()) # 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
Generator
Iterators
Built-in functions
Homework
First, generator1.1. List GeneratorProblem Introduction: See List [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], I ask you to add 1 to each value in the tableProgramme one:A = [1,3,4,6,7,7,8,9,11]for index,i in Enumerate (a): A[index] +=1print (a) original value modifiedScenario Two:>>> a[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]>>> a = map (lambda x:x+1, a) >>> AScenario Three: List Builder>>> a = [i+1 for i
The generator is a very cool feature in python.2.2 becomes a part of the standard. In many cases, it allows you to simplify operations related to unbounded (infinite) sequences in an elegant and lower memory consumption mode.
A generator is a special function that can be used as an iterator. Its function implementation relies on the keyword yield. The following is a simple demonstration of how it operates:>
Introduced1, generator expressions (generator expression) are also called generator derivation or generator parsing, and the usage is very similar to the list derivation, in the form generator deduction using parentheses (parentheses) as the delimiter, Instead of the squar
In understanding the data structure of Python, the container (container), the Iteration object (iterable), the iterator (iterator), the generator (generator), the list/collection/dictionary derivation (list,set,dict Comprehension) Many concepts are mixed together, it is inevitable for beginners to confused, I will use an article to try to put these concepts and their relationship between the clear.Container
= "Nicholas Zhao Si"
print ("Hip-hop dance" if name == "Nicholas Zhao Si" else "Can't hip-hop dance") One yuan: "Hip-hop dance" Binary: Judgment by if statement Ternary: "No hip-hop dance"
Output results:
Hip-hop
In fact, it is well understood that the if front can be understood as the return result that evaluates to true, else is the return result that evaluates to False, this is the ternary operation.
Ternary operations can also be used in conjunction with list generation,
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=
List Builder is a very simple but very powerful built-in python.Generate a list [1,2,3,4] can use list (range (1,5))Application of List BuilderIf the above formula is judged, you can filter out the desired result, such as just the square of the even numberUsing multi-layer loopsGeneratorThe essential difference between a generator and a list generator is that one has generated data, and when used, it genera
Js-generator Foundation (Fourth week)Read a few hours generator related articles, found that there are too many things, this week want to give up writing this, transliteration other aspects of the last time with this trick, but did not find other writable, and finally decided to write a fairly basic generatorWhat is generator?
List-generated--A list can be generated quickly , and another listcan be deduced from a list , and the code is simple:>>> [x * x for x in range (1, 11)][1, 4, 9, 16, 25, 36, 49, 64, 81, 100]>>> [x * x for x in range (1, one) if x% 2 = = 0][4, 16, 36, 64, 100]>>> [m + N for M in ' ABC ' for n in ' XYZ '][' AX ', ' AY ', ' AZ ', ' BX ', ' by ', ' BZ ', ' CX ', ' CY ', ' CZ ']Generator (Generator)--wit
1. Understanding GeneratorsUsing iterators, we can generate the data in each iteration (through the next () method) and follow a specific pattern. But when we implement an iterator, we need to record the current iteration to the state we want to generate the next data based on the current state. To achieve a record of the current state and iterate with the next () function, we can use a simpler syntax, the generator (
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