column

I don’t have a lot of expertise in keychain recovery. That’s not really an API issue, which is my focus, but more of a user-level issue, which is something for the folks over on Apple Support Community. However, I can answer some of this: [quote='829522022, rnikander, /thread/776581?answerId=829522022#829522022, /profile/rnikander'] Can I see every item name in login_renamed_1, without unlocking? [/quote] I’d ignore Keychain Access here and instead use the security tool. It’s very focused on file-based keychain. [quote='829522022, rnikander, /thread/776581?answerId=829522022#829522022, /profile/rnikander'] Is the entire data protection keychain in the file keychain-2.db? [/quote] Yes. Well, the entire data protection keychain for this specific user. Each user has their own data protection keychain. [quote='829522022, rnikander, /thread/776581?answerId=829522022#829522022, /profile/rnikander'] This is confusing me, since this looks to be file based as well [/quote] Sure. But all persistent storage on the Mac h

Here is a more simplified example of the app: import SwiftUI struct NSTableViewWrapper: NSViewRepresentable { class Coordinator: NSObject, NSTableViewDataSource, NSTableViewDelegate { var parent: NSTableViewWrapper init(parent: NSTableViewWrapper) { self.parent = parent } func numberOfRows(in tableView: NSTableView) -> Int { 1 } func tableView(_ tableView: NSTableView, viewFor tableColumn: NSTableColumn?, row: Int) -> NSView? { return NSTextField(labelWithString: Item) } func tableView(_ tableView: NSTableView, rowActionsForRow row: Int, edge: NSTableView.RowActionEdge) -> [NSTableViewRowAction] { return [NSTableViewRowAction(style: .destructive, title: Delete) { _, _ in }] } } func makeCoordinator() -> Coordinator { return Coordinator(parent: self) } func makeNSView(context: Context) -> NSScrollView { let scrollView = NSScrollView() let tableView = NSTableView() let column = NSTableColumn(identifier: NSUserInterfaceItemIdentifier(Column)) tableView.addTableColumn(column

NSTableView from AppKit works just as expected, while List from SwiftUI does this weird cropping. Here is the code for the NSTableView: import SwiftUI struct NSTableViewWrapper: NSViewRepresentable { class Coordinator: NSObject, NSTableViewDataSource, NSTableViewDelegate { var parent: NSTableViewWrapper init(parent: NSTableViewWrapper) { self.parent = parent } func numberOfRows(in tableView: NSTableView) -> Int { return parent.data.count } func tableView(_ tableView: NSTableView, viewFor tableColumn: NSTableColumn?, row: Int) -> NSView? { let cell = tableView.makeView(withIdentifier: NSUserInterfaceItemIdentifier(Cell), owner: nil) as? NSTextField ?? NSTextField(labelWithString: ) cell.identifier = NSUserInterfaceItemIdentifier(Cell) cell.stringValue = parent.data[row] return cell } } var data: [String] func makeCoordinator() -> Coordinator { return Coordinator(parent: self) } func makeNSView(context: Context) -> NSScrollView { let scrollView = NSScrollView() let tableView = NSTableView() let column

IMPORTANT The following contains a lot of implementation details. Don’t encode this knowledge into a product that you ship to a wide range of users. It has changed in the past and will likely change again in the future. Let’s start with the runningboardd man page. That’s not super helpful, but it does at least tell you that it’s responsible for managing processes. It started on iOS and has since moved to macOS. [quote='776288021, jaikiran, /thread/776288, /profile/jaikiran'] I suspect the identity it is talking about is the one explained as designated requirement [in TN3127] [/quote] That’s not the case. Rather, this is an internal identity used by runningboardd to classify the processes it knows about based on how they got started. For example, an application process has a description that starts with app. You can see these littered throughout the system log: type: default time: 13:12:54.328208+0000 process: runningboardd subsystem: com.apple.runningboard category: monitor message: Calculated state for app…

I recommend that you bookmark the Developer Account Helper > Reference > Supported capabilities (iOS) page (or the equivalent for the actual platform you’re targeting). It has a table that shows which capabilities are available to which team types. I suspect you’re using a Personal Team (the Apple Developer column) and that’s why you can’t use NE. If you are using a Personal Team, be aware that it has other significant limitations. For the details, see Developer > Support > Choosing a Membership. Share and Enjoy — Quinn “The Eskimo!” @ Developer Technical Support @ Apple let myEmail = eskimo + 1 + @ + apple.com

[quote='776126021, pikes, /thread/776126, /profile/pikes'] Is there a better way to handle a collapsing subview in an HSplitView? Why is the .frame not respected? [/quote] Have you checkout out inspector? Since you're using a NavigationSplitView, an inspector would present as a trailing column and by default, trailing column inspectors have their presentation state restored by the framework.

It's now possible in SwiftUI with TableColumnForEach [1] But don't use it. I tried and I got crashes when reloading data using Observable, I got crashes when changing columns. My app hung and needed killing when switching away from the table view and back. It crashes if there are zero columns. It's also really slow. Unusably so with about 200 rows and 150 columns. I tried with a release build and no difference was noticable. NSTable on the other hand handles everything admirably. [1] https://developer.apple.com/documentation/swiftui/tablecolumnforeach

@txoof import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.preprocessing import MinMaxScaler from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Input, LSTM, Dense, Dropout import tensorflow as tf from tensorflow.keras.callbacks import EarlyStopping import logging # Suppress warnings logging.getLogger(tensorflow).setLevel(logging.ERROR) logging.getLogger(urllib3).setLevel(logging.ERROR) # Verify GPU availability physical_devices = tf.config.list_physical_devices('GPU') print(fGPUs Available: {bool(physical_devices)}) # Load data with flexible features def load_data(filename, features=['Close']): df = pd.read_csv(filename, parse_dates=['DateTime']) df['DateTime'] = pd.to_datetime(df['DateTime'], format='%Y.%m.%d %H:%M:%S') required_columns = ['DateTime'] + features df_cleaned = df[required_columns].dropna().sort_values('DateTime') if df_cleaned.empty: raise ValueError(Dataset is empty after cleaning!) return df_cleaned, features # Example using mul