Best Practices in Django development

Google reinvented Python in past decade through its ambitious project called “Unladen swallow” that give name and fame to the language. Interestingly Google pause the project in the middle due to some internal problem still Python gained a performance boost of around three times than before. As a result, Python became a better choice for the industry to develop enterprise standard software applications. Moreover, Python get a tremendous support from the industry due to its exceptional performance for huge applications and that brought a positive vibe for Python among the software developers. In this situation, Django was born to make the Python development process not only easier but also efficient and faster. Django believes on “perfection within time frame” i.e., it doesn’t compromise on the quality of the Python application but it does the task efficiently within less time and deadline.

Develop efficient Python app in less time: As we discussed above Django is a powerful Python framework that helps the Python developers in developing quality and reliable end product in less time. It provides an awesome platform for Python web developers to develop modern futuristic web solutions for the industry that are backed with modern technologies and services. It provides performance report through various bottleneck calculations for your application like load testing, reliability, page loading time etc. This will definitely help the web developer to develop high performance web applications.

Django is MTV framework: Unlike common MVC architecture for frameworks Django provides a new generation MTV framework i.e., model template view architecture. Well this is not very different from that of MVC pattern. Rather it is the simpler form of the former. In MVC the view describes the interface for user data of the application but, in case of MTV, the same data is projected to the user but in a different form i.e., in a template. So it is just an advanced version of MVC architecture.

Develop asynchronous pages in Django: Django supports AJAX which is nothing but the foundation of asynchronous web application. Now the Python Django developers will get the advantage of AJAX and JSON while developing modern web applications for different devices that run on low memory like smart phones and tablets. Moreover, this will exert a dynamic look and feel to the web page of the application and hence this will improve the user experience as well as performance of the application.

Django templates are thin: As we discussed above about the MTV architecture of Django; now it’s time to spend few lines for the new template concept. Well Django provides a repository of templates for its Python developers. The best part is all these templates are extremely light weight but beautiful. These light weight or thin templates when integrated into the application creates light weight apps that are the requirement of the future generation browsers. Sometimes you may decide not to use any of those thin templates then Django gives you the freedom to integrate your own template for your application!! This proves the flexibility nature of Django.

Migration process is painless: Last but not the least, Django framework provides all types of support when a Python developer wants to migrate to a latest version of Django. This is a seamless process from the developer’s point of view. The best part is you can migrate to a lower version without any issue!!

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Avoid these mistakes while using Python for Big Data

Python – A true friend of web developer: Python is one of those old languages which were developed to give tough competition with C and C++. No need to say, it is highly inspired from the object oriented programming approach of C++ with some enhanced features within it. Due to its similarity with C and C++, it can be used for developing machine programming, mobile application development, desktop application and web application too. Its motto is “Batteries included” indicates its potential to develop huge applications at a very less time due to presence of all necessary and common methods and modules. Hence, Python gets maximum priority from the software developers while developing any big data application. It has the potential to develop big applications in small time with maximum efficiency. At the same time due to its large library, often the web developer miss to use the inbuilt optimized functions which creates trouble in future like performance issue, optimisation issue and synchronization issues. Let us have a quick look over these common mistakes made by the Python developers while dealing with big data projects.

Django - The web framework for perfectionists

Django a web framework for modern web developers: In the era of web applications, it will be unfair if we don’t discuss about an powerful web development tool of the industry. We are talking about Django!! Last week, one of my friends asked me about Python programming. I told him that, Python is a super powerful language just like Java or in some cases it is better than Java. Moreover, if we compare the inbuilt functions, modules etc then Python is simply unbeatable. Python developers can deveop any complex and huge project with much better efficiency and accuracy that any other language. That time, we discussed about Django which is a Python web framework. Though Python can be used to develop any type of applications starting from web apps, Desktop apps, Mobile Apps etc but, Django is dedicated to web apps only and fortunately it performs outstanding for its cause.

Pythonista - What is it and how does it help in iOS development?

Pythonista can be called a universal app which is used for the writing as well as execution of Python scripts as an interpreter for iOS. This solid app allows the working as well as running of core Python modules. In fact, the design is such that it is more than simply an app. In terms of interface and navigation, some differences are there between the iPad and iPhone versions. However, there is a certain consistency in Pythonista across the platforms. There are several features in it which are similar to a respectable code editor.

This application acts as a great companion that helps in learning Python language with its interactive prompt. This prompt function allows experimentation as well as has plenty of examples. Another great feature is that the whole documentation can be easily read within the app itself. The design is extremely attractive with lots of non-standard UI controls and subtle shading. The syntax highlighting feature contains six colour schemes for highlighting. It even includes two solarised options- light and dark. It is obvious that the application is the fruit of a lot of thought as well as consideration.

