WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
when I've install the phpexcel and update the composer this error is occurred, I tried to clear the cache but the error appeared again.

Issue 2:
After updating from 2.8.9 to 2.8.10 I experience the following exception for any request. Downgrading again resolves the issue. No other composer dependencies were updated in the process.

RuntimeException in appDevDebugProjectContainer.php line 7425:
You have requested a synthetic service ("request"). The DIC does not know how to construct this service.
in appDevDebugProjectContainer.php line 7425
at appDevDebugProjectContainer->getRequestService() in bootstrap.php.cache line 2221
at Container->get('request', '2') in appDevDebugProjectContainer.php line 10835
at appDevDebugProjectContainer->synchronizeRequestService() in bootstrap.php.cache line 2157
at Container->set('request', null, 'request') in bootstrap.php.cache line 3360
at ContainerAwareHttpKernel->handle(object(Request), '1', true) in bootstrap.php.cache line 2535
at Kernel->handle(object(Request)) in app_dev.php line 28

This might be related to #19825 and also feels like a BC break.
Issue 1:
Original ticket http://projects.scipy.org/scipy/ticket/712 on 2008-08-04 by @jpaalasm, assigned to unknown.

scipy.cluster.distance.pdist does not work when the Canberra distance is used.

As seen below, pdist outputs a pseudorandom number instead of the real distance (which, in this case, should be around 0.01492537).

In [27]: scipy.cluster.distance.pdist(([3.3], [3.4]), "canberra")
Out[27]: array([ 0.99999814])

In [28]: scipy.cluster.distance.pdist(([3.3], [3.4]), "canberra")
Out[28]: array([ 0.9999984])

In [29]: scipy.cluster.distance.pdist(([3.3], [3.4]), "canberra")
Out[29]: array([ 1.])

See the patch for a fix.

Issue 2:
Original ticket http://projects.scipy.org/scipy/ticket/711 on 2008-08-04 by @jpaalasm, assigned to trac user damian.eads.

scipy.cluster.distance.pdist does not work when the Canberra distance is used.

As seen below, pdist outputs a pseudorandom number instead of the real distance (which, in this case, should be around 0.01492537).

In [27]: scipy.cluster.distance.pdist(([3.3], [3.4]), "canberra")
Out[27]: array([ 0.99999814])

In [28]: scipy.cluster.distance.pdist(([3.3], [3.4]), "canberra")
Out[28]: array([ 0.9999984])

In [29]: scipy.cluster.distance.pdist(([3.3], [3.4]), "canberra")
Out[29]: array([ 1.])

See the patch for a fix.
Issue 1:
Vue.js version

2.2.2

Reproduction Link

https://jsfiddle.net/8azt2xz9/3/

and click filter, vue.js throw error duplicate keys error

if bind key is an object, vnode updateChildren algorithm has problems.

So the key is strictly required a string value?

Issue 2:
Version

2.6.11

Reproduction link

vueschool/vuejs-components-fundamentals@3a90eea

Steps to reproduce

Currently, when I get a Vue "warn"ing like

[Vue warn]: Avoid mutating a prop directly since the value will be overwritten whenever the parent component re-renders. Instead, use a data or computed property based on the prop's value. Prop being mutated: "groupBy"

found in

---> <OpsSidebarTab> at src/components/a/b/c.vue

What is expected?

The warning should go to console.warn

What is actually happening?

The warning goes to console.error

To duplicate the issue, check out the link, then mutate one of the props in the example.

Currently, when I get a Vue "warn"ing like

[Vue warn]: Avoid mutating a prop directly since the value will be overwritten whenever the parent component re-renders. Instead, use a data or computed property based on the prop's value. Prop being mutated: "groupBy"

found in

---> <OpsSidebarTab> at src/components/a/b/c.vue

It actually logs it to console.error.

How can I instead make warnings log to console.warn instead?

I know I could do Vue.config.warnHandler, but I don't know how to get it be the same format as the regular Vue output. For example, would I do something like

Vue.config.warnHandler = fucntion (msg, vm, trace) {
console.warn(`[Vue warn]: ${msg}\nfound in\n--->${trace}`)
}

?

Are there ever other formats I have to worry about? I wish I could just redirect these errors to console.warn without having to reformat them
Issue 1:
The ufunc reference contains the following notes about out and where usage:

If ‘out’ is None (the default), a uninitialized return array is created. The output array is then filled with the results of the ufunc in the places that the broadcast ‘where’ is True. If ‘where’ is the scalar True (the default), then this corresponds to the entire output being filled. Note that outputs not explicitly filled are left with their uninitialized values.

and

Note that if an uninitialized return array is created, values of False will leave those values uninitialized.

