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Top 10 Python IDEs and Code Editors

Over the years, Python language has evolved enormously with the contribution of developers. Python is one of the most popular programming languages. It was designed primarily for server-side web development, software development, evaluation, scripting and artificial intelligence. For this feature Python encloses certain code editors and IDEs that are used for software development say, Python itself. If you are new to programming, learning Python is highly recommended as it is fast, efficient and easy to learn. Python interpreters are available on various operating systems such as Windows, Linux, Mac OS. This article provides a look into code editors and IDEs along with their features, pros and cons and talks about which are the best suited for writing Python codes. But first let us see what are code editors and IDEs. What is a Code Editor? A code editor is built for editing and modifying source code. A standalone text editor is used for writing and editing computer programs. Excellent ones can execute code as well as control a debugger as well as interact with source control systems. Compared to an IDE, a good dedicated code editor is usually smaller and quicker, but is less functional. Typically they are optimized for programming languages. One major feature of a text editor is that they are designed to modify various files and work with whatever language or framework you choose. What is IDE? IDE (Integrated Development Environment) understands the code significantly better than a text editor. It is a program exclusively built for software development. It is designed with a set of tools that all work together:  Text editor  Compiler Build automation Debugging Libraries, and many more to speed up the work.  These tools integrate: An editor designed to frame codes with text formatting, auto-completionetc., build, execution, debugging tools, file management and source and version control. It reduces manual efforts and combines all the equipment in a typical framework. IDE comes with heavy files. Hence, the downloads and installation is quite tedious. IDE requires expertise along with a lot of patience.  How does an IDE and Code editor differ from each other? An IDE is distinctive from code editors in the following ways: Integrated build process:The user does not have to write his own scripts to build apps in an IDE.  File management: IDE has an integrated file management system and deployment tool. It provides support to other framework as well. On the other hand, a Text editor is a simple editor where source code can be edited and it has no other formatting or compiling options. Development Environment: An IDE is mainly used for development purposes as it provides comparatively better features than a text editor. It allows you to write, compile and debug the entire script.  Syntax Highlighting:The editor displays the text message and puts the source code in different colours to improve its readability. Even error messages are displayed in different colours so that the user understands where he has written the wrong code.  Auto completion:It identifies and inserts a common code for the user instantly. This feature acts as an assistance for the programmer. The code suggestion automatically gets displayed.  Debugger: This tool helps the programmer to test and debug the source code of the main program.  Although IDEs have far better features than a Text editor one major significance of Text editor is that it allows modifying all types of files rather than specifying any definite language or types. Features For a good software development, we need code editors and IDEs which help the developer to automate the process of editing, compiling, testing, debugging and much more. Some of the features of these editors are listed below: Good user interface: They allow users to interact and run programs easily. Incredibly fast: Although these IDEs need to import heavy libraries, compile and debug, they offer fast compilation and run time.  Syntax stylizing: Codes are colorized automatically and syntax is highlighted.    Debugging tool: Itruns the code, set breakpoints, examine the variables. Provides good language syntax: IDEs usually work on a specific language but the others are designed for multi-language support. Code editors are designed with multi-language support.  Good source and version control environment: IDEs come with source control feature to keep a track of changes made in source code and other text files during the development of any software. Intelligent code completion:This feature speeds up the coding process by automatically suggesting for incomplete codes. It reduces typos and other common mistakes. Why do we need a good coding environment? For a good software development one seeks a better coding environment. Although features vary from app to app, a definite set of features is required for one. There are many other things involved such as source code control, extension tools, language support etc. Listed below are the core features which make a good coding environment : Retrieve files: All the codes written in an IDE get saved. Also, the programmer can retrieve his code file at the same state where the work is left off. Run within the environment: It should be able to compile and run within the environment where the codes are written. No external file shall be needed to be downloaded for the execution of the programs.  Good Debugging Tool: An IDE or editor should be able to diagnose and  troubleshoot the programmer’s works and highlight the lines with errors if any. A pop-up window should display the error message. This way the programmer can keep a track of his errands and diagnose them.   Automatic formatting tool: Indentation is done automatically as soon as the programmer moves onto the next line. It keeps the code clean and readable. Quick highlighting: keywords, variables and symbols are highlighted. This feature keeps the code clean and easy to understand. Also, pops up the variables making them easy to spot. This makes it a whole lot easier to pick out portions of code than simply looking at a wall of undifferentiated text. Some of the IDEs and code editors There are various Python IDEs and text editors. Some of the IDEs and text editors along with their features and pros and cons are mentioned below: IDLEKey Features: It is an open source IDE entirely written in Python. It is mainly supported by WINDOWS, LINUX, MAC OS etc.. IDLE is a decent IDE for learning because it is lightweight and quite simple to use. IDLE is installed by default as soon as installation of Python is complete. This makes it easier to get started in Python. IDLE features include the Python shell window(interactive interpreter), auto-completion, syntax highlighting, smart indentation, and a basic integrated debugger. It is however not suitable for the completion of larger projects and best suitable for educational purposes only.  Pros A cross-platform where a developer can search within any window, search through multiple files and replace within the windows editor  Supports syntax highlighting, auto code completion, smart indentation and editable configurations Includes Python shell with highlighter Powerful Integrated Debugger with continuous breakpoints, global view, and local spaces Improves the performance  Call stack visibility Increases the flexibility for developers Cons Used for programming just for beginners Limited to handle normal usage issues. Supports basic design  Large software development cannot be handled  Sublime text Key Features: It is a source code editor, supported on all platforms. It is a very popular cross-platform  and a better text editor. It possesses a built-in support for Python for code editing and packages to extend the syntax and editing features. All Sublime Text packages are written in Python and also a Python API. Installation of the packages often requires you to execute scripts directly in Sublime Text. it is designed to support huge programming and markup languages. Additional functions can be applied by the user with the help of plugins.  Pros More reliable for developers and is cross-platform Supports GOTO anything to access files  Generates wide index of each method, class, and function. AllowsUser interface toolkit Easy navigation to words or symbols Multiple selections to change things at one time Offers command palette to sort, edit and modify the syntax and maintain the indentation.  Offers powerful API and package ecosystem Great performance Highly customizable Allows split editing and instant project switch  Better compatibility with language grammar Custom selection on specific projects Cons Not free Installation of extensions is quite tricky Does not support for direct executing or debugging code from within the editor Less active GIT plugin AtomKey Features: It is an open source code editor developed by Github. It is supported on all platforms. It has features similar to that of Python. It has a framework based on atom shells which help to achieve cross platform functionality. With a sleek interface, file system browser, and marketplace for extensions, it offers a framework for creating desktop applications using JavaScript, HTML, CSS . Extensions can be installed when Atom is running.It enables support for third party packages. Its major feature is that although it is a code editor,it can also be used as an IDE. It is also used for educational purposes. Atom is being improvised day by day, striving to make the user experience rewarding and not remain confined to beginners use only.  Pros Cross-platform  Smooth editing Improves performance of its users Offers built-in package manager and file system browser Faster scripting  Offers smart auto-completion  Smart and flexible Supports multiple pane features Easy navigation across an application Simple to use Allows user interface customization Full support from GitHub Quick access to data and information Cons For beginners only Tedious for sorting configurations and plugins Clumsy tabs reduce performance  Slow loading Runs on JavaScript process  Built on Electron, does not run as a native application VimKey Features: Categorized as a stable open source code editor, VI and VIM are modal editors. As it is supported on almost every platform such as: Windows, LINUX, MAC OS, IOS, Android, UNIX, AmigaOS, MorphOS etc. it is highly configurable. Because of its modal mode of operation, it differs from most other text editors. It possesses three basic modes: insert mode, normal or command mode and command line mode. It is easily customized by the addition of extensions and configuration which makes it easily adaptable for Python development.  