Blog

Setting up the development environment
This entry is part 2 of 2 in the series Commodities

In this post I will describe setting up a development environment on a Mac machine. If you are following along and are using Windows I will indicate any differences to the procedure.
1. Creating a Directory
2. Creating a Virtual Environment
3. Add some Python Packages to the Python Virtual Environment
4. Open Project in VS Code
5. Initialise Git
Creating a Directory

I suggest you allocate yourself a directory somewhere on your computer (Mac, Windows, Linux) and then create a sub-directory within for each project your embark on.

To prevent problems with some packages, I suggest you avoid directory names containing spaces.

On my Mac I have a directory on my desktop called Python and within that I have created a sub-directory called commodities.
```
(base) peter@Peters-MacBook-Pro-3 commodities % pwd
/Users/peter/Desktop/Python/commodities
(base) peter@Peters-MacBook-Pro-3 commodities % 
```
Creating a Virtual Environment

I will be using the ta-lib package which sometimes won’t install in pip created virtual environments so I am going to use conda to create my environment instead.

Add some Python Packages

Ta-Lib
```
(commodities) peter@Peters-MacBook-Pro-3 commodities % conda install conda-forge::ta-lib
```
August 13, 2025
Introduction to the Commodity Futures Project

This entry is part 1 of 2 in the series Commodities

In this series of posts, I am going to describe the full setup, design and operation of a Python Django application to acquire and analyse commodity futures with the aim of finding a winning strategy for predicting a [pretend] winning strategy.

Note that this is just for a bit of fun and to demonstrate the power of Python.

In no way should anything written on this website be taken as encouragement to make financial decisions.

August 13, 2025

Exploring the Python os Module: A gateway to the Operating System

Python is widely celebrated for its simplicity and power, and one of the key reasons behind its versatility is the vast collection of built-in modules. Among these, the os module stands out as a foundational tool for interacting with the operating system. Whether you’re managing files, navigating directories, or accessing system variables, the os module makes it easy to perform OS-level tasks directly from Python.

What is the os module?

The os module provides a way of using operating system-dependent functionality like reading or writing to the file system, modifying environment variables, or working with processes. It is a part of Python’s standard library, meaning you don’t need to install anything extra—just import it and you’re ready to go:

Python

import os

import os

Common use cases

Navigating the file system
Listing files and directories
Creating and removing directories
File manipulation
Working with paths
Environment variables

Why use the os module?

The os module abstracts away platform-specific details, allowing your scripts to run across Linux, Windows, and macOS without change. It helps automate workflows, manage resources, and build more powerful, adaptable applications.

Files and Directory Operations

Python

os.getcwd()                  # Get current working directory
os.chdir(path)               # Change current working directory
os.listdir(path='.')         # List files and dirs
os.mkdir(path, mode=0o777)   # Create directory
os.makedirs(path, exist_ok=False)  # Create nested directories
os.rmdir(path)               # Remove empty directory
os.removedirs(path)          # Remove nested directories
os.remove(path)              # Delete a file
os.rename(src, dst)          # Rename/move file or dir
os.replace(src, dst)         # Rename/move, overwrite if needed
os.stat(path)                # Get file metadata
os.scandir(path='.')         # Iterator of DirEntry objects
os.walk(top)                 # Recursively list files/dirs

os.getcwd()                  # Get current working directory
os.chdir(path)               # Change current working directory
os.listdir(path='.')         # List files and dirs
os.mkdir(path, mode=0o777)   # Create directory
os.makedirs(path, exist_ok=False)  # Create nested directories
os.rmdir(path)               # Remove empty directory
os.removedirs(path)          # Remove nested directories
os.remove(path)              # Delete a file
os.rename(src, dst)          # Rename/move file or dir
os.replace(src, dst)         # Rename/move, overwrite if needed
os.stat(path)                # Get file metadata
os.scandir(path='.')         # Iterator of DirEntry objects
os.walk(top)                 # Recursively list files/dirs

Path Manipulation (os.path)

Python

os.path.join(a, b, ...)      # Join paths safely
os.path.abspath(path)        # Absolute path
os.path.basename(path)       # File name from path
os.path.dirname(path)        # Directory from path
os.path.exists(path)         # Path exists?
os.path.isfile(path)         # Is file?
os.path.isdir(path)          # Is directory?
os.path.getsize(path)        # File size in bytes
os.path.split(path)          # (dir, file)
os.path.splitext(path)       # (filename, extension)

os.path.join(a, b, ...)      # Join paths safely
os.path.abspath(path)        # Absolute path
os.path.basename(path)       # File name from path
os.path.dirname(path)        # Directory from path
os.path.exists(path)         # Path exists?
os.path.isfile(path)         # Is file?
os.path.isdir(path)          # Is directory?
os.path.getsize(path)        # File size in bytes
os.path.split(path)          # (dir, file)
os.path.splitext(path)       # (filename, extension)

