WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
[Enter steps to reproduce below:]

...

...

Atom Version: 0.166.0

System: linux 3.13.0-35-generic

Thrown From: Atom Core

Stack Trace

Uncaught Error: Atom can only handle files < 2MB for now.

At /usr/share/atom/resources/app/src/project.js:355

Error: Atom can only handle files < 2MB for now.
at Project.module.exports.Project.buildBuffer (/usr/share/atom/resources/app/src/project.js:355:15)
at Project.module.exports.Project.bufferForPath (/usr/share/atom/resources/app/src/project.js:332:63)
at Project.module.exports.Project.open (/usr/share/atom/resources/app/src/project.js:286:19)
at Workspace.module.exports.Workspace.openUriInPane (/usr/share/atom/resources/app/src/workspace.js:485:29)
at Workspace.module.exports.Workspace.open (/usr/share/atom/resources/app/src/workspace.js:412:19)
at Ipc.<anonymous> (/usr/share/atom/resources/app/src/window-event-handler.js:45:32)
at Ipc.emit (events.js:110:17)
at process.<anonymous> (/usr/share/atom/resources/atom/renderer/api/lib/ipc.js:22:29)
at process.emit (events.js:118:17)

Commands

Config

{
"core": {
"disabledPackages": [
"autocomplete-clang"
]
},
"editor": {
"fontSize": 13,
"invisibles": {}
}
}

Installed Packages

# User
minimap, v3.5.2
vim-mode, v0.24.0

# Dev
No dev packages

Issue 2:
I really like having different panes but that aren't very friendly to the keyboard.

For example if I want to open a new file into a split right pane, I have to open an EXISTING file into the pane, have two copies of it open long enough for me to CLICK into the new file then open the file I want on the right side of my screen. Then I close the duplicate file that allowed me to have the pane open in the first place.

Alot of effort.

I'd love the ability to open a new pane at least from the Fuzzy File Finder, something like maybe an alt-enter or command+1 for "Open in nth pane" would be such a huge improvement.
Issue 1:
Hello, I've been using the search engine with powertoys run a lot. Something I've noticed is that every time I try and run an application I use less frequently, the search engine only brings up files with a similar name, essentially every program I have installed has smaller bin with the same name. It would be incredible if there was a way to prioritize programs that are installed onto my disc, because right now I have my search engine set to only show 6 results, and very often, not a single one of those 6 are my application.

Issue 2:
I tend to search for already running processes quite frequently. It would be awesome to write something like this Chrome @running

Do you think this concept can be generalized as a search query mechanism for Power Toys Run?
Issue 1:
System information (version)

OpenCV => 4.2.0

Operating System / Platform => Windows 10 64 Bit

Compiler => MSVC++ 14.24

Detailed description

The static variables named "__initialization_mutex" are never freed, causing (false) memory leak detections.

For example one such variable is in modules/core/src/system.cpp .

IPP also produces a lot of false positives since it leaves a lot of TLS objects on the heap without cleaning them up upon unloading the DLL (exiting the application). But IPP can be disabled.

I have not yet checked if this issue is also present on linux or not.

Steps to reproduce

I used link to check for memory leaks, linked OpenCV (compiled from source) as a DLL to my application.

There is a solution in link that gets rid of this issue in certain cases.

Issue 2:
From question asked on stackoverflow: http://stackoverflow.com/questions/32845535/opencv-3-0-visual-studio-memory-leak-detector-false-positive

If I enabled memory leaks detector in Visual Studio (to detect leaks in my application) I have always some additional memory leaks from OpenCV and it's very difficult to find out the real memory leak from my application.

The leak comes from function: opencv/modules/calib3d/src/stereobm.cpp file.

In function: StereoBMImpl->compute() we have statement:

if(ocl::useOpenCL() && disparr.isUMat() && params.textureThreshold == 0)

The function: ocl::useOpenCL invokes getCoreTlsData() and this function executes operator new but never deletes this object:

static TLSData *value = new TLSData();

I disabled OpenCL but this code is still executed and memory leak is also reported.