Pros Free and easily accessible Customizable and persistent  Has a multi-level undo tree  Extensions are added manually Configuration file is modified Multi-buffers support simultaneous file editing Automated indentation  Good user interface Recognition and conversion of file formats Exclusive libraries including wide range of languages Comes with own scripting language with powerful integration, search and replace functionality Extensive system of plugins Allows debugging and refactoring  Provides two different modes to work: normal and editing mode Strings in VIM can be saved and reused  Cons Used as a text editor only No different color for the pop-up option Not good for beginners PyDev Key Features: It is also categorized as an open source IDE mainly written with JAVA.Since it is an eclipse plugin, the Java IDE is transformed into Python IDE. Its integration with Django gives a Python framework. It also has keyword auto-completion, good debugging tool, syntax highlighting and indentation. Pros Free open source Robust IDE feature set Auto-completion of codes and analysis Smart indentation Interactive console shortcuts Integrated with Django configuration  Platform independent Cons: User interface is not great  Visual studioKey Features: It is categorized as an IDE, is a full-featured IDE developed by Microsoft. It is compatible with Windows and Mac OS only and comes with free as well as paid versions. It has its own marketplace for extensions. PTVS(Python Tools for Visual Studio) offers various features as in coding for Python development, IntelliSense, debugging, refactoring etc. Pros Easy and less tedious installation for development purposes Cons Spacious files  Not supported on Linux Visual studio code Key Features: VS code is a code editor and is way more different from VS. It is a free open source code editor developed by Microsoft can be run on platforms such as Windows, Linux and Mac OS X.  It has a full-featured editor that is highly configurable with Python compatibility for software development. Python tools can be added to enable coding in Python.VS code is integrated with Git which promotes it to perform operations like push, commit directly from the editor itself. It also has electron framework for Node JS applications running on the Blink browser engine. It is enclosed with smart code completion with function definition, imported modules and variable types. Apart from these, VS code also comes with syntax highlighting, a debugging console and proprietary IntelliSense code auto completion. After installing Python, VS code recognizes Python files and libraries immediately.  Pros Free and available on every platform  Small, light-weight but highly extensible Huge compatibility Has a powerful code management system Enables debugging from the editor Multi-language support  Extensive libraries Smart user interface and an acceptable layout Cons Slow search engine Tedious launch time Not a native app just like Atom WingKey Features: Wing is also one of the powerful IDEs today and comes with a lot of good features. It is an open source IDE used commercially. It also is constituted with a strong framework and has a strong debugger and smart editor for Python development making it fast, accurate and fun to perform. It comes with a 30 day trial version. It supports text driven development with unit test, PyTest and Django testing framework.  Pros Open source Find and go-to definition Customizable and extensible Auto-code completion Quick Troubleshoot  Source browser shows all the variables used in the script Powerful debugger  Good refactoring  Cons Not capable of supporting dark themes Wing interface is quite intimidating Commercial version is expensive Python-specific IDEs and Editors Anaconda - Jupyter NotebooksKey Features: It is also an open source IDE with a server-client structure, used to create and edit the codes of a Python. Once it is saved, you can share live code equations, visualizations and text. It has anaconda distribution i.e., libraries are preinstalled so downloading the anaconda itself does the task. It supports Python and R language which are installed by default at installation.  This IDE is again used for data science learning. Quite easy to use, it is not just used as an editor but also as an educational tool or presentation. It supports numerical simulation, machine  learning visualization and statistical modelling. Pros Free Open source  Good user interface Server-client structure Educational tool- Data science, Machine learning  Supports numerical simulation  Enables to create, write, edit and insert images Combines code, text and images Integrated libraries - Matplotlib, NumPy, Pandas Multi-language support Auto code completion Cons Sometimes slow loading is experienced Google Colaboratory Key Features: It is the simplest web IDE used for Python. It gives a free GPU access. Instead of downloading heavy files and tedious launch time, one can directly update the files from Colab to the drive. All you need to do is log in to your google account and open Colab. There is no need for extra setup. Unlike other IDEs no files are required to download. Google provides free computation resources with Colaboratory. It is designed for creating machine learning models. For compilation and execution, all you need to do is to update Python package and get started.   Pros Available to all Code can be run without any interruption Highly user interactive No heavy file downloads Integrated libraries Multi-language support Updated in google drive Update the Python package for execution  Runs on cloud Comments can be added in cells Can import Jupiter or IPython notebooks Cons  All colaboratory files are to be stored in google drive Install all specific libraries No access to unsaved files once the session is over Pycharm Key Features: Developed by Jet Brains and one of the widely used full-featured Python IDE, this is a cross-platform IDE for Python programming and  is well-integrated with Python console and IPython Notebook. It is supported by Windows, Linux, Mac OS and other platforms as well. It has massive productivity and saves ample amount of time. It comes with smart code navigation, code editor, good debugging tool, quick refactoring etc. and supports Python web development frameworks such as Angular JS, JavaScript, CSS, HTML  and live editing functions. The paid version offers advanced features such as full database management and a multitude Framework than the community version such as Django, Flask, Google App, Engine, Pyramid and web2py. Pros Great supportive community Brilliant performance. Amazing editing tools Robust debugging tool Smart code navigation Quick and safe refactoring  Built in developer tools Error detection and fix up suggestions Customizable interface Available in free and paid version Cons Slow loading  Installation is quite difficult and may hang up in between SpyderKey Features: It is an open source IDE supported on all platforms. Ranked as one of the best Python compilers, it supports syntax highlighting, auto completion of codes just like Pycharm. It offers an advanced level of editing, debugging, quick diagnose, troubleshoot and many data exploration features. To get started with Spyder, one needs to install anaconda distribution which is basically used in data science and machine learning. Just like Pycharm it has IntelliSense auto-completion of code. Spyder is built on a structured and powerful framework which makes it one of the best IDE used so far. It is most commonly used for scientific development. Pros Free open source IDE Quick troubleshoot Active framework Smart editing and debugging Syntax is automatically highlighted Auto completion of codes Good for data science and machine learning Structured framework Integrates common Python data science libraries like SciPy, NumPy, and Matplotlib Finds and eliminates bottlenecks Explores and edits variables directly from GUI  Performs well in multi-language editor and auto completion mode Cons Spyder is not capable to configure a specific warning Too many plugins degrades its performance ThonnyKey Features: Thonny is another IDE best suited for beginners for Python development and provides a good virtual environment. It is supported on all platforms. It gives a simple debugger with F5, F6 and F7 keys for debugging. Also, Thonny supports highlighting errors, good representation of function calls, auto code completion and smart indentation. It even allows the developers to configure their code and shell commands. by default,  in Thonny Python is pre-installed as it downloads with its own version of Python.  Pros Simple Graphical user interface.  Free open source IDE Best for beginners Simple debugger with F5, F6, F7 Keys Tackles issues with Python interpreters Highlights syntax error Auto-completion of code Good representation of function calls User can change reference mode easily Step through expression evaluation Reply and resolve to comments Cons Interface is not that good for developers Confined to text editing No template support Slow plugin creation Too basic IDE for software development Which Python IDE is right for you? Requirements vary from programmer to programmer. It is one’s own choice to pick the right tool that is best suited for the task at hand. Beginners need to use a simple tool with few customizations whereas experts require tools with advanced features to bring new updates. Few suggestions are listed below:- Beginners should start with IDLE and Thonny as they do not have complex features and are pretty easy to learn. For data science learners Jupyter Notebooks and Google Colaboratory is preferred. Generally, large scale enterprises prefer the paid versions of IDEs like PyCharm, Atom, Sublime Text etc. in order to get extensive service support from the company. Also, they provide easy finance options and manpower. On the other hand, middle and small scale enterprises tend to look for open source tools which provides them with excellent features. Some of such IDEs are Spyder, Pydev, IDLE and Visual Studio. Conclusion Today, Python stands out as one of the most popular programming languages worldwide. IDE being a program dedicated to software development has made it easier for developers to build, execute, and debug their codes. Code editors can only be used for editing codes whereas an IDE is a feature rich editor which has inbuilt text editor, compiler, debugging tool and libraries. Different IDEs and code editors are detailed in this article along with their merits and demerits. Some are suitable for beginners because of their lightweight nature and simplicity like IDLE, Thonny whereas experts require advance featured ones for building software.  For learning purposes say data science, machine learning Jupyter and Google Colaboratory are strongly recommended. Again there are large scale enterprises who prefer PyCharm, Atom, Sublime Text for software development. On the other hand, small scale enterprises prefer Spyder, Pydev, IDLE and Visual Studio. Hence,the type of IDE or code editor that should be used completely depends upon the requirement of the programmer . To gain more knowledge about Python tips and tricks, check our Python tutorial and get a good hold over coding in Python by joining the Python certification course. 

