Introduction to Python Programming – A Complete Guide to Installing Python and Setting Up Your Environment

Jupyter Notebook, JupyterLab, PyCharm, VS Code and IDLE

Installing Python and Choosing an IDE

Differences, official websites, installation steps, commands, shortcuts and classroom practice

Learning outcomes

• Explain the difference between Python, an interpreter, a package manager, a notebook, a code editor, and an IDE.
• Select Jupyter Notebook, PyCharm, VS Code, or IDLE according to the task.
• Install and verify Python using safe commands.
• Launch Jupyter Notebook and create, run, save, and close a notebook correctly.
• Create and run a Python file in PyCharm or VS Code.
• Use common package-management commands and important keyboard shortcuts.
• Recognize and solve beginner problems such as ‘Python not found,’ ‘Jupyter not found,’ and ModuleNotFoundError.

Contents at a glance

• 1. Essential terms and how the tools work together
• 2. Text editor versus IDE
• 3. Difference between Python, Anaconda, Jupyter, IDLE, PyCharm and VS Code
• 4. Which tool should be used for which purpose?
• 5. Official websites and safe downloads
• 6. Route A: Anaconda + Jupyter (recommended for the workshop)
• 7. Route B: Python.org + pip + Jupyter
• 8. Installing and using PyCharm
• 9. Installing and using VS Code
• 10. Commands and shortcuts
• 11. Common errors and solutions
• 12. Guided practical, revision and glossary

1. Essential terms: understand these before installation

Most important idea: Python is the language and interpreter. Jupyter Notebook, PyCharm, and VS Code are interfaces in which we write and run Python. Installing an IDE alone does not always install Python.

Term	Easy meaning
Python	A programming language. The Python interpreter reads and executes Python instructions.
Interpreter	The program that actually executes Python code. Without a working interpreter, the Run button cannot execute Python.
IDE	Integrated Development Environment: one application that combines editing, running, debugging, project tools and code assistance.
Code editor	A flexible text editor designed for code. Extra features are commonly added through extensions.
Notebook	An interactive document made of cells. It can contain code, Markdown explanation, output, equations and charts.
Kernel	The running computational process behind a Jupyter notebook. It stores variables and executes cells.
Package / library	Reusable code written by others, such as pandas for data tables or matplotlib for graphs.
pip	Python’s package installer. It downloads and installs Python packages into a selected interpreter/environment.
conda	A package and environment manager supplied with Anaconda/Miniconda. It can manage Python and non-Python dependencies.
Environment	An isolated place containing a particular Python version and packages for one course or project.

Figure 1. The IDE/notebook provides the workspace; the Python interpreter performs the execution.

File types you will see

Extension	Meaning	Where commonly used
.py	A Python script file. It usually runs from top to bottom.	IDLE, PyCharm, VS Code, terminal
.ipynb	A Jupyter notebook containing cells, outputs and metadata.	Jupyter Notebook, JupyterLab, VS Code, PyCharm
.csv	A comma-separated data file.	pandas, Excel, notebooks
.txt	A plain text file.	Any text editor or IDE

2. Text editor versus IDE

A plain text editor can write code, but it normally does not understand the complete Python project. An IDE adds tools that help us write, test and correct programs. VS Code starts as a code editor but becomes IDE-like after installing Python and Jupyter extensions.

Feature	Plain text editor	IDE / IDE-like setup
Write text	Yes	Yes
Syntax colours	Usually limited	Yes
Automatic suggestions	Usually no	Yes: autocomplete / IntelliSense
Run code	Usually requires a terminal command	Run button and terminal options
Find errors	Mostly manual	Warnings, linting and error highlighting
Debug step by step	Usually no	Yes: breakpoints, step-over, variable view
Manage projects	Basic files only	Folders, interpreters, tests and version control
Computer resources	Very light	Usually heavier

Advantages of an IDE over a plain text editor

• Syntax highlighting makes keywords, strings, numbers, and comments visually different.
• Autocomplete reduces typing and spelling mistakes.
• Immediate error indicators help students locate missing brackets, incorrect indentation, and undefined names.
• A Run button executes code without repeatedly typing a terminal command.
• A debugger can pause the program and show how variables change line by line.
• Interpreter selection helps a project use the correct Python installation and packages.
• Project navigation, search, refactoring, testing, and Git support become available in one place.

