4 ответов
+ 8
The short answer is that if you’re a beginner, you should focus on Python 3. And if you’re an experienced programmer, unless you are inheriting a legacy software project, you should also use Python 3 for your future software projects.
🔷Python 2 vs Python 3: Which to Learn?⬇️
https://wsvincent.com/python2-vs-python3/
🔼Most major software packages now work on Python 3
🔼Django recommends using Python 3 and new versions no longer support Python 2
🔼Development on Python 2.7 itself will stop after 2020🤔
🔼The short answer is that if you’re a beginner, you should focus on Python 3.
⏩Now Python 3 has very big community support and gradually it increases rapidly, Python is so popular due to one of the reasons that it has very rich libraries which helps Programmer with less coding is needed due to a lot of ready coding supports are available in it's libraries and day by day it's also increasing heavily.
⏹So as a new learner it's always acceptable where changes and development are done with time to adjust with changes and market demands.
🔽On the other hand after 2010 no further progress is made on Python 2 and Libraries development are also stopped from 2016.
https://www.sololearn.com/discuss/1067691/?ref=app
⏸The short answer is that if you’re a beginner, you should focus on Python 3. And if you’re an experienced programmer, unless you are inheriting a legacy software project, you should also use Python 3 for your future software projects.
🔷Python 2 vs Python 3: Which to Learn?⬇️
https://wsvincent.com/python2-vs-python3/
+ 3
They are 2 version of Python.
Due to a lot of modifications in Python3, now they are working like two separate Programs.
Some options of Python2 doesn't support Python3 and same way some options of Python3 also doesn't support Python2.
Django framework is now support only Python3.
All these happens to make Python3 more dynamic, to make more supportive with modern technology.
🔼Most major software packages now work on Python 3
🔼Django recommends using Python 3 and new versions no longer support Python 2
🔼Development on Python 2.7 itself will stop after 2020🤔
🔼The short answer is that if you’re a beginner, you should focus on Python 3.
⏩Now Python 3 has very big community support and gradually it increases rapidly, Python is so popular due to one of the reasons that it has very rich libraries which helps Programmer with less coding is needed due to a lot of ready coding supports are available in it's libraries and day by day it's also increasing heavily.
⏹So as a new learner it's always acceptable where changes and development are done with time to adjust with changes and market demands.
🔽On the other hand after 2010 no further progress is made on Python 2 and Libraries development are also stopped from 2016.
https://www.sololearn.com/discuss/1067691/?ref=app
0
String: single or double quote
Though both are permitted in Python, but it's more wise to use " " , because it supports to use apostrophe ( ' ) with a word.For example -print("John\'s book") >>> John's book
If you want to use the same kind of quotes inside your string, you have to escape them (put a \ before them). Otherwise, the extra quotes will end your string too early. Ex:
print('Printing "double-quotes" and \'single-quotes\' '')
#Output: Printing "double-quotes" and 'single-quotes'
0
The biggest difference between the two languages is that Java is a statically typed and Python is a dynamically typed.
Python is strongly but dynamically typed. This means names in code are bound to strongly typed objects at runtime. The only condition on the type of object a name refers to is that it supports the operations required for the particular object instances in the program. For example, I might have two types Person and Car that both support operation "run", but Car also supports "refuel". So long as my program only calls "run" on objects, it doesn't matter if they are Person or Car. This is called "duck typing" after the expression "if it walks like a duck and talks like a duck, it's a duck".
This makes Python very easy to write and not too bad to read, but difficult to analyze. Static type inference in Python is a known hard problem. The lack of type information in function signatures combined with support for operator overloading and just-in-time loading of modules at runtime means that the most common type inference algorithms have nothing to work with until the point in the program's execution when the types are known anyway. The Hindley-Milner algorithm that is commonly used in functional languages like Haskell and ML depends on being able to know, for example, that certain operations are restricted to particular types. These languages also typically have function signatures that "seed" the algorithm with the type information for their arguments
https://www.activestate.com/blog/2016/01/python-vs-java-duck-typing-parsing-whitespace-and-other-cool-differences