Top 10 Python IDEs and Code Editors

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Top 10 Python IDEs and Code Editors

Over the years, Python language has evolved enormously with the contribution of developers. Python is one of the most popular programming languages. It was designed primarily for server-side web development, software development, evaluation, scripting and artificial intelligence. For this feature Python encloses certain code editors and IDEs that are used for software development say, Python itself. If you are new to programming, learning Python is highly recommended as it is fast, efficient and easy to learn. Python interpreters are available on various operating systems such as Windows, Linux, Mac OS. This article provides a look into code editors and IDEs along with their features, pros and cons and talks about which are the best suited for writing Python codes. But first let us see what are code editors and IDEs. 

What is a Code Editor? 

A code editor is built for editing and modifying source code. A standalone text editor is used for writing and editing computer programs. Excellent ones can execute code as well as control a debugger as well as interact with source control systems. Compared to an IDE, a good dedicated code editor is usually smaller and quicker, but is less functional. Typically they are optimized for programming languages. One major feature of a text editor is that they are designed to modify various files and work with whatever language or framework you choose. 

What is IDE? 

IDE (Integrated Development Environment) understands the code significantly better than a text editor. It is a program exclusively built for software development. It is designed with a set of tools that all work together:  

  • Text editor  
  • Compiler 
  • Build automation 
  • Debugging 
  • Libraries, and many more to speed up the work.  

These tools integrate: An editor designed to frame codes with text formatting, auto-completionetc., build, execution, debugging tools, file management and source and version control. It reduces manual efforts and combines all the equipment in a typical framework. IDE comes with heavy files. Hence, the downloads and installation is quite tedious. IDE requires expertise along with a lot of patience.  

How does an IDE and Code editor differ from each other? 

An IDE is distinctive from code editors in the following ways: 

  • Integrated build process:The user does not have to write his own scripts to build apps in an IDE.  
  • File management: IDE has an integrated file management system and deployment tool. It provides support to other framework as well. On the other hand, a Text editor is a simple editor where source code can be edited and it has no other formatting or compiling options. 
  • Development Environment: An IDE is mainly used for development purposes as it provides comparatively better features than a text editor. It allows you to write, compile and debug the entire script.  
  • Syntax Highlighting:The editor displays the text message and puts the source code in different colours to improve its readability. Even error messages are displayed in different colours so that the user understands where he has written the wrong code.  
  • Auto completion:It identifies and inserts a common code for the user instantly. This feature acts as an assistance for the programmer. The code suggestion automatically gets displayed.  
  • Debugger: This tool helps the programmer to test and debug the source code of the main program.  

Although IDEs have far better features than a Text editor one major significance of Text editor is that it allows modifying all types of files rather than specifying any definite language or types. 

Features 

For a good software development, we need code editors and IDEs which help the developer to automate the process of editing, compiling, testing, debugging and much more. Some of the features of these editors are listed below: 

  • Good user interface: They allow users to interact and run programs easily. 
  • Incredibly fast: Although these IDEs need to import heavy libraries, compile and debug, they offer fast compilation and run time.  
  • Syntax stylizing: Codes are colorized automatically and syntax is highlighted.    
  • Debugging tool: Itruns the code, set breakpoints, examine the variables. 
  • Provides good language syntax: IDEs usually work on a specific language but the others are designed for multi-language support. Code editors are designed with multi-language support.  
  • Good source and version control environment: IDEs come with source control feature to keep a track of changes made in source code and other text files during the development of any software. 
  • Intelligent code completion:This feature speeds up the coding process by automatically suggesting for incomplete codes. It reduces typos and other common mistakes. 

Why do we need a good coding environment? 

For a good software development one seeks a better coding environment. Although features vary from app to app, a definite set of features is required for one. There are many other things involved such as source code control, extension tools, language support etc. Listed below are the core features which make a good coding environment : 

  • Retrieve files: All the codes written in an IDE get saved. Also, the programmer can retrieve his code file at the same state where the work is left off. 
  • Run within the environment: It should be able to compile and run within the environment where the codes are written. No external file shall be needed to be downloaded for the execution of the programs.  
  • Good Debugging Tool: An IDE or editor should be able to diagnose and  troubleshoot the programmer’s works and highlight the lines with errors if any. A pop-up window should display the error message. This way the programmer can keep a track of his errands and diagnose them.   
  • Automatic formatting tool: Indentation is done automatically as soon as the programmer moves onto the next line. It keeps the code clean and readable. 
  • Quick highlighting: keywords, variables and symbols are highlighted. This feature keeps the code clean and easy to understand. Also, pops up the variables making them easy to spot. This makes it a whole lot easier to pick out portions of code than simply looking at a wall of undifferentiated text. 

Some of the IDEs and code editors 

There are various Python IDEs and text editors. Some of the IDEs and text editors along with their features and pros and cons are mentioned below: 

IDLE

IDLEKey Features: It is an open source IDE entirely written in Python. It is mainly supported by WINDOWS, LINUX, MAC OS etc.. IDLE is a decent IDE for learning because it is lightweight and quite simple to use. IDLE is installed by default as soon as installation of Python is complete. This makes it easier to get started in Python. IDLE features include the Python shell window(interactive interpreter), auto-completion, syntax highlighting, smart indentation, and a basic integrated debugger. It is however not suitable for the completion of larger projects and best suitable for educational purposes only.  

Pros 

  • A cross-platform where a developer can search within any window, search through multiple files and replace within the windows editor  
  • Supports syntax highlighting, auto code completion, smart indentation and editable configurations 
  • Includes Python shell with highlighter 
  • Powerful Integrated Debugger with continuous breakpoints, global view, and local spaces 
  • Improves the performance  
  • Call stack visibility 
  • Increases the flexibility for developers 

Cons 

  • Used for programming just for beginners 
  • Limited to handle normal usage issues. 
  • Supports basic design  
  • Large software development cannot be handled  

Sublime text 

Sublime text

Key Features: It is a source code editor, supported on all platforms. It is a very popular cross-platform  and a better text editor. It possesses a built-in support for Python for code editing and packages to extend the syntax and editing features. All Sublime Text packages are written in Python and also a Python API. Installation of the packages often requires you to execute scripts directly in Sublime Text. it is designed to support huge programming and markup languages. Additional functions can be applied by the user with the help of plugins.  

Pros 

  • More reliable for developers and is cross-platform 
  • Supports GOTO anything to access files  
  • Generates wide index of each method, class, and function. 
  • AllowsUser interface toolkit 
  • Easy navigation to words or symbols 
  • Multiple selections to change things at one time 
  • Offers command palette to sort, edit and modify the syntax and maintain the indentation.  
  • Offers powerful API and package ecosystem 
  • Great performance 
  • Highly customizable 
  • Allows split editing and instant project switch  
  • Better compatibility with language grammar 
  • Custom selection on specific projects 

Cons 

  • Not free 
  • Installation of extensions is quite tricky 
  • Does not support for direct executing or debugging code from within the editor 
  • Less active GIT plugin 

Atom

Atom

Key Features: It is an open source code editor developed by Github. It is supported on all platforms. It has features similar to that of Python. It has a framework based on atom shells which help to achieve cross platform functionality. With a sleek interface, file system browser, and marketplace for extensions, it offers a framework for creating desktop applications using JavaScript, HTML, CSS . Extensions can be installed when Atom is running.It enables support for third party packages. Its major feature is that although it is a code editor,it can also be used as an IDE. It is also used for educational purposes. Atom is being improvised day by day, striving to make the user experience rewarding and not remain confined to beginners use only.  

