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What is Python? Powerful,
intuitive programming
http://www.asterixsolution.com/python-training-in-mumbai.html
• Python is easy to learn and use
The number of features in the language itself is modest, requiring
relatively little investment of time or effort to produce your first
programs. The Python syntax is designed to be readable and
straightforward. This simplicity makes Python an ideal teaching
language, and it lets newcomers pick it up quickly. As a result,
developers spend more time thinking about the problem they’re trying
to solve and less time thinking about language complexities or
deciphering code left by others.
• Python is broadly adopted and supported
Python is both popular and widely used, as the high rankings in surveys
like the Tiobe Index and the large number of GitHub projects using
Python attest. Python runs on every major operating system and
platform, and most minor ones too. Many major libraries and API-
powered services have Python bindings or wrappers, letting Python
interface freely with those services or directly use those libraries.
• Python is not a “toy” language
Even though scripting and automation cover a large chunk of Python’s use
cases (more on that later), Python is also used to build professional-
quality software, both as standalone applications and as web services.
Python may not be the fastest language, but what it lacks in speed, it
makes up for in versatility.
• Python keeps moving forward
Each revision of the Python language adds useful new features to keep
pace with modern software development practices. Asynchronous
operations and coroutines, for instance, are now standard parts of the
language, making it easier to write Python apps that perform concurrent
processing.
• What Python is used for
The most basic use case for Python is as a scripting and automation
language. Python isn’t just a replacement for shell scripts or batch files;
it is also used to automate interactions with web browsers or
application GUIs or to do system provisioning and configuration in tools
such as Ansible and Salt. But scripting and automation represent only
the tip of the iceberg with Python.
• General application programming with Python
You can create both command-line and cross-platform GUI applications
with Python and deploy them as self-contained executables. Python
doesn’t have the native ability to generate a standalone binary from a
script, but third-party packages like cx_Freeze and PyInstaller can be
used to accomplish that.
• Data science and machine learning with Python
Sophisticated data analysis has become one of fastest-moving areas of
IT and one of Python’s star use cases. The vast majority of the libraries
used for data science or machine learning have Python interfaces,
making the language the most popular high-level command interface to
for machine learning libraries and other numerical algorithms.
• Web services and RESTful APIs in Python
Python’s native libraries and third-party web frameworks provide fast and
convenient ways to create everything from simple REST APIs in a few lines of
code to full-blown, data-driven sites. Python’s latest versions have strong
support for asynchronous operations, letting sites handle tens of thousands
of requests per second with the right libraries.
• Metaprogramming and code generation in Python
In Python, everything in the language is an object, including Python modules
and libraries themselves. This lets Python work as a highly efficient code
generator, making it possible to write applications that manipulate their own
functions and have the kind of extensibility that would be difficult or
impossible to pull off in other languages.
• “Glue code” in Python
• Python is often described as a “glue language,” meaning it can let disparate code (typically libraries with
C language interfaces) interoperate. Its use in data science and machine learning is in this vein, but that’s
just one incarnation of the general idea. If you have applications or program domains that you would like
to hitch up, but cannot talk to each other directly, you can use Python to connect them.
• Where Python falls short
• Also worth noting are the sorts of tasks Python is not well-suited for.
• Python is a high-level language, so it’s not suitable for system-level programming—device drivers or OS
kernels are out of the picture.
• It’s also not ideal for situations that call for cross-platform standalone binaries. You could build a
standalone Python app for Windows, MacOS, and Linux, but not elegantly or simply.
• Finally, Python is not the best choice when speed is an absolute priority in every aspect of the
application. For that, you’re better off with C/C++ or another language of that caliber.
• How Python makes programming simple
• Python’s syntax is meant to be readable and clean, with little pretense. A standard “hello
world” in Python 3.x is nothing more than:
• print(“Hello world!”)
• Python provides many syntactical elements to concisely express many common program
flows. Consider a sample program for reading lines from a text file into a list object, stripping
each line of its terminating newline character along the way:
• with open(‘myfile.txt’) as my_file:
• file_lines = [x.rstrip(‘n’) for x in my_file]
• The with/as construction is a context manager, which provides an efficient way to instantiate
an object for a block of code and then dispose of it outside that block. In this case, the object
is my_file, instantiated with the open() function. This takes the place of several lines of
boilerplate to open the file, read individual lines from it, then close it up.
• The [x … for x in my_file] construction is another Python idiosyncrasy, the
list comprehension. It lets an item that contains other items (here, my_file
and the lines it contains) be iterated through, and it lets each iterated
element (that is, each x) be processed and automatically appended to a list.
