Anyone who has needs related to technical projects can be confused or frustrated by the broad range of options available among programming languages. When you have to source an IT project, there is a good chance that you might become intimidated by the number of static and dynamic coding languages to choose from. The needs related to programming languages are specific to each project, but there are certain comprehensive steps for narrowing down the options.
When you have to choose a programming language, you have to keep certain usage patterns or requirements in mind.
- Find out what works for your team
- Figure out what will work in context
- Take into account the ease of learning
- Look at the tools available for each of the programming languages you consider.
- Examine the cross-platform ability
- Evaluate the security and general access provided by the programming languages
When you do most of your work on the web, the language you use should have frameworks and tools to help you with that. However, since all your work is not on the web, it is good if you can use the language for other things also. This can make it easier for you to manage it all and improve maintainability.
If you are a busy developer and bill by the hour, it is better if you can program quickly and provide more value. So, you should have tools to help you prototype quickly and, if you have to change direction, turn around quickly.
Why developers prefer python?
Python is a programming language that offers such attributes, among others.
It has dynamic semantics and is a high-level programming language that is object-oriented. You can use it to develop applications rapidly as it has built-in data structures of a high level, along with dynamic binding and dynamic typing. It is also useful for connecting existing components and, so, can be used as a ‘glue’ or scripting language.
It brings down the cost of program maintenance because it has a syntax which is easy to learn and is focused on readability. Python promotes code reuse and program modularity as it supports packages and modules.
You can freely distribute Python’s extensive standard library and interpreter, which are available in binary or source form, free of charge, for all the main platforms.
Python’s edit-test-debug cycle is very fast as it doesn’t have a compilation step. It is easy to debug Python programs, as a bad input or bug doesn’t cause a segmentation fault. The interpreter raises an exception when it finds an error. The interpreter creates a stack trace when the program doesn’t get the exception.
It is possible to inspect global and local variables through the source-level debugger. Besides, you can examine the code a line at a time, set break points and evaluate arbitrary expressions, among other things.
To debug programs quickly, add a few print statements to the source. This approach is made effective by Python’s quick edit-test-debug cycle.
The main reasons are as follows:
- Mature and stable frameworks for web development
- Standard library supports different programming paradigms and has tools for various tasks
- Frameworks that support fast development
Mature and stable frameworks for web development
Python has a number of mature and stable frameworks for web development. Django is for a larger framework. Tornado is there for frameworks based on event-loop and developed for scaling out concurrent requests. Bottle, Flask and web.py are there for web frameworks that are smaller and without any frills. Generally, client libraries are available for the provision of almost everything required for the functioning of a proper web app.
Python provides connectors of a high quality for nearly every database system available, in addition to access to tools that offer long-running backend processes or caching, among other things.
Standard library supports different programming paradigms and has tools for various tasks
The standard library contains several tools for the performance of various tasks and supports many programming paradigms (functional, procedural and object oriented programming). There are libraries of a very high quality for scientific calculations as well as for image processing. You can also write GUI app in Python as the language has mature bindings for QT and GTK. Python has been used for client side apps, mail routers and shell scripts, among others.
Frameworks that support fast development
Python frameworks enable fast development for the web. For example, Django provides in-built group and user permissions, site admin and forms which are common for most sites. Most of these are modular. The framework lets you use modular sections of your app in other projects and thus promotes reusable apps. For example, if you have integrated a social network with one site, you can use that code for other projects as well. So, you don’t have to create new code every time you build an app.
Additionally, the majority of Python frameworks have a development server. You only have to change a line of code to switch among various database backends, if you use the Django ORM. You can use a real database such as postgres to deploy your app and use sqlite to work on your local machine. Unless you use complicated queries, which is not really required in most projects in any case, there is negligible difference. So, you can run your code locally and work on it almost anywhere, without affecting your base system in terms of setting up or installing databases and servers.
Startups are choosing Python
As you would know, selecting the platform or language for use at a startup is among the most significant decisions.
Many startups choose Python these days. Apparently, PHP is not as good a language as Python, although PHP is somewhat easier to get started with. PHP is not very standardized and there are several ways of doing the same thing.