I suppose this error isn't dangerous because it's assignment to static object, but it makes very difficult to find out leaks in applications which links to OpenCV.
Issue 1:
Issue Type:

“Feature Idea”

Ansible Version:

c6b26ff

Summary:

Hi,

I need to dump all the vars available at certain steps of playbook so I tried to follow this tip.

At first it looks like it does what I need but then I noticed that dumping vars gives me variables specified only in role's vars file and no vars inherited from group_vars/.

Inspecting lib/ansible/runner/__init__.py I see this:

# use combined_cache and host_variables to template the module_vars
# we update the inject variables with the data we're about to template
# since some of the variables we'll be replacing may be contained there too
module_vars_inject = utils.combine_vars(host_variables, combined_cache.get(host, {}))
module_vars_inject = utils.combine_vars(self.module_vars, module_vars_inject)
module_vars = template.template(self.basedir, self.module_vars, module_vars_inject)

and I see that vars inherited from group_vars are contained in host_variables.

Now I'm in doubt whether they should get in module_vars here and there's just a bug at this point

or they should not and then I'd like to add them later to inject dict like it's done with module_vars:

inject['vars'] = self.module_vars

Issue 2:
Currently if we are trying to register an instance that has not yet

been registered with the elb an exception is thrown as follows:

Traceback (most recent call last):

File "/home/ubuntu/.ansible/tmp/ansible-1388916053.26-72858643329411/ec2_elb", line 1412, in

main()

File "/home/ubuntu/.ansible/tmp/ansible-1388916053.26-72858643329411/ec2_elb", line 335, in main

elb_man.register(wait, enable_availability_zone)

File "/home/ubuntu/.ansible/tmp/ansible-1388916053.26-72858643329411/ec2_elb", line 168, in register

self.awaitelb_instance_state(lb, 'InService', initial_state)

File "/home/ubuntu/.ansible/tmp/ansible-1388916053.26-72858643329411/ec2_elb", line 213, in awaitelb_instance_state

if instance_state.state != initial_state.state:

AttributeError: 'NoneType' object has no attribute 'state'

This is expected because the code is querying the elb for the state of the new instance and it responds with a "InvalidInstance" response (as its not been registered with the ELB yet) and the code sets the value of the initial_state to None.

This code change checks if the initial_state is None. If it is, its safe to assume that its state has changed.

I have create #5506 as a suggested fix
Issue 1:
Is there interest in adding the mish activation function to jax.nn?

It has a much smoother curve vs relu, and in theory, that drives information more deeply through the network. It is slower than ReLU, but on average adds about 1-3% improvement vs ReLU. - LessW2020, Fastai forums

Issue 2:
While implementing setdiff1d, I've come across this weird case where the np.in1d would return duplicate items if it finds such items and the np.in1d implementation would return the set-like array.

I've attached a code sample to reproduce this below:

from jax import numpy as jnp # version: 0.2.3
import numpy as np # version: 1.19.2

a = jnp.array([3,-1,0,0,7,-3,-5,0,3,-5,-3,7,0,1,-1,-1,0,1,-1,0,-7,-4,3,-2])
b = jnp.array([-2,-3,-1,0,3,-2,6,0,1,0,0,-5,-2,0,0,0,-2,-2,6,2,-6,-3,-2,-3])

lax_ar = jnp.in1d(a, b, invert=True)
np_ar = np.in1d(a, b, assume_unique=True, invert=True)

print(a[lax_ar])
print(a[np_ar])

Upon further verification of this issue I've found that the problem reproduces due to numpy's implementation of in1d. I believe we might need to implement the sorting based option for longer sequences.

