download: Python automated test development practice a test course can be employed
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Since the Python language was born in the early 1990s, it has been increasingly widely used for system processing tasks and for Web programming.
The founders of Python were the DutchGuido van Rossum [6]
ABC is an educational language which Guido participated in the planning. In Guido’s own opinion, the ABC language is beautiful and robust, designed for non-professional programmers. However, ABC speech did not succeed, and Guido thought that it was formed by its non-opening. Guido is determined to prevent this error in Python. Together, he wanted to end what had flashed but never ended in ABC.
In this way, Python was born in Guido’s hands. Arguably, Python started out as ABC and was first influenced by Modula-3, another rather beautiful and robust language designed for small groups. And combined with the Unix shell and C habits.
Python [7]
Because of the Python languageconcisePython is used by more and more foreign research institutions for scientific accounting, and some well-known universities are now using Python to teach programmingcourse. For example,Carnegie Mellon UniversityProgramming foundation,Massachusetts Institute of TechnologyThe introduction to computer science and programming in Python uses language education. Many open source scientific accounting packages provide Python callsinterface, such as the famous accounting machine vision libraryOpenCV, 3D visualization library VTK, medical picture processing library ITK. Numpy, Scipy, and Matplotlib provide Python with fast array handling, numerical manipulation, and drawing capabilities, respectively. Therefore, the Python language and its many extension libraries constitute a suitable development environmentengineeringSkills, researchers handling experimental data, making charts, and even developing scientific accountsUsing the program. In March 2018, the speech author announced on the mailing list that Python 2.7 would discontinue support on January 1, 2020. Users, assuming they want continued support related to Python 2.7 beyond this date, will have to pay a commercial vendor. [9]
Download the equipment
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Before you get started, your computer will require Python, but you may not need to download it. First check (type python in a command line window in the same directory) to see if there is device python. Suppose you see a Python illustration, then you can get a section number in its display window. The general version is Python compatible forward.
Assume that you need equipment, you might as well download the latest safe edition. That’s the highest edition that was released as an alpha or Beta without a symbol. Currently, the most stable version is Python3.0 + [10]
Let’s say you’re running Windows: The most secure download for Windows is “Python 3.9.0 for Windows”.
Suppose you’re running a Mac, MacOS 10.2 (Jaguar), 10.3 (_Panther_), and 10.4 (Tiger) device that already integrates Python, but you probably need the most recent common build for the device.
About Red Hat, devices Python2 and Python2-devel packages.
About Debian, the device Python2.5 and Python2.5-Dev packages.
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style
Python’s insistence on a clean style of planning makes it an easy-to-read, easy-to-protect, and versatile language that is welcomed by a large number of users.
The general guiding thinking for planners is that there is only one best way to deal with a particular problem. This is preferably described as “There should be one– and preferably only one– obvious way to do it” in The Python Motto written by Tim Peters, preferably The Zen of Python. This is the exact opposite of the central idea of “TMTOWTDI” (There’s More Than One Way To Do It) in Perl (another high-grade dynamic language that serves a similar purpose).
Python’s authors deliberately programmed a very restrictive syntax, so that even bad programming practices (such as not indenting the next line of an if sentence to the right) could not be compiled. An important part of this is Python’s indentation rules.
One difference from most other languages, such as C, is that the spacing of a module is determined entirely by the position of the first character on the line. (In C, the spacing of a module is clearly defined by a pair of curly braces {}, regardless of the position of the character.) This was controversial in the early years. Since the birth of a language like C, the grammatical meaning of a language is separated from the way the characters are placed, and in the early years, it was thought to be a kind of progress of procedural language. But there’s no denying that by forcing programmers to indent (including if, for, function definitions, all of which require modules), Python does make programs cleaner and prettier.
With the MATLAB
Speaking of scientific accounting, the first one to be mentioned is probably MATLAB. But in addition to some very professional MATLAB box can not be replaced, most of the common use of MATLAB can be found in the Python world of the corresponding extension library. Compared to MATLAB, using Python for scientific accounting has the following advantages:
● First, MATLAB is a commercial software, and expensive. Python is completely free, and many open source scientific accounting libraries provide Python’s calling interface. Users are able to install Python and most of its extension libraries free of charge on any computer.
● Second, Python is a much easier and more careful programming language to learn than MATLAB. It allows users to write code that is easier to read and secure.
● After all, MATLAB is primarily focused on engineering and scientific accounting. But even in the field of accounting, also often encountered file processing, interface planning, network communication and other requirements. Python, on the other hand, has a rich library of extensions that make it easy to end all kinds of high-grade tasks, and developers can use Python to end all kinds of functions that a program needs without any problems.
Planning and positioning
Python’s planning philosophy is “elegant,” “clear,” and “short.” As a result, the idea that there are always more than one way to do the same thing in the Perl language is generally intolerable to Python developers. The philosophy of Python developers is “one way, preferably only one way, to do something.” Given that there are many choices to be made when planning a Python language, Python developers tend to reject fancy grammars in favor of clear grammars with little or no ambiguity. Because of this difference in planning concepts, Python source code is generally considered to be more readable than Perl and to support large-scale software development. These principles are known as Python maxims. To get a complete list, do import this in the Python tool.