Environment Variables

Python

os.environ                   # Dict-like env vars
os.environ.get(key, default) # Get env var
os.environ['VAR'] = value    # Set env var
os.putenv(key, value)        # Set env var (less common)
os.unsetenv(key)             # Remove env var

os.environ                   # Dict-like env vars
os.environ.get(key, default) # Get env var
os.environ['VAR'] = value    # Set env var
os.putenv(key, value)        # Set env var (less common)
os.unsetenv(key)             # Remove env var

Process Management

Python

os.system(command)           # Run shell command
os.startfile(path)           # Open file/app (Windows)
os.execv(path, args)         # Replace current process
os.fork()                    # Create process (Unix)
os.spawn*()                  # Start process (multiple variants)
os.kill(pid, sig)            # Send signal to process
os.getpid()                  # Current process ID
os.getppid()                 # Parent process ID

os.system(command)           # Run shell command
os.startfile(path)           # Open file/app (Windows)
os.execv(path, args)         # Replace current process
os.fork()                    # Create process (Unix)
os.spawn*()                  # Start process (multiple variants)
os.kill(pid, sig)            # Send signal to process
os.getpid()                  # Current process ID
os.getppid()                 # Parent process ID

File Descriptor Ops (low-level)

Python

os.open(path, flags, mode=0o777) # Open file descriptor
os.read(fd, n)                   # Read n bytes
os.write(fd, b'some bytes')      # Write bytes
os.close(fd)                     # Close file descriptor

os.open(path, flags, mode=0o777) # Open file descriptor
os.read(fd, n)                   # Read n bytes
os.write(fd, b'some bytes')      # Write bytes
os.close(fd)                     # Close file descriptor

OS Info & Constants

Python

os.name               # 'posix', 'nt', 'java'
os.sep                # Path separator ('/' or '\\')
os.altsep             # Alt path sep (Windows)
os.extsep             # Extension separator '.'
os.pathsep            # PATH separator
os.linesep            # Newline character(s)
os.devnull            # Null device path
os.cpu_count()        # Number of CPUs

os.name               # 'posix', 'nt', 'java'
os.sep                # Path separator ('/' or '\\')
os.altsep             # Alt path sep (Windows)
os.extsep             # Extension separator '.'
os.pathsep            # PATH separator
os.linesep            # Newline character(s)
os.devnull            # Null device path
os.cpu_count()        # Number of CPUs

Miscellaneous

Python

os.urandom(n)         # n random bytes
os.getlogin()         # Logged-in username
os.getuid(), os.getgid()   # User/group ID (Unix)
os.chmod(path, mode)  # Change permissions
os.access(path, mode) # Check permissions

os.urandom(n)         # n random bytes
os.getlogin()         # Logged-in username
os.getuid(), os.getgid()   # User/group ID (Unix)
os.chmod(path, mode)  # Change permissions
os.access(path, mode) # Check permissions

August 9, 2025

Adding Emojis to a Python print statement
The icons in the print() statements — like 🎉, ✅, 🚫 — are Unicode emojis. Python (especially Python 3) supports printing Unicode characters, including emojis, directly to the console — as long as the terminal or console supports Unicode (which most modern terminals do).

🔍 Here’s how it works:
Python
```
print("🎉 Welcome to the Number Guessing Game!")
```
You’re actually inserting a Unicode emoji character (🎉 = U+1F389) as part of the string. Python sees it just like any other string character and prints it.

✅ No special library needed

You don’t need to import any emoji or Unicode library — these are just standard Unicode characters inside your strings.

⚠️ Terminal Support

While this works out-of-the-box on:
- macOS Terminal
- Linux terminal
- Windows Terminal / PowerShell (modern versions)
- VS Code terminal
- PyCharm terminal
…some older terminals might not display the emoji correctly and may show boxes or question marks instead.
August 8, 2025

How to set up a Python Virtual Environment on Mac, Windows or Linux

Setting up a Python virtual environment is one of the most important skills you can learn as a Python developer. It helps you manage dependencies, avoid version conflicts, and keep your global environment clean — especially when working on multiple projects.

In this guide, I’ll walk you through setting up a virtual environment on macOS, Windows, and Linux with clear, step-by-step instructions.

So what is a Virtual Environment?

