_learning.python.cpp_wrappers.expected_improvement import ExpectedImprovement
     13 from moe.optimal_learning.python.python_version.expected_improvement import ExpectedImprovement as PythonExpectedImprovement

/home/msultan/software/miniconda/lib/python2.7/site-packages/moe/optimal_learning/python/cpp_wrappers/expected_improvement.py in <module>()
     13 import numpy
     14
---> 15 import moe.build.GPP as C_GP
     16 from moe.optimal_learning.python.constant import DEFAULT_EXPECTED_IMPROVEMENT_MC_ITERATIONS, DEFAULT_MAX_NUM_THREADS
     17 import moe.optimal_learning.python.cpp_wrappers.cpp_utils as cpp_utils

ImportError: libboost_python.so.1.55.0: cannot open shared object file: No such file or directory

moe is generally very tricky to install. you can try following their docs at http://yelp.github.io/MOE/.

Scott Clark is currently maintaining this version for sigopt: https://github.com/sigopt/moe


Request for backoff templates

Hi,
Currently the retry policy supports linear retry policy only, unless I decide on the backoff delay myself in the onRejection hook.
While this works, it's inconvenient and requires me to implement myself the various backoff policies.
Since this library is inspired by Polly, I'd be happy if you add this as well :)

Thanks for sharing this issue @johnib
backoff policies looks like a nice piece to be added to the retry module.

Hi @johnib ,
They are several backoff behaviors that could be implemented using the onRejection hook.
Here is a code snippet of some:
new Retry({
  attempts: 4,
  interval: 100,
  // Constant - default [100, 100, 100, 100]
  onRejection (err, attempt) { return this.interval; },
  // Constant - first fast [0, 100, 100, 100]
  onRejection (err, attempt) { return (attempt === 0) ? 0 : this.interval; },
  // Linear [100, 200, 300, 400]
  onRejection (err, attempt) { return this.interval + (attempt * this.interval) },
  // Exponential [100, 200, 400, 800]
  onRejection (err, attempt) { return this.interval * Math.pow(2, attempt); }
})

Could you explain a bit what are your use-cases, and what would be your preferred API?

Hey,
I know it's possible, but look at what Polly does with their templates, you don't have to implement the retry logic, you just have simple notches to tweak the implementation to your flavor.
Would you really want to implement the complex retry policy that Polly offers? Decorrelated V2


Ensure required properties of components are enforced

Some components do not enforce their required properties. This should not be the case

All the components reviewed are enforcing their required properties, possibly fixed when fixing the other issues.

All the components reviewed are enforcing their required properties, possibly fixed when fixing the other issues.


Add None as a possible colormap. This wont draw the ticks, min, max o…

…r gradient but only the the gradient boundary (in order for the user to know the colormap is here.). This is used especially for RGB(A) image. This /close #989

LGTM


What is the proper way to handle PATCH?

What is the recommended way to handle PATCH request for entities with several attributes and relationships? What should DTOs look like?
I saw example https://github.com/toedter/spring-hateoas-jsonapi/blob/master/lib/src/test/java/com/toedter/spring/hateoas/jsonapi/support/WebMvcMovieController.java .
We have to differentiate usecases:

setting attribute/relationship to another value
setting them to null
property isn't sent - don't want to change property

Our solution:
We've introduced for our use case OptionalProperty<T> interface which is "wrapper" around entity property. Its implementation NoneProperty represents property which isn't sent in PATCH and SomeProperty<T> (property was sent).
class Person {
  //attributes
  private String name;
  private Integer age;

  // relationships
  private City city;
  private List<Job> jobs;
}

class PatchPerson {
  //attributes
  private OptionalProperty<String> name;
  private OptionalProperty<Integer> age;

  // relationships
  private OptionalProperty<City> city;
  private OptionalProperty<List<Job>> jobs;
}

We have our OptionalPropertyDeserializer registered to object mapper. It works fine for attributes but we have problem with relationships because our OptionalProperty is generic non-collection so it's skipped in JsonApiEntityModelDeserialize::convertToRepresentationModel (https://github.com/toedter/spring-hateoas-jsonapi/blob/master/lib/src/main/java/com/toedter/spring/hateoas/jsonapi/JsonApiEntityModelDeserializer.java#L84).
If OptionalProperty works for you I can help with implementation to library (also with any other solution).
Thank you!
Adam

Thanks for asking, I will think about it.

sorry for not reacting in time, I am a little busy right now. I did not forget it and will try to respond before Christmas.

OK, thank you!

Hi Adam,
to get the information for the relationships, you can use the @JsonApiRelationships annotation, like
@Data
@Entity
@NoArgsConstructor
class Person {
  @Id
  @GeneratedValue
  @JsonIgnore
  private Long id;

  //attributes
  private String name;
  private Integer age;

  // relationships
  @OneToOne
  @JsonApiRelationships("city")
  @JsonIgnore
  private City city;

  @OneToMany
  @JsonApiRelationships("jobs")
  @JsonIgnore
  private List<Job> jobs;

Then a person will be serialized to
{
    "data": {
        "type": "persons",
        "attributes": {
            "name": "Kai",
            "age": 56
        },
        "relationships": {
            "city": {
                "data": {
                    "id": "2",
                    "type": "cities"
                }
            },
            "jobs": {
                "data": [
                    {
                        "id": "1",
                        "type": "jobs"
                    }
                ]
            }
        }
    }
}

If you want to patch a person, send a PATCH request like
{
    "data": {
        "type": "persons",
        "attributes": {
            "name": "Kay",
            "age": 57
        },
        "relationships": {
            "city": {
                "data": {
                    "id": "4",
                    "type": "cities"
                }
            },
            "jobs": {
                "data": [
                    {
                        "id": "7",
                        "type": "jobs"
                    }
                ]
            }
        }
    }
}

If you want to distinguish between a value that should explicitly be set to null and a value that is not set at all in the patch body, one solution could be to use a special marker identifier like  <<<null>>> in your patch body. Then your controller could react on set and update the DTO's value to null.
I have created a little demo with your example, you can download it at https://my.hidrive.com/share/ylcmjtbywn
Password is patch-demo
Please re-open if you have further questions or contact me via email<EMAIL_ADDRESS>


Email settings

Surprisingly we have no email settings panel yet. We'll need this for subscribers etc.
@joecohens is this something you've added in the new notifications branch that you've been working on?

@joecohens closing this because it'll need to be done as part of #36 and the configuration menu, essentially this is a duplicate issue :smile:

:+1:


Fix broken link

https://docs.microsoft.com/en-us/microsoft-365/security/office-365-security/submit-spam-non-spam-and-phishing-scam-messages-to-microsoft-for-analysis is broken (404) please change to https://docs.microsoft.com/en-us/microsoft-365/security/office-365-security/report-junk-email-messages-to-microsoft
Also note the section on manually submitting phish/junk to individual email addresses is removed from the target article. Consider removing from this page as well, if the (non-email) Admin/User submission methods are preferred and supported.

@hudish  which Article are you referring to?

Apologies. https://docs.microsoft.com/en-us/windows/security/threat-protection/intelligence/phishing

@hudish , Thanks changed to new link.

Thank you @hudish for raising this issue, and thank you @RAJU2529 for the fix. The pull request is merged and the updates will be live a little later this morning (around 11 Pacific Time).


