WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
Duplicate of #13302

When reading via read_fwf and passing both na_values and converters at the same time, na_value detection does not work:

Code Sample, a copy-pastable example if possible

Assume a fwf-style text file like this:

A B C

10 -1 10

10 10 10

In: read_fwf(file_path, converters={'B':lambda x: int(x)/10.}, na_values={'B':-1})
Out:
> A B C
> 0 10 -0.1 10
> 1 10 1.0 10

Expected Output

> A B C
> 0 10 NaN 10
> 1 10 1.0 10

It would be nice if this could be handled behind the scenes.

In pandas.io.parsers._clean_na_values, float representations of the na_values are produced by _floatify_na_values. Maybe passing the converters to this function might be a solution?

Output of pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 23 Stepping 10, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.19.2

(...)

Issue 2:
On master (commit 40b4bb4):

>>> data = """A
1
CAT
3"""
>>> f = lambda x: x
>>> read_csv(StringIO(data), na_values='CAT', converters={'A': f}, engine='c')
A
0 1
1 CAT
2 3
>>> read_csv(StringIO(data), na_values='CAT', converters={'A': f}, engine='python')
A
0 1
1 NaN
2 3

I expect both to give the same output, though I believe the Python output is more correct because it respects na_values unlike the C engine. I thought the simple fix would be to remove the continue statement here, but that causes test failures, so probably a more involved refactoring might be needed to align the order of converter application, NaN value conversion, and dtype conversion.

IMO this should be added to #12686, as this is a difference in behaviour between the two engines.

xref #5232
Issue 1:
Hi,

For the past few months, atom has become extremely slow and after searching for the causes, it was found that processes named Atom Helper goes into the state of Not Responding after few minutes of starting the editor. These processes consume more than 200 MB of memory and affects the overall Mac's performance.

How can this be eliminated?

If this continues that probably I would be forced to replace atom with some other editor.

Issue 2:
Looking at activity monitor, I always get a Atom Helper (Not Responding), even if I start atom in safe mode.

I'm on OSX mavericks and atom 0.138.0. I noticed this at least a few versions back too.
Issue 1:
Angel opened SPR-8636 and commented

Example

@Controller
@SessionAttributes({"context"})
public class AuthenticationAction {
@RequestMapping("/login")
public String login(@RequestParam(required=false, "errorCode") String errorCode,
@ModelAttribute("context") String context) {
return "redirect:/action/login/" + context;
}
}

This example will redirect to the url: .../action/login/{context}?context=value

The parameter "context" and its value should not appear in the url query string by default in this case because they are already in session.

Affects: 3.1 M2

Issue Links:

#11462 Provide precise control over the attributes used in a redirect scenario ("duplicates")

1 votes, 2 watchers

Issue 2:
Evgeny Goldin opened SPR-7424 and commented

CommonsClientHttpRequestFactory used by Rest Template depends on outdated "commons-httpclient" v3.1.

Version 4.0.1 is available and it's a serious upgrade to HttpClient:

http://hc.apache.org/httpcomponents-client-4.0.1/index.html

http://hc.apache.org/httpcomponents-client/download.html

It would be nice if CommonsClientHttpRequestFactory was updated to use v4.x of Apache HttpClient

Affects: 3.0.3

Issue Links:

#11385 CommonsClientHttpRequestFactory getHttpClient() returns HttpClient from Commons HttpClient 3.x which has been EOL'd ("duplicates")
Issue 1:
I'm plotting the same image (a numpy float32 array) with imshow(..., interpolation='bilinear') on matplotlib 2.0.0 and 2.0.2.

Click to see in full:

On 2.0.0 the image is perfectly smooth. However, on 2.0.2 there are noticeable pixelization effects.

Has imshow() changed between these two versions?

Issue 2:
Bug report

Bug summary

With imshow(), image interpolation gives wrong results near pixels with values exceeding vmax. A large rectangular region (given by the interpolation kernel size) is filled with color corresponding to maximum value.

Code for reproduction

t = zeros((50, 50))
t[10, 10] = 1
t[10, 20] = 2
imshow(t, vmin=0, vmax=1, interpolation='lanczos')

see gist

Actual outcome

Expected outcome

Ok with matplotlib 2.0.0

Matplotlib version

Operating System: macOS

Matplotlib Version: 2.0.1, 2.0.2

Python Version: 2.7

Jupyter Version (if applicable):

Other Libraries:

matplotlib installed via conda-forge
Issue 1:
Apache Airflow version

2.3.2 (latest released)

What happened

For latest version (2.3.2) Airflow, on grid view UI all the task cells in the same row are showing same state(latest state):

In the response json of grid_data API we can see all the instances have the same data except run_id.