A virtual environment is a self-contained directory where Python packages can be installed independently of your system’s global Python setup. It’s perfect for:

Keeping dependencies isolated per project
Preventing version conflicts
Making your projects easier to share and deploy

Prerequisites

Before you begin, make sure you have:

Python 3.3 or later installed
pip (Python’s package manager)

To check the system version of Python you have installed on a Mac open a terminal prompt and run:

(base) peter@MacBookPro Python % python -V
Python 3.9.12

(base) peter@MacBookPro Python % python -V
Python 3.9.12

Similarly, to check your pip installation:

(base) peter@MacBookPro Python % pip -V
pip 24.0 from /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pip (python 3.9)
(base) peter@MacBookPro Python %

(base) peter@MacBookPro Python % pip -V
pip 24.0 from /Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pip (python 3.9)
(base) peter@MacBookPro Python %

Create a Project Directory

Create a Directory where you are going to be developing your project and the navigate to it in a terminal or bash window:

(base) peter@MacBookPro Python % mkdir newdirectory
(base) peter@MacBookPro Python % cd newdirectory

(base) peter@MacBookPro Python % mkdir newdirectory
(base) peter@MacBookPro Python % cd newdirectory

Create the Virtual Environment

Enter the following command to create the virtual environment;

Bash

python3 -m venv virtualenvname

python3 -m venv virtualenvname

This will create.a subdirectory containing your virtual environment. I tend to call my virtual environments (or ‘virtual envs’) .venv but the choice is yours,

Activating the Virtual Environment

Mac OS / Linux

Before activation

Bash

(base) peter@MacBookPro sbs %

(base) peter@MacBookPro sbs %

Activated

Bash

(base) peter@MacBookPro sbs % source virtenv/bin/activate<br>(virtenv) (base) peter@MacBookPro sbs %

(base) peter@MacBookPro sbs % source virtenv/bin/activate<br>(virtenv) (base) peter@MacBookPro sbs %

Windows

Command Prompt

myenv\Scripts\activate.bat

myenv\Scripts\activate.bat

Powershell

PowerShell

myenv\Scripts\Activate.ps1

myenv\Scripts\Activate.ps1

Installing Packages

Now that your environment is active, you can install packages without affecting your global Python installation.

An example of how to install a package. With the virtual environment (virtenv) activated:

(virtenv) (base) peter@MacBookPro sbs % pip install requests

(virtenv) (base) peter@MacBookPro sbs % pip install requests

The response I get:

(virtenv) (base) peter@MacBookPro sbs % pip install requests
Collecting requests
  Using cached requests-2.32.4-py3-none-any.whl.metadata (4.9 kB)
Requirement already satisfied: charset_normalizer<4,>=2 in ./virtenv/lib/python3.9/site-packages (from requests) (3.4.2)
Requirement already satisfied: idna<4,>=2.5 in ./virtenv/lib/python3.9/site-packages (from requests) (3.10)
Requirement already satisfied: urllib3<3,>=1.21.1 in ./virtenv/lib/python3.9/site-packages (from requests) (2.4.0)
Requirement already satisfied: certifi>=2017.4.17 in ./virtenv/lib/python3.9/site-packages (from requests) (2025.4.26)
Using cached requests-2.32.4-py3-none-any.whl (64 kB)
Installing collected packages: requests
Successfully installed requests-2.32.4

[notice] A new release of pip is available: 25.1.1 -> 25.2
[notice] To update, run: pip install --upgrade pip
(virtenv) (base) peter@MacBookPro sbs %

(virtenv) (base) peter@MacBookPro sbs % pip install requests
Collecting requests
  Using cached requests-2.32.4-py3-none-any.whl.metadata (4.9 kB)
Requirement already satisfied: charset_normalizer<4,>=2 in ./virtenv/lib/python3.9/site-packages (from requests) (3.4.2)
Requirement already satisfied: idna<4,>=2.5 in ./virtenv/lib/python3.9/site-packages (from requests) (3.10)
Requirement already satisfied: urllib3<3,>=1.21.1 in ./virtenv/lib/python3.9/site-packages (from requests) (2.4.0)
Requirement already satisfied: certifi>=2017.4.17 in ./virtenv/lib/python3.9/site-packages (from requests) (2025.4.26)
Using cached requests-2.32.4-py3-none-any.whl (64 kB)
Installing collected packages: requests
Successfully installed requests-2.32.4

[notice] A new release of pip is available: 25.1.1 -> 25.2
[notice] To update, run: pip install --upgrade pip
(virtenv) (base) peter@MacBookPro sbs %

The pip process will install any dependencies which may or may not already be present on your local system so the response you get may vary from mine.