Also, if it is possible, I would like to try and implement it :).
Issue 1:
Version

2.6.10

Reproduction link

https://jsfiddle.net/ae82rfnv/

Steps to reproduce

While operating, carefully notice of the transitions

Working flow

tick first box (parent transition plays)

tick second box (child transition plays)

untick second box (child transition plays)

untick first box (parent transition plays)

Broken flow n°1

tick first box (parent transition plays)

tick second box (child transition plays)

untick first box (only parent transition plays)

Broken flow n°2

tick second box (nothing happens)

tick first box (the 2 transitions play in sync)

untick first box (only parent transition plays)

What is expected?

While unmounting, a transition should search for nested transition and operates in sequence carefully, running children transition first, then playing its own transition before unmounting, so all children transition could run their "leave" transition carefully.

What is actually happening?

Only the parent transiton runs, ignoring the children transition.

I understand why it does what it does as is, and it makes sense from mounting point of view ; where the logic fails is in the "final effect" : while the 2 transitions (parent and child) play correctly when mounting, it doesn't run "the opposite way/backwards" when unmounting.

Issue 2:
Version

2.5.22

Reproduction link

https://jsfiddle.net/wx91uLft/

other: https://jsfiddle.net/ae82rfnv/

Steps to reproduce

Show/hide elements with the "Toggle" button.

Show/hide elements with the "Toggle Ticked" button. Shows a workaround.

What is expected?

All transitions should be triggered on leave, even for nested child elements.

What is actually happening?

Transition classes don't get applied to nested child elements, when conditions for leaving transitions occur on the same tick.

Workaround: Delaying the parent transitions by one tick fixes the problem.

This has been reported, but got closed due to the sample code did not use appear on the <transition> elements. (See issues #7643 and #9243)

My example is more detailed and also provides a workaround.
Issue 1:
So here's my setup (using pandas 0.16.2):

>>> midx = pd.MultiIndex.from_product([['bar', 'baz', 'foo', 'qux'], ['one', 'two']],names=['first','second'])
>>> df = pd.DataFrame(np.random.randint(10,size=(8,8)),index=midx)

>>> df
0 1 2 3 4 5 6 7
first second
bar one 0 5 5 5 6 2 6 8
two 2 6 9 0 3 6 7 9
baz one 9 0 9 9 2 5 7 4
two 4 8 1 2 9 2 8 1
foo one 2 7 3 6 5 5 5 2
two 3 4 6 2 7 7 1 2
qux one 0 8 5 9 5 5 7 3
two 7 4 0 7 3 6 8 6

I recently found that I can select multiple levels by indexing with a tuple of tuples

>>> df.loc[( ('bar','baz'), ), :]
0 1 2 3 4 5 6 7
first second
bar one 0 5 5 5 6 2 6 8
two 2 6 9 0 3 6 7 9
baz one 9 0 9 9 2 5 7 4
two 4 8 1 2 9 2 8 1

Or even select at multiple depths of levels

>>> df.loc[( ('bar','baz'), ('one',) ), :]
0 1 2 3 4 5 6 7
first second
bar one 0 5 5 5 6 2 6 8
baz one 9 0 9 9 2 5 7 4

The issue is this: if I add any levels to the index tuple that don't exist in the dataframe, pandas drops them silently

>>> df.loc[( ('bar','baz','xyz'), ('one',) ), :]
0 1 2 3 4 5 6 7
first second
bar one 0 5 5 5 6 2 6 8
baz one 9 0 9 9 2 5 7 4

It seems to me like this should raise an exception since

The shape of the dataframe that is returned in this instance is not what you'd expect

There's no way to unambiguously fill the returned dataframe with NaNs where a level didn't exist (as is done in the case where there is only a single level index)

Issue 2:
xref #2567

In [27]: data = pd.DataFrame({'hr1': [514, 573], 'hr2': [545, 526],
...: 'team': ['Red Sox', 'Yankees'],
...: 'year1': [2007, 2008], 'year2': [2008, 2008]})
...:

In [28]: data
Out[28]:
hr1 hr2 team year1 year2
0 514 545 Red Sox 2007 2008
1 573 526 Yankees 2008 2008