Balanced view: A text editor is still useful for very small changes and for learning command-line execution. An IDE is not ‘better for every task’; it is better when its assistance saves time or prevents mistakes.

3. Difference between the available tools

Tool	What it is	Best use	Main file	Remember
Python	Language + interpreter	Running Python code	.py	Essential; not an IDE
Anaconda Distribution	Python distribution	Easy scientific/data setup	Many	Includes Python, conda, Jupyter and many packages
Anaconda Navigator	Graphical launcher	Opening Jupyter and managing environments without commands	N/A	Not an IDE and not Python itself
IDLE	Simple editor + shell	First tiny scripts and immediate experiments	.py	Usually installed with Python from python.org
Jupyter Notebook	Interactive notebook	Teaching, data analysis, graphs and explanations	.ipynb	Best starting point for this workshop
JupyterLab	Advanced notebook workspace	Multiple notebooks, files, terminals and data	.ipynb	More powerful interface than classic Notebook
PyCharm	Full Python IDE	Structured Python projects and debugging	.py / .ipynb	Python-focused and feature-rich
VS Code	Extensible code editor	Python plus many other languages and tools	.py / .ipynb	Needs Python and extensions configured

Jupyter Notebook versus JupyterLab

Point	Jupyter Notebook	JupyterLab
Interface	Focused on one notebook	Workspace with tabs, file browser, terminals and notebooks
Beginner learning	Very easy	Easy, but has more visible options
Large data workflow	Adequate	More convenient
Commands	jupyter notebook	jupyter lab
File format	.ipynb	.ipynb

4. Which tool should be used for what purpose?

Situation	Recommended tool	Reason
First B.Pharm practical class	Jupyter Notebook	Students can see code, explanation, and output together.
Biostatistics, data tables and graphs	Jupyter Notebook or JupyterLab	Interactive analysis and visual output are convenient.
Very first five-line Python script	IDLE or Jupyter	Minimum setup and fewer distractions.
Larger multi-file Python application	PyCharm	Strong project structure, refactoring, and debugging.
Python plus HTML, SQL, R, JavaScript or other tools	VS Code	One flexible editor can support many languages through extensions.
Institution-managed laboratory	Python.org + venv + pip, or an institution-approved distribution	The institution can control versions, licensing, and packages.
Low-storage computer	Python.org + IDLE, or Miniconda	Smaller than the full Anaconda Distribution.

Simple recommendation: For this B.Pharm course, start with Jupyter Notebook. Later, introduce VS Code or PyCharm after students understand variables, operators, strings, conditions, and loops.

5. Official websites and safe downloads

Always download software from the official website. Search advertisements and third-party download pages may provide old, modified or bundled installers.

Product	Official website	Purpose
Python	https://www.python.org/downloads/	Python interpreter and IDLE
Jupyter	https://jupyter.org/install	Official pip/conda installation commands
Anaconda Distribution	https://www.anaconda.com/download	Python, conda, Jupyter and data-science packages
Anaconda install guide	https://www.anaconda.com/docs/getting-started/anaconda/install/windows-gui-install	Windows graphical installation steps
PyCharm	https://www.jetbrains.com/pycharm/download/	Python-focused IDE
VS Code	https://code.visualstudio.com/download	Cross-platform code editor
VS Code Python tutorial	https://code.visualstudio.com/docs/python/python-tutorial	Python interpreter, extension and editor setup
IDLE documentation	https://docs.python.org/3/library/idle.html	IDLE editor and shell

Important Anaconda note: Anaconda’s current website includes licensing conditions for some organizations. A college or institution should review the current Terms of Service before a laboratory-wide deployment. Python, Jupyter, and pip can also be installed directly without the full Anaconda Distribution.