I understand why the API is like this, and that there are legitimate use cases that prevent unnecessary initialization. But it would be nice to also have this warning on the specific functions, like np.divide etc. - especially because this is a construct where an innocent looking statement may result in non-deterministic behavior.

Thanks!

Issue 2:
The numpy documentation on the use of the argument 'where' in numpy.divide says:

where : array_like, optional

Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.

I am wondering what value is used for the positions in the array where the condition in the argument 'where' evaluates to False. It does not set it to np.nan, nor takes the value from x1 / from x2, it seems to assign a random value. Sometimes it takes the value 0, which could make sense, but it is not very convenient to get a value that is not the same across the array, or not the same between two runs of the script.

Obviously, it is possible for the user to assign values in the output array subsequently using Boolean indexing. So, I am wondering if this is the expected behaviour? If so, so be it and I will just assign values subsequently.

Thank you.

Reproducing code example:

import numpy as np
arr = np.ones((10,), dtype=int)
x1 = arr * 2
x2 = arr * 3
d = np.divide(x1, x2, where=(arr != 1))
print(d)

Numpy/Python version information:

('1.15.0', '2.7.13 (v2.7.13:a06454b1afa1, Dec 17 2016, 20:53:40) [MSC v.1500 64 bit (AMD64)]')
Issue 1:
The wrong character (œ) is displayed for the lowercase æ

The capitalized version (Æ) is working fine

(Atom Version 0.138.0, OS X 10.10 Yosemite)

Issue 2:
Original issue: atom/atom#1625

Use https://atom.io/packages/keyboard-localization until this issue gets fixed (should be in the Blink upstream).
Issue 1:
I use multiple monitors on my laptop and can't use FancyZones on both. Only the primary laptop display will have all the zones but the external monitors is just considered and one zone.

Issue 2:
Summary of the new feature/enhancement

Currently the new FZ editor only comes up and applies zone layouts to the primary monitor. In order to get a layout on a different monitor, the original custom editor is needed. Bret and Jeff have a design for this change and now they need to implement it.

Proposed technical implementation details (optional)

Note that when this is done the original editor should be removed as well as the setting to toggle between editors.
Issue 1:
The following code does not show markers.

my_data = [1,2,5,3,0]
sns.lineplot(data = my_data,markers=True);

this code doesn't show markers either

ax = sns.lineplot(x = [1,2,3,4,5], y=[1,2,5,3,0],markers=True);

on the other hand, this code does:

my_data=pd.DataFrame([1,2,5,3,0])
sns.lineplot(data = my_data,markers=True);

seaborn version 0.11.1

matplotlib version 3.3.1

Issue 2:
I am running matplotlib 3.0.2 and Seaborn 0.9.0 in python 3.7 on MacOs.

There appears to be a bug in Seaborn which makes its line plot function ignore the markers argument. The matplotlib plot still plots the markers, i.e. this is not the problem and I also set lines.markeredgewidth as was recommended in an earlier issue on missing markers. Still whatever I set markers to, line plot accepts this and ignores it.

See a broken example: Matplotlib plots as it should, but Seaborn shows no markers:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

sns.set()
sns.set_context("paper",rc={"lines.linewidth": 2.5,'lines.markeredgewidth': 1,'lines.markersize': 10})

df_test = pd.DataFrame(data={'x':[1,2,3],'y':[4,5,6]})
plt.figure()
plt.plot(df_test['x'],df_test['y'],'o-')
plt.figure()
sns.lineplot(data=df_test,x='x',y='y',markers=['o'])
plt.show()
Issue 1:
Here is some strange code uncovered by a test I wrote for #23536:

fn id<T>(x: T) -> T { x }

fn main() {
let spot: Option<i8>;
let x = 1_i8 << id(8_i8);
spot = Some(x);
assert_eq!(spot.unwrap(), 0);
println!("so we stored a zero byte ... but:");
assert_eq!(x, 0);
}

Even in the playpen, this prints:

so we stored a zero byte ... but:
thread '<main>' panicked at 'assertion failed: `(left == right) && (right == left)` (left: `0`, right: `0`)', <anon>:9
playpen: application terminated with error code 101

Note those "crazy, non-matching" left and right values.