New version: Oracle.VirtualBox version 7.0.10

Pull request has been created with Komac v1.9.1 :rocket:
Microsoft Reviewers: codeflow:open?pullrequest=https://github.com/microsoft/winget-pkgs/pull/116846&drop=dogfoodAlpha

Duplicate of #115697

Duplicate of https://github.com/microsoft/winget-pkgs/pull/115697


Removing entries from the shuttingdownBrokerIds upon broker startup

Consider a cluster having two brokers (id=0 and id=1) configured with
<property name="kafka.controlledShutdownEnable" value="true">
<property name="kafka.controlledShutdownMaxRetries" value="2147483640">
<property name="kafka.controlledShutdownSafetyCheckEnable" value="true">
<property name="kafka.controlledShutdownSafetyCheckRedundancyFactor" value="0">

and a partition having two replicas on these two brokers.
If broker1 goes through the controlled shutdown process and starts up, the current implementation uses the following logic to update the shuttingdownBrokerIds:
shuttingDownBrokerIds = shuttingDownBrokerIds.filter(b =>
      liveBrokerEpochs.contains(b._1) && b._2 < liveBrokerEpochs(b._1))

which means broker1's previous shutting epoch is still retained in the shuttingDownBrokerIds after it restarts.
Later on, if broker0 needs to restart, the controller uses the leaderForControlledShutdown method to elect a new leader for partitions led by broker0:
def leaderForControlledShutdown(controllerContext: ControllerContext,
                                  leaderAndIsrs: Seq[(TopicPartition, LeaderAndIsr)]): Seq[ElectionResult] = {
    val shuttingDownBrokerIdSet = controllerContext.shuttingDownBrokerIds.keySet.toSet
    leaderAndIsrs.map { case (partition, leaderAndIsr) =>
      leaderForControlledShutdown(partition, leaderAndIsr, shuttingDownBrokerIdSet, controllerContext)
    }
  }

The leaderForControlledShutdown would still treat broker1 as a shutting down broker, and therefore won't be able to transfer the leadership to broker1, despite its readiness to serve as the leader.
This PR resolves the problem by changing the update logic of shuttingDownBrokerIds such that the entry of a restarted broker would be removed from it.
Committer Checklist (excluded from commit message)

[ ] Verify design and implementation
[ ] Verify test coverage and CI build status
[ ] Verify documentation (including upgrade notes)

The failed tests are being resolved at https://github.com/linkedin/kafka/pull/188


add deprecation warning for scvi and pin version

fixes #1443

Thanks for reviewing! Just pushed requested changes.


Android licences not accepted

C:\Users\user>flutter doctor
Doctor summary (to see all details, run flutter doctor -v):
[√] Flutter (Channel stable, v1.2.1, on Microsoft Windows [Version 10.0.17134.590], locale en-US)
[!] Android toolchain - develop for Android devices (Android SDK version 28.0.3)
X Android licenses not accepted.  To resolve this, run: flutter doctor --android-licenses
[!] Android Studio (version 3.3)
X Flutter plugin not installed; this adds Flutter specific functionality.
X Dart plugin not installed; this adds Dart specific functionality.
[!] Connected device
! No devices available
! Doctor found issues in 3 categories.

By running flutter doctor --android-licenses, you should be able to accept the licenses pressing "y" key.
For installing the Flutter and Dart plugins, go through this: https://flutter.dev/docs/get-started/editor?tab=androidstudio

@sagarsamantaa What could we have done to solve this problem more effectively for you? Did To resolve this, run: flutter doctor --android-licenses not solve the problem?


Finalizer & namespace deletion issue

Deleting the namespace without having deleted first the chi- resources will make the delete command hang indefinitely.
Tested on 0.18.4.

it will happens if clickhouse-operator install in the same namespace with chi
and you have situation when finalizer deleted before custom resource
use separate namespace for installation clickhouse-operator
if you install in kube-system, then operator will watch all namespaces for chi reconciling
in other case specify watchNamespaces in custom chopconf resource for customizing clickhouse-operator settings
look kubectl explain chopconf for details


Facilitate dynamic inventory and custom environments

Add elasticsearch_index role. This will be incorporated into the development playbooks at a later point.
Update some variables to default to False when they're not defined.
Parameterize some configuration file parameters.
Change common role to observe all_group_name for more flexibility with custom environments.
Update common role to work better in dynamic inventory situations.
Update postgresql role to use IP addresses instead of hostnames, for simplicity, and to avoid having to convert characters in dynamic-inventory hostnames.
Tidy up various minor things.

:+1:


Also trigger Dev rebuild on tag push

This commit sets the OBS workflow to also rebuild Dev environment when a tag is pushed to main branch. This is relevant to ensure the latest Dev build is also taking the correct package version.
Signed-off-by: David Cassany<EMAIL_ADDRESS>

Unfortunately due to #522 this can be verified (that's mostly the reason I did not commit it yet). Hopefully OBS will be fixed soon, the bug is on their planned column in their public project board 🤞🏽


request file got error: {"error":"volume id 20 not found: volume id 20 not found"}

版本： version 30GB 1.78 linux amd64
我线上有3台机器（同一网段）部署了master，因为做了负载均衡，请求同一个文件有时候正常，有时候报如题的错误。重启服务之后就正常了。猜测是master数据不一致导致

Please follow the issue template.

Sponsors SeaweedFS via Patreon https://www.patreon.com/seaweedfs
Report issues here. Ask questions here https://stackoverflow.com/questions/tagged/seaweedfs
Describe the bug
我线上有3台机器（同一网段）部署了master，因为做了负载均衡，请求同一个文件有时候正常，有时候报如题的错误。重启服务之后就正常了。猜测是master数据不一致导致
System Setup

List the command line to start
weed master -mdir=/root/weedfs/master/data -defaultReplication=010 -ip="<IP_ADDRESS>" -peers=<IP_ADDRESS>:9333,<IP_ADDRESS>:9333,<IP_ADDRESS>:9333 -volumePreallocate
weed volume -max=67 -port=8081 -dir=./data -mserver="<IP_ADDRESS>:9333,<IP_ADDRESS>:9333,<IP_ADDRESS>:9333" -rack=rack1 -idleTimeout=300
OS version
Debian GNU/Linux 10
output of weed version
version 30GB 1.78 linux amd64

Expected behavior
A clear and concise description of what you expected to happen.
Screenshots
If applicable, add screenshots to help explain your problem.
Additional context
Add any other context about the problem here.

Can you please show the error logs?

How did you request the file? And what was the logs at that time?

How did you request the file? And what was the logs at that time?

通过round robin的方式请求3个master,有的master就报了这个错，log应该是没有的吧，这个错误对seaweedfs来说应该是正常的。


[keycloak role] : aligned with a theme config change

This aligns the role to the recent change of theme's paths.
The theme paths were changed to adapt to the upcoming quarkus-based keycloak.

UPDATE:
I managed to alter the ansible in such a way that it does not write on any filesystem paths for the theme.
It just uses the theme's API to upload any configuration resources to the theme.
The theme itself knows where it stores its config files and ansible does not interfere with that at all.
I think it is a lot cleaner now and completely backwards compatible!
No need to bump our theme version to the latest in the inventory.
Tested it with versions [4.0.2, 4.1.0] on 16.1.0 and also with [4.0.2, 4.1.0] on 18.0.0


'test' command

Use this command inside an app dir to unit test.