Pros 

  • Cross-platform  
  • Smooth editing 
  • Improves performance of its users 
  • Offers built-in package manager and file system browser 
  • Faster scripting  
  • Offers smart auto-completion  
  • Smart and flexible 
  • Supports multiple pane features 
  • Easy navigation across an application 
  • Simple to use 
  • Allows user interface customization 
  • Full support from GitHub 
  • Quick access to data and information 

Cons 

  • For beginners only 
  • Tedious for sorting configurations and plugins 
  • Clumsy tabs reduce performance  
  • Slow loading 
  • Runs on JavaScript process  
  • Built on Electron, does not run as a native application 

Vim

Vim

Key Features: Categorized as a stable open source code editor, VI and VIM are modal editors. As it is supported on almost every platform such as: Windows, LINUX, MAC OS, IOS, Android, UNIX, AmigaOS, MorphOS etc. it is highly configurable. Because of its modal mode of operation, it differs from most other text editors. It possesses three basic modes: insert mode, normal or command mode and command line mode. It is easily customized by the addition of extensions and configuration which makes it easily adaptable for Python development.  

Pros 

  • Free and easily accessible 
  • Customizable and persistent  
  • Has a multi-level undo tree  
  • Extensions are added manually 
  • Configuration file is modified 
  • Multi-buffers support simultaneous file editing 
  • Automated indentation  
  • Good user interface 
  • Recognition and conversion of file formats 
  • Exclusive libraries including wide range of languages 
  • Comes with own scripting language with powerful integration, search and replace functionality 
  • Extensive system of plugins 
  • Allows debugging and refactoring  
  • Provides two different modes to work: normal and editing mode 
  • Strings in VIM can be saved and reused  

Cons 

  • Used as a text editor only 
  • No different color for the pop-up option 
  • Not good for beginners 

PyDev 

PyDev

Key Features: It is also categorized as an open source IDE mainly written with JAVA.Since it is an eclipse plugin, the Java IDE is transformed into Python IDE. Its integration with Django gives a Python framework. It also has keyword auto-completion, good debugging tool, syntax highlighting and indentation. 

Pros 

  • Free open source 
  • Robust IDE feature set 
  • Auto-completion of codes and analysis 
  • Smart indentation 
  • Interactive console shortcuts 
  • Integrated with Django configuration  
  • Platform independent 

Cons

  • User interface is not great  

Visual studio

Visual studioKey Features: It is categorized as an IDE, is a full-featured IDE developed by Microsoft. It is compatible with Windows and Mac OS only and comes with free as well as paid versions. It has its own marketplace for extensions. PTVS(Python Tools for Visual Studio) offers various features as in coding for Python development, IntelliSense, debugging, refactoring etc. 

Pros 

  • Easy and less tedious installation for development purposes 

Cons 

  • Spacious files  
  • Not supported on Linux 

Visual studio code 

Visual studio code Key Features: VS code is a code editor and is way more different from VS. It is a free open source code editor developed by Microsoft can be run on platforms such as Windows, Linux and Mac OS X.  It has a full-featured editor that is highly configurable with Python compatibility for software development. Python tools can be added to enable coding in Python.VS code is integrated with Git which promotes it to perform operations like push, commit directly from the editor itself. It also has electron framework for Node JS applications running on the Blink browser engine. It is enclosed with smart code completion with function definition, imported modules and variable types. Apart from these, VS code also comes with syntax highlighting, a debugging console and proprietary IntelliSense code auto completion. After installing Python, VS code recognizes Python files and libraries immediately.  

Pros 

  • Free and available on every platform  
  • Small, light-weight but highly extensible 
  • Huge compatibility 
  • Has a powerful code management system 
  • Enables debugging from the editor 
  • Multi-language support  
  • Extensive libraries 
  • Smart user interface and an acceptable layout 

Cons 

  • Slow search engine 
  • Tedious launch time 
  • Not a native app just like Atom 

Wing

Wing

Key Features: Wing is also one of the powerful IDEs today and comes with a lot of good features. It is an open source IDE used commercially. It also is constituted with a strong framework and has a strong debugger and smart editor for Python development making it fast, accurate and fun to perform. It comes with a 30 day trial version. It supports text driven development with unit test, PyTest and Django testing framework.  

Pros 

  • Open source 
  • Find and go-to definition 
  • Customizable and extensible 
  • Auto-code completion 
  • Quick Troubleshoot  
  • Source browser shows all the variables used in the script 
  • Powerful debugger  
  • Good refactoring  

Cons 

  • Not capable of supporting dark themes 
  • Wing interface is quite intimidating 
  • Commercial version is expensive 

Python-specific IDEs and Editors 

Anaconda - Jupyter Notebooks

Anaconda - Jupyter Notebooks

Key Features: It is also an open source IDE with a server-client structure, used to create and edit the codes of a Python. Once it is saved, you can share live code equations, visualizations and text. It has anaconda distribution i.e., libraries are preinstalled so downloading the anaconda itself does the task. It supports Python and R language which are installed by default at installation.  This IDE is again used for data science learning. Quite easy to use, it is not just used as an editor but also as an educational tool or presentation. It supports numerical simulation, machine  learning visualization and statistical modelling. 

Pros 

  • Free Open source  
  • Good user interface 
  • Server-client structure 
  • Educational tool- Data science, Machine learning  
  • Supports numerical simulation  
  • Enables to create, write, edit and insert images 
  • Combines code, text and images 
  • Integrated libraries - Matplotlib, NumPy, Pandas 
  • Multi-language support 
  • Auto code completion 

Cons 

  • Sometimes slow loading is experienced 

Google Colaboratory 

Google Colaboratory

Key Features: It is the simplest web IDE used for Python. It gives a free GPU access. Instead of downloading heavy files and tedious launch time, one can directly update the files from Colab to the drive. All you need to do is log in to your google account and open Colab. There is no need for extra setup. Unlike other IDEs no files are required to download. Google provides free computation resources with Colaboratory. It is designed for creating machine learning models. For compilation and execution, all you need to do is to update Python package and get started.   

Pros 

  • Available to all 
  • Code can be run without any interruption 
  • Highly user interactive 
  • No heavy file downloads 
  • Integrated libraries 
  • Multi-language support 
  • Updated in google drive 
  • Update the Python package for execution  
  • Runs on cloud 
  • Comments can be added in cells 
  • Can import Jupiter or IPython notebooks 

Cons  

  • All colaboratory files are to be stored in google drive 
  • Install all specific libraries 
  • No access to unsaved files once the session is over 

Pycharm 

Pycharm

Key Features: Developed by Jet Brains and one of the widely used full-featured Python IDE, this is a cross-platform IDE for Python programming and  is well-integrated with Python console and IPython Notebook. It is supported by Windows, Linux, Mac OS and other platforms as well. It has massive productivity and saves ample amount of time. It comes with smart code navigation, code editor, good debugging tool, quick refactoring etc. and supports Python web development frameworks such as Angular JS, JavaScript, CSS, HTML  and live editing functions. The paid version offers advanced features such as full database management and a multitude Framework than the community version such as Django, Flask, Google App, Engine, Pyramid and web2py. 

Pros 

  • Great supportive community 
  • Brilliant performance. 
  • Amazing editing tools 
  • Robust debugging tool 
  • Smart code navigation 
  • Quick and safe refactoring  
  • Built in developer tools 
  • Error detection and fix up suggestions 
  • Customizable interface 
  • Available in free and paid version 

Cons 

  • Slow loading  
  • Installation is quite difficult and may hang up in between 

Spyder

Spyder

Key Features: It is an open source IDE supported on all platforms. Ranked as one of the best Python compilers, it supports syntax highlighting, auto completion of codes just like Pycharm. It offers an advanced level of editing, debugging, quick diagnose, troubleshoot and many data exploration features. To get started with Spyder, one needs to install anaconda distribution which is basically used in data science and machine learning. Just like Pycharm it has IntelliSense auto-completion of code. Spyder is built on a structured and powerful framework which makes it one of the best IDE used so far. It is most commonly used for scientific development. 

