Python Certification Exam PCAP Practice Tests

Now is the time to get certified for Python! Python Institute PCAP-31-03/PCAP-31-02: Certified Associate in Python ProgrammingEvery question has an explanation and a Try-It-Yourself-Codewhich you can run to better understand the topic. You can download the Try-It-Yourself-Code for all questions. Exam SyllabusModules and Packagesimport variants; advanced qualifiying for nested modulesdir(); sys. path variablemath: ceil(), floor(), trunc(), factorial(), hypot(), sqrt(); random: random(), seed(), choice(), sample()platform: platform(), machine(), processor(), system(), version(), python implementation(), python version tuple()idea, pycache, name, public variables, init pyExceptionsexcept, except:-except; except:-else:, except (e1, e2)the hierarchy of exceptionsraise, raise ex, assertevent classes, except E as e, arg propertyself-defined exceptions, defining and usingStringsASCII, UNICODE, UTF-8, codepoints, escape sequenceschr/ord(), literalsindexing, slicing, immutabilityiterating through, concatenating, multiplying, comparing (against strings and numbers)in, not in. isxxx(), .join(), .split().sort(), sorted(), .index(), .find(), .rfind()Object-Oriented Programmingideas: class, object, property, method, encapsulation, inheritance, grammar vs class, superclass, subclassinstance vs class variables: declaring, initializing dict property (objects vs classes)private components (instance vs classes), name manglingmethods: declaring, using, self parameterinstrospection: hasattr() (objects vs classes), name, module, bases propertiesinheritance: single, multiple, isinstance(), overriding, not is and is operatorsinheritance: single, multiple, isinstance(), overriding, not is and is operatorsconstructors: declaring and invokingpolymorphism name, module, bases properties, str () methodmultiple inheritance, diamondsMiscellaneous (List Comprehensions, Lambdas, Closures, and I/O Operations)list comprehension: if operator, using list comprehensionslambdas: defining and using lambdas, self-defined functions taking lambda as as arguments; map(), filter();closures: meaning, defining, and using closuresI/O Operations: I/O modes, predefined streams, handles; text/binary modes, open(), errno and its values; close(), .read(), .write(), .readline(); readlines() (along with bytearray())Why learn Python?Python is easy to learn. The syntax is simple and the code is very readable. With Python, you can write programs in fewer lines of code than with most other programming languages. The popularity of Python is growing rapidly. It is now one of the most popular programming languages. Python has a wide variety of applications. It is used for automation, web application development, artificial intelligence, data science and so on: AutomationPython can make life easier by automating many tasks, such as scraping a website to collect data, automating test cases in software development, or automating everyday office tasks. Python can easily access and read all kinds of files, which opens up the possibility of saving a lot of time by automating repetitive tasks. Web DevelopmentPython is a good choice for rapid web application development. With many frameworks like Django, Pyramid, and Flask, you can develop web applications with great speed using Python. Python is used on the server side of web development. You can use Python to interact with database and create RESTful API services. Artificial IntelligenceThe near future will be the era of artificial intelligence. In the past, computers and machines were used to perform mathematical calculations at very high speeds, but now many large organizations and researchers are working to develop intelligent systems that can perform tasks like a human. To some extent, machines are able to understand human emotions and their natural language. They can mimic certain human actions that were not possible before. Again, Python is very popular for developing AI systems. Data ScienceEarlier, Python was mainly used to build applications and write scripts to automate tasks, but now a brand new trend of data science has given Python an even bigger boost. Data scientists are heavily dependent on Python because it is so simple, has a large community, and can perform huge calculations with ease. Python is being used in a wide variety of fields, and there are no signs that this trend is coming to a halt. It’s safe to say that Python is here to stay for the long haul in this ever-changing and evolving IT industry.