For web platform, added.
Other platforms, test command will be added in the future.
Code needs improve but anyway, it's added and can be closed until next platform implements.


To add Cisco ASA inventory for network-ee jobs

To add Cisco ASA inventory for network-ee jobs

cc. @pabelanger

cc. @GomathiselviS


Allow duplicates not working if tag contains dot

tagSelected function is buggy. If there is a tag that contains dot (ie. email address) then you can add it multiple times.
Perhaps comparison should be:
(compareable.search(searchQuery) > -1
instead of
compareable == searchQuery
in tagSelected function

Thanks! This has been fixed in v.2.0.2.


Improve molecular inventory export

In the export_inventory() function:
res_names = " ".join(set(sorted(nx.get_node_attributes(graph, "residue_name").values())))

Get the full sequence of residues, not unique residues (with set())
In the final dictionary (final_dict variable), also add the checksum of the input file:
final_dict = {"inventory": list_dict_molecule,
              "resolution": resolution,
              "date": str(datetime.datetime.today()),
              "file_name": filename,
              "file_md5sum" : XXX
             }

Also, save the json file in the current directory (not in the directory of the input file) with the date and time in the name. For instance: grodecoder_2024-05-21_11-07-00.json

What do you mean by "checksum of the input file" ?


remove unnecessary new from samples

Analysis issues around constructor order are also showing up in head, and look related to a Dart roll, not this PR.

LGTM, but let's get the CI job working in head before we merge this

cc @cbracken is someone looking at the CI issue?

I'm fixing the CI issues.

As the build failures are now the same as in master (and as this PR only touch READMEs and docs) I'm tempted to merge this PR.
WDYT?

@cbracken can we land this?

Merging as CI is passing now

@a14n looks like the CI job failed after the merge; does this look related to your changes?
https://cirrus-ci.com/build/6241182061428736

I don't think it's related to my PR (only README and comments had been changed).


chore(deps): update dependency @nuxtjs/seo to v2.0.2

This PR contains the following updates:

Package
Type
Update
Change

@nuxtjs/seo (source)
devDependencies
patch
2.0.0-rc.10 -> 2.0.2

Release Notes

harlan-zw/nuxt-seo (@nuxtjs/seo)
v2.0.2
Compare Source
No significant changes
View changes on GitHub
v2.0.1
Compare Source
No significant changes
View changes on GitHub
v2.0.0
Compare Source
Nuxt SEO v2 Stable :tada:
This release has been almost two years in the making. Please read the Announcing Nuxt SEO Stable post to learn about the history of Nuxt SEO, what the stable means and what is planned for the module.
Ready to upgrade? Check out the migration guides:

Nuxt SEO RC to Stable
Nuxt SEO Beta to RC
Nuxt SEO Kit to Nuxt SEO Beta

Changelog
🚨 Breaking Changes

No longer render default og:image, requires defineOgImage()  -  by @harlan-zw (f50ec)
No longer render default og:image, requires defineOgImage()  -  by @harlan-zw (5eac2)
Drop nuxt-seo-ui module  -  by @harlan-zw (cc7c5)
Migrate to @nuxtjs/robots  -  by @harlan-zw (991bf)
Bump @nuxtjs/sitemap v6 beta  -  by @harlan-zw (a6204)
Migrate core features to nuxt-seo-utils  -  by @harlan-zw (dd466)

🚀 Features

Nuxt-seo-experiments  -  by @harlan-zw (2de57)
Add canonicalDomain config  -  by @harlan-zw (1a6ce)
Support identity site config  -  by @harlan-zw (5a90e)
Support twitter site config  -  by @harlan-zw (807f7)
Support currentLocale site config  -  by @harlan-zw (47b2f)
Nuxt Simple Sitemap v4  -  by @harlan-zw (578e5)
Implement fallbackTitle as separate plugin  -  by @harlan-zw (eb3bc)
useBreadcrumbItems()  -  by @harlan-zw (1b5d8)
Nuxt Sitemap v5  -  by @harlan-zw (b1e43)
canonicalQueryWhitelist  -  by @harlan-zw in https://github.com/harlan-zw/nuxt-seo/issues/282 (568c2)
Docs for v2 stable  -  by @harlan-zw in https://github.com/harlan-zw/nuxt-seo/issues/338 (5ed69)

🐞 Bug Fixes

Nav re-order  -  by @harlan-zw (5dae2)
Misc kit bugs  -  by @harlan-zw (a1e98)
Redirect to canonical domain in production by default  -  by @harlan-zw (ccbab)
Prefer useServerHead for static head data  -  by @harlan-zw (ba518)
Drop fallback title support  -  by @harlan-zw (185b8)
Only expose name and url from site config  -  by @harlan-zw (0585c)
Drop fallback title support"  -  by @harlan-zw (6d00c)
Use lower priority for nuxtseo defaults  -  by @harlan-zw (6fcf8)
Only set description if set  -  by @harlan-zw (164a2)
Tag priorities for nuxt.config overrides  -  by @harlan-zw (0f309)
Tag priorities for nuxt.config overrides  -  by @harlan-zw (1cda3)
Support %siteName param  -  by @harlan-zw (fb23e)
Give <html lang=""> higher priority than nuxt.config  -  by @harlan-zw (c306a)
Provide all site config as template params and render client-side  -  by @harlan-zw (9560a)
Update splash for beta  -  by @harlan-zw (8cd22)
Nuxt-og-image 2.1.0 beta  -  by @harlan-zw (a7edb)
Fallback to defaultLocale for lang attribute  -  by @harlan-zw (ce573)
Redirect canonical site url requires opt-in  -  by @harlan-zw (f0387)
Remove Schema.org defaults, moved to nuxt-schema-org  -  by @harlan-zw (38514)
Enable fallbackTitle by default  -  by @harlan-zw (9e0a0)
Module exports  -  by @harlan-zw (44830)
Safer version resolving  -  by @harlan-zw (66929)
Redirect logic  -  by @harlan-zw (75ddb)
Add og:type back in  -  by @harlan-zw (9dae0)
Apply trailingSlash config to NuxtLink component  -  by @harlan-zw (18793)
Don't apply default trailing slashes while upstream bug  -  by @harlan-zw (79d42)
2s timeout on update check, allow failure  -  by @harlan-zw (c34fe)
Avoid using nuxt/ui types for breadcrumb item  -  by @harlan-zw (534f5)
Explicitly import $fetch  -  by @harlan-zw (ca435)
Only run version check in dev on stable branch  -  by @harlan-zw (b0dcd)
Breadcrumb to optional  -  by @harlan-zw (48353)
Avoid running plugins in server components  -  by @harlan-zw (5c0c9)
Ensure defaults are applied after i18n site config  -  by @harlan-zw (31f0d)
Ensure breadcrumb schema.org paths are fully resolved  -  by @harlan-zw (09a4c)
Opt in to import.meta.* properties  -  by @danielroe in https://github.com/harlan-zw/nuxt-seo/issues/211 (0fad0)
Redirect using url config key  -  by @94726 in https://github.com/harlan-zw/nuxt-seo/issues/256 (2f195)
Disable splash by default  -  by @harlan-zw (840cf)
Avoid infinite redirects with redirectToCanonicalSiteUrl redirects  -  by @harlan-zw (bac31)
useBreadcrumbItems generating invalid schema.org  -  by @harlan-zw (e321b)
Missing nuxt app context when using useBreadcrumbItems  -  by @harlan-zw (2005a)
Reactive lang when using Nuxt I18n  -  by @harlan-zw (58e4f)
Wait for i18n plugin, handle fallback  -  by @harlan-zw (81163)
useBreadcrumbItems support static meta from dynamic routes  -  by @terion-name in https://github.com/harlan-zw/nuxt-seo/issues/323 (d3895)
Avoid og-image and sitemap version locks  -  by @harlan-zw (76b7e)
breadcrumbs:

Support computed overrides  -  by @thorge in https://github.com/harlan-zw/nuxt-seo/issues/331 (79e4d)

doc:

Broken config key for robot user agents  -  by @harlan-zw (b76b2)

useBreadcrumbItems:

Avoid infinite recursion  -  by @harlan-zw (f6fd1)
Enable schema.org by default  -  by @harlan-zw (6b0d7)
Allow overrides, append and prepend  -  by @harlan-zw (a1d8b)
Ensure i18n prefix is correct  -  by @harlan-zw (919a2)
Nuxt instance in computed  -  by @harlan-zw (c1696)
Avoid route path becoming label  -  by @harlan-zw (bc1dc)
Route meta regression  -  by @harlan-zw (f5a4d)

View changes on GitHub
v2.0.0-rc.23
Compare Source
🐞 Bug Fixes

Avoid og-image and sitemap version locks  -  by @harlan-zw (76b7e)

View changes on GitHub
v2.0.0-rc.22
Compare Source
🐞 Bug Fixes

useBreadcrumbItems:

Avoid route path becoming label  -  by @harlan-zw (bc1dc)
Route meta regression  -  by @harlan-zw (f5a4d)
Support static meta from dynamic routes  -  by @terion-name in https://github.com/harlan-zw/nuxt-seo/issues/323 (d3895)

View changes on GitHub
v2.0.0-rc.21
Compare Source
🐞 Bug Fixes

useBreadcrumbItems: Nuxt instance in computed  -  by @harlan-zw (c1696)

View changes on GitHub
v2.0.0-rc.20
Compare Source
🚨 Breaking Changes

Bump @nuxtjs/sitemap v6 stable  -  by @harlan-zw (a6204).

⚠  Please see https://github.com/nuxt-modules/sitemap/pull/320 if you have submitted multi-sitemap URLS in Google Search Console as the paths have changed.
:warning: Please verify your sitemap output.
View changes on GitHub
v2.0.0-rc.19
Compare Source
No significant changes
View changes on GitHub
v2.0.0-rc.18
Compare Source
🐞 Bug Fixes

Wait for i18n plugin, handle fallback  -  by @harlan-zw (81163)

View changes on GitHub
v2.0.0-rc.17
Compare Source
🚨 Breaking Changes

Bump @nuxtjs/sitemap v6 beta  -  by @harlan-zw (a6204).

⚠  Please see https://github.com/nuxt-modules/sitemap/pull/320 if you have submitted multi-sitemap URLS in Google Search Console as the paths have changed.
🚀 Features

canonicalQueryWhitelist  -  by @harlan-zw in https://github.com/harlan-zw/nuxt-seo/issues/282 (568c2)

🐞 Bug Fixes

Missing nuxt app context when using useBreadcrumbItems  -  by @harlan-zw (2005a)
Reactive lang when using Nuxt I18n  -  by @harlan-zw (58e4f)

View changes on GitHub
v2.0.0-rc.16
Compare Source
🐞 Bug Fixes

useBreadcrumbItems generating invalid schema.org  -  by @harlan-zw (e321b)

View changes on GitHub
v2.0.0-rc.15
Compare Source
Nuxt SEO v2 stable is approaching, see the v2 Stable Release Tasks issue to track.
This release fixes all submodules from having explicit dependencies for DevTools (such as shiki).
No significant changes
View changes on GitHub
v2.0.0-rc.14
Compare Source
Nuxt SEO v2 stable is approaching, see the v2 Stable Release Tasks issue to track.
This bumps all sub modules.
No significant changes
View changes on GitHub
v2.0.0-rc.13
Compare Source
🚨 Breaking Changes

nuxt-simple-robots has been migrated into @nuxtjs/robots. There should be no breaking changes but please test the update.

View changes on GitHub
v2.0.0-rc.12
Compare Source
🐞 Bug Fixes

Avoid infinite redirects with redirectToCanonicalSiteUrl redirects  -  by @harlan-zw (bac31)

View changes on GitHub
v2.0.0-rc.11
Compare Source
🐞 Bug Fixes

Opt in to import.meta.* properties  -  by @danielroe in https://github.com/harlan-zw/nuxt-seo/issues/211 (0fad0)
Redirect using url config key  -  by @94726 in https://github.com/harlan-zw/nuxt-seo/issues/256 (2f195)
Disable splash by default  -  by @harlan-zw (840cf)
doc: Broken config key for robot user agents  -  by @harlan-zw (b76b2)

View changes on GitHub

Configuration
📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).
🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.
♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
🔕 Ignore: Close this PR and you won't be reminded about this update again.

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You can manually request rebase by checking the rebase/retry box above.
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Add label names as filter in issue search api

I am working on some sort of Gitea integration that needs to comment on a list of issues
with a certain label. I don't want to manually keep track of the label ID for each repository
I am running the service against.
Sample request:
http://localhost:3000/api/v1/repos/damn/KKKKK/issues?labels=bug,duplicate

Codecov Report

Merging #5946 into master will increase coverage by 0.01%.
The diff coverage is 70.83%.

@@            Coverage Diff             @@
##           master    #5946      +/-   ##
==========================================
+ Coverage   38.54%   38.55%   +0.01%
==========================================
  Files         330      330
  Lines       48526    48549      +23
==========================================
+ Hits        18702    18716      +14
- Misses      27116    27123       +7
- Partials     2708     2710       +2

Impacted Files
Coverage Δ

models/issue_label.go
60.59% <100%> (+1.05%)
:arrow_up:

routers/api/v1/repo/issue.go
31.19% <58.82%> (+1.16%)
:arrow_up:

models/repo_list.go
63.29% <0%> (-1.27%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 746cf22...4cce53f. Read the comment docs.


On audio interface error the CLI freezes while waiting for input

Expected behavior
When executing the record option in the CLI and there is a problem/error with the audio interface it should tell the user there is a problem and return to waiting for new user input.
Actual behavior
If the audio interface is broken and returns an error, the program will still be trying to transcribe and wait for the user to speak.
Steps to reproduce

I guess disable all audio interfaces (?)
Try to record

Additional context
n/a

I will try to solve this using sounddevice instead of PyAudio which is much more Python-esque


Undefined name: from pyspark.util import _exception_message

flake8 testing of https://github.com/apache/spark on Python 3.7.0
$ flake8 . --count --select=E901,E999,F821,F822,F823 --show-source --statistics
./python/pyspark/java_gateway.py:172:20: F821 undefined name '_exception_message'
            emsg = _exception_message(e)
                   ^
1     F821 undefined name '_exception_message'
1

@HyukjinKwon
What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Please review http://spark.apache.org/contributing.html before opening a pull request.

Can one of the admins verify this patch?

Can one of the admins verify this patch?

Can one of the admins verify this patch?

ok to test

Test build #95412 has started for PR 22265 at commit 197ef63.

