All Projects → milaan9 → 05_Python_Files

milaan9 / 05_Python_Files

Licence: MIT License
Python too supports file handling and allows users to handle files i.e., to read and write files, along with many other file handling options, to operate on files. The concept of file handling has stretched over various other languages, but the implementation is either complicated or lengthy, but like other concepts of Python, this concept here …

Programming Languages

Jupyter Notebook
11667 projects
python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to 05 Python Files

07 Python Advanced Topics
You'll learn about Iterators, Generators, Closure, Decorators, Property, and RegEx in detail with examples.
Stars: ✭ 232 (+42.33%)
Mutual labels:  python-tutorials, ipython-notebook, python4beginner, python-tutorial-notebook, python-tutor, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
11 Python Matplotlib Module
Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. It was introduced by John Hunter in the year 2002. One of the greatest benefits of visualization is that it allows us visual access to …
Stars: ✭ 206 (+26.38%)
Mutual labels:  python-tutorials, ipython-notebook, python4beginner, python-tutorial-notebook, python-tutor, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
91 Python Mini Projects
No description or website provided.
Stars: ✭ 212 (+30.06%)
Mutual labels:  python-tutorials, python4beginner, python-tutorial-notebook, python-tutor, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
01 Python Introduction
Learn the basics of Python. These tutorials are for Python beginners. so even if you have no prior knowledge of Python, you won’t face any difficulty understanding these tutorials.
Stars: ✭ 229 (+40.49%)
Mutual labels:  python-tutorials, python4beginner, python-tutorial-notebook, python-tutor, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
03 Python Flow Control
Flow control is the order in which statements or blocks of code are executed at runtime based on a condition. Learn Conditional statements, Iterative statements, and Transfer statements
Stars: ✭ 207 (+26.99%)
Mutual labels:  python-tutorials, ipython-notebook, python4beginner, python-tutorial-notebook, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
90 Python Examples
The best way to learn Python is by practicing examples. The repository contains examples of basic concepts of Python. You are advised to take the references from these examples and try them on your own.
Stars: ✭ 190 (+16.56%)
Mutual labels:  python4beginner, python-tutorial-notebook, python-tutor, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
04 Python Functions
The function is a block of code defined with a name. We use functions whenever we need to perform the same task multiple times without writing the same code again. It can take arguments and returns the value.
Stars: ✭ 204 (+25.15%)
Mutual labels:  python4beginner, python-tutorial-notebook, python-tutor, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
milaan9
No description or website provided.
Stars: ✭ 190 (+16.56%)
Mutual labels:  python4beginner, python-tutorial-notebook, python-tutor, python4everybody, python4datascience, tutor-milaan9
02 Python Datatypes
Data types specify the different sizes and values that can be stored in the variable. For example, Python stores numbers, strings, and a list of values using different data types. Learn different types of Python data types along with their respective in-built functions and methods.
Stars: ✭ 192 (+17.79%)
Mutual labels:  python-tutorials, python-tutorial-notebook, python4everybody, python-tutorial-github, python4datascience, tutor-milaan9
Python Computer Vision from Scratch
This repository explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply…
Stars: ✭ 219 (+34.36%)
Mutual labels:  ipython-notebook, python4everybody, python4datascience, tutor-milaan9
93 Python Data Analytics Projects
This repository contains all the data analytics projects that I've worked on in python.
Stars: ✭ 208 (+27.61%)
Mutual labels:  ipython-notebook, python4everybody, python4datascience, tutor-milaan9
bugsnag-java
Bugsnag error reporting for Java.
Stars: ✭ 51 (-68.71%)
Mutual labels:  exceptions, exception-handling
React-Jupyter-Viewer
A react component to embed .ipyb notebooks in a blog or something
Stars: ✭ 50 (-69.33%)
Mutual labels:  ipython, ipython-notebook
Coderr.Client
Core client library for Coderr
Stars: ✭ 23 (-85.89%)
Mutual labels:  exceptions, exception-handling
rk
The remote Jupyter kernel/kernels administration utility
Stars: ✭ 53 (-67.48%)
Mutual labels:  ipython, ipython-notebook
nbmerge
A tool to merge / concatenate Jupyter (IPython) notebooks
Stars: ✭ 75 (-53.99%)
Mutual labels:  ipython, ipython-notebook
stack-trace-art
Turning programming exceptions into art
Stars: ✭ 39 (-76.07%)
Mutual labels:  exceptions, exception-handling
Sqlcell
SQLCell is a magic function for the Jupyter Notebook that executes raw, parallel, parameterized SQL queries with the ability to accept Python values as parameters and assign output data to Python variables while concurrently running Python code. And *much* more.
Stars: ✭ 145 (-11.04%)
Mutual labels:  ipython, ipython-notebook
Ipywebrtc
WebRTC for Jupyter notebook/lab
Stars: ✭ 171 (+4.91%)
Mutual labels:  ipython, ipython-notebook
DuckOS
Such OS; Very Duck!
Stars: ✭ 16 (-90.18%)
Mutual labels:  exceptions, exception-handling