Python developers try to avoid optimizations that are immature and perhaps not important. Some fixes for non-critical parts to speed up operations are not generally incorporated into Python. So a lot of people think Python is slow. However, according to the rule of 28, most programs do not require high speed. In some cases where speed is a high priority, Python planners tend to apply JIT skills, perhaps rewriting parts of the program in C/C++. The available JIT skill is Pypy.
Python is thoroughly policy-oriented language. Functions, modules, numbers, and strings are all policies. And support inheritance, overloading, derivation, multiple inheritance, is beneficial to enhance the reuse of source code. Python supports overloaded operators and dynamic typing. Python provides only limited support for functional planning in relation to Lisp, a traditional functional programming language. Two libraries (Functools, Itertools) provide the tried-and-true functionality of functional programming in Haskell and Standard ML.
Although Python may be loosely classified as a “script language,” it is also widely used by Google in large planning software development projects such as Zope, Mnet, and BitTorrent. Python’s proponents prefer to call it a high-class dynamic programming language, because “scripting language” generally refers to languages that do only a brief programming mission. Shellscript, VBScript and other languages that do only a brief programming mission are not to be confused with Python.
Python itself is programmed to be extensible. Not all features and functions are integrated into the speech center. Python provides a rich set of APIs and things that make it easy for programmers to write extension modules using the C language, C++, and Cython. The Python compiler itself can also be integrated into other programs that require scripting languages. As a result, many people also use Python as a “glue language.” Use Python to integrate and encapsulate programs written in other languages. Many projects within Google, such as Google Engine, write highly functional parts in C++ and then call the corresponding modules in Python or Java/Go. Alex Martelli, author of the Python Skills Manual, says: “It’s hard to say, but in 2004, Python was already being used internally at Google, and Google had already decided to use Python before they recruited a lot of Python experts. The intent is Python where we can, C++ where we must, C++ for controlling hardware, and Python for rapid development.”
The implementation of
In the implementation of Python, the source code in the.py file is first compiled into Python’s byte code, and then the Python Virtual Machine (Python Virtual Machine) implements the compiled byte code. The fundamental thinking of this mechanism is common to Java and.NET. However, Python Virtual Machine is different from Java or. NET Virtual Machine is different from Python Virtual Machine is a more high-end Virtual Machine. This is not high-end in the general sense, not to say that Python’s Virtual Machine is better than Java or. NET is more robust than Java. NET, Python’s Virtual Machine is much farther apart than the Machine. It’s probably fair to say that Python’s Virtual Machine is a Virtual Machine with a higher level of abstraction. A bytecode file compiled from C Python, usually in a.pyc format. In addition, Python can also work in an interactive way, such as the mainstay operating systems UNIX /Linux, Mac, Windows can be directly under the command of the Python interactive environment. Direct instruction to end the interactive operation.
Roots syntax in
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One of Python’s planning policies is to make code highly readable. When it is planned, it tries to use punctuation marks and English words commonly used in other languages to make the code look neat and beautiful. It does not require repetition of declarative sentences like other static languages such as C and Pascal, nor does it often have special conditions and surprises like their syntax.
Python developers deliberately force programmers to develop good programming habits by making programs that violate the indent rules not compile. And the Python language uses indentation to indicate the initial and exit (off-side rules) of a sentence block, rather than using curly braces or certain keywords. Adding indentation indicates the beginning of a sentence block, while reducing indentation indicates the exit of a sentence block. Indentation becomes part of the syntax. For example, the if sentence: python3
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Age = int(” Please enter your age: “))
if age < 21:
Print (” You can’t buy wine.” )
Print (” But you can buy gum.” )
Print (” This sentence is outside the if sentence block.” )
According to the PEP, it is necessary to use four Spaces to indicate each level of indentation. Using Tab characters and other numeric intent Spaces will compile, but will not comply with the coding specification. The support for Tab characters and other numeric intent Spaces is just for compatibility with very old Python programs and some problematic correcting programs.
Control the sentence
If sentence, work sentence block when condition is established. Often used in conjunction with else, elif(equivalent to else if).
The for sentence iterates through list, string, dictionary, marshal, and so on, processing each element in the iterator in turn.
While sentence, which loops through the sentence block when the condition is true.
The try sentence, together with except,finally, operates as an anomaly in program operations.
Class sentence, used to define the type.
A def sentence, used to define methods for functions and types.
The pass sentence indicates that this action is empty and does not perform any operations.
Assert sentence used to test whether job conditions are met during the debug phase of a program.
With sentences, Python2.6 defines back syntax, working sentence blocks in a scene. For example, encrypt a sentence block before the job and decrypt it after the sentence block job exits.
The yield sentence, applied within an iterator function, returns an element. Not since Python 2.5. This sentence becomes an operator.
Raise the sentence, make an error.
The import sentence imports a module or package.
The from… An import sentence that imports a module from a package or a policy from a module.