I think the children were same for all the instances here, which caused the problem:

https://github.com/apache/airflow/blob/2.3.2/airflow/www/views.py#L300

What you think should happen instead

Each task cell should show correct data.

How to reproduce

No response

Operating System

Ubuntu 19.10

Versions of Apache Airflow Providers

No response

Deployment

Other 3rd-party Helm chart

Deployment details

No response

Anything else

No response

Are you willing to submit PR?

Yes I am willing to submit a PR!

Code of Conduct

I agree to follow this project's Code of Conduct

Issue 2:
Apache Airflow version

2.3.2 (latest released)

What happened

Task status is applied to task groups of all dag runs.

Task Name overlaps with "Hide details panel" UI element

What you think should happen instead

Task group status of only corresponding dag run should be updated when a task status changes.

No overlap of html elements

How to reproduce

No response

Operating System

Ubuntu 20.04.3 LTS

Versions of Apache Airflow Providers

No response

Deployment

Virtualenv installation

Deployment details

No response

Anything else

No response

Are you willing to submit PR?

Yes I am willing to submit a PR!

Code of Conduct

I agree to follow this project's Code of Conduct
Issue 1:
Bug report

When using log scale with a scatter plot the axes are not set correctly if there is a zero value in the data.

Code for reproduction

import matplotlib.pyplot as plt

x=[1e4, 1e5, 1e6, 0]
y=[1, 1, 1, 1]

fig, ax = plt.subplots()

ax.scatter(x, y, marker='o')
ax.set_xscale('log')
plt.show()

Actual outcome

The first point does not appear in the plot:

Expected outcome

Expected all the points to be inside the axis limits as it appears when using plot instead of scatter:

Matplotlib version

Operating system: MacOS

Matplotlib version: 3.3.2

Matplotlib backend: Both MacOS and Jupyter module://ipykernel.pylab.backend_inline

Python version: 3.8.5

Jupyter version (if applicable): 6.1.4

Other libraries: N/A

Python and matplotlib installed with conda in a fresh environment

conda create --name matplotlib-log-scatter-bug matplotlib jupyter

Issue 2:
I installed the 3.2.0rc3 package, and I can confirm that this fixes almost all the issues with autoscaling and scatter. However, if you have points with 0 for the y-axis and enable log scaling there is still an issue with the scatter plot auto scaling (that doesn't show up with the standard plot function).

import itertools

import numpy as np
from matplotlib import pyplot as plt

x_vals = [4.38462e-06,
5.54929e-06,
7.02332e-06,
8.88889e-06,
1.125e-05,
1.42383e-05,
1.80203e-05,
2.2807e-05,
2.88651e-05,
3.65324e-05,
4.62363e-05,
5.85178e-05,
7.40616e-05,
9.37342e-05,
0.000118632,
]

y_vals = [0.0,
0.10000000000000002,
0.182,
0.332,
0.604,
1.1,
2.0,
3.64,
6.64,
12.100000000000001,
22.0,
39.60000000000001,
71.3,
]

pts = np.array(list(itertools.product(x_vals, y_vals)))

fig = plt.figure("Scatter plot")
ax = fig.gca()
ax.set_xscale('log')
ax.set_yscale('log')
ax.scatter(pts[:,0], pts[:,1]) # This only shows four rows of points

fig = plt.figure("Regular plot")
ax = fig.gca()
ax.set_xscale('log')
ax.set_yscale('log')
ax.plot(pts[:,0], pts[:,1], marker="o", ls="") # This works

plt.show()

Originally posted by @moloney in #6015 (comment)
Issue 1:
Electron version: v0.36.7

OS: linux

Code:

"use strict";
class GetterTest {
get foo() {
return "bar"
}
}

global.foo = new GetterTest();

console.log(global.foo.foo)

const electron = require("electron");
const app = electron.app;
const BrowserWindow = electron.BrowserWindow;

var window = null;

app.on("ready", () => {
window = new BrowserWindow();

window.loadURL(`file://${__dirname}/index.html`);
});

<html>
<head>
<script>
var remote = require("remote");
var foo = remote.getGlobal("foo");

console.log(foo.foo);
</script>
</head>
</html>

Expected: both console.log statements print "bar".

Actual: only console.log on main process prints "bar", the chrome debug console shows "undefined".