Pros 

  • Free open source IDE 
  • Quick troubleshoot 
  • Active framework 
  • Smart editing and debugging 
  • Syntax is automatically highlighted 
  • Auto completion of codes 
  • Good for data science and machine learning 
  • Structured framework 
  • Integrates common Python data science libraries like SciPy, NumPy, and Matplotlib 
  • Finds and eliminates bottlenecks 
  • Explores and edits variables directly from GUI  
  • Performs well in multi-language editor and auto completion mode 

Cons 

  • Spyder is not capable to configure a specific warning 
  • Too many plugins degrades its performance 

Thonny

Thonny

Key Features: Thonny is another IDE best suited for beginners for Python development and provides a good virtual environment. It is supported on all platforms. It gives a simple debugger with F5, F6 and F7 keys for debugging. Also, Thonny supports highlighting errors, good representation of function calls, auto code completion and smart indentation. It even allows the developers to configure their code and shell commands. by default,  in Thonny Python is pre-installed as it downloads with its own version of Python.  

Pros 

  • Simple Graphical user interface.  
  • Free open source IDE 
  • Best for beginners 
  • Simple debugger with F5, F6, F7 Keys 
  • Tackles issues with Python interpreters 
  • Highlights syntax error 
  • Auto-completion of code 
  • Good representation of function calls 
  • User can change reference mode easily 
  • Step through expression evaluation 
  • Reply and resolve to comments 

Cons 

  • Interface is not that good for developers 
  • Confined to text editing 
  • No template support 
  • Slow plugin creation 
  • Too basic IDE for software development 

Which Python IDE is right for you? 

Requirements vary from programmer to programmer. It is one’s own choice to pick the right tool that is best suited for the task at hand. Beginners need to use a simple tool with few customizations whereas experts require tools with advanced features to bring new updates. Few suggestions are listed below:- 

  • Beginners should start with IDLE and Thonny as they do not have complex features and are pretty easy to learn. 
  • For data science learners Jupyter Notebooks and Google Colaboratory is preferred. 

Generally, large scale enterprises prefer the paid versions of IDEs like PyCharm, Atom, Sublime Text etc. in order to get extensive service support from the company. Also, they provide easy finance options and manpower. On the other hand, middle and small scale enterprises tend to look for open source tools which provides them with excellent features. Some of such IDEs are Spyder, Pydev, IDLE and Visual Studio. 

Conclusion 

Today, Python stands out as one of the most popular programming languages worldwide. IDE being a program dedicated to software development has made it easier for developers to build, execute, and debug their codes. Code editors can only be used for editing codes whereas an IDE is a feature rich editor which has inbuilt text editor, compiler, debugging tool and libraries. Different IDEs and code editors are detailed in this article along with their merits and demerits. Some are suitable for beginners because of their lightweight nature and simplicity like IDLE, Thonny whereas experts require advance featured ones for building software.  

For learning purposes say data science, machine learning Jupyter and Google Colaboratory are strongly recommended. Again there are large scale enterprises who prefer PyCharm, Atom, Sublime Text for software development. On the other hand, small scale enterprises prefer Spyder, Pydev, IDLE and Visual Studio. Hence,the type of IDE or code editor that should be used completely depends upon the requirement of the programmer . To gain more knowledge about Python tips and tricks, check our Python tutorial and get a good hold over coding in Python by joining the Python certification course

Priyankur

Priyankur Sarkar

Data Science Enthusiast

Priyankur Sarkar loves to play with data and get insightful results out of it, then turn those data insights and results in business growth. He is an electronics engineer with a versatile experience as an individual contributor and leading teams, and has actively worked towards building Machine Learning capabilities for organizations.

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What are Python KeyError Exceptions and How to Handle Them

