With the increasing number of users in the digital world, a lot of raw data is being generated out of which insights could be derived. This is where REST APIs come into picture, as they help in filling the communication gap between the client (your software program) and the server (website’s data) Introduction REST APIs act as a gateway to establish a two-way communication between two software applications.
With increasing number of power hungry applications, the demand for speed and low latency has become a challenge in certain situations. However, the availability of machines with multiple processors/processors with multiple cores help us combat such situations. This post would guide you through using multiprocessing in python. Introduction In contemporary times, a lot of CPUs are being manufactured with multiple cores to boost performance by enabling parallelism and concurrency of applications.
Often we build applications which might require several tasks to run simultaneously within the same application. This is where the concept of multithreading comes into play. This post provides a comprehensive explanation of using the Multithreading(Threading) module in Python. Introduction Multithreading a.k.a Threading in python is a concept by which mutliple threads are launched in the same process to achieve parallelism and multitasking within the same application. Executing different threads are equivalent to executing different programs or different functions within the same process.