Issue 2:
ES6 classes treat member functions as non-enumerable in the instantiated class. However remote currently only works with enumerable properties, which means I have to use the old school prototype style to define classes for remote use. I find it a little bit inconvenient.

Here is an example:

in main process

class ClientSocket {
connect() {
//..
}
}
app.clientSocket = new ClientSocket();

in render process

const clientSocket = remote.app.clientSocket;
clientSocket.connect() // this doesn't work because connect() is not enumerable.

I mostly write new code in ES6 style and I'd like to keep my code style consistent. Is there any way to enable remote for ES6 class?
Issue 1:
TypeScript Version:

1.7.5 / 1.8.0-beta / nightly (1.9.0-dev.20160217)

Code

// A self-contained demonstration of the problem follows...

Expected behavior:

Actual behavior:

Issue 2:
I have a particular setup

class Foo {
get bar() {
return 'foobar';
}
}

class Bar {
get foo() {
return 'foobar';
}
}

class Foobar {
data: Foo | Bar;

baz() {
if (isFooInstance(this.data) {
return this.data.bar;
}
}
}

TypeScript throws an error in this situation saying bar does not exist on Foo | Bar - this is incorrect behavior IMO, especially if I have already screened out what type it is via other mechanisms.
Issue 1:
scipy.interpolate.insert allows for inserting a knot (with an arbitrary multiplicity) in a B-spline between two knots (say u_i and u_{i+1}) without modifying the others knots, as described in "Inserting new knots into B-spline", W. Boehm, Comp.-Aided Design 12(4), pp.199-201, 1980.

I have code that relies on that property and worked well for the past few years (since 2010).

Some change may have been committed that did not respect this non-modification of knots, see attached minimal example where for a simple knot sequence (obtained with splprep) some knot is deleted (6), another one is inserted (5 with multiplicity going from 1 to 2).

Has anybody experienced that already ? A clue on the commit that introduced that ?

Issue 2:
From @opoplawski: With Fedora Rawhide (but not Fedora 19) I'm seeing:

ERROR: test_fitpack.TestSplder.test_kink
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python2.7/site-packages/nose/case.py", line 197, in runTest
self.test(*self.arg)
File
"/builddir/build/BUILDROOT/scipy-0.13.0-0.1.b1.fc21.x86_64/usr/lib64/python2.7/site-packages/scipy/interpolate/tests/test_fitpack.py",
line 326, in test_kink
splder(spl2, 2) # Should work
File
"/builddir/build/BUILDROOT/scipy-0.13.0-0.1.b1.fc21.x86_64/usr/lib64/python2.7/site-packages/scipy/interpolate/fitpack.py",
line 1186, in splder
"and is not differentiable %d times") % n)
ValueError: The spline has internal repeated knots and is not differentiable 2
times

and the same with python3.
Issue 1:
I have two issues:

copy_to should copy values to upper nested_types by dot notation

copy_to should copy values inside of just created dynamic fields defined with dynamic_template

see https://gist.github.com/hbartnick/9954ef86a1f3285ff5ba

Issue 2:
Arrays of integers seem to be showing incorrect behavior when subjected to facets and script filters.

Here is a reproducer for the facet behavior. We index two arrays with 16 entries, but the facet count 3 and 6 respectively. This can be reproduced with numbers other than 0 filling most of the array.

https://gist.github.com/superfuego/5ebfc33431edddf4b387

Edit: Drew Raines started looking into this when I first posed this question in IRC, and said he found more inconsistent behavior than I had described.
Issue 1:
Q
A

Bug report?
yes

Feature request?
no

BC Break report?
no

RFC?
no

Symfony version
3.2?

Creating a ticket to follow up on #24865

From @weaverryan

Tangentially related to this: thanks to the same lack of laziness in Doctrine, the Doctrine Connection object is also instantiated. This means that a DATABASE_URL environment variable must be available at cache:warmup time. It doesn't need to be valid (no connection is make), but it does need to be defined: https://user-images.githubusercontent.com/121003/32516437-56ceb114-c3d1-11e7-8249-597c514117c1.png

And from @nicolas-grekas

The only way around is using a real lazy proxy from proxy-manager, which has tighter integration with the DI component and is able to call a factory lazily.

Issue 2:
Q
A

Bug report?
no

Feature request?
yes

BC Break report?
maybe

RFC?
yes

Symfony version
3.3, 3.4, 4.0

I have a CI build & run pipeline.