There are times when you have written your code but while you execute, it might not run. These types of situations occur when the input is inappropriate or you try to open a file with a wrong path or try to divide a number by zero. Due to some errors or incorrect command the output will not be displayed. This is because of errors and exceptions which are a part of the Python programming language. Learn about such concepts and gain further knowledge by joining Python Programming Course.What is Exception Handling?Python raises exceptions when it encounters errors during execution. A Python Exception is basically a construct that signals any important event, such as a run-time error.Exception Handling is the process of responding to executions during computations, which often interrupts the usual flow of executing a program. It can be performed both at the software level as part of the program and also at hardware level using built-in CPU mechanisms.Why is Exception Handling Important?Although exceptions might be irritating when they occur, they play an essential role in high level languages by acting as a friend to the user.An error at the time of execution might lead to two things— either your program will die or will display a blue screen of death. On the other hand, exceptions act as communication tools. It allows the program to answer the questions — what, why and how something goes wrong and then terminates the program in a delicate manner.In simple words, exception handling protects against uncontrollable program failures and increases the potency and efficiency of your code. If you want to master yourself in programming, the knowledge of exceptions and how to handle them is very crucial, especially in Python.What are the Errors and Exceptions in Python?Python doesn’t like errors and exceptions and displays its dissatisfaction by terminating the program abruptly.There are basically two types of errors in the Python language-Syntax Error.Errors occuring at run-time or Exceptions.Syntax ErrorsSyntax Errors, also known as parsing errors, occur when the parser identifies an incorrect statement. In simple words, syntax error occurs when the proper structure or syntax of the programming language is not followed.An example of a syntax error:>>> print( 1 / 0 )) File "", line 1 print( 1 / 0 ))   ^SyntaxError: invalid syntaxExceptionsExceptions occur during run-time. Python raises an exception when your code has a correct syntax but it encounters a run-time issue which it is not able to handle.There are a number of defined built-in exceptions in Python which are used in specific situations. Some of the built-in exceptions are:ExceptionCause Of ErrorArithmeticErrorRaised when numerical computation fails.FloatingPointErrorRaised when floating point calculation fails.AssertionErrorRaised in case of failure of the Assert statement.ZeroDivisionErrorRaised when division or modulo by zero takes place for all numerical values.OverflowErrorRaised when result of an arithmetic operation is very large to be represented.IndexErrorRaised when an index is not found in a sequence.ImportErrorRaised when the imported module is not found.IndentationErrorRaised when indentation is not specified properly.KeyboardInterruptRaised when the user hits interrupt key.RuntimeErrorRaised when a generated error does not fall into any category.SyntaxErrorRaised when there is an error in Python syntax.IOErrorRaised when Python cannot access a file correctly on disk.KeyErrorRaised when a key is not found in a dictionary.ValueErrorRaised when an argument to a function is the right type but not in the right domain.NameErrorRaised when an identifier is not found in the local or global namespace.TypeErrorRaised when an argument to a function is not in the right type.There are another type of built-in exceptions called warnings. They are usually issued in situations where the user is alerted of some conditions. The condition does not raise an exception; rather it  terminates the program.What is a Python KeyError?Before getting into KeyError, you must know the meaning of dictionary and mapping in Python. Dictionary (dict) is an unordered collection of objects which deals with data type key. They are Python’s implementation of data structures and are also known as associative arrays. They comprise key-value pairs, in which each pair maps the key to its associated value.Dictionary is basically a data structure that maps one set of values into another and is the most common mapping in Python.Exception hierarchy of KeyError:->BaseException              ->Exception                         ->LookupError                                       ->KeyErrorA Python KeyError is raised when you try to access an invalid key in a dictionary. In simple terms, when you see a KeyError, it denotes that the key you were looking for could not be found.An example of KeyError:>>> prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25} >>> prices['Eraser'] Traceback (most recent call last): File "", line 1, in prices['Eraser'] KeyError: 'Eraser'Here, dictionary prices is declared with the prices of three items. The KeyError is raised when the item ‘Eraser’ is being accessed which is not present in prices.Whenever an exception is raised in Python, it is done using traceback, as you can see in the example code above. It tells why an exception is raised and what caused it.Let’s execute the same Python code from a file. This time, you will be asked to give the name of the item whose price you want to know:# prices.py prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25} item = input('Get price of: ') print(f'The price of {item} is {prices[item]}')You will get a traceback again but you’ll also get the information about the line from which the KeyError is raised:Get price of: Eraser Traceback (most recent call last): File "prices.py", line 5, in print(f'The price of {item} is {prices[item]}') KeyError: 'Eraser'The traceback in the example above provides the following information:A KeyError was raised.The key ‘Eraser’ was not found.The line number which raised the exception along with that line.Where else will you find a Python KeyError?Although most of the time, a KeyError is raised because of an invalid key in a Python dictionary or a dictionary subclass, you may also find it in other places in the Python Standard Library, such as in a zipfile. However, it denotes the same semantic meaning of the Python KeyError, which is not finding the requested key.An example of such:>>> from zipfile import ZipFile >>> my_zip_file = ZipFile('Avengers.zip') >>> my_zip_file.getinfo('Batman')Traceback (most recent call last): File "", line 1, in File "myzip.py", line 1119, in getinfo 'There is no item named %r in the archive' % name) KeyError: "There is no item named 'Batman' in the archive"In this example, the zipfile.ZipFile class is used to derive information about a ZIP archive ‘Batman’ using the getinfo() function. Here, the traceback indicates that the problem is not in your code but in the zipfile code, by showing the line which caused the problem. The exception raised here is not because of a LookUpError but rather due to the zipfile.ZipFile.getinfo()function call.When do you need to raise a Python KeyError?In Python Programming, it might be sensible at times to forcefully raise exceptions in your own code. You can usually raise an exception using the raise keyword and by calling the KeyError exception:>>> raise KeyError('Batman')Here, ‘Batman’ acts as the missing key. However, in most cases, you should provide more information about the missing key so that your next developer has a clear understanding of the problem.Conditions to raise a Python KeyError in your code:It should match the generic meaning behind the exception.A message should be displayed about the missing key along with the missing key which needs to be accessed.How to Handle a Python KeyError?The main motive of handling a Python KeyError is to stop unexpected KeyError exceptions to be raised. There are a number of number of ways of handling a KeyError exception.Using get()The get()is useful in cases where the exception is raised due to a failed dictionary LookupError. It returns either the specified key value or a default value.# prices.py prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25} item = input('Get price of: ') price = prices.get(item) if price:   print(f'The price of {item} is {prices[item]}')   else:   print(f'The price of {item} is not known')This time, you’ll not get a KeyError because the get() uses a better and safer method to retrieve the price and if not found, the default value is displayed:Get price of: EraserThe price of Eraser is not knownIn this example, the variable price will either have the price of the item in the dictionary or the default value ( which is None by default ).In the example above, when the key ‘Eraser’ is not found in the dictionary, the get() returns  None by default rather than raising a KeyError. You can also give another default value as a second argument by calling get():price = prices.get(item,0)If the key is not found, it will return 0 instead of None.Checking for KeysIn some situations, the get() might not provide the correct information. If it returns None, it will mean that the key was not found or the value of the key in Python Dictionary is actually None, which might not be true in some cases. In such situations, you need to determine the existence of a key in the dictionary. You can use the if and in operator to handle such cases. It checks whether a key is present in the mapping or not by returning a boolean (True or False) value:dict = dictionary() for i in range(50):   key = i % 10     if key in dict: dict[key] += 1 else: dict[key] = 1In this case, we do not check what the value of the missing key is but rather we check whether the key is in the dictionary or not. This is a special way of handling an exception which is used rarely.This technique of handling exceptions is known as Look Before You Leap(LBYL).Using try-exceptThe try-except block is one of the best possible ways to handle the KeyError exceptions. It is also useful where the get() and the if and in operators are not supported.Let’s apply the try-except block on our earlier retrieval of prices code:# prices.py prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25} item = input('Get price of: ') try: print(f'The price of {item} is {prices[item]}') except KeyError: print(f'The price of {item} is not known')Here, in this example there are two cases— normal case and a backup case. try block corresponds to the normal case and except block to the backup case. If the normal case doesn’t print the name of the item and the price and raises a KeyError, the backup case prints a different statement or a message.Using try-except-elseThis is another way of handling exceptions. The try-except-else  has three blocks— try block, except block and else block.The else condition in a try-except statement is useful when the try condition doesn’t raise an exception. However, it must follow all the except conditions.Let us take our previous price retrieval code to illustrate try-except-else:# prices.py prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25} item = input('Get price of:') try: print(f'The price of {item} is {prices[item]}') except KeyError: print(f'The price of {item} is not known') else: print(f'There is no error in the statement')First, we access an existing key in the try-except block. If the Keyerror is not raised, there are no errors. Then the else condition is executed and the statement is displayed on the screen.Using finallyThe try statement in Python can have an optional finally condition. It is used to define clean-up actions and is always executed irrespective of anything. It is generally used to release external sources.An example to show finally:# prices.py prices = { 'Pen' : 10, 'Pencil' : 5, 'Notebook' : 25} item = input('Get price of: ') try: print(f'The price of {item} is {prices[item]}') except KeyError: print(f'The price of {item} is not known') finally: print(f'The finally statement is executed')Remember, the finally statement will always be executed whether an exception has occurred or not.How to raise Custom Exceptions in Python?Python comprises of a number of built-in exceptions which you can use in your program. However, when you’re developing your own packages, you might need to create your own custom exceptions to increase the flexibility of your program.You can create a custom Python exception using the pre-defined class Exception:def square(x): if x
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What are Python KeyError Exceptions and How to Han...

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How to Work With a PDF in Python

