Faced up with the same problem in Vue3 and Bootstrap 5 after bs-toaster has been plugged in. Cure it by comment out "import 'bootstrap/dist/js/bootstrap.bundle.min.js';" from main.js. Still not sure that not brake something elsewhere, but on first glance, everything works.
I was wrestling with this problem some years ago. My solution was to use Panels instead of Buttons, since all i needed was the Click-event. If you REALLY want or need to use Buttons that of course is not a solution.
My issue was that in the raw query I was using the @parameters (that were strings) surrounded with single quotes. Removing the single quotes solved my problem.
Just posting an update for anyone using a more recent version of the {lintr} package.
The with_defaults() function has been deprecated and is now linters_with_defaults().
The 'camel_case_linter' doesn't work for me, and I have to replace it with 'object_name_linter'.
My configuration also includes two common adjustments:
commented_code_linter = NULL: Disables warnings about commented-out code (useful for temporarily removing code like install.packages()).
line_length_linter(...): Increases the maximum line length to 120 characters from the default of 80 (far too narrow for the VS Code).
Regarding the file format, the .lintr file uses DCF syntax. The safest way to avoid parsing errors is to write the configuration on a single line (it can work when cut in multiple lines with tabulation but if you have a problem, put it in one line).
To answer my own question, it seems like buildSrc modules share the same classloader with gradle and somehow lead to dependency leaks that end up triggering internal compiler errors. So the solution I chose to go with was to create a separate module (i.e. build-logic) and then include that into my project, that way the build-logic module gets its own classloader and such issues are avoided.
Nowadays it's not possible and only thing you can do - open your application settings inside system settings. Below iOS 12 there was workaround with App-prefs, but since it's is private api your app will be rejected from App Store.
public static int GetIndex(this DataRowView rowView)
{
for (int i = 0; i < rowView.DataView.Count; i++)
{
if (rowView.DataView[i].Row == rowView.Row) // <-----
return i;
}
return -1;
}
The file history is not visible entirely in TIMELINE, but if you right-click on the file, then select File History | Open File History (with the Git Lens plugin), then everything can be displayed:
Moving away from publishing to folder on OneDrive to a local folder on the C: drive seems to work.
I also tried to change the rights to write to a folder on OneDrive, but it seems that applying new settings by unchecking "read only" folder attribute is not accepted.
Giving ALL users full rights does also not work.
Running VS in administrator mode also does not solve the problem.
Thank you. The webshot then magick method worked for me. I encountered a message to install phantomjs so I followed that. So now the first part is:
webshot::install_phantomjs()
webshot::webshot("presentation.html", "presentation.png")
Upgrading to <PackageReference Include="MSTest.TestAdapter" Version="4.1.0-preview.25514.12" /> <PackageReference Include="MSTest.TestFramework" Version="4.1.0-preview.25514.12" />
fixed the issue as @Youssef13 suggested above.
I also had to change from Sdk="MSTest.Sdk/x.y.z" to Sdk="Microsoft.NET.Sdk" since the first one seems to overwrite packages even if and update element is added to the project file: <ItemGroup> <PackageReference Update="MSTest.TestAdapter" Version="4.1.0-preview.25514.12" /> </ItemGroup>
That behavior is a bit unpredictable but not related to this issue.
as far as i know if you are (at the moment you are capturing the image) using v4l2 you can adjust the brightness and contrast of the camera itself(unless you are using pipewire which then im not even sure what to do)
Try to restore the UID for that property in the model JSON file (and make otherwise sure it's sound, like undoing adding it to the retired UID list). Then run the generator again.
Background: If you remove a poperty from the model it's data is not actually deleted from objects when "upgrading" the database to the new model. Only once you put an existing object the existing data would get overwritten.
Yes, this can likely be done with a Docusign CLM Document Smart Rule, but it requires a more advanced configuration using XPath within the Rename action to dynamically capture the parent folder name and retain the original document name.
Your previous attempt failed because the "Rename" action, when used with a literal value, completely replaces the document name instead of appending or prepending to it.
Fantastic post! Really helpful for anyone exploring Windows 11 upgrades and software options. 👉 I highly recommend checking out the website link in my profile for more tips and tools.
I had the same issue in my case i have installed SignalR NuGet Package in my Blazor Server Project as you know SignalR already exists in the Blazor Server due to that conflict i got that error.
Before buying from any site of the online platform, the buyers first look at the reviews on Google. If Google Reviews are present when buyers visit your site, the sales of theat site will increase at a faster rate. So increase the amount of sales through Google Reviews on your site.
I have found the issue . The cause is <View> and <BottomSheet> are react native components , not MapView overlays . on IOS , MapView accepts react subviews (and ignores unsupported once ) , but on android MapView is a native SurfaceView , which cannot have nested React views unless they're valid map overlays like <Marker> , <Circle> etc .
so to avoid this UI error on android simply do not put nested views inside the MapView . and by doing so my component mounts on android without an issue .