6. Route A – Install Anaconda and use Jupyter Notebook

Recommended classroom route: This is usually the easiest route for beginners because one installer supplies Python, Conda, Jupyter Notebook, JupyterLab, and many scientific packages. Use this route only after the individual or institution accepts the current Anaconda terms.

A. Before installation

• Use a Windows 10 or Windows 11 computer with sufficient free space.
• Save or close important work before installation.
• Remove incomplete older Anaconda installations if they are causing conflicts; do not delete working environments without backup.
• Decide on a simple course folder, for example, Documents\BPharm_Python.
• Do not install a second Python distribution unless you understand how to select interpreters and environments.

B. Download and install on Windows

Step 1—Open the official download page

Visit https://www.anaconda.com/download and choose the Windows 64-bit graphical installer appropriate for the computer.

Step 2—Start the installer

Open the downloaded .exe file from the Downloads folder. If Windows asks for permission, verify the publisher and continue.

Step 3 – Accept the license terms

Read the current terms and select I Agree only if they are acceptable for the intended use.

Step 4 – Choose the user scope

For a personal student computer, ‘Just Me’ normally avoids administrator and permission problems.

Step 5—Choose a simple location

Keep the suggested location or use a folder without special characters. The official guide advises avoiding spaces or special characters where possible.

Step 6: Complete installation

Keep the default options unless the institution provides different instructions. Finish the installer, then open Anaconda Navigator or Anaconda Prompt from the Start menu.

C. Verify the installation

Open Anaconda Prompt from the Windows Start menu. Type one command at a time and press Enter.

Verification commands

conda –version python –version jupyter –version

A version number means the command was found. The exact number may differ from the examples shown in class; that is normal.

D. Create the course folder and open Jupyter

Commands in Anaconda Prompt

cd %USERPROFILE%\Documents mkdir BPharm_Python cd BPharm_Python jupyter notebook

The command starts a local Jupyter server and normally opens the file browser in your default web browser. The address usually begins with http://localhost:. This does not mean the notebook is stored on a public website; the program is running on your computer.

Do not close the prompt immediately: The Anaconda Prompt window is running the Jupyter server. Save your notebook, use File > Shut Down or close the notebook interface as appropriate, then return to the prompt and press Ctrl+C (confirm if asked) to stop the server.

E. Open Jupyter without commands

1. Open Anaconda Navigator from the Start menu.
2. Find Jupyter Notebook or JupyterLab.
3. Select Launch.
4. Navigate to the BPharm_Python folder.
5. Create a new Python notebook.

F. Create and run the first notebook

1. Select New > Python 3 (or the available Python kernel).
2. Rename the notebook from Untitled to 01_First_BPharm_Program.
3. Click the first code cell and type the program below.
4. Press Shift+Enter to run the cell.
5. Check the output and save the notebook with Ctrl+S.

First B.Pharm example

medicine_name = “Paracetamol” tablet_strength_mg = 500 print(“Medicine:”, medicine_name) print(“Strength:”, tablet_strength_mg, “mg”)

Expected output: Medicine: Paracetamol and Strength: 500 mg. The value 500 is only a programming example; it is not a prescribing or dosing instruction.

G. Create an optional course environment

An environment keeps the course packages separate from unrelated projects. For a very first class, the base environment may be used if the faculty has already prepared it. For a clean setup, use:

Optional environment commands

conda create -n bpharm_python python conda activate bpharm_python conda install jupyter numpy pandas matplotlib seaborn scipy jupyter notebook

To leave the environment later, use conda deactivate. The environment name bpharm_python can be changed, but avoid spaces.

7. Route B—Install Python from python.org and add Jupyter

Use this route when: You want a smaller, direct setup; the institution does not want the full Anaconda Distribution; or you want to learn standard Python, venv, and pip commands.

A. Install Python

Step 1 – Download Python

Go to https://www.python.org/downloads/ and choose the latest stable Python 3 installer supported by your operating system.

