How to query the total number of data in PHP TP5?

The settings.json file is located in the user-level or workspace-level path and is used to customize VSCode settings. 1. User-level path: Windows is C:\Users\\AppData\Roaming\Code\User\settings.json, macOS is /Users//Library/ApplicationSupport/Code/User/settings.json, Linux is /home//.config/Code/User/settings.json; 2. Workspace-level path: .vscode/settings in the project root directory

ReadonlypropertiesinPHP8.2canonlybeassignedonceintheconstructororatdeclarationandcannotbemodifiedafterward,enforcingimmutabilityatthelanguagelevel.2.Toachievedeepimmutability,wrapmutabletypeslikearraysinArrayObjectorusecustomimmutablecollectionssucha

Use datetime.strptime() to convert date strings into datetime object. 1. Basic usage: parse "2023-10-05" as datetime object through "%Y-%m-%d"; 2. Supports multiple formats such as "%m/%d/%Y" to parse American dates, "%d/%m/%Y" to parse British dates, "%b%d,%Y%I:%M%p" to parse time with AM/PM; 3. Use dateutil.parser.parse() to automatically infer unknown formats; 4. Use .d

First, use JavaScript to obtain the user system preferences and locally stored theme settings, and initialize the page theme; 1. The HTML structure contains a button to trigger topic switching; 2. CSS uses: root to define bright theme variables, .dark-mode class defines dark theme variables, and applies these variables through var(); 3. JavaScript detects prefers-color-scheme and reads localStorage to determine the initial theme; 4. Switch the dark-mode class on the html element when clicking the button, and saves the current state to localStorage; 5. All color changes are accompanied by 0.3 seconds transition animation to enhance the user

Yes, a common CSS drop-down menu can be implemented through pure HTML and CSS without JavaScript. 1. Use nested ul and li to build a menu structure; 2. Use the:hover pseudo-class to control the display and hiding of pull-down content; 3. Set position:relative for parent li, and the submenu is positioned using position:absolute; 4. The submenu defaults to display:none, which becomes display:block when hovered; 5. Multi-level pull-down can be achieved through nesting, combined with transition, and add fade-in animations, and adapted to mobile terminals with media queries. The entire solution is simple and does not require JavaScript support, which is suitable for large

Use performance analysis tools to locate bottlenecks, use VisualVM or JProfiler in the development and testing stage, and give priority to Async-Profiler in the production environment; 2. Reduce object creation, reuse objects, use StringBuilder to replace string splicing, and select appropriate GC strategies; 3. Optimize collection usage, select and preset initial capacity according to the scene; 4. Optimize concurrency, use concurrent collections, reduce lock granularity, and set thread pool reasonably; 5. Tune JVM parameters, set reasonable heap size and low-latency garbage collector and enable GC logs; 6. Avoid reflection at the code level, replace wrapper classes with basic types, delay initialization, and use final and static; 7. Continuous performance testing and monitoring, combined with JMH

itertools.combinations is used to generate all non-repetitive combinations (order irrelevant) that selects a specified number of elements from the iterable object. Its usage includes: 1. Select 2 element combinations from the list, such as ('A','B'), ('A','C'), etc., to avoid repeated order; 2. Take 3 character combinations of strings, such as "abc" and "abd", which are suitable for subsequence generation; 3. Find the combinations where the sum of two numbers is equal to the target value, such as 1 5=6, simplify the double loop logic; the difference between combinations and arrangement lies in whether the order is important, combinations regard AB and BA as the same, while permutations are regarded as different;

Python is an efficient tool to implement ETL processes. 1. Data extraction: Data can be extracted from databases, APIs, files and other sources through pandas, sqlalchemy, requests and other libraries; 2. Data conversion: Use pandas for cleaning, type conversion, association, aggregation and other operations to ensure data quality and optimize performance; 3. Data loading: Use pandas' to_sql method or cloud platform SDK to write data to the target system, pay attention to writing methods and batch processing; 4. Tool recommendations: Airflow, Dagster, Prefect are used for process scheduling and management, combining log alarms and virtual environments to improve stability and maintainability.