• You could write such a thing as a formal for… loop in Python, much as you
would in another language. The point is that Python has a way to
economically express things like loops that iterate over multiple objects
and perform a simple operation on each element in the loop, or to work
with things that require explicit instantiation and disposal.
• Constructions like this let Python developers balance terseness and
readability.
• Python’s libraries
• The success of Python rests on a rich ecosystem of first- and third-party software.
Python benefits from both a strong standard library and a generous assortment
of easily obtained and readily used libraries from third-party developers. Python
has been enriched by decades of expansion and contribution.
• Python’s standard library provides modules for common programming tasks—
math, string handling, file and directory access, networking, asynchronous
operations, threading, multiprocess management, and so on. But it also includes
modules that manage common, high-level programming tasks needed by modern
applications: reading and writing structured file formats like JSON and XML,
manipulating compressed files, working with internet protocols and data formats
(webpages, URLs, email). Most any external code that exposes a C-compatible
foreign function interface can be accessed with Python’s ctypes module.
• Python 2 vs. Python 3
• Python is available in two versions, which are different enough to trip up many new
users. Python 2.x, the older “legacy” branch, will continue to be supported (that is,
receive official updates) through 2020, and it might persist unofficially after that. Python
3.x, the current and future incarnation of the language, has many useful and important
features not found in Python 2.x, such as new syntax features (e.g., the “walrus
operator”), better concurrency controls, and a more efficient interpreter.
• Python 3 adoption was slowed for the longest time by the relative lack of third-party
library support. Many Python libraries supported only Python 2, making it difficult to
switch. But over the last couple of years, the number of libraries supporting only Python
2 has dwindled; all of the most popular libraries are now compatible with both Python 2
and Python 3. Today, Python 3 is the best choice for new projects; there is no reason to
pick Python 2 unless you have no choice. If you are stuck with Python 2, you have various
strategies at your disposal.
• Python’s compromises
• Like C#, Java, and Go, Python has garbage-collected memory management,
meaning the programmer doesn’t have to implement code to track and release
objects. Normally, garbage collection happens automatically in the background,
but if that poses a performance problem, you can trigger it manually or disable it
entirely, or declare whole regions of objects exempt from garbage collection as a
performance enhancement.
• An important aspect of Python is its dynamism. Everything in the language,
including functions and modules themselves, are handled as objects. This comes
at the expense of speed (more on that later), but makes it far easier to write high-
level code. Developers can perform complex object manipulations with only a few
instructions, and even treat parts of an application as abstractions that can be
altered if needed.

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What is python

  • 1. What is Python? Powerful, intuitive programming http://www.asterixsolution.com/python-training-in-mumbai.html
  • 2. • Python is easy to learn and use The number of features in the language itself is modest, requiring relatively little investment of time or effort to produce your first programs. The Python syntax is designed to be readable and straightforward. This simplicity makes Python an ideal teaching language, and it lets newcomers pick it up quickly. As a result, developers spend more time thinking about the problem they’re trying to solve and less time thinking about language complexities or deciphering code left by others.
  • 3. • Python is broadly adopted and supported Python is both popular and widely used, as the high rankings in surveys like the Tiobe Index and the large number of GitHub projects using Python attest. Python runs on every major operating system and platform, and most minor ones too. Many major libraries and API- powered services have Python bindings or wrappers, letting Python interface freely with those services or directly use those libraries.
  • 4. • Python is not a “toy” language Even though scripting and automation cover a large chunk of Python’s use cases (more on that later), Python is also used to build professional- quality software, both as standalone applications and as web services. Python may not be the fastest language, but what it lacks in speed, it makes up for in versatility. • Python keeps moving forward Each revision of the Python language adds useful new features to keep pace with modern software development practices. Asynchronous operations and coroutines, for instance, are now standard parts of the language, making it easier to write Python apps that perform concurrent processing.
  • 5. • What Python is used for The most basic use case for Python is as a scripting and automation language. Python isn’t just a replacement for shell scripts or batch files; it is also used to automate interactions with web browsers or application GUIs or to do system provisioning and configuration in tools such as Ansible and Salt. But scripting and automation represent only the tip of the iceberg with Python.
  • 6. • General application programming with Python You can create both command-line and cross-platform GUI applications with Python and deploy them as self-contained executables. Python doesn’t have the native ability to generate a standalone binary from a script, but third-party packages like cx_Freeze and PyInstaller can be used to accomplish that.
  • 7. • Data science and machine learning with Python Sophisticated data analysis has become one of fastest-moving areas of IT and one of Python’s star use cases. The vast majority of the libraries used for data science or machine learning have Python interfaces, making the language the most popular high-level command interface to for machine learning libraries and other numerical algorithms.