Whether it is an ebook, digitally signed agreements, password protected documents, or scanned documents such as passports, the most preferred file format is PDF or Portable Document Format. It was originally developed by Adobe and is a file format used to present and transfer documents easily and reliably. It uses the file extension .pdf. In fact, PDF being the most widely used digital media, is now considered as an open standard which is maintained by the International Standards Organization (ISO). Python has relatively easy syntax which makes it even easier for the ones who are in their initial stage of learning the language. The popular Python libraries are well suited and integrated which allows to easily extract documents from a PDF, rotate pages if required, split pdf to make separate documents, or add watermarks in them.Now an important question rises, why do we need Python to process PDFs? Well, processing a PDF falls under the category of text analytics. There are several libraries and frameworks available which are designed in Python exclusively for text analytics. This makes it easier to play with a PDF in Python. You can also extract information from PDF and use into Natural Language Processing or any other Machine Learning models. Get certified and learn more about Python Programming and apply those skills and knowledge in the real world.History of  pyPDF, PyPDF2, pyPDF4The first PyPDF package was released in 2005 and the last official release in 2010. After a year or so, a  company named Phasit sponsored a branch of the PyPDF called PyPDF2 which was consistent with the original package and worked pretty well for several years.A series of packages were released later on with the name of PyPDF3 and later renamed as PyPDF4. The biggest difference between PyPDF and the other versions was that the later versions supported Python3. PyPDF2 has been discarded recently. But since PyPDF4 is not fully backward compatible with the PyPDf2, it is suggested to use PyPDF2. You can also use a substitute package - pdfrw. Pdfrw was created by Patrick Maupin and allows you to perform all functions which PyPDF2 is capable of except a few such as encryption, decryption, and types of decompression.Some common libraries in PythonLet us look into some of the libraries Python offers to handle PDFs:PdfMiner It is a tool used to extract information from PDF documents. PDFMiner allows the user to analyze text data and obtain the definite location of a text. It provides information such as fonts and lines. We can also use it as a PDF transformer and a PDF parser.PyPDF2PyPDF2 is purely a Python library which allows users to split, merge, crop, encrypt, and transform PDFs. You can also add customized data, view options, and passwords to the documents. Tabula-pyIt is a Python wrapper of tabula-java which can read tables from PDF files and convert into Pandas Dataframe or into CSV/TSV/JSON file formats.SlateIt is a Python package which facilitates the extraction of information and is dependent on the PdfMiner package.PDFQueryA light Python wrapper which uses minimum code to extract data from PDFs.xPDFIt is an open source viewer of PDF which also includes an extractor, converter and other utilities. Out of all the libraries mentioned above, PyPDF2 is the most used to perform operations like extraction, merging, splitting and so on.Installing PyPDF2If you're using Anaconda, you can install PyPDF2 using pip or conda. To install PyPDF2 using pip, run the following command in the command line:pip install PyPDF2The module is case-sensitive. So you need to make sure that proper syntax is followed. The installation is really quick since PyPDF2 is free of dependencies.Extracting Document Information from a PDF in PythonPyPDF2 can be used to extract metadata and all sorts of texts from PDF when you are performing operations on preexisting PDF files. The types of data you can extract are:AuthorCreatorProducerSubjectTitleNumber of PagesTo understand it better, let us use an existing PDF in your system or you can go to Leanpub and download a book sample.The code for extracting the document information from the PDF—# get_doc_info.py from PyPDF2 import PdfFileReader def getinfo(path):     with open(path, 'rb') as f:         PDF = PdfFileReader(f)         information = PDF.getDocumentInfo()         numberofpages = PDF.getNumPages()     print(information)     author = information.author     creator = information.creator     producer =information .producer     subject = information.subject     title = information.title if __name__ == '__main__':     path = 'reportlab-sample.pdf'     getinfo(path)The output of the program above will look like—Here, we have firstly imported PdfFileReader from the PyPDF2 package. The class PdfFileReader is used to interact with PDF files like reading and extracting information using accessor methods. Then, we have created our own function getinfo with a PDF file as an argument and then called the getdocumentinfo(). This returned an instance of DocumentInformation. And finally we got extract information like the author, creator, subject or title, etc.getNumPages() is used to count the number of pages in the document. PdfMiner can be used when you want to extract text from a PDF file. It is potent and particularly designed for extracting text from PDF.We have learned to extract information from PDF. Now let’s learn how to rotate a PDF. Rotating pages in PDFA lot of times we receive PDFs which contain pages in landscape orientation instead of portrait. You may also find certain documents to be upside down, which happens while scanning a document or mailing. However, we can rotate the pages clockwise or counterclockwise according to our choice using Python with PyPDF2.The code for rotating the article is as follows—# rotate_pages.py from PyPDF2 import PdfFileReader, PdfFileWriter def rotate(pdf_path):     pdf_write = PdfFileWriter()     pdf_read = PdfFileReader(path)     # Rotate page 90 degrees to the right     page1 = pdf_read.getPage(0).rotateClockwise(90)     pdf_write.addPage(page1)     # Rotate page 90 degrees to the left     page2 = pdf_read.getPage(1).rotateCounterClockwise(90)     pdf_write.addPage(page2)     # Add a page in normal orientation     pdf_write.addPage(pdf_read.getPage(2))     with open('rotate_pages.pdf', 'wb') as fh:         pdf_write.write(fh) if __name__ == '__main__':     path = 'mldocument.pdf'     rotate(path)The output of the code will be as follows—Here firstly we imported the PdfFileReader and the PdfFileWriter so that we can write out a new PDF file. Then we declared a function rotate with a path to the PDF that is to be modified. Within the function, we created a read object pdf_read and write object pdf_write.Then, we used the getPage() to grab the pages. Two pages page1 and page2 are taken and rotated to 90 degrees clockwise and 90 degrees counterclockwise respectively using rotateClockwise() and rotateCounterClockwise().We used addPage() function after each rotation method calls. This adds the rotated page to the write object. The last page we add is page3 without any rotation.Lastly, we have used write() with a file-like parameter to write out the new PDF. The final PDF contains three pages, the first two will be in the landscape mode and rotated in reversed direction and the third page will be in normal orientation.Now we will learn to merge different PDFs into one.Merging PDFsIn many cases, we need to merge two PDFs into a single one. For example, suppose you are working on a project report and you need to print it and bind it into a book. It contains a cover page followed by the project report. So you have two different PDFs and you want to merge them into one PDF. You can simply use Python to do so. Let us see how can we merge PDFs into one.The code for merging two PDF documents using PyPDF in mentioned below:# pdf_merging.py from PyPDF2 import PdfFileReader, PdfFileWriter def pdfmerger(paths, output):     pdfwrite = PdfFileWriter()     for path in paths:         pdfread = PdfFileReader(path)         for page in range(pdfread.getNumPages()):             # Add each page to the writer object             pdfwrite.addPage(pdfread.getPage(page))     # Write out the merged PDF     with open(output, 'wb') as out:         pdfwrite.write(out) if __name__ == '__main__':     paths = ['document-1.pdf', 'document-2.pdf']     pdfmerger(paths, output='merged.pdf')Here we have created a function pdfmerger() which takes a number of inputs and a single output. Then we created a PdfFileReader() object for each PDF path and looped over the pages, added each page to the write object. Finally, using the write() function the object’s contents are written to the disk.PyPDF2 makes the process of merging simpler by creating the PdfFileMerger class.Code for merging two documents using PyPDF2—# pdf_merger2.py import glob from PyPDF2 import PdfFileMerger def merger(output_path, input_paths):     pdfmerge = PdfFileMerger()     file_handles = []     for path in input_paths:         pdfmerge.append(path)     with open(output_path, 'wb') as fileobj:         pdfmerge.write(fileobj) if __name__ == '__main__':     paths = glob.glob('d-1.pdf')     paths.sort()     merger('d-2.pdf', paths)The PyPDF2 makes it simpler in the way that we don’t need to loop the pages of each document ourselves.  Here, we created the object pdfmerge and looped through the PDF paths. The PyPDF2 automatically appends the whole document. Finally, we write it out.Let’s perform the opposite of merging now!Splitting PDFsThe PyPDF2 package has the ability to split up a single PDF into multiple PDFs. It allows us to split pages into different PDFs. Suppose we have a set of scanned documents in a single PDF and we need to separate the pages into different PDFs as per requirement, we can simply use Python to select pages we want to split and get the work done.Code for splitting a single PDF into multiple PDFs—# pdf_splitter.py import os from PyPDF2 import PdfFileReader, PdfFileWriter def splitpdf(path):     fname = os.path.splitext(os.path.basename(path))[0]     pdf = PdfFileReader(path)     for page in range(pdf.getNumPages()):         pdfwrite = PdfFileWriter()         pdfwrite.addPage(pdf.getPage(page))         outputfilename = '{}_page_{}.pdf'.format(             fname, page+1)         with open(outputfilename, 'wb') as out:             pdfwrite.write(out)         print('Created: {}'.format(outputfilename)) if __name__ == '__main__':     path = 'document-1.pdf'     splitpdf(path)Here we have imported the PdfFileReader and PdfFileWriter from PyPDF2. Then we created a function called splitpdf() which accepts the path of PDF we want to split. The first line of the function takes the name of the input file. Then we open the PDF and create a read object. Using the read object’s getNumPages(), we loop over all the pages.In the next step, we created an instance of PdfFileWriter inside the for loop. Then, we created a PDF write instance and added each page to it for each of the pages in the PDF input. We also created a unique filename using the original filename + the word ‘page’ + the page number + 1.Once we are done with running the script, we will have each of the pages of the input PDF split into multiple PDFs. Now let us learn how to add a watermark to a PDF and keep it secured.Adding Overlays/WatermarksAn image or superimposed text on selected pages in a PDF document is referred to as a Watermark. The Watermark adds security features and protects our rational property like images and PDFs. Watermarks are also called overlays.The PyPDF2 allows us to watermark documents. We just need to have a PDF which will consist of our watermark text, image or signature.Code for adding a watermark in a PDF—# watermarker.py from PyPDF2 import PdfFileWriter, PdfFileReader def watermark(inputpdf, outputpdf, watermarkpdf):     watermark = PdfFileReader(watermarkpdf)     watermarkpage = watermark.getPage(0)     pdf = PdfFileReader(inputpdf)     pdfwrite = PdfFileWriter()     for page in range(pdf.getNumPages()):         pdfpage = pdf.getPage(page)         pdfpage.mergePage(watermarkpage)         pdfwrite.addPage(pdfpage)     with open(outputpdf, 'wb') as fh:         pdfwrite.write(fh) if __name__ == '__main__':     watermark(inputpdf='document-1.pdf',               outputpdf='watermarked_w9.pdf',               watermarkpdf='watermark.pdf')The output of the code will look like— There are three arguments of the function watermark(): inputpdf: The path of the PDF that is to be watermarked. outputpdf: The path where the watermarked PDF will be saved. watermarkpdf: The PDF which contains the watermark.Firstly, we extract the PDF page which contains the watermark image or text and then open that PDF page where we want to give the desired watermark.Using the inputpdf, we create a read object and using the pdfwrite, we create a write object to write out the watermarked PDF and then iterate over the pages.Next, we call the page object’s mergePage and apply the watermark and add that to the write object pdfwrite.When the loop terminates, the watermarked PDF is written out to the disk and it’s done!Encrypting a PDFIn the PDF world, the PyPDF2 package allows an owner password which gives the user the advantage to work as an administrator. The package also provides the user password which allows us to open the document upon entering the password.The PyPDF2 basically doesn’t permit any allowances on any PDF file yet it allows the user to set the owner password and user password.Code to add a password and add encryption to a PDF—# pdf_encrypt.py from PyPDF2 import PdfFileWriter, PdfFileReader def encryption(inputpdf, outputpdf, password):     pdfwrite = PdfFileWriter()     pdfread = PdfFileReader(inputpdf)     for page in range(pdfread.getNumPages()):         pdfwrite.addPage(pdfread.getPage(page))     pdfwrite.encrypt(user_pwd=password, owner_pwd=None,                       use_128bit=True)     with open(outputpdf, 'wb') as fh:         pdfwrite.write(fh) if __name__ == '__main__':     encryption(inputpdf='document-1.pdf',                   outputpdf='document-1-encrypted.pdf',                   password='twofish')We declare a  function named encryption() with three arguments—the input PDF path, the output PDF path and the password that we want to keep. Then we create one read object pdfread and one write object pdfwrite. Now we loop over all the pages and add them to the write object since we need to encrypt the entire document.Finally, we call the encrypt() function which accepts three parameters—the user password, the owner password and the whether or not to use 128-bit encryption. The PDF  will be encrypted to 40-bit encryption if the argument use128bit is set to false. Also if the owner password is set to none, then it will be set to user password automatically.Reading the Table data from PDFSuppose you want to work with the Table data in Pdf, you can use tabula-py to read tables in a PDF. To install tabula-py, run:pip install tabula-pyCode to extract simple Text from pdf using PyPDF2:import tabula # readinf the PDF file that contain Table Data # you can find the pdf file with complete code in below # read_pdf will save the pdf table into Pandas Dataframe df = tabula.read_pdf("document.pdf") # in order to print first 5 lines of Table df.head()If you PDF file contains Multiple Tabledf = tabula.read_pdf("document.pdf",multiple_tables=True)If you want to extract Information from the specific part of any specific page of PDFtabula.read_pdf("document.pdf", area=(126,149,212,462), pages=1)If you want the output into JSON Formattabula.read_pdf("offense.pdf", output_format="json")Exporting PDF into ExcelSuppose you want to export a PDF into Excel, you can do so by writing the following code and convert the PDF Data into Excel or CSV.tabula.convert_into("document.pdf", "document_testing.xlsx", output_format="xlsx")Let us sum up what we have learned in the article:Extraction of data from a PDFRotate pages in a PDFMerge PDFs into one PDFSplit a PDF into many PDFsAdd watermarks or overlays in a PDFAdd password or encryption to a PDFReading table from PDFExporting PDF into Excel or CSVAs you have seen, PyPDF2 is one of the most useful tools available in Python. The features of PyPDF2 makes life easier whether you are working on a large project or even when you quickly want to make some changes to your PDF documents. Learn more about such libraries and frameworks as KnowledgeHut offers Python Certification Course for Programmers, Developers, Jr./Sr Software Engineers/Developers and anybody who wants to learn Python.
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How to Work With a PDF in Python