Test build #95412 has finished for PR 22265 at commit 197ef63.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/95412/
Test PASSed.

Can you fix the PR title prefix to [SPARK-25253][PYSPARK][FOLLOWUP] ...

Let's format PR description as well

thanks, lgtm
btw @HyukjinKwon I had expected jenkins testing to catch this ... but are there no tests run on python 3? is python 3 testing still manual from the contributor & reviewer?

Eh, I think Python 3 is used in Jenkins tests ..
========================================================================
Running PySpark tests
========================================================================
Running PySpark tests. Output is in<EMAIL_ADDRESS>Will test against the following Python executables: ['python2.7', 'python3.4', 'pypy']
Will test the following Python modules: ['pyspark-core', 'pyspark-sql', 'pyspark-streaming', 'pyspark-mllib', 'pyspark-ml']
Starting test(pypy): pyspark.streaming.tests
Starting test(python2.7): pyspark.mllib.tests
Starting test(pypy): pyspark.sql.tests
Starting test(pypy): pyspark.tests
Finished test(pypy): pyspark.streaming.tests (126s)
Starting test(python2.7): pyspark.sql.tests
Finished test(pypy): pyspark.tests (204s) ... 2 tests were skipped
Starting test(python2.7): pyspark.streaming.tests
Finished test(python2.7): pyspark.mllib.tests (234s)
Starting test(python2.7): pyspark.tests
Finished test(python2.7): pyspark.streaming.tests (125s)
Starting test(python3.4): pyspark.mllib.tests
Finished test(pypy): pyspark.sql.tests (332s) ... 109 tests were skipped
Starting test(python3.4): pyspark.sql.tests
Finished test(python2.7): pyspark.tests (201s)
Starting test(python3.4): pyspark.streaming.tests
Finished test(python2.7): pyspark.sql.tests (344s) ... 109 tests were skipped
Starting test(python3.4): pyspark.tests
Finished test(python3.4): pyspark.streaming.tests (130s)
Starting test(pypy): pyspark.accumulators
Finished test(pypy): pyspark.accumulators (9s)
Starting test(pypy): pyspark.broadcast
Finished test(pypy): pyspark.broadcast (7s)
Starting test(pypy): pyspark.conf
Finished test(pypy): pyspark.conf (5s)
Starting test(pypy): pyspark.context
Finished test(pypy): pyspark.context (22s)
Starting test(pypy): pyspark.profiler
Finished test(python3.4): pyspark.mllib.tests (286s)
Starting test(pypy): pyspark.rdd
Finished test(pypy): pyspark.profiler (9s)
Starting test(pypy): pyspark.serializers
Finished test(pypy): pyspark.serializers (12s)
Starting test(pypy): pyspark.shuffle
Finished test(pypy): pyspark.shuffle (2s)
Starting test(pypy): pyspark.sql.catalog
Finished test(pypy): pyspark.sql.catalog (11s)
Starting test(pypy): pyspark.sql.column
Finished test(pypy): pyspark.rdd (34s)
Starting test(pypy): pyspark.sql.conf
Finished test(pypy): pyspark.sql.conf (5s)
Starting test(pypy): pyspark.sql.context
Finished test(pypy): pyspark.sql.column (19s)
Starting test(pypy): pyspark.sql.dataframe
Finished test(pypy): pyspark.sql.context (15s)
Starting test(pypy): pyspark.sql.functions
Finished test(python3.4): pyspark.tests (211s) ... 3 tests were skipped
Starting test(pypy): pyspark.sql.group
Finished test(pypy): pyspark.sql.group (20s)
Starting test(pypy): pyspark.sql.readwriter
Finished test(pypy): pyspark.sql.dataframe (40s)
Starting test(pypy): pyspark.sql.session
Finished test(pypy): pyspark.sql.functions (40s)
Starting test(pypy): pyspark.sql.streaming
Finished test(pypy): pyspark.sql.readwriter (17s)
Starting test(pypy): pyspark.sql.types
Finished test(pypy): pyspark.sql.session (15s)
Starting test(pypy): pyspark.sql.udf
Finished test(pypy): pyspark.sql.streaming (12s)
Starting test(pypy): pyspark.sql.window
Finished test(pypy): pyspark.sql.types (5s)
Starting test(pypy): pyspark.streaming.util
Finished test(pypy): pyspark.streaming.util (1s)
Starting test(pypy): pyspark.util
Finished test(pypy): pyspark.util (1s)
Starting test(python2.7): pyspark.accumulators
Finished test(python2.7): pyspark.accumulators (5s)
Starting test(python2.7): pyspark.broadcast
Finished test(pypy): pyspark.sql.udf (13s)
Starting test(python2.7): pyspark.conf
Finished test(pypy): pyspark.sql.window (11s)
Starting test(python2.7): pyspark.context
Finished test(python2.7): pyspark.broadcast (5s)
Starting test(python2.7): pyspark.ml.classification
Finished test(python2.7): pyspark.conf (3s)
Starting test(python2.7): pyspark.ml.clustering
Finished test(python2.7): pyspark.context (19s)
Starting test(python2.7): pyspark.ml.evaluation
Finished test(python2.7): pyspark.ml.evaluation (14s)
Starting test(python2.7): pyspark.ml.feature
Finished test(python2.7): pyspark.ml.clustering (31s)
Starting test(python2.7): pyspark.ml.fpm
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Starting test(python2.7): pyspark.ml.image
Finished test(python2.7): pyspark.ml.image (9s)
Starting test(python2.7): pyspark.ml.linalg.__init__
Finished test(python2.7): pyspark.ml.linalg.__init__ (0s)
Starting test(python2.7): pyspark.ml.recommendation
Finished test(python2.7): pyspark.ml.classification (50s)
Starting test(python2.7): pyspark.ml.regression
Finished test(python2.7): pyspark.ml.regression (32s)
Starting test(python2.7): pyspark.ml.stat
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Starting test(python2.7): pyspark.ml.tests
Finished test(python2.7): pyspark.ml.recommendation (53s)
Starting test(python2.7): pyspark.ml.tuning
Finished test(python2.7): pyspark.ml.stat (15s)
Starting test(python2.7): pyspark.mllib.classification
Finished test(python2.7): pyspark.ml.tuning (17s)
Starting test(python2.7): pyspark.mllib.clustering
Finished test(python2.7): pyspark.mllib.classification (25s)
Starting test(python2.7): pyspark.mllib.evaluation
Finished test(python3.4): pyspark.sql.tests (536s) ... 3 tests were skipped
Starting test(python2.7): pyspark.mllib.feature
Finished test(python2.7): pyspark.mllib.evaluation (13s)
Starting test(python2.7): pyspark.mllib.fpm
Finished test(python2.7): pyspark.mllib.feature (18s)
Starting test(python2.7): pyspark.mllib.linalg.__init__
Finished test(python2.7): pyspark.mllib.linalg.__init__ (0s)
Starting test(python2.7): pyspark.mllib.linalg.distributed
Finished test(python2.7): pyspark.mllib.fpm (15s)
Starting test(python2.7): pyspark.mllib.random
Finished test(python2.7): pyspark.mllib.clustering (41s)
Starting test(python2.7): pyspark.mllib.recommendation
Finished test(python2.7): pyspark.mllib.random (7s)
Starting test(python2.7): pyspark.mllib.regression
Finished test(python2.7): pyspark.mllib.recommendation (26s)
Starting test(python2.7): pyspark.mllib.stat.KernelDensity
Finished test(python2.7): pyspark.mllib.stat.KernelDensity (0s)
Starting test(python2.7): pyspark.mllib.stat._statistics
Finished test(python2.7): pyspark.mllib.regression (22s)
Starting test(python2.7): pyspark.mllib.tree
Finished test(python2.7): pyspark.mllib.linalg.distributed (35s)
Starting test(python2.7): pyspark.mllib.util