One of the most loved features of the app is the code editor which contains almost every feature that a person can possibly think of. The extended keyboard that it has is specifically meant for Python writing. The code editor with code completion advantage can be extended even with the scripts of a developer. The keyboard has a couple of extra rows which lend some additional keys for better and unique functions while writing Python. The features like auto pairing as well as code completion have been implemented with a lot of style. For example, with code completion the set of buttons is translucent and hover out of way. With the typing of function name, the completion list changes. Gesture controls is also there which gives a satisfying as well as smooth effect.

The scripts of Script library can be easily organized by virtue of this app. You can choose two kinds of views- a traditional list-like view and something which is known as snippet view. In the snippet view scripts are seen as thumbnails; the first code lines are given as preview. In both the views the scripts may be sorted by modified dates or names. There is a + button on the top which allows addition of scripts. Existing ones can be deleted by tapping the Edit button. Document library can be easily navigated. The library does not contain any hierarchy or folders.

There are several easily usable libraries which act as boons for incorporation of multitouch, sound as well as 2D graphics. They are really simple to work with; even accelerometer can be used for creation of interactive experiments or motion-controlled games.

Writing of codes has become a simple matter due to the interactive prompt as well as code completion features. With interactive prompt, a particular thing can be tried out very quickly. The code can be automatically completed by the suggestions that appear just above the keyboard. In fact, even the suggestions come coloured as per the chosen colour scheme. There is a “auto-complete bubble’ that appears while typing; typing on it allows Pythonista to complete the code. Another great thing about this feature is that only class names, functions, etc which is related to the imported module will be suggested.

If you are one those people you wants to conduct amazing things on their iOS enabled devices with Python, then Pythonista is the perfect answer to your prayers. This extremely powerful tool helps the developer take all the advantages, making it a compulsory app for everyone working in Python. You can hire developers from top python development companies in India who can help you build products within allocated budgets and time schedules.

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Moving from Python 2.7 to 3- Some pros & cons

It has been quite some time that Python 3 has been introduced in the software community, but due to some technical glitches, it was not widely accepted. Earlier, it did not have the basic Python libraries like SciPy and NumPy but now they have been imported. In fact, it is an incremental release and that is why the casual programmers may not have many new features to use. But it has now ironed out the glitches as well as quirks which were there in the earlier versions, making the syntax consistent. So before moving to version 3, here are some pros and cons to know about.

Pros

Using compatible syntax- There are many common features between versions 2.7 and 3 due to backporting which essentially allows you to use them in the old scripts, subsequently making the transition very easy. Like % operator that works in version 3; only the format method is different, and that gives increased flexibility.

Unicode support- The version’s text model has been revised which makes the primary string type totally Unicode-capable. Thus the models used in Unicode-capable Windows APIs, JVM, .NET CLR, etc. and Python 3 are brought closer. Its interpreter core is more tolerant to paths containing Unicode characters, which leads to less chances of problems when running scripts on Windows from home directory if, for example, the user name has non-ASCII characters. In fact, the support is more deeply embedded in the language itself. Since a huge variety of Unicode characters are now allowed, developers can use other languages, apart from English when naming; they do not have to use names which suit the fixed character set.

Set literals- Sets in the version have new literal syntax. {1, 2, 3} can be written instead of the set([1, 2, 3)]; the former is quite clean. In fact, both work perfectly, but using the new one gives less problems.

Abstract base classes- Support to make abstract base classes is contained by abc module; in it a property or method may be marked as “abstract” on base classes and implemented in subclasses. This is for definition of interfaces with the creation of classes which has no concrete method(s). One example of the concept is the mathematical class hierarchy.

Cons

Using ported libraries- The pure libraries may be converted semi-automatically to Python 3 but those depending on C extensions are really hard to port. Many libraries have been already ported, but there are some which have not been ported yet. However, this may not be of much problem if the project is small.However, in case of large scale projects this might pose a problem.

Differences in builtin functions- All functions of the previous version are not compatible or rather related to the Python 3 counterparts. Like when you use filter function, an iterator is returned in version 3 but the previous versions return a list. The same is applicable for .keys method.

Filesystem access- It is assumed by the software that all the filesystems have encoding, but then as a matter of fact, there is no encoding in many Linux systems as well as OS X. In fact, different rules for Unicode normalization are applied for filesystem on OS X than for applications. So the filename has to be normalized manually to separate encoding when filenames have to be compared in file system.

Beginners in the world of programming can benefit if they learn Python 3, especially if they do not know C. All in all, there is no huge difference between the implementation of Python 2.7 and 3. In fact, the usage of version 3 seems to be a complicated procedure for many, especially if the project is a big one and there is less time for unit testing. When unit testing is conducted the ultimate code turns out to be well tested as well as reproducable. Porting to Python 3 will yield in plenty of minor and innocent changes, but this will make it more dangerous, making it necessary to test particular and individual functions in the scripts. This will ultimately lead to profit in the long run, but you will have to waste some of your precious time which could have been devoted in bettering the application and other such things.

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