  • 8. • Web services and RESTful APIs in Python Python’s native libraries and third-party web frameworks provide fast and convenient ways to create everything from simple REST APIs in a few lines of code to full-blown, data-driven sites. Python’s latest versions have strong support for asynchronous operations, letting sites handle tens of thousands of requests per second with the right libraries. • Metaprogramming and code generation in Python In Python, everything in the language is an object, including Python modules and libraries themselves. This lets Python work as a highly efficient code generator, making it possible to write applications that manipulate their own functions and have the kind of extensibility that would be difficult or impossible to pull off in other languages.
  • 9. • “Glue code” in Python • Python is often described as a “glue language,” meaning it can let disparate code (typically libraries with C language interfaces) interoperate. Its use in data science and machine learning is in this vein, but that’s just one incarnation of the general idea. If you have applications or program domains that you would like to hitch up, but cannot talk to each other directly, you can use Python to connect them. • Where Python falls short • Also worth noting are the sorts of tasks Python is not well-suited for. • Python is a high-level language, so it’s not suitable for system-level programming—device drivers or OS kernels are out of the picture. • It’s also not ideal for situations that call for cross-platform standalone binaries. You could build a standalone Python app for Windows, MacOS, and Linux, but not elegantly or simply. • Finally, Python is not the best choice when speed is an absolute priority in every aspect of the application. For that, you’re better off with C/C++ or another language of that caliber.
  • 10. • How Python makes programming simple • Python’s syntax is meant to be readable and clean, with little pretense. A standard “hello world” in Python 3.x is nothing more than: • print(“Hello world!”) • Python provides many syntactical elements to concisely express many common program flows. Consider a sample program for reading lines from a text file into a list object, stripping each line of its terminating newline character along the way: • with open(‘myfile.txt’) as my_file: • file_lines = [x.rstrip(‘n’) for x in my_file] • The with/as construction is a context manager, which provides an efficient way to instantiate an object for a block of code and then dispose of it outside that block. In this case, the object is my_file, instantiated with the open() function. This takes the place of several lines of boilerplate to open the file, read individual lines from it, then close it up.
  • 11. • The [x … for x in my_file] construction is another Python idiosyncrasy, the list comprehension. It lets an item that contains other items (here, my_file and the lines it contains) be iterated through, and it lets each iterated element (that is, each x) be processed and automatically appended to a list. • You could write such a thing as a formal for… loop in Python, much as you would in another language. The point is that Python has a way to economically express things like loops that iterate over multiple objects and perform a simple operation on each element in the loop, or to work with things that require explicit instantiation and disposal. • Constructions like this let Python developers balance terseness and readability.
  • 12. • Python’s libraries • The success of Python rests on a rich ecosystem of first- and third-party software. Python benefits from both a strong standard library and a generous assortment of easily obtained and readily used libraries from third-party developers. Python has been enriched by decades of expansion and contribution. • Python’s standard library provides modules for common programming tasks— math, string handling, file and directory access, networking, asynchronous operations, threading, multiprocess management, and so on. But it also includes modules that manage common, high-level programming tasks needed by modern applications: reading and writing structured file formats like JSON and XML, manipulating compressed files, working with internet protocols and data formats (webpages, URLs, email). Most any external code that exposes a C-compatible foreign function interface can be accessed with Python’s ctypes module.
  • 13. • Python 2 vs. Python 3 • Python is available in two versions, which are different enough to trip up many new users. Python 2.x, the older “legacy” branch, will continue to be supported (that is, receive official updates) through 2020, and it might persist unofficially after that. Python 3.x, the current and future incarnation of the language, has many useful and important features not found in Python 2.x, such as new syntax features (e.g., the “walrus operator”), better concurrency controls, and a more efficient interpreter. • Python 3 adoption was slowed for the longest time by the relative lack of third-party library support. Many Python libraries supported only Python 2, making it difficult to switch. But over the last couple of years, the number of libraries supporting only Python 2 has dwindled; all of the most popular libraries are now compatible with both Python 2 and Python 3. Today, Python 3 is the best choice for new projects; there is no reason to pick Python 2 unless you have no choice. If you are stuck with Python 2, you have various strategies at your disposal.
  • 14. • Python’s compromises • Like C#, Java, and Go, Python has garbage-collected memory management, meaning the programmer doesn’t have to implement code to track and release objects. Normally, garbage collection happens automatically in the background, but if that poses a performance problem, you can trigger it manually or disable it entirely, or declare whole regions of objects exempt from garbage collection as a performance enhancement. • An important aspect of Python is its dynamism. Everything in the language, including functions and modules themselves, are handled as objects. This comes at the expense of speed (more on that later), but makes it far easier to write high- level code. Developers can perform complex object manipulations with only a few instructions, and even treat parts of an application as abstractions that can be altered if needed.