Finished test(python2.7): pyspark.mllib.stat._statistics (11s)
Starting test(python2.7): pyspark.profiler
Finished test(python2.7): pyspark.mllib.util (13s)
Starting test(python2.7): pyspark.rdd
Finished test(python2.7): pyspark.mllib.tree (15s)
Starting test(python2.7): pyspark.serializers
Finished test(python2.7): pyspark.profiler (5s)
Starting test(python2.7): pyspark.shuffle
Finished test(python2.7): pyspark.shuffle (0s)
Starting test(python2.7): pyspark.sql.catalog
Finished test(python2.7): pyspark.serializers (7s)
Starting test(python2.7): pyspark.sql.column
Finished test(python2.7): pyspark.sql.catalog (10s)
Starting test(python2.7): pyspark.sql.conf
Finished test(python2.7): pyspark.sql.conf (4s)
Starting test(python2.7): pyspark.sql.context
Finished test(python2.7): pyspark.rdd (26s)
Starting test(python2.7): pyspark.sql.dataframe
Finished test(python2.7): pyspark.sql.column (18s)
Starting test(python2.7): pyspark.sql.functions
Finished test(python2.7): pyspark.sql.context (13s)
Starting test(python2.7): pyspark.sql.group
Finished test(python2.7): pyspark.sql.group (17s)
Starting test(python2.7): pyspark.sql.readwriter
Finished test(python2.7): pyspark.sql.readwriter (15s)
Starting test(python2.7): pyspark.sql.session
Finished test(python2.7): pyspark.sql.dataframe (37s)
Starting test(python2.7): pyspark.sql.streaming
Finished test(python2.7): pyspark.sql.functions (37s)
Starting test(python2.7): pyspark.sql.types
Finished test(python2.7): pyspark.sql.types (4s)
Starting test(python2.7): pyspark.sql.udf
Finished test(python2.7): pyspark.sql.streaming (10s)
Starting test(python2.7): pyspark.sql.window
Finished test(python2.7): pyspark.sql.session (13s)
Starting test(python2.7): pyspark.streaming.util
Finished test(python2.7): pyspark.streaming.util (0s)
Starting test(python2.7): pyspark.util
Finished test(python2.7): pyspark.util (0s)
Starting test(python3.4): pyspark.accumulators
Finished test(python2.7): pyspark.ml.tests (188s)
Starting test(python3.4): pyspark.broadcast
Finished test(python2.7): pyspark.sql.udf (11s)
Starting test(python3.4): pyspark.conf
Finished test(python3.4): pyspark.accumulators (5s)
Starting test(python3.4): pyspark.context
Finished test(python3.4): pyspark.conf (4s)
Starting test(python3.4): pyspark.ml.classification
Finished test(python2.7): pyspark.sql.window (11s)
Starting test(python3.4): pyspark.ml.clustering
Finished test(python3.4): pyspark.broadcast (5s)
Starting test(python3.4): pyspark.ml.evaluation
Finished test(python3.4): pyspark.ml.evaluation (14s)
Starting test(python3.4): pyspark.ml.feature
Finished test(python3.4): pyspark.context (20s)
Starting test(python3.4): pyspark.ml.fpm
Finished test(python3.4): pyspark.ml.fpm (0s)
Starting test(python3.4): pyspark.ml.image
Finished test(python3.4): pyspark.ml.image (9s)
Starting test(python3.4): pyspark.ml.linalg.__init__
Finished test(python3.4): pyspark.ml.linalg.__init__ (0s)
Starting test(python3.4): pyspark.ml.recommendation
Finished test(python3.4): pyspark.ml.clustering (31s)
Starting test(python3.4): pyspark.ml.regression
Finished test(python3.4): pyspark.ml.classification (52s)
Starting test(python3.4): pyspark.ml.stat
Finished test(python3.4): pyspark.ml.regression (29s)
Starting test(python3.4): pyspark.ml.tests
Finished test(python3.4): pyspark.ml.stat (20s)
Starting test(python3.4): pyspark.ml.tuning
Finished test(python3.4): pyspark.ml.feature (65s)
Starting test(python3.4): pyspark.mllib.classification
Finished test(python3.4): pyspark.ml.recommendation (58s)
Starting test(python3.4): pyspark.mllib.clustering
Finished test(python3.4): pyspark.ml.tuning (18s)
Starting test(python3.4): pyspark.mllib.evaluation
Finished test(python3.4): pyspark.mllib.evaluation (14s)
Starting test(python3.4): pyspark.mllib.feature
Finished test(python3.4): pyspark.mllib.classification (29s)
Starting test(python3.4): pyspark.mllib.fpm
Finished test(python3.4): pyspark.mllib.fpm (15s)
Starting test(python3.4): pyspark.mllib.linalg.__init__
Finished test(python3.4): pyspark.mllib.feature (19s)
Starting test(python3.4): pyspark.mllib.linalg.distributed
Finished test(python3.4): pyspark.mllib.linalg.__init__ (0s)
Starting test(python3.4): pyspark.mllib.random
Finished test(python3.4): pyspark.mllib.clustering (42s)
Starting test(python3.4): pyspark.mllib.recommendation
Finished test(python3.4): pyspark.mllib.random (8s)
Starting test(python3.4): pyspark.mllib.regression
Finished test(python3.4): pyspark.mllib.regression (23s)
Starting test(python3.4): pyspark.mllib.stat.KernelDensity
Finished test(python3.4): pyspark.mllib.stat.KernelDensity (0s)
Starting test(python3.4): pyspark.mllib.stat._statistics
Finished test(python3.4): pyspark.mllib.recommendation (31s)
Starting test(python3.4): pyspark.mllib.tree
Finished test(python3.4): pyspark.mllib.linalg.distributed (45s)
Starting test(python3.4): pyspark.mllib.util
Finished test(python3.4): pyspark.mllib.stat._statistics (13s)
Starting test(python3.4): pyspark.profiler
Finished test(python3.4): pyspark.profiler (6s)
Starting test(python3.4): pyspark.rdd
Finished test(python3.4): pyspark.mllib.tree (17s)
Starting test(python3.4): pyspark.serializers
Finished test(python3.4): pyspark.mllib.util (14s)
Starting test(python3.4): pyspark.shuffle
Finished test(python3.4): pyspark.shuffle (0s)
Starting test(python3.4): pyspark.sql.catalog
Finished test(python3.4): pyspark.serializers (8s)
Starting test(python3.4): pyspark.sql.column
Finished test(python3.4): pyspark.sql.catalog (11s)
Starting test(python3.4): pyspark.sql.conf
Finished test(python3.4): pyspark.sql.conf (4s)
Starting test(python3.4): pyspark.sql.context
Finished test(python3.4): pyspark.rdd (28s)
Starting test(python3.4): pyspark.sql.dataframe
Finished test(python3.4): pyspark.sql.column (18s)
Starting test(python3.4): pyspark.sql.functions
Finished test(python3.4): pyspark.sql.context (14s)
Starting test(python3.4): pyspark.sql.group
Finished test(python3.4): pyspark.sql.group (19s)
Starting test(python3.4): pyspark.sql.readwriter
Finished test(python3.4): pyspark.sql.dataframe (39s)
Starting test(python3.4): pyspark.sql.session
Finished test(python3.4): pyspark.sql.functions (39s)
Starting test(python3.4): pyspark.sql.streaming
Finished test(python3.4): pyspark.sql.readwriter (17s)
Starting test(python3.4): pyspark.sql.types
Finished test(python3.4): pyspark.sql.streaming (13s)
Starting test(python3.4): pyspark.sql.udf
Finished test(python3.4): pyspark.sql.types (5s)
Starting test(python3.4): pyspark.sql.window
Finished test(python3.4): pyspark.sql.session (14s)
Starting test(python3.4): pyspark.streaming.util
Finished test(python3.4): pyspark.streaming.util (0s)
Starting test(python3.4): pyspark.util
Finished test(python3.4): pyspark.util (0s)
Finished test(python3.4): pyspark.ml.tests (206s)
Finished test(python3.4): pyspark.sql.window (12s)
Finished test(python3.4): pyspark.sql.udf (13s)
Tests passed in 1295 seconds