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Web Development Using PHP And MySQL

PHP (or PHP Hypertext Preprocessor) is a server-side scripting language that is used to create dynamic web pages that can interact with databases. It is a widely-used open source language that is specifically used for web application development and can be embedded within HTML. Why PHP? The distinguishing feature of PHP is that the scripting code is executed on the server, which generates HTML that is sent back to the client. The client receives the result of executing the script without knowing the underlying code. Developers can configure the web server to process all the HTML files (containing the PHP script). PHP course is easy to learn for any newcomer, but also offers advanced programming features. Using PHP with a database system PHP, as a scripting language, is popular among web developers because of its ability to interact with database systems including Oracle and MySQL. This article discusses the use of PHP scripting language with the MySQL database. Any website can require a variety of data or information to display and to retrieve them from the database. This can include display of a simple list to the running of the website based on data stored in the database. Listed below are some examples where PHP and MySQL can be used together: • Digital Ad banners, where the PHP script can be used to retrieve a digital banner from the database, which then selects a random banner from its table records and sends it back to the calling script. The PHP script can also maintain a count of banner views and clicks from the website. • Internet forums or digital boards, which use PHP and MySQL to store and retrieve user messages. • Website designing, where the design of an entire website can be changed using a couple of PHP scripts, instead of changing and uploading each web page. The PHP script can access the MySQL database to retrieve all information about the web page. Setting up the MySQL database The procedure of setting up the MySQL database varies according to the host. Every database would require a user name and password, in order to access the database. Database administration can be done using PHP scripts or using a program like PHPMyAdmin. The next step is to create the database tables for storing the website information. Creating a database table using PHPMyAdmin is also simple. Alternatively, one can create and configure the entire database using the following PHP script: CREATE TABLE tablename { Fields } Where the Fields are coded as fieldname type(length) extra_info Example: first varchar(15) NOT NULL The following command is used in the PHP script to connect to the MySQL database: mysql_connect(localhost,$username,$password); where: • localhost is the server address on which the web site is running, • $username is the user name for the database access • $password is the password for the database access Executing PHP commands After configuring and connecting to the MySQL database, you can start executing PHP commands on the server. Following are the 2 methods of executing a PHP command: • Entering the command in PHP using the following syntax: Mysql_query($query) This form of command can be used to repeat the command simply by changing the variable. • Defining the command as a variable. The result of the operation will be assigned to the variable. Data input and output Inserting data using PHP is identical to the procedure of data input using HTML pages. The advantage of using PHP is that the script does not need to be changed for each new piece of input data. Users can also input their own data on the web page. Following is an example of an HTML page with textboxes that can be used to enter data in a form: Alternatively, you can use variables to input information into the database. Example: $first=$_POST[‘first’]; $last=$_POST[‘last’]; $phone=$_POST[‘phone’]; $mobile=$_POST[‘mobile’]; $fax=$_POST[‘fax’]; $email=$_POST[’email’]; $web=$_POST[‘web’]; … $query = “INSERT INTO contacts VALUES (”,’$first’,’$last’,’$phone’,’$mobile’,’$fax’,’$email’,’$web’)”; mysql_query($query); This script is saved in the insert.php file, which can be called from the HTML form. Using this method, data entered in the web page form is stored in the defined variables, which are then passed to the PHP. To display (or output) the entered data using PHP, you can use the following MySQL command with the result assigned to the variable. $query=”SELECT * FROM contacts”; $result=mysql_query($query); PHP provides 2 submission methods, GET and POST to get the data submitted by the form into your PHP script. GET method displays the variables and the data in the page address, while they are invisible in the POST method. For example, a script can be created that will display different web pages depending on the clicked link. yourpage.php?user=david (to show David’s page) yourpage.php?user=tom (to show Tom’s page)
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Web Development Using PHP And MySQL

PHP (or PHP Hypertext Preprocessor) is a server-si... Read More

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