Python offers better code conciseness and speed of development than Java. For small startups, the ability for new-feature implementation and speed to market are of great significance. A number of modern sites were based on Python, while being small startups. Such websites are usually horizontally scalable, i.e., you can add webservers along with increase in traffic volumes.
According to research conducted by the Altabel Group, Python appears to be favored over Ruby by startups trying to launch a minimum viable product and get venture capital.
This has less to do with either language’s merits than with philosophies that either language’s frameworks represent. It’s hard to beat Ruby on Rails as a framework for developing applications quickly. Django is supposed to do the same, but the community built around Python is minimalistic. Generally, Python developers select tools such as libraries, persistency layers and ORMs on their own.
Many begin Python-based web development with Django but switch to something like Flask, which is more minimalistic. The community appears predisposed to developing its own stack in this manner. On the other hand, Ruby on Rails developers are more likely to ‘hit the ground running’, especially in the field of startups.
Python’s main advantage over Ruby has little to do with the features of the language. Apparently, Python is preferred more by computer scientists. It is becoming more and more popular for scientific and academic applications.
While Ruby offers product solutions that are ‘out of the box’ and slick, Python has more of components such as Tornado that are well-written.
Python also seems to be the better bet as it is used at Google and there is great potential for things like LiveNode getting open source releases.
Why Python is ideal for startups
The first step to get your tech startup up and running, after you have a great business idea, is to decide which programming language to use to write your IT products. Although you can write your product in any language and do it rather well, situations such as those where startups have limited time and budgets can make a difference. Python can prove quite economical in terms of both time and money.
Python is useful for startups in the following ways:
- The specific requirements of startups that Python fulfills
- Python helps tackle complexity
- You can create working prototypes easily
- A small team can write code almost effortlessly
- Python helps startups get investments easily
- Startups can start earning faster using Python
- Good custom support is available
The specific requirements of startups that Python fulfills
At their journey’s beginning, startups usually don’t have much money to spare. They often work with budgets of around $15,000-$20,000. In the IT world, that kind of a budget may not be realistic, except if you work with Python. Secondly, they don’t have much time to convince investors and partners about the project’s potential. Finally, they have to build the product as soon as they can to be able to make their first money and survive.
Python helps tackle complexity
Social networks, media streaming projects and other such startups are typically based on the web and big data drives the web. Python is ideal for web solutions and helps tackle complexity. Using Python, you can overcome issues such as integration of different systems, which would otherwise take a lot more of effort. The language also performs well with respect to scalability. It is essential for startups to gain initial success and grow their businesses in order to do well for many years to follow.
You can create working prototypes easily
Python can provide ready solutions for large projects. If necessary, you can rewrite something written in Python in another language. This can give startups more time to attain success. The faster the startup reaches a breakeven point the better.
Python is very useful for writing prototypes. While other languages can take too long to get there, Python doesn’t need much time and already has a working prototype. Prototypes can help save startups a lot of time and money as they can see through these whether the business idea is likely to work or not.
A small team can write code almost effortlessly
Python lets programmers write proof of concept almost effortlessly. You don’t have to assemble a large team of developers and designers to create a good-quality product. So, startups get a chance to try out various ideas and see how these work. A working prototype can provide the boost of confidence necessary to move forward.
Python helps startups get investments easily
Once you have a system that works, you only have to fix bugs and obtain investments rapidly. Startups have to show the investors what the product is all about, so as to induce them to provide funds. The project won’t progress despite promotion and the niche you find in the market, unless investors agree to provide you the money you require to move forward. Most of the time, proof of concept is used only to persuade investors and not any further in the business.
Startups can start earning faster using Python
Your startup project may flop unless you get to the market and begin earning money quickly. If you build and support your project in Python, the returns will be faster as Python will let you work fast. Also, because of low initial spending, you’ll have a larger profit.
Good custom support is available
This allows your product to be of high quality and be stable and less prone to crashes or flaws. Python provides you with prompt support, besides quick resolution of technical issues.
Startups have to move fast and try to succeed as quickly as they can as competition is fierce. Python helps them have a working product within a month or two and at a very low cost, with the help of a small development team. That makes it one of the best programming languages for startups.