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

To correctly handle JDBC transactions, you must first turn off the automatic commit mode, then perform multiple operations, and finally commit or rollback according to the results; 1. Call conn.setAutoCommit(false) to start the transaction; 2. Execute multiple SQL operations, such as INSERT and UPDATE; 3. Call conn.commit() if all operations are successful, and call conn.rollback() if an exception occurs to ensure data consistency; at the same time, try-with-resources should be used to manage resources, properly handle exceptions and close connections to avoid connection leakage; in addition, it is recommended to use connection pools and set save points to achieve partial rollback, and keep transactions as short as possible to improve performance.

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

fixture is a function used to provide preset environment or data for tests. 1. Use the @pytest.fixture decorator to define fixture; 2. Inject fixture in parameter form in the test function; 3. Execute setup before yield, and then teardown; 4. Control scope through scope parameters, such as function, module, etc.; 5. Place the shared fixture in conftest.py to achieve cross-file sharing, thereby improving the maintainability and reusability of tests.

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;

DependencyInjection(DI)isadesignpatternwhereobjectsreceivedependenciesexternally,promotingloosecouplingandeasiertestingthroughconstructor,setter,orfieldinjection.2.SpringFrameworkusesannotationslike@Component,@Service,and@AutowiredwithJava-basedconfi

JavaFlightRecorder(JFR)andJavaMissionControl(JMC)providedeep,low-overheadinsightsintoJavaapplicationperformance.1.JFRcollectsruntimedatalikeGCbehavior,threadactivity,CPUusage,andcustomeventswithlessthan2%overhead,writingittoa.jfrfile.2.EnableJFRatsta

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.