Last Commit Last Commit Stars Badge Forks Badge Size Pull Requests Badge Issues Badge Language MIT License

binder colab

05_Python_Files

Introduction 👋

Python file I/O (a.k.a File handling) is one of the essential topics for programmers and automation testers. It is required to work with files for either writing to a file or read data from it.

Also, if you are not already aware, I/O operations are the costliest operations where a program can stumble. Hence, you should be quite careful while implementing file handling for reporting or any other purpose. Optimizing a single file operation can help you produce a high-performing application or a robust solution for automated software testing.

In Python, file processing takes place in the following order.

  • Open a file that returns a filehandle.
  • Use the handle to perform read or write action.
  • Close the filehandle.

Before you do a read or write operation to a file in Python, you need to open it first. And as the read/write transaction completes, you should close it to free the resources tied with the file.


Table of contents 📋

No. Name
01 Python_File_Input_Output
02 Python_File_Directory
03 Python_File_Exception
04 Python_Exceptions_Handling
05 Python_User_defined_Exceptions

These are online read-only versions. However you can Run ▶ all the codes online by clicking here ➞ binder


Frequently asked questions

How can I thank you for writing and sharing this tutorial? 🌷

You can Star Badge and Fork Badge Starring and Forking is free for you, but it tells me and other people that it was helpful and you like this tutorial.

Go here if you aren't here already and click ➞ ✰ Star and ⵖ Fork button in the top right corner. You'll be asked to create a GitHub account if you don't already have one.


How can I read this tutorial without an Internet connection? GIF

  1. Go here and click the big green ➞ Code button in the top right of the page, then click ➞ Download ZIP.

    Download ZIP

  2. Extract the ZIP and open it. Unfortunately I don't have any more specific instructions because how exactly this is done depends on which operating system you run.

  3. Launch ipython notebook from the folder which contains the notebooks. Open each one of them

    Kernel > Restart & Clear Output

This will clear all the outputs and now you can understand each statement and learn interactively.

If you have git and you know how to use it, you can also clone the repository instead of downloading a zip and extracting it. An advantage with doing it this way is that you don't need to download the whole tutorial again to get the latest version of it, all you need to do is to pull with git and run ipython notebook again.


Authors ✍️

I'm Dr. Milaan Parmar and I have written this tutorial. If you think you can add/correct/edit and enhance this tutorial you are most welcome🙏

See github's contributors page for details.

If you have trouble with this tutorial please tell me about it by Create an issue on GitHub. and I'll make this tutorial better. This is probably the best choice if you had trouble following the tutorial, and something in it should be explained better. You will be asked to create a GitHub account if you don't already have one.

If you like this tutorial, please give it a star.


Licence 📜

You may use this tutorial freely at your own risk. See LICENSE.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].