Step 2—Run the installer

On a traditional Windows installer, select the option that makes Python available from the command line (commonly shown as Add python.exe to PATH). Newer installer experiences may present this differently.

Step 3—Complete installation

Keep the standard components, including pip and IDLE, unless institutional policy says otherwise.

Step 4 – Open a new terminal

Close old Command Prompt windows and open a fresh Command Prompt or PowerShell so the updated command path is loaded.

B. Verify Python and pip

Preferred Windows commands

py –version py -m pip –version

If the py command is unavailable but Python works, use `python –version` and `python -m pip –version` instead. Using python -m pip is safer than typing only pip because it connects pip to the selected interpreter.

C. Create a virtual environment

Windows Command Prompt

cd %USERPROFILE%\Documents mkdir BPharm_Python cd BPharm_Python py -m venv bpharm_env bpharm_env\Scripts\activate

After activation, the prompt normally shows (bpharm_env). PowerShell may require a different activation command or an institution-approved execution policy; use the local IT policy rather than bypassing security controls.

D. Install and launch Jupyter

Install the classroom packages

python -m pip install –upgrade pip python -m pip install notebook jupyterlab numpy pandas matplotlib seaborn scipy jupyter notebook

For JupyterLab, use jupyter lab. To finish, save files, stop the server with Ctrl+C, and run deactivate to leave the virtual environment.

8. Installing and using PyCharm

PyCharm is a Python-focused IDE from JetBrains. Since PyCharm 2025.1, JetBrains provides one unified PyCharm product: essential core features remain free, while advanced Pro features require a subscription after the trial. Current official documentation states that core Jupyter support is included in the free functionality.

Installation steps

Step 1—Install Python first

Use Python from python.org, Anaconda/conda, or allow PyCharm to create/select an interpreter during project setup.

Step 2—Download PyCharm

Visit https://www.jetbrains.com/pycharm/download/ and download the installer for Windows.

Step 3 – Install

Run the installer or use JetBrains Toolbox. Keep the default keymap unless you already use another one.

Step 4 – Create a project

Open PyCharm > New Project. Select a project folder and a Python interpreter. A project-specific virtual environment is good practice.

Step 5 – Create a Python file

Right-click the project folder > New > Python File. Name it first_bpharm_program.py.

Step 6 – Run

Enter the program and select the green Run button, or use the Windows shortcut Shift+F10 for the current run configuration.

first_bpharm_program.py

batch_number = “BPH-001” stock_units = 120 print(“Batch:”, batch_number) print(“Stock units:”, stock_units)

Interpreter check: If PyCharm underlines an installed package as missing, open Settings > Project > Python Interpreter and confirm that the project is using the same environment in which the package was installed.

9. Installing and using VS Code

VS Code is a general-purpose code editor. For Python work, three separate pieces are required: VS Code, the Microsoft Python extension and a Python interpreter. The official VS Code documentation clearly states that the Python extension does not include Python itself.

Installation steps

Step 1 – Install Python

Install Python from python.org or an approved conda distribution.

Step 2 – Install VS Code

Download it from https://code.visualstudio.com/download and complete the Windows installer.

Step 3—Install the Python extension

Open Extensions with Ctrl+Shift+X, search for Python by Microsoft and install it.

Step 4—Install the Jupyter extension

Install Jupyter by Microsoft if you will open or create .ipynb notebooks.

Step 5—Open the course folder

Select File > Open Folder and choose BPharm_Python.

Step 6 – Select the interpreter

Press Ctrl+Shift+P, choose Python: Select Interpreter and select the correct Python or course environment.

Step 7 – Create and run a file

Create first_bpharm_program.py, type the code, save it, and use the Run Python File play button. The integrated terminal can also run python first_bpharm_program.py.

Terminal command to run a .py file

python first_bpharm_program.py

Opening a notebook in VS Code

1. Create a file ending in .ipynb or open an existing notebook.
2. Select the kernel shown near the upper-right area of the notebook editor.
3. Choose the environment that contains the required packages.
4. Use Shift+Enter to run a cell and move to the next cell.