In [29]: pd.lreshape(data, {'year': ['year1', 'year2'], 'hr': ['hr1', 'hr2']})
Out[29]:
team year hr
0 Red Sox 2007 514
1 Yankees 2008 573
2 Red Sox 2008 545
3 Yankees 2008 526

In [30]: pd.wide_to_long(data, ['hr', 'year'], 'team', 'index')
Out[30]:
hr year
team index
Red Sox 1 514 2007
Yankees 1 573 2008
Red Sox 2 545 2008
Yankees 2 526 2008

So we should drop one of these.
Issue 1:
The following throws a very confusing error (pandas 0.13.1):

pd.DataFrame([[1,"abc", 1]], columns=["a", "b", "a"]).describe()

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\frame.py", line 3790, in describe

numdata = self._get_numeric_data()

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\generic.py", line 1894, in _get_numeric_data

self._data.get_numeric_data()).finalize(self)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2596, in get_numeric_data

return self.get_data(**kwargs)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2610, in get_data

return self.combine(blocks)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2624, in combine

return self.class(new_blocks, new_axes, do_integrity_check=False)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2037, in init

self._set_ref_locs(do_refs=True)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2189, in _set_ref_locs

rl[loc] = (block, i)

IndexError: list assignment index out of range

pd.DataFrame([[1,"abc", 1]], columns=["a", "b", "a"]).info()

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\frame.py", line 1443, in info

counts = self.count()

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\frame.py", line 3862, in count

result = notnull(frame).sum(axis=axis)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\common.py", line 273, in notnull

res = isnull(obj)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\common.py", line 125, in isnull

return _isnull(obj)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\common.py", line 137, in _isnull_new

return obj._constructor(obj._data.apply(lambda x: isnull(x.values)))

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2384, in apply

do_integrity_check=do_integrity_check)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2037, in init

self._set_ref_locs(do_refs=True)

File "C:\Program Files\Python 3.3.3\lib\site-packages\pandas\core\internals.py", line 2177, in _set_ref_locs

'have _ref_locs set' % (block, labels))

AssertionError: Cannot create BlockManager._ref_locs because block [BoolBlock: [a, a], 2 x 1, dtype: bool] with duplicate items [Index(['a', 'b', 'a'], dtype='object')] does not have _ref_locs set

Note that there are multiple ways to avoid the error:

not having duplicate column names

changing the type of column "b" or deleting it!

In my program I had duplicate names only accidently, but still this behaviour and dependence on the non-duplicate column looks like a bug to me.

Issue 2:
In [88]: idx = pd.Index([1, 2, 3])

In [89]: idx.summary()
Out[89]: 'Int64Index: 3 entries, 1 to 3'
Issue 1:
All the downloadable packages are named "atom.x86_64.rpm" , could you please specify the version in the package names , it will be so helpful

Thank you

Issue 2:
Can we get the version appended to the rpm, deb and dmg packages as they are built.

I can't speak to dmg for mac, but it is considered standard practice to include the version and release as part of the filename in rpm and deb packages, especially since atom doesn't update itself and there are no YUM repos (yet).
Issue 1:
For certain well-chosen inputs, group_var_float64 may return small negative values due to roundoff error. This then interferes with e.g. computing aggregate standard deviations:

>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame({'a': (0, 0, 0), 'b': 0.832845131556193 * np.ones(3)})
>>> df.groupby('a').std()
b
a
0 NaN

To see the cause of this in isolation, consider

import numpy as np
from pandas.algos import group_var_float64

out = np.array([[0.0]], dtype=np.float64)
counts = np.array([0])
values = 0.832845131556193 * np.ones((3, 1), dtype=np.float64)
labels = np.zeros(3, dtype=np.int)

group_var_float64(out, counts, values, labels)

print out # This prints [[ -1.48029737e-16]] on my machine.

The fix for this should be easy (round up negative values to zero). I can provide a fix (+ tests) if needed.

