Introduction

Welcome to Mirai Solutions’s Python Technical Guidelines!

About Mirai Solutions

Mirai Solutions is a Zurich-based software development and consultancy firm, delivering cutting-edge technology and best practices to the industry, helping companies elevate their data analytics and operations.

We are an interdisciplinary team of data scientists, software engineers, business consultants and IT architects with specialist knowledge ranging from finance and risk management to math/stats techniques to software development and project management.

Our areas of expertise include Enterprise IT Architecture, Software Engineering & DevOps, Large-Scale Data Analytics, Financial Modeling and Training & Coaching.

The Guides

We structured the guide for an audience of Python practitioners working in or planning to work in enterprise environments. The reader should have a basic understanding of:

• variables and data types
• control flow
• functions
• data structures
• file handling
• exception handling
• basic input/output

Why Learn Python?

Let’s first answer a highly relevant question though: Why would you want to learn Python?

1. Versatility:
   Python is an incredibly versatile language that can be used for a wide range of tasks. It excels in tasks such as web development, data science, machine learning, scripting, automation, game development, and more.

2. Readability and Maintainability:
   Python’s emphasis on readability and clean syntax makes it easier to write and understand code. Its enforced indentation leads to more maintainable and bug-resistant code.

3. Platform Independence:
   Python is platform-independent, allowing applications to run seamlessly on various operating systems, including Windows, macOS, and Linux.

4. Integration Capabilities:
   Python’s ability to integrate with other programming languages and technologies can offer a significant advantage. You can extend Python applications by using C, C++, or Java modules, allowing you to leverage existing code bases and take advantage of performance-critical functionalities on demand.

5. Rich Ecosystem of Libraries and Frameworks:
   Python boasts a vast collection of libraries and frameworks that cater to various needs. From NumPy and pandas for data analysis, TensorFlow and PyTorch for machine learning and deep learning, matplotlib, seaborn and plotly for data visualization, to Flask, Django and FastAPI for web development. Python also offers a number of other frameworks and libraries for interactive data application and dashboards, web scraping, database management, and more.

6. Community Support and Documentation:
   Python has a large and active community that provides a wealth of resources, tutorials, and expert advice. The community-driven development ensures the language remains up-to-date and secure.

R guides

R Logo

If you are interested in learning R, you can access our free R Technical Guidelines here.