The Python Apprentice

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Comprehensions, iterables, and generators: We explore the elegant, pervasive, and powerful sequence-oriented parts of Python such as comprehensions and generator functions.

Files and Resource Management: We look at how to work with files in Python, and we cover the tools Python has for Resource Management. The great thing about the course is that it is very flexible and can be tailored to meet the needs of each individual and their employer. Welcome to The Python Apprentice! Our goal with this book is to give you a practical and thorough introduction to the Python programming language, providing you with the tools and insight you need to be a productive member of nearly any Python project. Python is a big language, and its not our intention with this book to cover everything there is to know. Rather we want to help you build solid foundations, orient you in the sometimes bewildering universe of Python, and put you in a position to direct your own continued learning. In addition to installing the Python runtime and standard library, the installer will register various file types, such as *.py files, with the Python interpreter. Prior to the ‘Data Analyst Level 4’ I had very little knowledge of the various software that was available to me as a Data Analyst outside of Microsoft Power BI. I am now confident in using Python as well as improving my Power BI core skills. The course is interesting, interactive and provides various learning activities to cater for different learning styles and is therefore a must for anyone who is involved in modelling data on a day-to-day basis.”

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The aim of this development programme is to increase confidence, competence, and career capability. Built-in types and the object model: We examine Python's type system and object system in detail, and we develop a strong sense of Python’s reference semantics. As mentioned earlier, Python comes with an extensive standard library, an aspect of Python that is often referred to as batteries included. The standard library is structured as modules, a topic we'll discuss in depth later. What's important at this stage is to know that you gain access to standard library modules by using the import keyword. Python is a general-purpose programming language. It's not intended for use in any particular domain or environment, but instead can be fruitfully used for a wide variety of tasks. There are, of course, some areas where it's less suitable than others – for example in extremely time-sensitive or memory-constrained environments – but for the most part Python is as flexible and adaptable as many modern programming language, and more so than most. Another of these PEPs, called PEP 20 is called “The Zen of Python”. It refers to 20 aphorisms describing the guiding principles of Python, only 19 of which have been written down. Conveniently, the Zen of Python is never further away than the nearest Python interpreter, as it can always be accessed from the REPL by typing: >>> import this The Zen of Python, by Tim Peters Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do it. Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now. If the implementation is hard to explain, it's a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea -- let's do more of those!

Exploring Built-in Collection Types: We go into more depth on some of the Python collection types, as well as introduce a few more. So when Python present us with the three dot prompt, we provide those four spaces and a statement to form the body of the loop: ... x = i * 10 One essential rule is NEVER to mix spaces and tabs. The Python interpreter will complain, and your colleagues will hunt you down.

Now practice using help() to request specific help on the factorial function: >>> help(math.factorial) Help on built-in function factorial in module math: factorial(...) factorial(x) -> Integral Find x!. Raise a ValueError if x is negative or non-integral.