INSTALLED VERSIONS

commit: None

python: 2.7.6.final.0

python-bits: 64

OS: Darwin

OS-release: 14.3.0

machine: x86_64

processor: i386

byteorder: little

LC_ALL: None

LANG: nl_BE.UTF-8

pandas: 0.16.1

nose: 1.3.4

Cython: 0.22

numpy: 1.9.2

scipy: 0.15.1

statsmodels: None

IPython: 3.1.0

sphinx: 1.3.1

patsy: None

dateutil: 2.4.2

pytz: 2014.9

bottleneck: None

tables: 3.1.1

numexpr: 2.4

matplotlib: 1.4.3

openpyxl: None

xlrd: None

xlwt: None

xlsxwriter: None

lxml: None

bs4: 4.3.2

html5lib: 0.999

httplib2: None

apiclient: None

sqlalchemy: 1.0.4

pymysql: None

psycopg2: None

Issue 2:
I propose adding a pipe method to GroupBy objects, having the same interface as DataFrame.pipe/Series.pipe.

The use case is reusing a GroupBy object when doing calculations, see use case example below.

Use case

A pipe is useful for succintly reusing Groupby objects in calculations, for example calculating prices given a column of revenue and a columns of quantity sold:

>>> from numpy.random import choice, random
>>> n = 100_000
>>> df = pd.DataFrame({'Store': choice(['Store_1', 'Store_2'], n),
'Year': choice(['Year_1', 'Year_2', 'Year_3', 'Year_4'], n),
'Revenue': (np.random.random(n)*50+10).round(2),
'Quantity': np.random.randint(1, 10, size=n)})
>>> df.head(2)
Quantity Revenue Store Year
0 2 14.69 Store_1 Year_1
1 9 25.89 Store_2 Year_4

Then having .pipe, we could for example get prices per store/year like so

>>> (df.groupby(['Store', 'Year'])
... .pipe(lambda grp: grp.Revenue.sum()/grp.Quantity.sum())
... .unstack().round(2))
Year Year_1 Year_2 Year_3 Year_4
Store
Store_1 6.99 6.99 7.01 6.92
Store_2 6.95 6.98 6.97 6.96

Note that the above is vectorized and piping makes the code succint and clear.

Alternatives to .pipe

The alternatives would be:

use .apply,

create a function and call that with a GroupBy object as its argument

Create a price column

Option 1 is not good because of slowness.

A pipe is just syntactic sugar for option 2, but would piping be more readable, especially it you're piping other stuff already.

Creating a concrete calculated column is in some instances the right approach, but in other cases it is better to calculate stuff.
Issue 1:
0.189.0 crash often......

when I copy text

Issue 2:
I'm using Atom ver. 0.189.0 on Ubuntu 14.04.2 LTS. When I copy a piece of text in atom and I try to paste it the right-click menu either won't show up or will show up without giving me option to paste. The paste shortcut doesn't work either and it creates issues even if I try to copy and paste text from other programs (after I have coping something from atom). I have disable all the extra plugins, so it isn't a plugin issue. I didn't had this issue with the previous version (I am using webupd8 ppa). If I do a right click on a place where there isn't a text entry (meaning a place where it doesn't support paste anyway) the right click menu appears fine.
Issue 1:
Example: https://github.com/symfony/symfony/blob/v3.1.3/src/Symfony/Component/Security/Core/Authentication/AuthenticationProviderManager.php#L33

Could be like:

/**
* @var AuthenticationProviderInterface[]
*/
private $providers;

Or at least:

/**
* @var array
*/
private $providers;

Adding PhpDocs would ease up reading the code, as one could just see the type of data stored in a field, instead of reading all the class' code, to reason what it contains. And of course, it would make IDE autocompletion better supported.

I volunteer to add them and submit a PR.

Issue 2:
Hi,

I recently upgrade from sf 2.3.9 to 2.3.10 and i'm surprised that elements cannot be removed from collections in forms.

But after i debugged the symfony form's core, i found that there's a problem with the method onSubmit in class Symfony\Component\Form\Extension\Core\EventListener\ResizeFormListener.