Skipped tests in pyspark.sql.tests with pypy:
    test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_fallback_disabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_fallback_enabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_toggle (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_with_array_type (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_with_incorrect_schema (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_with_int_col_names (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_with_names (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_with_schema (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_createDataFrame_with_single_data_type (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_filtered_frame (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_null_conversion (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_pandas_round_trip (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_schema_conversion_roundtrip (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_timestamp_dst (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_toPandas_arrow_toggle (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_toPandas_fallback_disabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_toPandas_fallback_enabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_toPandas_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_toPandas_with_array_type (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_alias (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_array_type (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_basic (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_complex_expressions (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_complex_groupby (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_invalid_args (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_manual (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_sql (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_udfs (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_multiple_udfs (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_retain_group_columns (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_unsupported_types (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_array_type_correct (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_coerce (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_column_order (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_complex_groupby (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_datatype_string (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_decorator (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_empty_groupby (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_scalar_udfs_followed_by_grouby_apply (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_positional_assignment_conf (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_register_grouped_map_udf (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_self_join_with_pandas (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_supported_types (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_timestamp_dst (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_udf_with_key (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_unsupported_types (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_wrong_args (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_wrong_return_type (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_unbounded_frames (pyspark.sql.tests.HiveContextSQLTests) ... skipped "Unittest < 3.3 doesn't support mocking"
    test_pandas_udf_basic (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_pandas_udf_decorator (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_stopiteration_in_udf (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_udf_wrong_arg (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_query_execution_listener_on_collect_with_arrow (pyspark.sql.tests.QueryExecutionListenerTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_create_dataframe_from_pandas_with_timestamp (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_create_dateframe_from_pandas_with_dst (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_to_pandas (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_to_pandas_avoid_astype (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_datasource_with_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_udf_and_sql (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_nondeterministic_vectorized_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_nondeterministic_vectorized_udf_in_aggregate (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_register_nondeterministic_vectorized_udf_basic (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_register_vectorized_udf_basic (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_timestamp_dst (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_type_annotation (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_array_type (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_basic (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_chained (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_check_config (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_complex (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_datatype_string (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_dates (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_decorator (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_empty_partition (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_exception (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_invalid_length (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_array (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_binary (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_boolean (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_byte (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_decimal (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_double (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_float (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_int (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_long (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_short (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_null_string (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_return_scalar (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_return_timestamp_tz (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_string_in_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_timestamps (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_timestamps_respect_session_timezone (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_unsupported_types (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_varargs (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_vectorized_udf_wrong_return_type (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_array_type (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_invalid_args (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_sql (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_sql_and_udf (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_mixed_udf (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_multiple_udfs (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_replace_existing (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_simple (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'
    test_without_partitionBy (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, it was not found.'

Skipped tests in pyspark.tests with pypy:
    test_statcounter_array (pyspark.tests.NumPyTests) ... skipped 'NumPy not installed'
    test_serialize (pyspark.tests.SciPyTests) ... skipped 'SciPy not installed'

Skipped tests in pyspark.sql.tests with python2.7:
    test_createDataFrame_column_name_encoding (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_does_not_modify_input (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_fallback_disabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_fallback_enabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_toggle (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_with_array_type (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_with_incorrect_schema (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_with_int_col_names (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_with_names (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_with_schema (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_createDataFrame_with_single_data_type (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_filtered_frame (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_null_conversion (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_pandas_round_trip (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_schema_conversion_roundtrip (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_timestamp_dst (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_toPandas_arrow_toggle (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_toPandas_fallback_disabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_toPandas_fallback_enabled (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_toPandas_respect_session_timezone (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_toPandas_with_array_type (pyspark.sql.tests.ArrowTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_alias (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_array_type (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_basic (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_complex_expressions (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_complex_groupby (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_invalid_args (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_manual (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_sql (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_udfs (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_multiple_udfs (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_retain_group_columns (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_unsupported_types (pyspark.sql.tests.GroupedAggPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_array_type_correct (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_coerce (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_column_order (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_complex_groupby (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_datatype_string (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_decorator (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_empty_groupby (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_scalar_udfs_followed_by_grouby_apply (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_positional_assignment_conf (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_register_grouped_map_udf (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_self_join_with_pandas (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_supported_types (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_timestamp_dst (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_udf_with_key (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_unsupported_types (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_wrong_args (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_wrong_return_type (pyspark.sql.tests.GroupedMapPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_unbounded_frames (pyspark.sql.tests.HiveContextSQLTests) ... skipped "Unittest < 3.3 doesn't support mocking"
    test_pandas_udf_basic (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_pandas_udf_decorator (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_stopiteration_in_udf (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_udf_wrong_arg (pyspark.sql.tests.PandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_query_execution_listener_on_collect_with_arrow (pyspark.sql.tests.QueryExecutionListenerTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_create_dataframe_from_pandas_with_timestamp (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_create_dateframe_from_pandas_with_dst (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_to_pandas (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_to_pandas_avoid_astype (pyspark.sql.tests.SQLTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_datasource_with_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_udf_and_sql (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_nondeterministic_vectorized_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_nondeterministic_vectorized_udf_in_aggregate (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_register_nondeterministic_vectorized_udf_basic (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_register_vectorized_udf_basic (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_timestamp_dst (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_type_annotation (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_array_type (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_basic (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_chained (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_check_config (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_complex (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_datatype_string (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_dates (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_decorator (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_empty_partition (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_exception (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_invalid_length (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_array (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_binary (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_boolean (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_byte (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_decimal (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_double (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_float (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_int (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_long (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_short (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_null_string (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_return_scalar (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_return_timestamp_tz (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_string_in_udf (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_timestamps (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_timestamps_respect_session_timezone (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_unsupported_types (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_varargs (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_vectorized_udf_wrong_return_type (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_array_type (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_invalid_args (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_sql (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_sql_and_udf (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_mixed_udf (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_multiple_udfs (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_replace_existing (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_simple (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'
    test_without_partitionBy (pyspark.sql.tests.WindowPandasUDFTests) ... skipped 'Pandas >= 0.19.2 must be installed; however, your version was 0.16.0.'

