equilateral, the rectangle is a square, and so on.Obviously, if an object is made up of many components, we cannot hard code in the construction method to meet the requirements of the various users on the structure of the component. Therefore, in the abstract-oriented principle, we should not do any coding in the Geometry class construction method, but instead divide the construction method of the geometry class object into several steps, that is to define several methods in one port according
· Python · use a generator and iterator to implement your own xrange Disclaimer: This article is published by love butterfly at http://blog.csdn.net/lanphaday. all rights are available. Welcome to download this article. The statement should be reprinted. Thank you.
Those who have used Python must be familiar with the following two lines:
Code : >>> For I in xrange (0, 10, 1 ):
Print I The above two lines of code print the 10 numbers 0-9 in a loop.
Parse the generator in Python and its differences with the iterator.
GeneratorA generator is an iterator and a special function. It is constructed into an iterator using the yield operation. A common function has an entry and a return value. When a function is called, it is executed from the entry and the return value is returned at the end. The function defined by the
What is a generator?A generator is a function that contains the special keyword yield. When called, the generator function returns a generator. You can use the send, throw, and close methods to allow the generator to interact with the outside world.
The
Python learning diary: day13 ------ iterator and generator, pythonday13 ------I. Import 1. the dir function print (dir ([]) tells me that all the methods in this list contain double underscores. 2. The returned value after a list executes _ iter _ () is an iterator 3, the number of _ length_hint _ elements 4, and the value of _ setstate _ from the specified position is 5, []. _ iter _ () iterator ----> _ next _ you can use next to get values from the
()) # Print (i.__next__ ()) # Print (i.__next__ ()) # Print (i.__next__ ()) #StopIteration Iterator determines whether an iterator object iterabl is required to iterate over the object as an iterative object. __iter__ () is converted to an iterator to iterate over an iterator object that can iterate the iterator directly to the application: 1 provides a unified iterative Method 2 lazy computation that does not depend on the index, For example, to fetch each line of a fileIv.
, 8, 12]]This in turn writes the same as follows:transposed = []for i in Range (4): transposed_row = [] for row in matrix: transposed_row.append (Row[i]) Transposed.append (transposed_row) Print transposed# [[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]There is also a python built-in function zip (), also can be implemented as above functionZip (*matrix) # [(1, 5, 9), (2, 6, 10), (3, 7, 11), (4, 8, 12)]2.del statement (The DEL statement)>>> a = [-1, 1, 66.25, 333, 333, 1234.5]>>
exactly the same:>>> for N in Fab (5): ... Print N ... 1 1 2) 3 5 Simply put, the function of yield is to turn a function into a generator, the function with yield is no longer a normal function, the Python interpreter treats it as a generator, and the Call to FAB (5) does not execute the FAB function, but instead returns a Iterab Le Object! When the For loop executes, each loop executes the code
) return Ncalc (8)
The result is:
84.02.0n:2.0res:2.0n:4.0res:4.0n:8
Second, generator
The generator is a function with a yield statement. A function or subroutine is returned only once, but a generator can pause execution and return an intermediate result, returning a value to the caller and pausing execution. When the next () method of the
The running process of next and send in the Python generator (detailed description) and pythongenerator
For a normal generator, the first next call is equivalent to starting the generator. It starts to execute the first line of code of the generator function until the first execution of the yield statement (row 4th) is
eliminates the need to create a complete list, which saves a lot of space. In Python, this side loop computes the mechanism, called the Generator (Generator).To create a generator, there are a number of ways, the first method is simple, as long as a list-generated [] is changed to (), a generator is created: for inch
In fact, it should have been released early. I am probably the first batch of people to sort out Google's skills in China. Later, sniper wrote Google hack, which made it even lazy. Now I am helping my wife find a paper, and the keyword matching is so tired. These skills are after I sort them out. If you are interested, you can ask for them directly.
Http: // www.feelids.com
By swap
The intra-site search address is:
Http://www.google.com/custom? Do
Based on the revision and source code analysis of mybatis-generator-core 1.3.5, mybatisgeneratorcoreProject Description
Mybatis-generator is used to generate code files such as entity classes based on database tables and fields. During the National Day, I analyzed the mybatis-generator-core source code and wrote quite detailed Chinese comments. Let's take a look.
first, the new test projectCreate a new MAVEN project MybatisDemo2, modify Pom.xml to introduce dependencies. Dependencies added on the previous sectionDependency> groupId>Org.mybatis.generatorgroupId> Artifactid>Mybatis-generator-coreArtifactid> version>1.3.2version>Dependency>Build Add PluginBuild> Plugins> plugin> groupId>Org.mybatis.generatorgroupId> Artifactid>Mybatis-
Python [5]-generative, generator, and python generativeI. Condition and loop 1. if statement
If
For example:
age=5if age>=18: print 'adult'elif age>=6: print 'teenager'else: print 'kid'
Be sure to pay attention to the colon at the end of the Condition Statement and the indentation of the code segment.
As long as the if parameter is a non-zero value, non-empty string, non-empty list, etc., it is determinedTrueOtherwiseFalse.2. Loop
Range (num): Re
Tornado 4.0 has been released for a long time, and the new version has widely applied the Future feature. We have now upgraded the Tornado to the latest version, and have also used a lot of the coprocessor features.
A long time no update blog, today is a simple introduction to the implementation of the Tornado, the Tornado is based on the Python generator implementation, so first of all to review the generator
__next__() methodsNote: For an iterator object, the __iter__ method is executed, and the result is still itself
5. Advantages and disadvantages of iterators
Advantages:1. Provides an iterative approach that does not rely on subscript2. More memory savings on the drop iterator itselfDisadvantages:1. Unable to get the length of the iterator object2. The value of the sequence type is flexible, is a one-time, can only be taken back to the value, not forwardSecond,
http://www.cnblogs.com/qixiaoyizhan/p/7597315.html "Preface"Using Mybatis-generator to automatically generate DAO, Model, mapping related files, the role of Mybatis-generator is to act as a code generator, and using code generators not only simplifies our workload, Productivity is improved, and the probability of code errors can be greatly reduced. In the SSM (Sp
: ret.append (expr)Example: for inch if and i%3==for ifif i%3==0]the use of a list-resolved multilayer loop:A list of analytic expressions:[Expr for I in Iterable1 for J in Iterable2]Natural notation:ret = [] for in iterable1: for in iterable2: Ret.append (expr)Example[(x, Y) forXinch 'ABCDE' forYinchRange (3)][[x, y] forXinch 'ABCDE' forYinchRange (3)][{x:y} forXinch 'ABCDE' forYinchRange (3)]Generator e
1. Generator functionsThe difference between a generator function and a normal function is that1. Use yield instead of return in the generator function, and yield can be called multiple times2. When the function runs to yield, the yield current state is preserved, waiting for the next nextUsage examples: def Test (): yield 1 yield 2 yield 3a=test () b=
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