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  - ANTLR
    
    ANTLR
    
    Parser and ANTLR4
    
    From parser to interpreter
    
    Parser, intepreter and compiler
  - Airflow + PySpark
  - Parallel and distributed computing
    
    Parallel and distributed computing
    
    Intro
    
    Communication between processes
    
    Dask, Modin and Celery libraries
  - Data versioning
  - Data Science - focus Pharma
  - Technical debt and architectural smell
  - Django
    
    Django
    
    Introduction to Django
    
    Django models
    
    Django authentication and model form
  - Docker
    
    Docker
    
    Intro Docker
    
    Advanced concepts
  - FastAPI
    
    FastAPI
    
    Intro
    
    First API with TDD approach
    
    SQLModel
    
    Back-end with FastAPI and SQLModel
    
    Async, OAuth2, profiling and dockerization
  - Flask
    
    Flask
    
    Intro to Flask
    
    Advanced Jinja and forms
    
    Flask with database
    
    Review
    
    App evolution
    
    Blueprints, refactoring and automated testing
    
    Authentication
    
    Profiles, roles and blog
    
    Heroku and docker - deploy
    
    Rest API
  - Generative AI
    
    Generative AI
    
    Discovering large language model
    
    Building an intelligent agent with LangChain, Gradio, and OpenAI
  - Genropy
    
    Genropy
    
    Introduction, demo, and first steps
    
    Bag, Structure, ORM, and project start
    
    UI resources, lookup tables, and formula columns
    
    Other UI resources, data import, hierarchical tables,printing, users, multi-tenancy
    
    Users, Staff, and Donors in a multi-tenant perspective Users, Staff, and Donors in a multi-tenant perspective
    On this page
    
    Intro
    
    Material
    
    Meetup video
  - Exception handling
  - Bear and hunters game
    
    Bear and hunters game
    
    Part 1
    
    Part 2
  - Git basics
  - GitHub Actions
  - GPT Detection system
  - GraphQL and Strawberry
  - Introduction to Machine Learning
    
    Introduction to Machine Learning
    
    Introduction to Machine Learning and Scikit-Learn
    
    Scikit-Learn pipeline, metrics, and linear regression
    
    Scikit-Learn - unsupervised learning
  - Introduction to Deep Learning
    
    Introduction to Deep Learning
    
    Introduction to Deep Learning and TensorFlow
    
    Neural Networks for images
    
    Recurrent Neural Networks
  - Introduction to Kubernetes
    
    Introduction to Kubernetes
    
    Part 1
    
    Part 2
  - Introduction to Databricks
  - Learning Python through games
    
    Learning Python through games
    
    Python basics
    
    PyGameZero
    
    Creating games
    
    Review and creation of complex games
  - Text manipulation
    
    Text manipulation
    
    Introduction to regular expressions
    
    Regex library in Python
    
    Text analysis pipeline and Spacy
    
    A text analysis and classification project with ML
  - Micropython
    
    Micropython
    
    Introduction to the makers world
    
    IoT e cloud
  - MkDocs
    
    MkDocs
    
    Main elements of mkdocs
    
    Extra, plugins and site deployment
  - Modern data engineering
    
    Modern data engineering
    
    State of the art and Apache Airflow
    
    Project
  - Modern python development
    
    Modern python development
    
    Tools, libraries, best practices for Python development
    
    Poetry, PDM, Ruff, and other useful tools
  - MLOps
    
    MLOps
    
    Introduction to MLOps
    
    MLOps on AWS
  - ML Pipeline
    
    ML Pipeline
    
    Introduction to Pytorch
    
    Introduction to Hydra
  - NLP - topic modeling
  - NVIDIA Triton
  - Open Source
    
    Open Source
    
    First interview - Marcelo Trylesinski
    
    Second interview - Patrick Arminio
    
    Third interview - Juliana Nicacio
    
    Fourth interview - Giovanni Barillari
  - Pandas basics
    
    Pandas basics
    
    Introduction and csv module
    
    Operations with dataframes
    
    Series and exercises
    
    Live coding and in-depth discussions
    
    In-depth, indexing, filters, multiIndexing
  - Data analysis learning path
    
    Data analysis learning path
    
    Pandas - data manipulation
    
    Tools for data visualization
    
    Tools for data engineering
    
    Tools for production deployment
  - Polars
    
    Polars
    
    Introduction to Polars
    
    Data wrangling with Polars
    
    Discover functime
  - Pygame
    
    Pygame
    
    Introduction to pygame
    
    Sprites, collisions, and simulations
    
    Animations, camera, and gravity
  - Python basics
    
    Python basics
    
    Basic concepts and primitive types
    
    Flow control, iterations, and functions
    
    Basic OOP
    
    Advanced OOP
  - Reinforcement learning - DIAMBRA
    
    Reinforcement learning - DIAMBRA
    
    Theoretical concepts and environment setup
    
    Practical session and coding
  - Robotic Process Automation
  - Squirrel Telegram Bot
  - Telegram Bot
  - Tensorflow serving
  - Testing and documenting data
  - Testing with python
    
    Testing with python
    
    Testing - Intro
    
    Testing - Pytest and unittest
    
    Testing - Doctest and behave
  - Twitter sentiment analysis
  - Web scraping
    
    Web scraping
    
    Beautiful Soup and Requests
    
    Selenium and Scrapy
  - XGBoost
Learning
Learning
- Better code
  Better code
  - Bandit
  - Black
  - Flake8
  - Mypy
  - Pydantic
  - Ruff
- Create a package
  Create a package
- Data analysis
  Data analysis
  - DuckDB
  - Numpy
  - Pandas
  - Polars
- Document your code
  Document your code
- Linux basics
  Linux basics
- Manage dependencies
  Manage dependencies
  - Anaconda
  - PDM
  - Pipx
  - Poetry
  - Poetry avanzato
  - Pyenv
  - Virtualenv
- Extra material
- MkDocs tutorial
  MkDocs tutorial
  - Setup
  - Document your code
  - Extra functionalities
  - Deploy
    Deploy
    
    Deployment
    
    Github pages
  - Extensions
  - MkDocs vs Sphinx
- Pre-commit
- Project structure
  Project structure
  - Bear
- Python basics
  Python basics
  - Perchè Python
- Advanced Python
  Advanced Python
- Manage different python versions
  Manage different python versions
  - ASDF
  - REPL
- Roadmap
  Roadmap
- Manage configurations
  Manage configurations
- Tech independence
  Tech independence
- Testing
  Testing
  - Tutorial
    
    Tutorial
    
    Introduction
    
    What a Test Looks Like
    
    Types
    
    Good practices for writing tests
    
    Unittest
    
    Using pytest
    
    Doctest
    
    BDD tests with Behave
  - Resources
    
    Resources
    
    Bibliography
    
    Software
    
    Code snippets
    
    Reccommended talks
- VS Code
Blog
Blog
Supporters
Supporters
Speakers
Speakers
- Speaker guide

On this page

Intro
Material
Meetup video

Users, Staff, and Donors in a multi-tenant perspective

Intro¶

In this bonus video, we continue learning Genropy through pair programming, incrementally improving our open-source project "Blood Donor." We address topics related to managing multi-tenant projects and users with different profiles.

Material¶

Meetup video¶

February 25, 2024

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Other UI resources, data import, hierarchical tables,printing, users, multi-tenancy

Exception handling

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