Advanced python
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Exception Handling in Python allows programs to handle and recover from errors and unexpected situations gracefully. A try statement runs a block of code and catches any exceptions in except blocks. Even if a statement is syntactically valid, it may cause an error at runtime. Exceptions can be handled through try-except blocks and the finally block is used for cleanup code. Multiprocessing uses multiple processors to run code concurrently for improved speed while multithreading runs multiple threads within a single process using shared memory for lighter resource usage but potential for race conditions.
Advanced python
- 2. Exception Handling in Python
- 3. An exception is an error which happens at the time of execution of a program. However, while running a program, Python generates an exception that should be handled to avoid your program to crash. In Python language, exceptions trigger automatically on errors, or they can be triggered and intercepted by your code. The exception indicates that, although the event can occur, this type of event happens infrequently.When the method is not able to handle the exception, it is thrown to its caller function. Eventually, when an exception is thrown out of the main function, the program is terminated abruptly. What is an Exception in Python?
- 4. • Division by Zero • Accessing a file which does not exist. • Addition of two incompatible types • Trying to access a nonexistent index of a sequence • Removing the table from the disconnected database server. • ATM withdrawal of more than the available amount Common Examples of Exception:
- 5. • Exceptions must be class objects • For class exceptions, you can use try statement with an except clause which mentions a particular class. • Even if a statement or expression is syntactically correct, it may display an error when an attempt is made to execute it. • Errors found during execution are called exceptions, and they are not unconditionally fatal. Rules of Exceptions
- 7. A try statement includes keyword try, followed by a colon (:) and a suite of code in which exceptions may occur. It has one or more clauses. During the execution of the try statement, if no exceptions occurred then, the interpreter ignores the exception handlers for that specific try statement. In case, if any exception occurs in a try suite, the try suite expires and program control transfers to the matching except handler following the try suite. TheTry Statement
- 8. Catch blocks take one argument at a time, which is the type of exception that it is likely to catch.These arguments may range from a specific type of exception which can be varied to a catch-all category of exceptions. The catch Statement Rules for catch block: • You can define a catch block by using the keyword catch • Catch Exception parameter is always enclosed in parentheses • It always represents the type of exception that catch block handles. • An exception handling code is written between two {} curly braces. • You can place multiple catch block within a single try block. • You can use a catch block only after the try block. • All the catch block should be ordered from subclass to superclass exception.
- 9. Finally Block Finally block always executes irrespective of an exception being thrown or not. The final keyword allows you to create a block of code that follows a try-catch block. Finally, clause is optional. It is intended to define clean-up actions which should be that executed in all conditions.
- 10. The Raise Statement The raise statement specifies an argument which exception object. Here, a comma follows the exception and argument or tuple of the argument that follows In this syntax, the argument is optional, and at the time of execution, the exception argument value is always none. Example: A Python exception can be any value like a string, class, number, or an object. Most of these exceptions which are raised by Python core are classes with an argument which is an instance of the class.
- 11. Multithreading vs Multiprocessing What's the difference?
- 12. A multiprocessing system has more than two processors. The CPUs are added to the system that helps to increase the computing speed of the system. Every CPU has its own set of registers and main memory. However, because each CPU are separate, it may happen that one CPU may not have anything to process. One processor may sit idle, and the other may be overloaded with the specific processes. In such a case, the process and resources are shared dynamically among the processors. What is Multiprocessing?
- 13. Multithreading is a program execution technique that allows a single process to have multiple code segments (like threads). It also runs concurrently within the "context" of that process. Multi-threaded applications are applications that have two or more threads that run concurrently.Therefore, it is also known as concurrency. What is Multithreading?
- 14. • A multiprocessing system has more than two processors whereas Multithreading is a program execution technique that allows a single process to have multiple code segments • Multiprocessing improves the reliability of the system while in the multithreading process, each thread runs parallel to each other. • Multiprocessing helps you to increase computing power whereas multithreading helps you create computing threads of a single process • In Multiprocessing, the creation of a process, is slow and resource-specific whereas, in Multiprogramming, the creation of a thread is economical in time and resource. • Multithreading avoids pickling, whereas Multiprocessing relies on pickling objects in memory to send to other processes. • Multiprocessing system takes less time whereas for job processing a moderate amount of time is taken. Key DIFFERENCES:
- 15. • The biggest advantage of a multiprocessor system is that it helps you to get more work done in a shorter period. • The code is usually straightforward. • Takes advantage of multipleCPU & cores • Helps you to avoid GIL limitations for CPython • Remove synchronization primitives unless if you use shared memory. • Child processes are mostly interruptible/killable • It helps you to get work done in a shorter period. • These types of systems should be used when very high speed is required to process a large volume of data. • Multiprocessing systems save money compared to single processor systems as processors can share peripherals and power supplies. Advantage of Multiprocessing
- 16. Disadvantage of Multiprocessing • IPC(Inter-Process Communication) a quite complicated with more overhead • Has a larger memory footprint
- 17. • Threads share the same address space • Threads are lightweight which has a low memory footprint • The cost of communication between threads is low. • Access to memory state from another context is easier • It allows you to make responsive UIs easily • An ideal option for I/O-bound applications • Takes lesser time to switch between two threads within the shared memory and time to terminate • Threads are faster to start than processes and also faster in task- switching. • AllThreads share a process memory pool that is very beneficial. • Takes lesser time to create a new thread in the existing process than a new process Advantage of Multithreading
- 18. • Multithreading system is not interruptible/killable • If not following a command queue and message pump model then manual use of synchronization needed which becomes a necessity • Code is usually harder to understand and increases the potential for race conditions increases dramatically Disadvantage of multithreading