10. Essential command reference

Command	Purpose
py –version	Show the Python version through the Windows launcher.
python –version	Show the Python version for the active interpreter.
python file_name.py	Run a Python script.
python -m pip –version	Show pip linked to the active Python interpreter.
python -m pip install package_name	Install a package with pip.
python -m pip install –upgrade package_name	Upgrade one package.
python -m pip uninstall package_name	Remove one pip package after confirmation.
python -m pip list	List installed pip packages.
python -m pip show pandas	Show details and installation location of pandas.
py -m venv bpharm_env	Create a virtual environment on Windows.
bpharm_env\Scripts\activate	Activate that environment in Windows Command Prompt.
deactivate	Leave a venv environment.
conda –version	Show the conda version.
conda create -n bpharm_python python	Create a conda environment.
conda activate bpharm_python	Activate a conda environment.
conda deactivate	Leave the active conda environment.
conda list	List packages in the active conda environment.
conda install pandas	Install pandas through conda.
conda remove pandas	Remove pandas from the active conda environment.
jupyter notebook	Start Jupyter Notebook.
jupyter lab	Start JupyterLab.
jupyter –version	Show installed Jupyter component versions.

Package rule for beginners: First activate the correct environment. Then install the package. Avoid mixing conda and pip randomly in the same environment. Prefer conda for packages available in the chosen conda channel; use pip when necessary and document what was installed.

11. Keyboard shortcuts

Shortcuts may vary by operating system, keyboard layout, software version, and custom keymap. The tables below use common Windows defaults. Always open the program’s Keyboard Shortcuts/Keymap screen when a shortcut behaves differently.

Jupyter Notebook: two modes

Mode	How to enter	What the keyboard controls
Edit mode	Enter or click inside a cell	Typing and editing inside the selected cell
Command mode	Esc or click outside the editing area	Whole-cell and notebook actions

Common beginner error: Pressing A, B, M or D works as a notebook command only in Command mode. Press Esc first.

Shortcut	Action	Mode
Shift+Enter	Run the cell and move to the next cell	Both / common
Ctrl+Enter	Run the cell and stay on it	Both / common
Alt+Enter	Run the cell and insert a new cell below	Both / common
Ctrl+S	Save the notebook	Both
Enter	Enter Edit mode	Command
Esc	Enter Command mode	Edit
A	Insert cell above	Command
B	Insert cell below	Command
M	Change selected cell to Markdown	Command
Y	Change selected cell to Code	Command
C / X / V	Copy / cut / paste selected cell	Command
D, D	Delete selected cell (press D twice)	Command
Z	Undo cell deletion	Command
1 to 6	Change Markdown cell to heading level 1-6	Command
L	Toggle line numbers for the selected cell	Command
I, I	Interrupt a busy kernel	Command
0, 0	Restart the kernel	Command
H	Show keyboard shortcuts	Command
Tab	Indent or request completion	Edit
Shift+Tab	Show information/tooltip when available	Edit
Ctrl+/	Comment or uncomment selected code	Edit; version/keymap dependent

PyCharm shortcuts (Windows default keymap)

Shortcut	Action
Shift+F10	Run the current run configuration
Shift+F9	Debug the current run configuration
Ctrl+Shift+F10	Run the current context/file
Ctrl+/	Comment or uncomment selected lines
Ctrl+Alt+L	Reformat code
Ctrl+Space	Code completion
Alt+Enter	Show quick fix / intention action
Double Shift	Search everywhere
Ctrl+Shift+A	Find an action by name
Ctrl+Alt+S	Open Settings

VS Code shortcuts (Windows)

Shortcut	Action
Ctrl+Shift+P or F1	Open Command Palette
Ctrl+Shift+X	Open Extensions
Ctrl+`	Open or hide the integrated terminal
Ctrl+S	Save
Ctrl+/	Comment or uncomment selected lines
Shift+Alt+F	Format the document
F5	Start debugging
Ctrl+F5	Run without debugging when a suitable run action is configured
Ctrl+K, Ctrl+S	Open Keyboard Shortcuts
Ctrl+P	Quickly open a file
Shift+Enter	Run notebook cell and advance (in a notebook)
Ctrl+Enter	Run notebook cell and stay (in a notebook)