(Presumably something with LLVM's low-level code is leaving x in a register, thus yielding hidden high-order bits after the shift is done; those need to be masked away before we attempt to compare with another register.)

Issue 2:
1 >> 24353125315
Issue 1:
Preflight Checklist

I have read the Contributing Guidelines for this project.

I agree to follow the Code of Conduct that this project adheres to.

I have searched the issue tracker for an issue that matches the one I want to file, without success.

Issue Details

Electron Version:

v12.0.0-beta.21

Operating System:

Ubuntu 20.04

Last Known Working Electron version:

v11.2.3 (the same provided example works most recent v11 release, tested!)

Expected Behavior

Expecting browserWindow.capturePage() to return a promise that resolves to captured image

Actual Behavior

The function call will at some point result an uncaught promise exception. Currently it seems it's random and about a 5% chance of this happening.

To Reproduce

Minimal example is a loop calling browserWindow.capturePage() every 1 second until eventually it fails. On my machine it will fail within a minute and result in the error.

I tried with the new @electron/remote and also with the old electron.remote. The example is using the new remote module as it will result in an error whereas the old electron.remote will not result an exception, but instead the promise will never resolve or reject

git clone https://github.com/ozooner/electron-capture-page.git
npm install
npm start

Screenshots

Issue 2:
Issue Details

Electron Version:

13.0.0-nightly.20201203

Operating System:

macOS

Last Known Working Electron version:

N/A

Expected Behavior

WebFrameMain.frames should never contain undefined

Actual Behavior

Uncaught Exception:
TypeError: Cannot read property 'processId' of undefined
at id (/private/var/folders/_7/jm5cr84j7jd4v7btf2d3bqwm0000gn/T/tmp-59557-p4DTr3KWOsNk/main.js:4:38)
at pft (/private/var/folders/_7/jm5cr84j7jd4v7btf2d3bqwm0000gn/T/tmp-59557-p4DTr3KWOsNk/main.js:6:36)
at Timeout._onTimeout (/private/var/folders/_7/jm5cr84j7jd4v7btf2d3bqwm0000gn/T/tmp-59557-p4DTr3KWOsNk/main.js:27:5)
at listOnTimeout (internal/timers.js:554:17)
at processTimers (internal/timers.js:497:7)

To Reproduce

Run https://gist.github.com/f46823470955034b4a456b6275862bfb for a short while and you'll observe the above error.

cc @samuelmaddock
Issue 1:
Description

A textbox is added to the UI next to each DAG to write/modify information regarding the DAG directly in the UI.

Use case/motivation

I work on a team and currently we are unable to relay information regarding a DAG through the UI. For example: reason why a maintainer temporarily disabled a particular DAG.

The DAG doc_md is not very useful in this case since that lives in code - which has to go through a review process. It is a better candidate for displaying lasting information in our case.

In general, this feature can be used to display/modify any information regarding a DAG.

Related issues

No response

Are you willing to submit a PR?

Yes I am willing to submit a PR!

Code of Conduct

I agree to follow this project's Code of Conduct

Issue 2:
Description

I have been an airflow user for since a long time and I have often asked myself "what did happen to this task 4 months ago?".

Usually, this question starts a long and tedious process of going through slack/github/jira/emails to understand what was the problem.

Wouldn't be nice having a small airflow component where users can insert notes about tasks?

What do you want to happen?

The idea is to have a "task note" which is related to a task instance. We would have a new table: task_notes which has 5 columns dag_id, task_id, execution_date, task_notes, timestamp, (potentially others such a user etc)

We would have a new view similar to the xcom (second screenshot) and we modify the task instance view and model to refer to this task note view (first screenshot).

Users would be able to insert notes from this view.

In my current implementation, it looks something similar to this.

-->

Are you willing to submit a PR?

Yes. I have been working on this for fun as a POC.

Related Issues
Issue 1:
系统及 Electron 的版本信息:

Electron version: v1.6.1

Operating system: os x 10.12.2

问题现象

中文输入法（百度五笔），在输入中文时，时常会出来「输入法候选词面板」位置异常，会出现在整个窗口的「左上角」

问题截图

Issue 2:
I'm encountering a weird situation. When I was inputting characters in Chinese, the IME window would appear at top left of the app first, and then in a normal position for the consecutive letters. Please see the snapshot below.

Maybe @zcbenz you can view this issue.

Electron Version: v0.36.7

OS: Latest Mac OS X, 10.0.2 as far as I can recall

Issue reproduced every time on several machines.

