In-Lab Examples (AIST-2110)

This repository contains the Jupyter Notebooks and small helper scripts I use during AIST-2110 labs at Augusta University. Content is organized by week under src/.

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Usage

There are several ways to use these materials:

1. Open in Google Colab (no install)

   • Upload any *.ipynb to Google Drive.
   • Right-click -> Open with -> Google Colab.
   • If you need local files from this repo (e.g., small .py helpers), upload them to the Colab runtime or mount Drive within the notebook.

2. Run locally with a Jupyter server (recommended)

   • Install Python and Jupyter (see “Guidelines for local install” below).
   • Start a Jupyter server:
     • VS Code (recommended, just like CodeSpace): install the Python and Jupyter extensions, open this folder, and open notebooks directly in VS Code.
     • JupyterLab: jupyter lab
     • Classic Notebook: jupyter notebook
   • Select the correct kernel for the notebook (the environment where you installed the dependencies).

3. Run individual Python scripts

   • A few weeks include .py files (e.g., formatting helpers). You can run them directly with python path/to/script.py.

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Guidelines for local install

Recommended: Use uv for fast, reproducible environments. A pyproject.toml and uv.lock are included.

Option A — Using uv (recommended)

1. Install uv
   See: https://docs.astral.sh/uv/getting-started/features/
2. Create/sync the environment

   uv sync

This will create a virtual environment and install all dependencies specified in pyproject.toml. 3. Select the kernel in Jupyter

• If prompted by VS Code/Jupyter, choose the uv virtual environment as the interpreter/kernel.

• Alternatively, register the kernel explicitly:

  uv run python -m ipykernel install --user --name aist2110 --display-name "Python (aist2110)"

Option B — Using pip (simpler, fewer guarantees)

1. Create/activate a virtual environment (optional but recommended)

   python -m venv .venv
   # Linux/macOS:
   source .venv/bin/activate
   # Windows (PowerShell):
   .\.venv\Scripts\Activate.ps1

2. Install minimal tools

   python -m pip install --upgrade pip
   python -m pip install ipython ipykernel 

3. Register a kernel (optional, helps with selection)

   python -m ipykernel install --user --name aist2110 --display-name "Python (aist2110)"

If you prefer VS Code: install the Python and Jupyter extensions, select the interpreter from the Command Palette (“Python: Select Interpreter”), then open any *.ipynb.

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Project Layout

.
├── create_REPL.ps1           # Windows: launches Python REPL with a preloaded clear() helper
├── create_REPL.sh            # macOS/Linux: same as above, POSIX shell script
├── LICENSE                   # Project license
├── pyproject.toml            # Project dependencies & metadata (used by uv/pip)
├── README.md                 # This document
├── src
│   ├── week1
│   │   └── week1_code.ipynb  # Week 1 in-class notebook
│   ├── week2
│   │   ├── test.txt
│   │   └── week2_code.ipynb
│   ├── week3
│   │   └── week3_code.ipynb
│   ├── week4
│   │   └── week4_code.ipynb
│   ├── week5
│   │   ├── in_class.py       # Helper/companion code for Week 5
│   │   ├── ticket.py         # Small exercise or sample program
│   │   └── week5_code.ipynb
│   ├── week6
│   │   ├── grade_formatter.py
│   │   ├── grades.py
│   │   └── week6_code.ipynb
│   ├── week7
│   │   ├── grade_formatter.py
│   │   ├── grades.py
│   │   └── week7_code.ipynb
│   ├── week8
│   │   └── no_class_this_week.txt
│   ├── week9
│   │   └── week9_code.ipynb
│   ├── week10
│   │   └── week10_code.ipynb
│   ├── week11
│   │   └── week11_code.ipynb
│   ├── week13
│   │   └── week13_code.ipynb
│   └── week14
│       └── week14_code.ipynb
└── uv.lock                   # Lockfile for uv to guarantee reproducible installs

• Per-week notebooks: src/weekX/weekX_code.ipynb contain the in-class examples and exercises used that week.
• Helper scripts (Weeks 5–7): small Python modules used in demonstrations (e.g., simple grading/formatting utilities).
• pyproject.toml / uv.lock: define and lock dependencies. Use uv sync to reproduce the environment.

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Python REPL Scripts

If you want a bare Python REPL with a convenient clear() helper (as used in lab):

• Windows (PowerShell):

  # If execution policy prevents running scripts:
  powershell -ExecutionPolicy Bypass -File .\create_REPL.ps1
  # or, if permitted:
  .\create_REPL.ps1

• macOS/Linux:

  chmod +x ./create_REPL.sh
  ./create_REPL.sh

Each script ensures Python 3 is available and then launches a REPL where clear() is pre-defined:

clear = lambda: os.system("cls" if os.name == "nt" else "clear")

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Troubleshooting

• Kernel not found / wrong environment selected

  • Re-install the kernel with:

    # Using uv environment
    uv run python -m ipykernel install --user --name aist2110 --display-name "Python (aist2110)"

  • In VS Code, use “Python: Select Interpreter” and choose the environment created by uv or your venv.

• Permission errors on scripts (macOS/Linux)

  • Add execute permission: chmod +x create_REPL.sh

• Windows PowerShell policy blocks script

  • Run with: powershell -ExecutionPolicy Bypass -File .\create_REPL.ps1

• Package/version mismatches

  • Prefer uv sync (it respects uv.lock). For pip, ensure you’re in the right venv and re-install:

    python -m pip install --upgrade pip
    python -m pip install ipython ipykernel # Version issues are common with pip; uv essentially solves this

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License

See LICENSE for terms.

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