Skipped tests in pyspark.sql.tests with python3.4:
    test_create_dataframe_required_pandas_not_found (pyspark.sql.tests.SQLTests) ... skipped 'Required Pandas was found.'
    test_to_pandas_required_pandas_not_found (pyspark.sql.tests.SQLTests) ... skipped 'Required Pandas was found.'
    test_type_annotation (pyspark.sql.tests.ScalarPandasUDFTests) ... skipped 'Type hints are supported from Python 3.5.'

Skipped tests in pyspark.tests with python3.4:
    test_sequencefiles (pyspark.tests.InputFormatTests) ... skipped 'serialize array of byte'
    test_newhadoop_with_array (pyspark.tests.OutputFormatTests) ... skipped 'serialize of array'
    test_sequencefiles (pyspark.tests.OutputFormatTests) ... skipped 'serialize array of byte'

flake8 @cclauss used here is a kind of linter which is not yet automatically ran in Jenkins.

I think we should really start to setup the Jenkins for Python coverage report site .... FYI @shaneknapp

Merged to master.

ah, of course, _exception_message is only used in the exception handling, so we never get an error about an undefined name in any of the tests.  Ok, thanks for the explanations, I appreciate it!


[Synapse] Fix/Disable Tests so they consistently pass

Disable a number of tests with https://github.com/Azure/azure-sdk-for-net/issues/17455 as a tracking issues
Update test-resources.json so you can run tests with preconfigured resources
"Smash" some test sets into single test so snippets run in correct consistent order
Update trigger tests to use derived trigger type (so the name comes back correctly).

Digging into why this is necessary is tracked in https://github.com/Azure/azure-sdk-for-net/issues/17459

I also removed some unnecessary/unused snippet regions
This PR may best be reviewed commit by commit

Ok, looks like I need to regenerate the saved test record for the trigger tests.

Reworking variable names and test async waiting as suggested. :heart: the ideas

Thanks for all the comments @maririos and @christothes . I've reworked the PR to include them, please re-review and see if you catch anything else.
I'm re-running LIVE tests locally right now to make sure the it didn't break anything.

Windows tests pass live.


NLPCRAFT-85: Maven profiles for Geo and Spell data

Moved Geo resources to nlpcraft-geo module
Moved Spell resources to nlpcraft-spell module
Created geo and spell Maven profiles to include/exclude those modules (excluded by default)

I've made some changes. However, the source build 'prepare 0.6.2' still includes all sources for all modules (standford, spell, geo). It should only do so for the binary build.


Convert lib/schema.js to typescript 1/3

Problem
[Github Issue #28]
Part 1 of 3
Converting files to typescript
Solution
This is file 1 of 4 of the files needed to be converted broken down into smaller prs.
Change summary:

Changed schema.js into schema.ts
changed typings in types to fulfill schema requirements

The failing check also looks like its from failing the build and dry run action from file lib/types/parquet_primitives.ts because I uncommented the MAP and LIST. My options are either to readd those two types to that file or just remove the test that uses map and list when it potentially shouldnt

Most likely needs review/answers on the comments

The current problem is that the code does not build because I uncommented MAP and LIST in the types/types.ts file so that part of the code does not give an error. Now within types/parquet_primitives.ts, they are expecting those typings along with respective toPrimitive functions but those functions have not been implemented yet which is why I assumed they were not in use


Update OSA SHA to 11.2.4

This patch updates the OSA SHA to the 11.2.4 release.
Fixes-Issue: #573

:+1:

:+1:


Replace print() with vim.notify()

Thanks for your support.

Have you used @rcarriga 's https://github.com/rcarriga/nvim-notify plugin?
This change looks good with that plugin

Yes, it is a great plugin. I did not hook to it ATM. but with your changes, I should hook that.


Add memester.xyz to Memes section of Projects

Hey, we just launched our meme platform built on Lens and we'd appreciate being featured in your list. Thanks!

Thanks for the contribution!


What's wrong with several zeros? Parser error.

Simple minor bug, parser breaks on pretty inoffensive 00 literal.
http://jsfiddle.net/wnb470qp/
new Ractive({
    el: 'body',
    template: '{{ true ? 11 : 00 }}',
});

Uncaught ParseError: Expected closing delimiter '}}' after reference at line 1 character 8:
{{ true ? 11 : 00 }}
       ^----

Looks like it's time to update my bullet-proof number regex... on it

fixed in edge, thanks


Upload failing with IDE 2.3.3 on Linux

I am trying to upload the data folder in the FSUpload example.
It looks as if all went well:
LittleFS Filesystem Uploader v1.2.0 -- https://github.com/earlephilhower/arduino-littlefs-upload

 Sketch Path: /tmp/.arduinoIDE-unsaved2024910-191894-1w98u7w.s05ig/FSUpload
   Data Path: /tmp/.arduinoIDE-unsaved2024910-191894-1w98u7w.s05ig/FSUpload/data
      Device: RP2040 series

Building LittleFS filesystem
Command Line: /home/steve/.arduino15/packages/rp2040/tools/pqt-mklittlefs/4.0.1-8ec9d6f/mklittlefs -c /tmp/.arduinoIDE-unsaved2024910-191894-1w98u7w.s05ig/FSUpload/data -p 256 -b 4096 -s 2097152 /tmp/tmp-192203-ftCuw8XwhzE3-.littlefs.bin
/file1.txt

4.0 or above

Generating UF2 image
Command Line: /home/steve/.arduino15/packages/rp2040/tools/pqt-picotool/4.0.1-8ec9d6f/picotool uf2 convert /tmp/tmp-192203-ftCuw8XwhzE3-.littlefs.bin -t bin /tmp/tmp-192203-ftCuw8XwhzE3-.littlefs.bin.uf2 -o 0x105ff000 --family data

Uploading LittleFS filesystem
Command Line: /home/steve/.arduino15/packages/rp2040/tools/pqt-python3/1.0.1-base-3a57aed-1/python3 /home/steve/.arduino15/packages/rp2040/hardware/rp2040/4.1.1/tools/uf2conv.py --serial /dev/ttyACM0 --family RP2040 /tmp/tmp-192203-ftCuw8XwhzE3-.littlefs.bin.uf2 --deploy
Resetting /dev/ttyACM0
Converting to uf2, output size: 4194304, start address: 0x2000
Scanning for RP2040 devices
Flashing /media/steve/RPI-RP2 (RPI-RP2)
Wrote 4194304 bytes to /media/steve/RPI-RP2/NEW.UF2

Completed upload.

However the "Files" window on RPI-RP2 never disconnects (as it does when uploading a sketch). When I reset the board manually, the filesystem has not been installed correctly.
The board is an Adafruit Feather RP2040 DVI. The Flash is set to 6MB sketch + 2MB FS.

Good catch.  The next 1.2.1 release will get you back running.  The RP2350 change ended up breaking RP2040 compatibility.


Cleanup should be improved

If cleanup was set to true, and then changed to false, ownership will still be there, while it should be removed (from all the child objects)
If both cleanup and deletionProtection are true, after removing a database from k8s, the secret with creds will be gone, and even though it's possible to connect to database, credentials are not accessible withing k8s anymore, so the application won't be able to connect to database.

1 - Should be fixed by #65
2 - I guess will not be fixed