The highest voted solution doesn't work for me. I am using version 6.5.4.
the Inno Setup keep generating the manifest with "asInvoker".
My solution is:
1, Use "Resource Hacker" to manually edit the file "SetupLdr.e32" from Inno Setup installation folder, usually it would be "C:\Program Files (x86)\Inno Setup 6" (make sure you have a backup), choose the "Manifest", change it from "asInvoker" to "requireAdministrator", compile and save, then override the file back.
2, Add the "DisablePrecompiledFileVerifications=setupldre32" under [Setup] Section, to avoid Inno compile issue(ask Inno to ignore it being changed outside).
@musicamante Ok thanks for steering me away from QComboBox. Got a working solution "starting from scratch" and it's probably quite a bit easier to code up than the QComboBox contortions - and the two issues in the original question are resolved. Will do some more styling and sizing and such, but:
The code:
# heavily adapted from Google AI Overview: 'pyqt popup under button'
from PyQt5.QtWidgets import (
QApplication, QWidget, QVBoxLayout, QTreeView,QMainWindow,QPushButton,QDialog
)
from PyQt5.QtGui import QStandardItemModel, QStandardItem
from PyQt5.QtCore import QModelIndex,Qt,QPoint
class MyPopup(QDialog):
def __init__(self, parent=None):
super().__init__(parent)
self.parent=parent
# Create the TreeView for the dropdown popup
self.tree_view = QTreeView(self)
self.tree_view.setHeaderHidden(True) # Hide the header to look like a simple tree
self.tree_view.setSelectionMode(QTreeView.SingleSelection)
self.tree_view.setEditTriggers(QTreeView.NoEditTriggers)
self.tree_view.setExpandsOnDoubleClick(False)
self.tree_view.setAnimated(True)
self.tree_view.setFixedHeight(300)
# Create a model for the tree view
self.model = QStandardItemModel()
self.tree_view.setModel(self.model)
self.tree_view.entered.connect(self.enteredCB)
self.tree_view.clicked.connect(self.clickedCB)
self.tree_view.expanded.connect(self.expandedCB)
self.tree_view.collapsed.connect(self.collapsedCB)
self.setWindowTitle("Popup Dialog")
self.setWindowFlags(Qt.Popup)
layout = QVBoxLayout(self)
layout.setContentsMargins(0,0,0,0)
layout.addWidget(self.tree_view)
self.setLayout(layout)
self.tree_view.setMouseTracking(True)
def enteredCB(self,i):
print('entered')
self.setFullLabel(i)
def expandedCB(self,i):
print('expanded')
self.collapseOthers(i)
def collapsedCB(self,i):
print('collapsed')
def clickedCB(self,i):
print('clicked')
self.setFullLabel(i)
self.close() # close the popup
def setFullLabel(self,i):
# Get the full hierarchy path for display
current_index = i
path_list = [self.model.data(i)]
while current_index.parent().isValid():
parent_index = current_index.parent()
parent_text = self.model.data(parent_index)
path_list.insert(0, parent_text)
current_index = parent_index
# Join path with a separator and set the text
self.parent.button.setText(' > '.join(path_list))
def populate(self, data):
"""Populates the tree model from a dictionary."""
self.model.clear()
for key, children in data.items():
parent_item = QStandardItem(key)
for child_text in children:
child_item = QStandardItem(child_text)
parent_item.appendRow(child_item)
self.model.appendRow(parent_item)
for r in range(self.model.rowCount()):
for c in range(self.model.columnCount()):
txt=self.model.item(r,c).text()
print(f'row {r} col {c} : {txt}')
def collapseOthers(self,expandedIndex):
QApplication.processEvents()
print('collapse_others called: expandedIndex='+str(expandedIndex))
def _collapse_recursive(parent_index: QModelIndex,sp=' '):
for row in range(self.model.rowCount(parent_index)):
index = self.model.index(row, 0, parent_index)
item=self.model.itemFromIndex(index)
txt=item.text()
print(sp+f'checking r={row} col=0 : {txt}')
if index.isValid() and index!=expandedIndex:
print(sp+' collapsing')
self.tree_view.collapse(index)
# self.tree_view.setExpanded(index,False)
# Recursively process children
if self.model.hasChildren(index):
_collapse_recursive(index,sp+' ')
# Start the recursion from the invisible root item
_collapse_recursive(QModelIndex())
QApplication.processEvents()
class MainWindow(QMainWindow):
def __init__(self):
super().__init__()
self.setWindowTitle("Main Window")
self.setGeometry(100, 100, 400, 300)
central_widget = QWidget()
self.setCentralWidget(central_widget)
layout = QVBoxLayout(central_widget)
self.button = QPushButton("Show Popup", self)
self.button.clicked.connect(self.show_popup_under_button)
layout.addWidget(self.button)
self.popup = MyPopup(self)
def show_popup_under_button(self):
# Get the global position of the button's top-left corner
button_pos = self.button.mapToGlobal(QPoint(0, 0))
# Calculate the desired position for the popup
popup_x = button_pos.x()
popup_y = button_pos.y() + self.button.height()
# Sample hierarchical data
data = {
"Fruits": ["Apple", "Banana", "Orange"],
"Vegetables": ["Carrot", "Broccoli", "Spinach"],
"Dairy": ["Milk", "Cheese", "Yogurt"]
}
self.popup.populate(data)
self.popup.move(popup_x, popup_y)
self.popup.exec_() # Show as a modal dialog
if __name__ == "__main__":
app = QApplication([])
window = MainWindow()
window.show()
app.exec_()
I think what's happening is you might be moving the mouse and clicking at the same time (unbeknownst to you). According to MOUSE_EVENT_RECORD, a MOUSE_MOVED (0x0001) + DOUBLE_CLICK (0x0002) = 0x0003, so it adds up the event codes into pme->dwEventFlags and never goes into your switch case. My suggestion would be to remove your switch and keep just the if ( pme->dwButtonState & FROM_LEFT_1ST_BUTTON_PRESSED ) check.