The cache is warmed up in the build process (using docker, withing the docker image build)

Environment variables are used to configure the application

The current implementation of the DI component requires to have all the ENV variables used in the config files as "defined" in the warmup environment, and this is really annoying...

I'm forced by this the to re-define all of them (with some default values) inside a file like parameters.yml just to be able to warm up the cache

There are too many env files to maintain:

Env variables are used "here and there" in the config files.

a list of env variables is available inside .env.dist

the customized env variables for development are stored inside the .env file

parameters.yml to workaround the warmup issue

Can the variable existence check be omitted? Default to null?

It is a common thing that in the "build" environment env variables are different from the "run" envs and having to define them just to have a default is annoying.
Issue 1:
Symfony version(s) affected: 3.4

Description

Calling a command that has a required argument from another command works fine normally, but when called from a command being run as the default command, an error such as 'Cannot add a required argument after an optional one' will be thrown.

It may have something to do with the way the $definition is built in Application when $name is falsey, then Command::mergeApplicationDefinition() is called on Command::run(), but I'm not really sure.

Possibly related issue

How to reproduce

Create app.php

<?php
use Symfony\Component\Console\Application;
use Symfony\Component\Console\Command\Command;
use Symfony\Component\Console\Input\ArrayInput;
use Symfony\Component\Console\Input\InputArgument;
use Symfony\Component\Console\Input\InputInterface;
use Symfony\Component\Console\Output\OutputInterface;
require(__DIR__ . '/vendor/autoload.php');

class DefaultCommand extends Command{
static public $defaultName = 'default';
protected function execute(InputInterface $input, OutputInterface $output){
$output->writeln('DefaultCommand');
$command = $this->getApplication()->find('other');
$command->run(new ArrayInput([
'command'=> 'other'
,'arg'=> 'a'
]), $output);
}
}
class OtherCommand extends Command{
static public $defaultName = 'other';
protected function configure(){
$this->addArgument('arg', InputArgument::REQUIRED);
}
protected function execute(InputInterface $input, OutputInterface $output){
$output->writeln('OtherCommand ' . $input->getArgument('arg'));
}
}

echo "----------\nRunning `" . implode(' ', $_SERVER['argv']) . "`\n";
$app = new Application();
$app->add(new DefaultCommand());
$app->add(new OtherCommand());
$app->setDefaultCommand('default');
$app->run();

Run in bash-like shell:

composer require symfony/console
php app.php default; php app.php

output:

----------
Running `app.php default`
DefaultCommand
OtherCommand a
----------
Running `app.php`
DefaultCommand

Cannot add a required argument after an optional one.

default

Issue 2:
Q
A

Bug report?
no

Feature request?
yes

BC Break report?
no

RFC?
no

Symfony version
4.0.2

Hi,

Consider moving dotenv dependency from require-dev to require by default.

Yes, I read docs about .env for development and setting environmental parameters on system.

But I don't think what there is some profit in it at all. I don't use Apache mod-php and docker. I want to be able to configure multiple application on one host easily.
Issue 1:
My understanding of priority queues is that they should allow duplicate keys: this is, for example, how the STL and Java priority queue implementations work as far as I can tell (cf. http://stackoverflow.com/questions/251438/stl-priority-queue-with-duplicate-keys-is-it-possible, http://stackoverflow.com/questions/10469701/how-to-configure-java-priority-queue-to-ignore-duplicates). Right now, our implementation doesn't do this because it acts more like a Dict than a queue.

Could we possibly rename our current implementation to PriorityQueueDict and then implement a more standard PriorityQueue that behaves like a queue/array?

Issue 2:
Hi everyone,

I am touching base with you since I have been trying to use the 0.3.11 version of the Julia kernel on JuliaBox for almost a week without success. Every time I switch to such kernel, the kernel dies as soon as it gets restarted and the problem is persistent.

I would like to know if anyone else is encountering the same issue and what I might do in order to get such issue solved.

Thank you very much in advance.
Issue 1:
Description of the new feature/enhancement

If the path can be moved to header and just use the binary name as Tab Name (With Tab Renaming for distinction). I feel this would make the terminal much more useful.

Proposed technical implementation details (optional)

I would suggest to make the Tab Interface two Layered stacked vertically, basically two rows. how it is implemented as of now is, the whole tab interface is on the header itself, i would suggest if header area(First Row) displays the path of the active tab and in 2nd row tabs are there displaying just the binary name would work better. for distinguishing between two same tabs the user should have ability to rename the tab.

If in future split screen is coming, such an interface would make much more sense, in my opinion.