IDLE shortcuts

Shortcut	Action
F5	Run Module (save the .py file first if prompted)
Ctrl+S	Save
Ctrl+N	New file
Ctrl+F	Find
Ctrl+Space	Show completion when available

12. Jupyter notebook operations students must know

Operation	What to do
Create a cell	Use + / Insert, or press Esc then A (above) or B (below).
Write code	Select a Code cell, press Enter and type Python code.
Write explanation	Press Esc then M, type Markdown, and run the cell to format it.
Run a cell	Press Shift+Enter.
Save	Press Ctrl+S and confirm the notebook name.
Interrupt	If a cell never finishes, use Kernel > Interrupt or Esc then I, I.
Restart	Use Kernel > Restart when the variable state is confusing or the kernel fails.
Run all	After restart, use Run > Run All Cells to reproduce the notebook from the beginning.
Download	Use File > Save and Export/Download as available. Keep the original .ipynb file.
Close safely	Save, close/shut down the notebook, then stop the terminal server with Ctrl+C.

Why restarting and running all cells is important

Jupyter remembers variables created earlier in the current kernel. A notebook may appear to work even when cells were executed in a confusing order. Before submission, save the notebook, restart the kernel, and run all cells from top to bottom. If it still works, the notebook is more reproducible.

Correct top-to-bottom order

# Cell 1 tablet_weight_mg = 500 # Cell 2 print(tablet_weight_mg)

13. Common errors and easy solutions

Problem	Likely reason	Solution
‘python’ is not recognized	Python is not on the command path, or the terminal was opened before installation.	Open a new terminal; try py –version; repair/reinstall Python using the official installer if needed.
‘jupyter’ is not recognized	Jupyter is not installed in the active environment.	Activate the correct environment; install notebook/jupyterlab; use Anaconda Prompt for Anaconda.
ModuleNotFoundError	The package is missing from the interpreter/kernel currently running the code.	Check the selected interpreter/kernel; install the package into that environment.
Kernel keeps showing busy	A cell may contain a long calculation or infinite loop.	Use Interrupt. If necessary, restart the kernel, correct the code, and run again.
NameError	A variable name is misspelled or the cell that creates it was not run.	Check spelling and execute cells from the beginning.
IndentationError	Spaces at the beginning of a line do not follow Python’s block structure.	Align lines carefully; use the editor’s formatting/indent guides.
No output appears	The cell/file was not run, or the expression was assigned without print in a script.	Run the cell/file; use print(…) when needed.
Wrong package version	A different interpreter or environment is selected.	Check python –version, package details and the IDE/kernel interpreter selector.
Notebook opens in the wrong folder	Jupyter was started from another directory.	Stop it, change directory with cd, and start jupyter notebook again.
Browser page closed	The Jupyter server may still be running in the prompt.	Use the URL displayed in the prompt, or stop and restart Jupyter safely.

Safe diagnostic commands

Windows Command Prompt / Anaconda Prompt

where python where jupyter python –version python -m pip –version python -m pip show pandas

The where command shows which executable will run. If multiple paths are listed, the first one is normally used. Do not delete files from these locations blindly; select the correct interpreter or ask the lab administrator.

14. Practical

Objective: Confirm that Python and the selected interface work by creating one Markdown explanation cell and three executable code cells.

Part A – Create the notebook

1. Open the BPharm_Python folder and start Jupyter Notebook.
2. Create a Python 3 notebook.
3. Rename it 02_IDE_Installation_Check.ipynb.
4. Change the first cell to Markdown and type the title: # Python Installation Check.
5. Run the Markdown cell with Shift+Enter.

Part B – Execute the cells

Cell 1 – Output test

print(“Python is working correctly.”)

