Millions of enterprise developers use the programming language Python, among the most popular and fastest-growing coding languages in the world. Python is increasingly used in a wide range of developer job roles and data science positions across industries, moving from a scripting solution for sysadmins, to web development for programmers, to the driving force behind machine learning, according to a Tuesday report from ActiveState.
The report examined how ActiveState customers use its commercial Python offering, ActivePython.
Here are the five most common Python use cases by industry, according to the report:
Top use: Creating business insights with machine learning
Case study: One American multinational finance and insurance corporation faced competition from smaller companies that were introducing services driven by machine learning. To compete, the insurer allowed teams to develop new applications and services using machine learning; however, with too many sets of data science tools involved, a number of different versions of Python and compatibility issues arose. The company settled on one version of Python to deliver all of the machine learning capabilities needed.
2. Retail banking
Top use: Flexible data transformation and manipulation
Case study: A large American department store chain with an in-store banking arm collects data centrally in a warehouse, and then shares it with multiple applications to enable its supply chain, retail banking, and analytics and reporting needs. While the company standardized on Python for data manipulation, each team created its own version, which created problems. The company decided on a single, standard Python build to increase engineering speed and decrease support costs.
Top use: Meeting software system deadlines
Case study: An American multinational aerospace, military, and defense corporation was contracted to provide a number of systems for the International Space Station. While aerospace software focused on critical safety systems is typically written in a language like Ada, those older languages do not lend themselves well to scripting tasks, GUI creation, or data science analysis. Selecting a single Python version offered a larger contract value and no exposure.
Top use: Data mining identify cross-sell opportunities
Case study: An American multinational financial services corporation wanted to mine complex customer and prospect behavioral data as part of a digital transformation project. The company used Python to initiate different data science and machine learning initiatives to examine the structured data it had been collecting for years, and correlated it with unstructured data from the web and social media to increase cross-selling and reclaim resources.
5. Business services
Top use: API access to financial information
Case study: A privately-held financial data and media company had previously provided partners with access to financial information through different electronic resources. Partners wanted to build desktop applications in a variety of languages, including Python, to incorporate the customer’s API directly into their own, and created a Python Software Development Kit (SDK) for their financial information API, leading to increased revenue and customer satisfaction.
For more on Python, check out this TechRepublic article on Python users’ favorite tools.