There is a webview tag in my app. Could this be the cause?
Issue 1:
from Tensor.java:

non-scalar DataType.STRING tensors are not supported yet

Is there a plan for adding them for the Java interface?

Issue 2:
Currently, string tensors are not supported in java:

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/java/src/main/java/org/tensorflow/Tensor.java#L90

Implementing this would be very helpful in scenarios of training a model in one language, and serving from a different one, as it allows moving some of the logic to the tensor flow model.
Issue 1:
See the reported issue and particularly scikit-image/scikit-image#954 (comment) for the details.

From what I've succeded to track, this may be related to a direct malloc call:

1 -> 2 -> 3.

Issue 2:
Original reported on the scipy-user list: gmane

import numpy as np
from scipy import ndimage

arr = np.zeros((1024, 1024))

arr_filt = ndimage.median_filter(arr, 150)

The call to ndimage.median_filter requires allocating a 4050000000 byte (= 150 * 150 * 150 * 150 * 8) buffer. This buffer is allocated in NI_InitFilterOffsets, on line 518, in ni_support.c which is called from line 726 of ni_filter.c, in Ni_RankFilter.
Issue 1:
Commit b149be5 specifically removed all processing of non-HTTP(s) URLs. Previous to this commit if you were to pass in params, it would be appended to the URL. Since this commit it no longer works. Specifically I ran into this issue when running docker-py against a unix socket.

I understand that for non standard URLs you don't want to parse them. It seems that if the params were passed, then you should still append them. I'll gladly put in a pull request for this if it seems like a valid issue. A simple fix would be the below

# Don't do any URL preparation for oddball schemes
if ':' in url and not url.lower().startswith('http'):
encoded_params = self._encode_params(params)
if len(encoded_params) > 0:
if url.find('?') == -1:
url = '%s?%s' % (url, encoded_params)
else:
url = '%s&%s' % (url, encoded_params)
self.url = url
return

Issue 2:
resquests.Session() adds extra Host field to the header dictionary passed as argument even if that field is already specified in the dictionary. This happens when transfer-encoding is specified in the header dictionary. Having duplicate host field in the header confuses apache traffic server.
Issue 1:
enum Empty {}
struct Unit;

trait Run {
fn run() -> u8;
}

impl Run for Empty {
fn run() -> u8 { 0 }
}

impl Run for Unit {
fn run() -> u8 { 1 }
}

fn main() {
println!("{} {}", Empty::run(), Unit::run());
}

$ rustc -V
rustc 1.3.0-nightly (6d71ce536 2015-07-06)

$ rustc test.rs
test.rs:1:1: 1:14 warning: enum is never used: `Empty`, #[warn(dead_code)] on by default
test.rs:1 enum Empty {}
^~~~~~~~~~~~~
test.rs:2:1: 2:13 warning: struct is never used: `Unit`, #[warn(dead_code)] on by default
test.rs:2 struct Unit;

The same doesn't happen for static methods implemented directly on the types.

Issue 2:
foo.rs:

trait Bar {
fn bar() {}
}

enum Foo {}

impl Bar for Foo {}

fn main() {
Foo::bar();
}

Warning:

> rustc --version
rustc 1.0.0-nightly (199bdcfef 2015-03-26) (built 2015-03-27)
> rustc foo.rs
foo.rs:5:1: 5:12 warning: enum is never used: `Foo`, #[warn(dead_code)] on by default
foo.rs:5 enum Foo {}
^~~~~~~~~~~
Issue 1:
Preflight Checklist

I have read the Contributing Guidelines for this project.

I agree to follow the Code of Conduct that this project adheres to.

I have searched the issue tracker for a feature request that matches the one I want to file, without success.

Electron Version

13.1.2

What operating system are you using?

Windows

Operating System Version

Microsoft Windows 10 Pro 10.0.19042 Build 19042

What arch are you using?

x64

Last Known Working Electron version

11.4.8

Expected Behavior

When a window.webContents.print function is called with the deviceName property: "MyPrinter", the print must be destined for the device "MyPrinter"

Actual Behavior

The problem occurs on Electron versions greater than 11.4.8 when a default printer is configured in the operating system.

In the window.webContents.print function the deviceName property has no behavior, it's as if it doesn't exist

Testcase Gist URL

https://gist.github.com/d2be71545b59c8449f8206180168d122

Additional Information

No response

Issue 2:
Preflight Checklist

I have read the Contributing Guidelines for this project.

I agree to follow the Code of Conduct that this project adheres to.