This is the source of problem:

// The data mapper only adds, but does not remove items, so do this

// here

if ($this->allowDelete) {

if ($data instanceof \IteratorAggregate) {

$iter = $data->getIterator();

while ($iter->valid()) {

$name = $iter->key();

if ($form->has($name)) {

$iter->next();

} else {

$iter->offsetUnset($name);

}

}

} else {

foreach ($data as $name => $child) {

if (!$form->has($name)) {

unset($data[$name]);

}

}

}

}

I fixed this problem by converting ArrayCollection to array in the getter of my form's model.
Issue 1:
Environment

Windows build number: windows 10
PowerToys version: 0.16.1
PowerToy module for which you are reporting the bug (if applicable): FancyZOnes and Window Walker

Steps to reproduce

Open chrome in two desktops, each window in different zone

go to 1st zone, 1st chrome window,

call for Window Walker, search for chrome window 2 title

press Enter to switch to the second chrome window on the second desktop

you will find its zone changed to the first window zone in the second desktop, not the zone you left

Expected behavior

i should find the window in the zone i left

Actual behavior

its zone will change to the other chrome window zone

Screenshots

Issue 2:
This issue is to keep track of all the FancyZones bugs related to Virtual Desktops.

Different layouts fight when assigned to different virtual desktops FIXED

Fancy Zones window re-arrange every active desktop switch FIXED

Windows don't stay in position FIXED

Windows losing zones after switching Virtual desktops CAN'T REPRO

Fancy Zones settings not retained across virtual desktops FIXED
Issue 1:
Is there a reason why allow-env does not support a whitelist?

I like the idea of knowing explicitly what environment variables the program can access. Often a program should only be able to access a few variables such as DEBUG.

Example invocation

DEBUG=* deno run --allow-env=DEBUG,TEST main.tsx

Of course the current alternative is something like this:

env -i HOME=$HOME PWD=$PWD PATH=$PATH DEBUG=* TEST=$TEST deno run --allow-env main.ts

Issue 2:
Currently --allow-env gives program unlimited permission to access any environment variable. It's much strong privilege and there should be more limited permission control for them.

Like --allow-net=:9999, how about these? --allow-env=DEBUG, --allow-env=DENO_DIR,DENO_INSTALL

Deno.env() should also be re-designed to get permitted variables.

I think even if full access to envars given to the process, It's dangerous to return key-value pair of all environment variables because malicious attackers are able to know some secret informations if they don't know envar's name. So how about re-design Deno.env to immutable map-like object?

Deno.env.get("DENO_DIR")
Deno.env.set("DEBUG", "*")
Deno.env.has("PORT")
Issue 1:
The following code works in requests 2.7.0 but raises an assertion error in 2.8.0:

import requests

session = requests.session()
session.headers.update({'x-api-key': 'blah', "Accept-Encoding": "gzip, deflate",
"User-Agent": "magnet-sdk-python"})
session.verify = True
req = requests.Request(method='POST', url='https://portal.niddel.com/api/v1-beta/alerts', params=None, json={'a': 1, 'b': 2})
req = session.prepare_request(req)
assert req.body

Since I provided neither files nor body, I would have expected json to work.

In case you need this info to reproduce the issue, all tests were performed on a Mac OS X with Python 2.7.10 (installed using homebrew).

Issue 2:
In version 2.7.0 I was using Requests constructor with json parameter specified, like:

json_data = [ ... ];
r = requests.Request('POST', url, json=json_data)

And in the 2.8.0 version this code does not work, because I do not specify data parameter. Inside constructor we get self.data assigned as [] if data is None else data, so we finally get self.data equal to [].

And because of this commit: 7a0cd16 we get json parameter ignored, because now we have to explicitly specify data={} when calling constructor, like:

json_data = [ ... ];
r = requests.Request('POST', url, json=json_data, data={})

I think that this issue definitely breaks documented API.