The import… As sentence that assigns the imported policy to a variable.
In sentence that checks if a policy is in a string/list/tuple.
expression
Python’s expression writing is similar to C/C++. It’s just written differently in some ways.
The primary arithmetic operator is similar to C/C++. +, -,, /, //, *, ~, % indicate that addition may take positive, subtraction may take negative, multiplication, division, division, power, complement, and remainder, respectively.
Python uses AND, OR, AND NOT to indicate logical operations.
IS, IS NOT is used to compare whether two variables are the same policy. In, not in is used to determine whether a policy belongs to another policy.
Python supports list comprehensions, such as calculating the sum of squares from 0 to 9:
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sum(x * x for x in range(10))
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Python uses lambda to designate anonymous functions. An anonymous function body can only be an expression. For example:
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add=lambda x, y : x + y
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Python uses y if cond else x to indicate conditional expressions. If cond is true, the value of the expression is y; otherwise, the value of the expression is x. Cond in C++ and Java? Y: x.
There are two types of Python difference lists and tuples. A list is written as [1,2,3], and a tuple as (1,2,3). You can change the elements in the list, but not the tuple. In some cases, the parentheses of a tuple can be omitted. Tuple has special treatment for assignment sentences. Thus, it is possible to assign values to multiple variables together, such as:
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X =1, y=2 # Assign values to x and y together. After all, the effect is: x=1, y=2
In particular, you can use the following method to communicate the values of two variables:
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X, y=y, x # =1, x=2
Python uses ‘(single quotes) and “(double quotes) to indicate strings. Unlike Perl, UNIX Shell languages, or Ruby, Groovy, etc., both symbols have the same effect. In general, single quotes are used to indicate strings, assuming that double quotes are present; Otherwise, double quotation marks are used. Assuming neither is present, choose according to personal preference. The characters (backslashes) that appear in the string are interpreted as special characters, such as n to indicate a newline character. The prefix r to the expression indicates that Python does not clarify what is rendered in the string. This is often used to write regular expressions or Windows files.
Python supports list slices, which give you access to a portion of the intact list. Str, Bytes, List, Tuple, and so on. Its syntax is… [left: right] maybe… [left: right: stride]. If the nums variable is [1, 3, 5, 7, 8, 13, 20], then the following sentences are true:
Nums [2:5] == [5, 7, 8] cuts from index 2 to index 5, but does not include index 5.
Nums [1:] == [3, 5, 7, 8, 13, 20]
Nums [:-3] == [1, 3, 5, 7] Nums [:-3] == [1, 3, 5, 7] Nums [:-3] == [1, 3, 5, 7]
Nums [:] == [1, 3, 5, 7, 8, 13, 20] Nums [:] == [1, 3, 5, 7, 8, 13, 20] Changing the new list does not affect NUMS.
Nums [1:5:2] == [3, 7] cuts from index 1 to index 5 with a step of 2.
function
Python functions support recursion, tacit argument values, and mutable arguments, but do not support function overloading. To enhance the readability of the code, “Documentation Strings” (or docstrings for short) can be written after the function to clarify the effect of the function, the types and meanings of parameters, return value types, value planning, and so on. Use assistance that can print out functions using the built-in function help(). For example:
def randint(a, b):
. “Return random integer in range [a, b], including both end points.”…
help(randint)
Help on function randint in module __main__:
randint(a, b)
Return random integer inrange[a, b], including both end points.
Policy approach
A policy method is a function bound to a policy. The syntax for calling policy methods is instance.method(arguments). This is equivalent to calling Class.method(instance, arguments). When defining a policy method, it is necessary to explicitly specify the first parameter, which is usually named self, to access the internal data of the policy. Here self is equivalent to the this variable in C++ and Java, but we can also use any other valid parameter name, such as this and mine, etc. Self is not exactly the same as this in C++ and Java, and it can be seen as a more conventional use. We can pass in any other legitimate name, such as:
class Fish:
def eat(self,food):
if food is not None:
self.hungry=False
class User:
def __init__(myself,name):
myself.name=name
Examples of the structure Fish:
f=Fish()
The following two invocation methods are equivalent:
Fish.eat(f,”earthworm”)
f.eat(“earthworm”)
u=User(‘username’)
print(u.name)
Python knows a few special method names that begin with “__” and end with “__”. They are used to end [operator overloading] and various special functions.
type
Python uses the dynamic type system. At compile time, Python does not check to see if the policy has the characteristics of the method or method being called, but does not check until job time. So it’s possible to throw an anomaly when operating a policy. However, while Python uses the dynamic typing system, it is also strongly typed. Python prevents operations that are not explicitly defined, such as adding numbers to strings.
Like other policy-oriented languages, Python allows programmers to define types. Constructing a policy requires only the same call type as a function. For example, for the Fish type defined above, use Fish(). The type itself is also a policy of a particular type (the type itself is also a policy of the type), and this particular programming allows for reflective programming of the type.
Python has a rich built-in set of data types. Compared to Java and C++, these data types effectively reduce the length of the code. The following list is a brief description of Python’s built-in data types (for Python 3.x) :