I have searched the issue tracker for a feature request that matches the one I want to file, without success.

Electron Version

12.0.2

What operating system are you using?

Windows

Operating System Version

Windows 10 Home Single Language 20H2 19042.867

What arch are you using?

ia32

Last Known Working Electron version

11.4.2

Expected Behavior

This script should print to all existing printers. The printers "Microsoft XPS Document Writer" and "Microsoft Print to PDF" should block the loop and ask for file name.

Actual Behavior

All prints will return success, but print will happen always only to print set as default in system.

Testcase Gist URL

https://gist.github.com/fc8b4a9fbf986965c51e8f92b8ddb39f

Good way to run the test is to set printer "Microsoft Print To PDF" as default printer.
Issue 1:
scipy/scipy/optimize/optimize.py

Line 1519
in
11509c4

result = OptimizeResult(fun=fval, jac=gfk, nfev=fcalls[0],

Issue 2:
There are several recent PRs featuring new functions for statistical tests:

A new binomial test function (gh-12603)

Page's L (gh-12531)

Somers' D (gh-12653)

Alexander-Govern (gh-12873)

Tukey-Kramer (gh-13002)

Cramer-von-Mises (gh-11119, merged)

The new make_tuple_bunch (gh-12323) is for adding new outputs to existing tests in a backwards compatible way, but what should the new functions return?

To finish gh-11119 without needing to make this decision, cramervonmises returns a bare-bones CramerVonMisesResult:

class CramerVonMisesResult:
def __init__(self, statistic, pvalue):
self.statistic = statistic
self.pvalue = pvalue

def __repr__(self):
return (f"{self.__class__.__name__}(statistic={self.statistic}, "
f"pvalue={self.pvalue})")

I'm not sure the decision about supporting Python 3.6 was made yet then (is it official?), but the same behavior could have been achieved with make_dataclass.

This suggests a few questions.

Should there be a class like OptimizeResult, say, StatsTestResult, that takes care of some of the common behavior, or should we use make_dataclass? Or should each test make it's own unrelated custom class? What behavior would we want this class to take care of? For instance, OptimizeResult is a subclass of dict but includes a __getattr__ that allows accessing elements as if they were fields.

Should fields statistic and pvalue be standard names of the fields (where applicable) or should the name of the statistic be more specific?

The new BinomTestResult currently returned by binomtest (gh-12603) brings a few other questions to mind.

A relatively expensive calculation that is related but not required by the binomial test is calculation of a confidence interval of the proportion of successes. Currently, a method for performing that test is included in the BinomTestResult so that it is easy for the user to follow up a binomtest with calculation of the confidence interval, but it does not take time if it is not required. Do we agree that this is a good compromise between performing the CI calculation within binomtest and making the CI calculation a totally separate function?

How much information about the test that was performed should be returned in the result? Currently, BinomTestResult includes (beside pvalue) much of the user's input, including k, n, and alternative. Should it include more of what the user entered (e.g. the proportion of successes of the null hypothesis), or only what it needs to retain for performing follow-up calculations (e.g. confidence interval).

@WarrenWeckesser please feel free to edit this directly
Issue 1:
What is it

Since the hooks launch, I've been working with various teams and developers, and all of them, I repeat, ALL of them, seniors and juniors. Have been using useEffect "wrong" (considering what the react team intended). They all use the dependency array as an update array. There is no reason to keep hammering us, telling us that it is a dependency array if no one uses that way.

What I propose

Change linters and documentation to reflect the array as an update array, not as a dependency. Maybe add a third argument that should run as an actual dependency array, that does not trigger the code inside.

Issue 2:
I've built a task execution pipeline utilizing React v14 and I've begun testing it against React v15 and have noticed that all of a sudden I'm getting an invariant error: React DOM tree root should always have a node reference.

When I comment the line that is causing this error (

react/src/renderers/dom/client/ReactDOMComponentTree.js

Line 171
in
3b96650

invariant(

) everything works as it did with v14, and all of my unit tests pass. I assume this check is important to the new internal updates that have been made since v14.

I was able to make it work with a hacky bit of code that adds properties to the instance, _flags and _nativeNode, you can see this here: https://github.com/mbrio/react-pipeline/blob/react-15/src/startTasks.js#L8-L9.

I believe the issue is that with v14 I was able to use the server rendering code but in v15 I can no longer call forceUpdate or setState without errors occurring. Is there a way of bypassing the above error using the client renderer, or a way of calling setState/forceUpdate with the server renderer?