I permanently deleted my Instagram account last year, which contained important personal photos and videos.
I understand it might be difficult, but I would like to know if there is any possibility to recover my deleted account or at least access some of the uploaded content.
You dont need to think about direction, instead of current floor of the elevator you should chose the destination floor.
The order shoud be unocupied > ocupied
if both unocupied choose current.closer
if both at the same floor choose elevator 1 (just a arbitrary because it wont matter)
if both occupied choose destination.closer
if elv1.destination = elv2.destination choose 1.
you could use a counter, once goes elv1, then elv2, then 1, then 2. so both elevators get used more evenly
this logic also lacks if 2 or more people press the button at the same time... anyway good luck
Also have a bunch of these. Annoyingly the default slide timer interval is five seconds which is much too long. I did note that in addition to a 24 MHz crystal it has a regular 32.768 kHz one which may be a potential modification eg swap it out for a 450kHz remote crystal.
You can not "copy" a media by a bot, but you can forward it removing the sender's name and editing it's description afterwards.
There is also another way to download the media in a data base and upload it manually.
In my case the reason was different: it did not show anything until I selected the checkbox "Show standard Jenkins list at the top of the page" in the "Dashboard Portlets" section.
Selenium can only access a HTML or XML document as a tree structure wherein each node is an object representing a part of the document. PDF does not offer this nor does it work in this way.
The browser has a PDF reader engine that paints the contests to the pdf-viewer element. This renderer draws the PDF onto a canvas (or a shadow DOM internal element) — a painted surface, not HTML. You will need to use a different tool such as a PDF parsing library that is able to piece through this and read its content and unfortunately Selenium was not designed for this.
Because React is in bed with cloud providers and Zuckerberg needs more profit$, you cannot have easily built client applications that leverage modern fetching techniques.
When using Service Accounts for authentication then the sharing settings for the service account within Google Calendar must be set to at least "Make changes to events" so "See all event details" is not enough to get colorId.
For a Block Blast-style solver, you'll want to balance computation with good heuristic evaluation. A full backtracking search is often too slow for real-time decisions.
A more efficient approach is a beam search that explores only the top N promising placements for your sequence of blocks. You need a strong heuristic function to evaluate board states. Focus on:
Line Clear Potential: Prioritize placements that clear rows/columns immediately.
Smoothness: Minimize the height differences across the board to avoid unreachable gaps.
Hole Prevention: Penalize placements that create enclosed empty spaces.
Density: Keep the board as filled as possible from the bottom up.
By combining these into a weighted score and only deeply exploring the best candidates, you can get near-optimal performance without the computational cost. You can test these kinds of strategies in action using a block blast solver to see how different heuristics play out in real-time.
Here’s a simple, one-step solution for PowerRename that will work for all your files, keeping the 4-digit file number, sheet number, and revision, and removing everything else in between:
Enable Use Regular Expressions, then use this search:
Had same issue, stems from using React-Native 0.81 with gradle plugin of 0.82 (in my case was auto-installed due to latent versioning)
Need to either update your react-native to 0.82 (requires react 19.1.1 or up) or downgrade the plugin
I'm developing a crash game similar to Aviator and want to implement a provably fair system. I understand the basic concept of using a server seed, client seed, and nonce to generate random outcomes, but I'm struggling with the specific algorithm for crash point calculation.