Issue 2:
The red/blue and as yellow/cyan colors are swapped in the new Terminal when using the Campbell color scheme.

The color order is incorrect in "profiles.json". They should have the same order as in campbell.ini
Issue 1:
I'm seeing NPE's occur on random shards while performing a snapshot. Cluster Health throughout the process is green with very little CPU usage and heap. I usually try and run another snapshot after it finishes and the previous failed shards will complete and a new set will fail.

host ip heap.percent ram.percent load node.role master name
<redacted> 127.0.1.1 55 59 0.38 d * Caldari
<redacted> 127.0.1.1 40 56 0.01 d m Amarr
<redacted> 127.0.1.1 44 56 0.01 d m Minmatar
<redacted> 127.0.1.1 30 66 0.00 d m Gallente

[2014-10-31 15:35:31,771][WARN ][snapshots ] [Amarr] [[<idx_name>][2]] [s3_backups:1414767797] failed to create snapshot
org.elasticsearch.index.snapshots.IndexShardSnapshotFailedException: [<idx_name>][2] null
at org.elasticsearch.index.snapshots.blobstore.BlobStoreIndexShardRepository.snapshot(BlobStoreIndexShardRepository.java:141)
at org.elasticsearch.index.snapshots.IndexShardSnapshotAndRestoreService.snapshot(IndexShardSnapshotAndRestoreService.java:86)
at org.elasticsearch.snapshots.SnapshotsService$6.run(SnapshotsService.java:829)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:744)
Caused by: java.lang.NullPointerException
at org.elasticsearch.index.snapshots.blobstore.BlobStoreIndexShardRepository$SnapshotContext.snapshot(BlobStoreIndexShardRepository.java:456)
at org.elasticsearch.index.snapshots.blobstore.BlobStoreIndexShardRepository.snapshot(BlobStoreIndexShardRepository.java:131)
... 5 more

Issue 2:
A snapshot run failed with IndexShardSnapshotFailedException caused by an NPE for a lot of shards:

[2014-07-30 18:11:56,063][WARN ][snapshots ] [node.name] [[index.name][274]] [node.name:index.name] failed to create snapshot
org.elasticsearch.index.snapshots.IndexShardSnapshotFailedException: [index.name][274] null
at org.elasticsearch.index.snapshots.blobstore.BlobStoreIndexShardRepository.snapshot(BlobStoreIndexShardRepository.java:141)
at org.elasticsearch.index.snapshots.IndexShardSnapshotAndRestoreService.snapshot(IndexShardSnapshotAndRestoreService.java:86)
at org.elasticsearch.snapshots.SnapshotsService$6.run(SnapshotsService.java:829)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.NullPointerException
at org.elasticsearch.index.snapshots.blobstore.BlobStoreIndexShardRepository$SnapshotContext.snapshot(BlobStoreIndexShardRepository.java:456)
at org.elasticsearch.index.snapshots.blobstore.BlobStoreIndexShardRepository.snapshot(BlobStoreIndexShardRepository.java:131)
... 5 more

This is an index with 500 shards, snapshotting to an NFS mount.
Issue 1:
Is this a request for help? (If yes, you should use our troubleshooting guide and community support channels, see http://kubernetes.io/docs/troubleshooting/.):

What keywords did you search in Kubernetes issues before filing this one? (If you have found any duplicates, you should instead reply there.):

Is this a BUG REPORT or FEATURE REQUEST? (choose one):

Kubernetes version (use kubectl version):

Environment:

Cloud provider or hardware configuration:

OS (e.g. from /etc/os-release):

Kernel (e.g. uname -a):

Install tools:

Others:

What happened:

What you expected to happen:

How to reproduce it (as minimally and precisely as possible):

Anything else do we need to know:

Issue 2:
Is this a BUG REPORT or FEATURE REQUEST? (choose one): BUG REPORT

Kubernetes version (use kubectl version): 1.3.6

Environment:

Cloud provider or hardware configuration: AWS

OS (e.g. from /etc/os-release): CoreOS 1122.2.0

Kernel (e.g. uname -a):

Install tools:

Others:

What happened: kube-controller-manager complains of multiple instances found for same dns name it is querying on in findInstanceByNodeName

What you expected to happen: Query by instance id or at least filtered to current VPC

How to reproduce it (as minimally and precisely as possible): Run two identical VPC's with kubernetes so that the dns names are duplicated (in this case I'm running about 20, so easily reproducible).

Anything else do we need to know: