The document highlights the launch of Visual Studio 2019, emphasizing its features for Python development, including environment management, profiling, and interactive experimentation. It outlines the importance of environments in running Python code and explains the differences between global and virtual environments. Additionally, various professional interests and humorous insights related to machine learning and data science are shared by an experienced software architect.

1. Visual Studio 2019 launch

2. • Software Architect @
o 17+ years professional experience
• Microsoft MVP (Azure)
• External Expert: Horizon 2020
• External Expert: Eurostars-Eureka
• External Expert: InnoFund Denmark
• Professional Interests
o Web, SOA, Integration
o IoT, Machine Learning
o Performance
• Contact
ivelin.andreev@icb.bg
www.linkedin.com/in/ivelin
www.slideshare.net/ivoandreev

3. “Difference between ML and AI?
- If it is written in Python, probably it is ML.
- If it is written in PowerPoint, probably it is AI.”
* * *
“When you’re fundraising, it’s AI. When you’re hiring, it’s ML.
When you’re implementing, it’s linear regression.“
* * *
“Data science is 80% waiting for your model to train and 20%
swearing because it didn't work”
* * *
“How many data scientists it takes to change a light bulb?
20 seniors and one intern.
Data scientists will argue over a month on the right approach while
the intern will copy the solution from StackOverflow.”
Why Python?

4.  Environments, Debugging, Profiling, Intellisense, Live Share
VS Code
executables

5. Visual Studio 2019 launch

6. • Open VS Installer
C:Program Files (x86)Microsoft Visual StudioInstallervs_installer.exe
• From Workloads
• From Installation Details
Installation Steps

7. Visual Studio 2019 launch

8. • Project filters by multiple tags
• Python Application
• From existing Python code
• Template
• Classification Project
• Regression Project
• Clustering Project
• Template
• IronPython Application
• IronPython Windows Forms App.
• IronPython WPF
New Python Project

9. Visual Studio 2019 launch

10. What is an environment?
• Context to run Python code
• Python Interpreter
• Standard Python library
• Standard & installed packages
• Automatic detection of Python interpreters
• Manual identification (fallback)

11. VS2019 Environment Types
• Global
• Available to all projects on computer
• Changes are valid for all projects on that environment
• Prone to version conflicts (different package versions from different projects)
• Easily gets cluttered, no application isolation
• Virtual
• Environment subfolder with copy of interpreter
• Any modifications are valid only in environment
• Environment config. in requirements.txt
• Conda (Miniconda or Anaconda)
• Created with Conda package manager
• Require Anaconda/Miniconda
• Environment config. in a environment.yml

12. Create Virtual Environment
• Describe dependencies requirements.txt
• Manage packages (View, Upgrade, Remove)
• Removing virtual environment from project
• Removes environment completely

13. Visual Studio 2019 launch

14. Interactive Window
• For runtime experimentation of editor code
• Individual for Python environment
• Improved REPL (Read Eval Print Loop) Shell
• Meta commands
• $help, $clear, $cls, $load, $reset, $attach (debug)
• Scope
• Project startup file (default)
• Import [module name] changes scope
• dir() – display valid identifiers in scope

15. Visual Studio 2019 launch

16. Profiling Python Performance
• Start profiling Analyze > Launch Python profiling
• Select profiling target (2 options)
• Project
• Standalone script
• Run script and collect data
• Interactive profiling report

17. DEMO
• Python Project
• Python Toolbar
• Add Environment
• Manage Packages
• Intellisense
• Debugging
• Live Share Session
• Interactive Window

18. aka.ms/pythonvs
aka.ms/pythonblog