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A115 is a London-based consultancy helping fast-growing businesses and scale-ups build sophisticated on-prem or cloud-based technology platforms when code quality matters.

We specialise in rapidly building, securing and scaling cloud-native greenfield platforms to add new capabilities or expand into new markets. With over 20 years' experience productionising experimental code and complex systems, A115 provides end-to-end services - from initial architecture and infrastructure design through development, deployment and maintenance. Leveraging expertise across industries and technologies like Python, SQL, AWS and Azure, A115 enables clients to launch innovative products faster while ensuring robustness, resilience and regulatory compliance.

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Python Training

Re-introduction to Python for Software Engineering

From Coding to Building Production Quality Code

Today, professionals without formal training in software engineering are often driven to learn just enough Python syntax to hack together scripts and proof-of-concept code that seem to work and gets the job done. As soon as requirements grow in complexity, their tangled webs of glued-together code quickly reach dead ends and begin breaking in unexpected ways. Businesses that are scaling up realise the need for software engineers with deep understanding of fundamental computer science basics and their application to building production-quality software.

This book fills the knowledge gap, guiding novice coders to think like seasoned software engineers with a pragmatic, hands-on approach to building modern business software. It grounds programming fundamentals in real-world business objectives. Readers gain mathematical clarity for taming complexity, while focusing on production-quality code.

Walking through essential data types and collections, the book bridges theory with practice. It introduces techniques for managing code complexity early on, instilling habits that prevent future pitfalls. Readers learn indispensible reusable code patterns to construct reliable, maintainable systems.

With lucid explanations and thought-provoking exercises, the book develops computational thinking skills applicable across domains. It covers core concepts for efficient data manipulation, enhanced through Python's elegant syntax and teaches you how to write truly "Pythonic" code.

Finally, the book connects Python's versatile data analysis capabilities with the modern world of connected systems and networked data. Readers learn the fundamentals of APIs and micro-services, readying them to participate in scalable distributed software architectures that are so widespread today.

Table of Contents

  • Invitation
  • Part 0: Setting the Stage for Productive Learning
  • Part 1: Introducing Fundamental Building Blocks - Data Types
  • Part 2: Working with Collections of Data
  • Part 3: The Dictionary Data Type and Conditional Logic
  • Part 4: Encapsulating Code into Reusable Functions
  • Part 5: Powerful Data Generation and Transformation Techniques
  • Part 6: The Essential Patterns of Data Manipulation
  • Part 7: On Code Quality and Managing Complexity
  • Part 8: Guiding Principles and Coding Best Practices
  • Part 9: Type Annotations and Reusability for Readable Code
  • Part 10: Dependency Management for Organised Projects
  • Part 11: Bundling Data with Behaviors using Classes and Objects
  • Part 12: Handling Exceptions Gracefully
  • Part 13: Working with Larger Datasets Stored in Files
  • Part 14: Gaining Confidence through Automated Testing
  • Part 15: Accessing Networked Data via APIs

Jordan Dimov is an experienced software consultant specializing in business process automation, Python code quality, cloud solutions, software engineering training and AI. With over 20 years in the industry, Jordan helps companies boost their productivity by building high-quality, scalable, bespoke software solutions.

Consulting some of the fastest growing brands in the UK and globally, the founder of A115 has a no-nonsense educational approach to modern enterprise software engineering.

Jordan's expertise spans a wide range of technologies and domains:

* Building cloud-based ETL data pipelines for industries like commodity trading and asset management
* Developing e-commerce platforms, online payment processing, and bespoke invoicing, billing, bookkeeping and accounting solutions
* Creating generative AI applications using Python, FastAPI, HuggingFace models, and vector databases
* Productionising code and optimizing software architecture for performance and reliability
* DevOps and infrastructure-as-code using AWS CDK, Azure, Terraform, and Kubernetes

Some of Jordan's notable projects include:

* A position and P&L visualization tool for Shell's trading desks, saving millions by improving efficiency
* An AWS-based platform for automating power trading auctions at Shell and LimeJump
* A high-throughput trading analytics platform for Centrica using Python, Kafka, and serverless tech
* Building multi-currency e-commerce and payments infrastructure for international expansion for a number of clients
* An innovative SMS parking payments system processing 100K+ transactions daily for the city of Sofia, Bulgaria

With strong communication skills, Jordan excels at understanding complex business needs, defining technical solutions, and leading teams to deliver results. He brings a focus on code quality, software security, and process optimization to every project.

Contact Jordan to discuss how he can help your company leverage technologies like Python, cloud platforms, and AI to solve business challenges and achieve your goals.

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