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    Python & Anaconda

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    MANISH SIKHWAL
    Python is a high-level, general-purpose, interpreted, dynamic programming language. It has a simple syntax that is readable and reusable. As an interpreted language, Python executes instructions directly without compiling to machine code. It has a robust standard library that supports modularity and code reuse through modules and packages. Python can be used for a wide variety of applications including desktop programs, web development, science/engineering, and more. It supports various development environments like Jupyter notebooks, Spyder, and PyCharm to make coding in Python easier.

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    Python & Anaconda

    Uploaded by

    MANISH SIKHWAL
    32 views6 pages
    Python is a high-level, general-purpose, interpreted, dynamic programming language. It has a simple syntax that is readable and reusable. As an interpreted language, Python executes instructions directly without compiling to machine code. It has a robust standard library that supports modularity and code reuse through modules and packages. Python can be used for a wide variety of applications including desktop programs, web development, science/engineering, and more. It supports various development environments like Jupyter notebooks, Spyder, and PyCharm to make coding in Python easier.

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    Python is a great Language.

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    1. Python & Anaconda

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    Python is a high-level, general-purpose, interpreted, dynamic programming language. It has a simple syntax that is readable and reusable. As an interpreted language, Python executes instructions directly without compiling to machine code. It has a robust standard library that supports modularity and code reuse through modules and packages. Python can be used for a wide variety of applications including desktop programs, web development, science/engineering, and more. It supports various development environments like Jupyter notebooks, Spyder, and PyCharm to make coding in Python easier.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    32 views6 pages

    Python & Anaconda

    Uploaded by

    MANISH SIKHWAL
    Python is a high-level, general-purpose, interpreted, dynamic programming language. It has a simple syntax that is readable and reusable. As an interpreted language, Python executes instructions directly without compiling to machine code. It has a robust standard library that supports modularity and code reuse through modules and packages. Python can be used for a wide variety of applications including desktop programs, web development, science/engineering, and more. It supports various development environments like Jupyter notebooks, Spyder, and PyCharm to make coding in Python easier.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    of 6
    At a glance
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    Python is a general-purpose, high-level, interpreted, dynamic programming language that is simple, open source, and has a robust standard library.

    An interpreter executes programs line by line while a compiler translates the entire program into machine code. Interpreters are easier to debug while compilers are faster.

    Some common applications of Python include desktop applications, image/video/audio processing, games, scientific/computational applications, machine learning, web development, and working with internet protocols.

    What is Python?

    HIGH-LEVEL
    SCRIPTING

    GENERAL-PURPOSE

    INTERPRETED

    It is a general-purpose, high-level, interpreted, dynamic programming language.

    • Simple -> Simple syntax, readable and resuable


    • Open Source --> We can use python software without any license and its freeware.
    • General-Purpose -> designed to be used for writing software in the widest variety
    of
    application domains High-level -> designed to be more or less independent of a particular
    type of computer, human-readable friendly Interpreted -> designed to execute
    instructions of a program directly, without previously compiling a program into
    machine-language instructions Robust Standard Library -> Python supports modules
    and packages, which encourages program modularity and code reuse.

    But, what is the difference between an interpreter and


    a compiler?
    Interpreter
    Compiler

    Executes program by taking one


    statement at a time
    Translates the entire program at once into machine code

    Errors are reported after the entire


    program is checked
    Error is reported as soon as the first error is encountered. Won't
    show the next set of errors if the existing one isn't solved

    Easier to debug
    Difficult

    No intermediate object code is generated, hence memory efficient


    Generates intermediate object code which further requires linking,
    hence requires more memory

    Less amount of time to analyze the


    source code
    More amount of time

    Overall execution is slower


    Faster

    Python
    Applications
    • Desktop-based
    Applications
    • Image, Video, Audio Processing (using modules like OpenCV and PyAudio
    or librosa)
    • Graphic Design Applications (used to create Inkscape, GIMP,
    Blender, 3ds Max
    software
    s)
    • Games (PySoy -> 3D game engine, PyGame -> library for
    game development)

    • Scientific and Computational


    Applications
    • Machine Learning (Regression, Decision Tree, Random Forest, Deep Learning)
    using
    libraries such as NumPy, SciPy, TensorFlow, Keras,
    Py Torch

    • Web
    Development
    · Framework such as Django,
    Pyramid
    • Micro-Framework such as Flask,
    Bottle

    • Internet Protocol
    • HTML,
    XML
    •
    JSON
    •
    Request
    s
    •
    BeautifulSoup

    Various Ways to execute Python


    1. Writing a code in notepad and execute in command prompt 2.
    Python (command prompt) 3. Python IDLE 4. Run file
    in Python IDLE

    Above all are without IDE (Integrated Development Environment)

    Anaconda Python
    Distribution
    Anaconda is an open-source package manager, environment manager, and
    distribution of the Python and R programming languages. It is commonly used for
    large-scale data processing, scientific computing, and predictive analytics,
    serving data scientists, developers, business analysts.

    Anaconda offers a collection of over 720 open-source packages, and is available


    in both free and paid versions. The Anaconda distribution ships with the conda
    command-line utility. You can learn more about Anaconda and conda by reading the
    Anaconda Documentation pages.

    • Comes either in full-meal-deal version, with numpy, scipy, Jupyter Notebook,


    spyder IDE,
    etc., where you can install what you want, when you
    need it
    • No risk of messing up required system
    libraries

    With IDE (integrated Development


    Environment)
    1. Jupyter notebook 2.
    Spyder 3.
    Pycharm
    localhost:8888/notebooks/SRK Classes/00. Python Introduction/0.1 About Python%2C Installation of
    Anaconda %26 Jupyter notebook.ipynb#
    3/
    3

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