The key point is you should receive a success message similar to line 10 in the example above.

Note: whenever you use pip for the first time in a virtual environment, you will receive a notice that your pip version is out of date (lines 12 & 13 in the example). Running an out of date version doesn’t appear to make any difference but you may want to consider upgrading (line 13) if only to remove this annoying message.

August 7, 2025

Number guessing 2

This entry is part 2 of 2 in the series Number Guessing

1 Number Guessing

Python

import random

def number_guessing_game():
    print("🎉 Welcome to the Number Guessing Game!")
    print("I'm thinking of a number between 1 and 100...")

    # Generate a random number between 1 and 100
    secret_number = random.randint(1, 100)
    attempts = 0

    while True:
        try:
            guess = int(input("Enter your guess: "))
            attempts += 1

            if guess < 1 or guess > 100:
                print("🚫 Please enter a number between 1 and 100.")
                continue

            if guess < secret_number:
                print("📉 Too low! Try again.")
            elif guess > secret_number:
                print("📈 Too high! Try again.")
            else:
                print(f"✅ Congratulations! You guessed it in {attempts} attempts.")
                break

        except ValueError:
            print("⚠️ Please enter a valid number.")

import random

def number_guessing_game():
    print("🎉 Welcome to the Number Guessing Game!")
    print("I'm thinking of a number between 1 and 100...")

    # Generate a random number between 1 and 100
    secret_number = random.randint(1, 100)
    attempts = 0

    while True:
        try:
            guess = int(input("Enter your guess: "))
            attempts += 1

            if guess < 1 or guess > 100:
                print("🚫 Please enter a number between 1 and 100.")
                continue

            if guess < secret_number:
                print("📉 Too low! Try again.")
            elif guess > secret_number:
                print("📈 Too high! Try again.")
            else:
                print(f"✅ Congratulations! You guessed it in {attempts} attempts.")
                break

        except ValueError:
            print("⚠️ Please enter a valid number.")

August 5, 2025

Number guessing 1

This entry is part 1 of 2 in the series Number Guessing
Number Guessing

August 5, 2025
Beginners Guide to GIT
Here’s a concise guide to the main Git commands and what they do. These are essential for version control and collaboration in software development:

Setup & Configuration
- git config –global user.name “Your Name”
  Set your Git username.
- git config –global user.email “you@example.com“
  Set your Git email.
Repository Management
- git init
  Initialize a new Git repository.
- git clone <url>
  Copy a remote repository to your local machine.
Tracking Changes
- git status
  Show the current state of the working directory and staging area.
- git add <file>
  Stage changes for commit.
- git add .
  Stage all changes in the current directory.
- git commit -m “message”
  Save staged changes with a descriptive message.
Branching & Merging
- git branch
  List all branches.
- git branch <name>
  Create a new branch.
- git checkout <branch>
  Switch to another branch.
- git merge <branch>
  Merge changes from another branch into the current one.
Working with Remotes
- git remote -v
  View remote repository URLs.
- git push
  Upload local commits to a remote repository.
- git pull
  Fetch and merge changes from a remote repository.
- git fetch
  Download changes from a remote repository (without merging).
Viewing History
- git log
  View commit history.
- git diff
  Show changes between commits, branches, or files.
- git show <commit>
  Show details of a specific commit.
Undoing Changes
- git reset <file>
  Unstage a file.
- git checkout — <file>
  Discard changes in a file.
- git revert <commit>
  Create a new commit that undoes a previous one.
Would you like a printable cheat sheet or a visual diagram to go with this?

In Git, “staged” refers to files that have been marked to be included in the next commit. It’s part of Git’s three-stage workflow:

Git Workflow States
1. Working Directory\ This is where you make changes to your files. These changes are not yet tracked by Git for committing.
2. Staging Area (Index)\ When you run git add <file>, Git moves the file to the staging area. This means you’re telling Git:\ “I want to include this change in the next snapshot (commit).”
3. Repository (Commit History)\ When you run git commit, Git takes everything in the staging area and saves it permanently in the repository as a new commit.
Example Workflow

# You modify a file

nano hello.py

# You stage the file

git add hello.py

# You commit the staged file

git commit -m “Add greeting script”

Only files that are staged will be included in the commit. If you modify other files but don’t stage them, they won’t be part of that commit.
August 4, 2025
Importing packages into Python

In Python, the import statement is used to bring in modules and their functionality so you can use them in your code. There are several variations of the import statement, each serving different purposes depending on what and how you want to import.

1. Basic Import

import math

This imports the entire math module. You access its functions with the module name:

math.sqrt(16)

2. Import with Alias

import numpy as np

This imports the module and gives it a shorter alias (np), which is useful for long module names or common conventions.