Cell 2 – Store values

medicine_name = “Paracetamol” batch_number = “BPH-001” stock_units = 120

Cell 3 – Display values

print(“Medicine:”, medicine_name) print(“Batch:”, batch_number) print(“Stock units:”, stock_units)

Part C—Verification checklist

• [ ] The notebook name is correct and ends in .ipynb.
• [ ] The Markdown heading is formatted, not shown with the # symbol after execution.
• [ ] All three code cells show a completed execution count.
• [ ] The output is correct, and no red error message is displayed.
• [ ] The notebook is saved.
• [ ] After Kernel Restart and Run All, the same output appears.

15. Quick revision

Question	Answer
Is Python an IDE?	No. Python is a language and interpreter.
Is Anaconda Navigator an IDE?	No. It is a graphical launcher and environment/package interface.
Is Jupyter Notebook a normal .py editor?	It is primarily an interactive .ipynb notebook interface.
Does the VS Code Python extension include Python?	No. Install/select a Python interpreter separately.
Which tool is recommended first for this course?	Jupyter Notebook.
Which is strongest for a structured Python-only project?	PyCharm.
Which is flexible for many languages?	VS Code.
What is the Jupyter kernel?	The process that executes code and stores variables.
What does Shift+Enter do?	Runs the current notebook cell and advances.
Why restart and run all?	To prove that the notebook works in a clean, top-to-bottom order.

16. Glossary

Word	Meaning
Autocomplete	Suggestions that complete variable, function or file names while typing.
Breakpoint	A marker that pauses a program during debugging.
Debugging	Finding and correcting errors by examining the program’s execution.
Extension	An add-on that gives VS Code or another editor additional features.
Kernel	The process that runs notebook code.
PATH	A system list of folders searched when a command is typed.
Package manager	A tool such as pip or conda that installs and manages packages.
Prompt / terminal	A text window in which commands are typed.
REPL / shell	An interactive place that reads one instruction, evaluates it and shows the result.
Virtual environment	An isolated Python setup for one project or course.

17. Final recommendation for the B.Pharm Python Students

Stage	Use	Reason
Initial classes	Jupyter Notebook	Best for explanation, code, output and graphs in one teaching file.
Data-analysis classes	JupyterLab or Jupyter Notebook	Interactive work with tables, statistics and plots.
Programming projects	PyCharm	Strong Python project organization and debugging.
Mixed-technology projects	VS Code	Supports Python, notebooks, SQL, web files and many extensions.
Very simple/offline fallback	IDLE	Installed with standard Python and suitable for tiny scripts.

Teacher’s one-line explanation: Python is the engine; Jupyter, PyCharm and VS Code are different dashboards used to control that engine.

Official references

Official documentation checked on 16 August 2026. Interfaces, shortcuts, versions and licensing can change, so use these links for the latest instructions.

• Python Software Foundation – Download Python: https://www.python.org/downloads/
• Python documentation – IDLE: https://docs.python.org/3/library/idle.html
• Project Jupyter – Installing Jupyter: https://jupyter.org/install
• Jupyter Notebook documentation – Notebook Basics: https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Notebook%20Basics.html
• Anaconda – Windows graphical installer: https://www.anaconda.com/docs/getting-started/anaconda/install/windows-gui-install
• Anaconda – Distribution download: https://www.anaconda.com/download
• JetBrains – Install PyCharm: https://www.jetbrains.com/help/pycharm/installation-guide.html
• JetBrains – Unified PyCharm overview: https://www.jetbrains.com/help/pycharm/unified-pycharm.html
• Microsoft – Getting Started with Python in VS Code: https://code.visualstudio.com/docs/python/python-tutorial
• Microsoft – VS Code keyboard shortcuts: https://code.visualstudio.com/docs/configure/keybindings

Educational note: All medicine names, batch numbers, stock figures and strengths in these notes are simulated examples used only to teach programming. They are not clinical or dosing advice.

Dr. Arpana Chaturvedi

HOD-IT, Associate Professor (Department of IT and Data ANalytics, AI ML)

New Delhi Institute of Management