Most documentation explains provably fair for classic casino games, but crash games have different requirements. The game should:
- Generate a random crash point for each round
- Allow players to verify the result was predetermined
- Prevent manipulation from either side
What's the recommended approach for crash point generation? I've reviewed several implementations but can't find consensus on:
1. What cryptographic hash function to use (SHA-256, HMAC, etc.)
2. How to convert the hash output to a crash multiplier
3. The optimal frequency distribution for crash points
Here's an example of a working implementation I'm trying to understand: Aviator Games
Any code examples or detailed explanations of the mathematics behind crash point calculation would be greatly appreciated.
I can't reproduce your issue cause it looks good on my side
I think the first thing you should do before filtering your dataframe is to make sure your whole row in Time column is cleaned enough (no null, no different format, same dtype)
okay, Cognito isn’t built to act as a SAML IdP — it only consumes SAML, it doesn’t issue it. You can connect it to something like Okta or Azure AD as your SAML provider, but you can’t make other apps use Cognito as their SAML source.
If your goal is just to let users log in directly with Cognito, it’s best to stick with OAuth2 or OpenID Connect since that’s what it actually supports.
theorem is the syntax defined by Lean 4 itself (sometimes referred to as "Lean core").
lemma is an alternative syntax provided by mathlib, which is a library maintained by the community.
If your project has mathlib as a dependency, you can import Mathlib.Tactic.Lemma to gain access to the lemma syntax in your file. If your project does not depend on mathlib, you should use theorem.
good, but Cognito isn’t designed to work as a SAML Identity Provider (IdP) for any random service provider. It mainly supports OpenID Connect (OIDC) and OAuth2 standards. While Cognito can connect to a SAML IdP, it can’t directly serve as one itself.
If you need Cognito users to sign in through a SAML-based service, you’ll have to place an identity broker or gateway in between. That gateway can handle the translation between Cognito’s OIDC flow and the SAML flow expected by the service provider. I’ve implemented this setup before using a SAML↔OIDC bridge, and it works well once you configure the metadata correctly. you can take a look at here
# Create sample data
import pandas as pd
import numpy as np
data = {'date': pd.to_datetime(['2025-01-01', '2025-01-01', '2025-01-02', '2025-01-02']),
'Sector': ['Tech', 'Finance', 'Tech', 'Finance'],
'col5': [10, 20, 15, 25],
'col6': [100, 200, 150, 250]}
df = pd.DataFrame(data)
# Create the pivot table
pivotdf = pd.pivot_table(df, values=["col5", 'col6'], index=['date'], columns='Sector')
# Merge by setting the index on the original dataframe and using .join()
# This avoids the MultiIndex column issue
df_with_index = df.set_index('date')
merged_df = df_with_index.join(pivotdf, how='left', rsuffix='_bySector_pivot')
merged_df = merged_df.reset_index() # If you want 'date' back as a column
# Print the merged dataframe
print(merged_df)
__builtin_is_constant_evaluated of GCC/Clang (and surprisingly MSVC)
std::_Is_constant_evaluated of MSVC (any C++ standard here)
Intel C++ Compiler can't do it at all except C++20/C++23 (here)
There isn't any standard way in pre-C++20 through.
Test script:
#if __cplusplus >= 202002L || _MSVC_LANG>= 202002L
#include <type_traits>
#endif
bool is_constant_evaluated() {
#if __cpp_if_consteval >= 202106L
if consteval { return true; }
// both MSVC (non-comformant __cplusplus) and by-default _MSVC_LANG and other compiles with conformant __cplusplus
#elif __cplusplus >= 202002L || _MSVC_LANG>= 202002L
if (std::is_constant_evaluated()) return true;
#elif defined(__GNUC__) // defined for both GCC and clang
if (__builtin_is_constant_evaluated()) return true;
#elif defined(_MSC_VER)
if (__builtin_is_constant_evaluated()) return true;
#else
#error "NAWH we don't think we can detect compile time in this compiler";
#endif
return false;
}
int main() {
return is_constant_evaluated();
}
And it compiles and works properly even if it's MSVC and C++17/C++14. (assembly here)
the best system design for that problem is while uploading video also you save the metadata in a Redis
for example duration, file type, quality and more
Realtor.com API Open is New Real Estate API - Fast - Uptime 99%– Comprehensive search for properties, agents, and locations across the United States with fast, structured JSON results ready for apps and web.
try on rapidapi https://rapidapi.com/moham3iof/api/realtor-com-open
A materialized view (MV) stores the result of a query on disk, so reads are fast, but the data may be stale between refreshes. (whether it’s eventually consistent or transactionally consistent depends on the database engine)
What you get:
Fast read
Indexing (engine-dependent)
Query rewrite (engine-dependent)
What you trade off:
Freshness
Write overhead
So I suggest you to use an MV when you prefer read speed and cost predictability over up-to-the-second data.