3. Import Specific Functions or Classes

from math import sqrt, pi

This imports only the specified items from the module. You can use them directly:

sqrt(25)

4. Import All (Not Recommended)

from math import *

This imports everything from the module into the current namespace. It’s discouraged because it can lead to name conflicts and makes code harder to read.

5. Dynamic Import (Using __import__)

module_name = “math”

math_module = __import__(module_name)

This is useful when the module name is determined at runtime.

6. Import from a Package

If you have a package with submodules:

from mypackage import submodule

Or even deeper:

from mypackage.submodule import myfunction

7. Relative Imports (Used in Packages)

from . import sibling_module

from ..parent_package import parent_module

These are used within packages to refer to other modules relative to the current module’s location.

August 4, 2025
Python: not necessarily as easy as they make out

1. Misunderstanding What “Easy” Means

Python has a simple syntax, but that doesn’t make programming itself easy. Logic, problem-solving, debugging, and understanding how computers “think” are still challenging — especially for those with no prior coding experience

2. Too Much Theory, Not Enough Practice

Many learners get stuck in “tutorial hell” — watching endless videos or reading about Python syntax without actually writing code. Without consistent practice, the concepts don’t stick.

✅ Tip: Build small projects early, even if they’re messy.

3. Confusion About Python Versions & Setup

Installing Python and dealing with versions (e.g., Python 2 vs Python 3), virtual environments, or package managers like pip can be confusing at first — especially on Windows or Linux.

✅ Tip: Beginners should follow a guided setup tutorial tailored to their OS.

4. Abstract Concepts Like Loops, Functions, and OOP

Things like loops, functions, and especially object-oriented programming can be hard to grasp without visual or practical examples. These are core concepts that take time to internalize.

✅ Tip: Use analogies and diagrams (like comparing functions to “kitchen recipes”) to make ideas more tangible.

5. Lack of a Clear Learning Path

New learners often jump between random tutorials, not knowing whether to focus on web development, data science, or automation. Without a roadmap, motivation fades.

✅ Tip: Choose one path (e.g., web apps with Flask, or data analysis with pandas) and go deep.

6. Debugging Frustration

Even a missing colon can crash your code. For beginners, error messages are often cryptic, and knowing how to fix bugs takes time and experience.

✅ Tip: Use an IDE like VS Code with Python extensions — it’ll catch many errors early.

7. Overwhelming Amount of Libraries and Tools

Python has libraries for everything — from web scraping to AI — but this abundance can overwhelm beginners. It’s hard to know what’s essential vs. what can wait.

✅ Tip: Start with the standard library and learn just enough to solve your current problem.

8. Fear of “Not Being Good Enough”

A lot of people compare themselves to others online. When they struggle with things that “should be easy,” they assume they’re not smart enough — which isn’t true.

✅ Tip: Programming is a skill, not a talent. You get better by doing, not by knowing everything upfront.

Summary

Python is a great first language, but learning to program involves way more than just syntax. With patience, the right guidance, and consistent practice, anyone can become proficient — but it takes time. If you’re struggling, that’s normal.

Want to make it easier? Start building something small — even a basic calculator — and learn as you go. That’s how real progress happens.

Would you like me to turn this into a blog post, infographic, or short video script for your site?

August 3, 2025

Blog

Creating a Directory

Creating a Virtual Environment

Add some Python Packages

Ta-Lib

In no way should anything written on this website be taken as encouragement to make financial decisions.

What is the os module?

Common use cases

Why use the os module?

Files and Directory Operations

Path Manipulation (os.path)

Environment Variables

Process Management

File Descriptor Ops (low-level)

OS Info & Constants

Miscellaneous

🔍 Here’s how it works:

✅ No special library needed

⚠️ Terminal Support

So what is a Virtual Environment?

Prerequisites

Create a Project Directory

Create the Virtual Environment

Activating the Virtual Environment

Mac OS / Linux

Before activation

Activated

Windows

Command Prompt

Powershell

Installing Packages

Setup & Configuration

Repository Management

Tracking Changes

Branching & Merging

Working with Remotes

Viewing History

Undoing Changes

Git Workflow States

Example Workflow

1. Misunderstanding What “Easy” Means

2. Too Much Theory, Not Enough Practice

3. Confusion About Python Versions & Setup

4. Abstract Concepts Like Loops, Functions, and OOP

5. Lack of a Clear Learning Path

6. Debugging Frustration

7. Overwhelming Amount of Libraries and Tools

8. Fear of “Not Being Good Enough”

Summary