Top 5 Performance optimization tips for Python
Why Performance optimization for Python?
Python is a language that has been really popular among the audience in terms of popularity, functionality and elegance. Research has proven that out of 10, 8 of the computer science departments are teaching the introductory courses for Python. The value of Python has gone above Python in terms of Java. Top-ranking CS departments at UC Berkeley and MIT are switching on to introductory courses to Python. The topmost MOOC providers such as Udemy and Coursera also offer introductory programming courses in Python. Why? Because Python is one of the most preferred languages at the time we were writing the first draft of this blog and by the time it was published. The syntax of Python is quite easy to learn. This would also scale up quite easily when it comes to cloud-based environments. Hence you need to consider performance optimization for Python seriously.
- Prepare the whole set up for testing beforehand
You need to prepare your Python editor before you start. If you are planning to write the files in your local, you need to create a virtual environment as well as activate it. By using the right testing tool, you can leverage pytest as well as “pip”-d in the virtual environment. You would also be able to write more small test scripts. Testing is also going to help you develop thought clarity. This can help you to write programs quickly. You can also refactor the code in a short period of time.
2. Intern the Strings to increase efficiency
This method is used to store only a particular copy meant for each string. The Python interpreter can reuse strings through manipulation of the code to trigger the string interning. When we create a string object, the Python interpreter should determine if the string has to be cached or not. The inherent nature of the interpreter is to reveal itself under specific conditions like identifier processing. Declaring the string with a specific name that starts with an underscore or a letter can include only a single set or combo of letters or numbers. This would allow the Python to intern the string through which you can create a hash.
3. Use internal code dictionaries
Since Python holds more internal code that uses dictionaries, it can lead to perform more identifier searches. Hence if you intern the identifier string, it can hasten the entire process. Since Python has been using a number of internal code with the help of dictionaries, it can lead to performing more searches meant for identifiers. Python would keep a number of identifiers in a single table. It can generate unique keys (hash) per object meant for future lookups. The optimization would happen at the time of compilation.
4. See if the code is working or not
Every developer has their own coding style. With the coding style that you are happy with, you can set the first-ever iteration. You can go on to optimize the code and make the most submissions. You can then check if it passes every code test cases. It is a success if it passes every test. Since Python does not support longer codes in most of the cases, you can easily check if the code you have written is valid or not. If it is not passing every test but fails a few, then you have to know that you still have more work in progress.
5. Leverage the standard library
Make use of the standard library and built-in functions how much ever you can. There are also the generator and list expressions. Make use of the standard library such as itertools since they are extremely faster to operate. If the containers are going to be tiny, then any code differences with the different libraries are going to be less. The cost you involve to create the containers would be above the gains you get.
6. Use Data structures and Algorithms
When you are making your code to run faster, you can use the data structure to speed up the process. You need to keep updating yourself about the latest innovations in Data structures and Algorithms in Python. Every day, there is some or the other new algorithms introduced in Python. This would always help you to stay a step ahead in the development curve. You would not stagnate. This would also give you an upper hand as a developer and code creator.
Why Pattem Digital for Performance optimization in Python?
With Pattem Digital by your side, you can be sure to optimize your Python code as per the standards. Python is going to bring in a lot of change to your product, in a better manner.
We have a team of Python Engineers to guide you. They are going to help you throughout the process.
Feel free to contact us at any point in time. We are here to help without any hesitation!
