Simple Tasks

This repository contains small Python scripts and examples for practicing common tasks, scientific or biochemical calculations, and data manipulation.

Repository Structure

python-simple-tasks/
├── README.md
├── bioinformatics/
│   ├── files/
│   ├── adenine_counter.py
│   ├── calculate_rmsd_numpy.py
│   ├── find_nearest_value.py
│   ├── protein_contacts.py
│   └── sequence_length_calculator.py
├── chemistry/
│   └── peptide_bond_distance.py
├── utils/
│   └── ip_validator.py
└── visualization/
    ├── plots/
    ├── 3d_surface_plot.py
    ├── barcelona_meteo.py
    ├── plot_trig_functions.py
    └── string_visualization.py

Scripts Overview

chemistry/

• peptide_bond_distance.py
  Calculates the distance of a peptide bond between a carbon (C) atom of the carbonyl group and a nitrogen (N) atom of the next amino acid residue using 3D Euclidean distance.
  Usage:

 python chemistry/peptide_bond_distance.py

Expected Output: distance in Ångstroms (~1.23 Å)

bioinformatics/

• adenine_counter.py
  Counts the number of adenines (A) in one or more DNA sequences provided as command-line arguments.
  Supports all IUPAC nucleotide codes (A, C, G, T, R, Y, S, W, K, M, B, D, H, V, N).
  If a sequence contains invalid characters, it prints an error message instead of counting.

  Usage:

  python bioinformatics/adenine_counter.py ATGCA NRYTGA

Example Output:

  Sequence 'ATGCA' has 2 adenine(s).
  Sequence 'NRYTGA' has 1 adenine(s).

• calculate_rmsd_numpy.py
  Calculates the Root Mean Square Deviation (RMSD) between two sets of atomic coordinates using NumPy.
  • Reads atomic coordinates directly from two PDB-like structures embedded in the script.
  • Extracts coordinates for each atom and stores them in NumPy arrays.
  • Computes RMSD using a fully vectorized approach with NumPy operations.
  • Prints the RMSD value as output.
  • Useful for bioinformatics and structural biology exercises involving molecular comparison. Usage:

python bioinformatics/calculate_rmsd_numpy.py

Example output:

RMSD between the two structures: 0.2538 Å

• find_nearest_value.py
  Finds the element in a NumPy array that is closest to a given target value.
  • Uses np.abs() and np.argmin() to compute differences efficiently.
  • Returns both the index and value of the nearest element.
  • Can be used with any numeric array and any target value.
    Usage:

python bioinformatics/find_nearest_value.py

Example Output:

Index of nearest element: 7
Nearest element value: 0.79486108

• protein_contacts.py
  Calculates atomic contacts between a receptor and a ligand from two PDB files.
  Two atoms are considered in contact if their distance is ≤ 5 Å.
  • Reads atomic coordinates from lines starting with ATOM in each PDB file.
  • Uses scipy.spatial.distance.cdist() to compute all pairwise distances between atoms.
  • Identifies atoms from both structures that are within 5 Å of each other.
  • Reports the number of contacting atoms in the receptor, the ligand, and the total. Usage:

  python bioinformatics/protein_contacts.py

Example Output:

Atoms of A in contact with B: 84
Atoms of B in contact with A: 63
Total atoms in contact: 147

• sequence_length_calculator.py
  Calculates the length of one or more DNA sequences provided as command-line arguments.
  Supports all IUPAC nucleotide codes (A, C, G, T, R, Y, S, W, K, M, B, D, H, V, N).
  If a sequence contains invalid characters, it prints an error message instead of calculating the length. Usage:

 python bioinformatics/sequence_length_calculator.py ATGC NRYTG

Example Output: 4

visualization/

• 3d_surface_plot.py
  Plots the 3D surface of the function f(x, y) = cos(x) + 2*sin(y) using Matplotlib.
  • Creates a grid in the range [-π, π] for both x and y.
  • Uses ax.plot_surface with the RdBu colormap.
  • Adds axis labels, title, and color bar for clarity.
  • Can display the plot in Jupyter or save it to a file.

Usage in Jupyter:

%run visualization/3d_surface_plot.py

Usage from the terminal:

from visualization.3d_surface_plot import plot_3d_surface

plot_3d_surface(output_file="3d_surface_plot.png")

Example output: A 3D surface plot of f(x, y) = cos(x) + 2*sin(y) over the interval [-π, π] for x and y.

• barcelona_meteo.py
  Visualizes meteorological data for Barcelona Airport.
  The script generates two plots:

  1. Temperature plot: maximum, minimum, and average monthly temperatures.
  2. Rain & humidity plot: monthly rainfall as a bar chart with relative humidity overlaid as a line.

  Features:

  • Automatically creates a plots/ folder inside visualization/ to save PNGs when running from a terminal.
  • Uses matplotlib for both line and bar plots.
  • Axis labels, titles, legends, and y-axis limits included for clarity.

Usage in terminal (.py file):

python visualization/barcelona_meteo.py

Usage in Jupyter Notebook:

from visualization.barcelona_meteo import plot_temperature, plot_rain_humidity

plot_temperature(meteo)
plot_rain_humidity(meteo)

• trig_functions_plot.py
  Plots the arcsin(x) and arccos(x) functions over the interval [-1, 1] in radians using Matplotlib.
  • Adds title, axis labels, legend, and grid for clarity.
  • Can display the plot in Jupyter or save it to a file.

Usage in Jupyter:

from visualization.trig_functions_plot import plot_trig_functions

plot_trig_functions()

Usage from the terminal (save plot to file)

from visualization.trig_functions_plot import plot_trig_functions

plot_trig_functions("arcsin_arccos_plot.png")

Example output A plot showing arcsin(x) in red and arccos(x) in green over the interval [-1, 1] radians.

• words_string_visualization.py
  Creates a colorful, dynamically sized text visualization of a list of words.
  • Works with any list of words.
  • Each letter is assigned a random color and a dynamic font size that grows toward the middle of the string and then decreases.
  • Can display the visualization in Jupyter/IPython or generate an HTML file for viewing in a browser.

Usage in Jupyter:

  from visualization.words_string_visualization import visualize_words_string

  words = ["Hello", "World", "Python"]
  visualize_words_string(words)

Usage from the terminal:

  python visualization/words_string_visualization.py Hello World Python

Example Output: The letters of "HelloWorldPython" will appear in varying sizes and random colors.

utils/

• ip_validator.py
  Validates an IPv4 address provided by the user.
  • Checks that the address has exactly 4 fields separated by dots.
  • Each field must be an integer between 0 and 255.
  • If the IP is invalid, prints a clear error message and exits.
  • Can be used interactively or by passing the IP as a command-line argument.

Usage from the terminal (with argument):

  python utils/ip_validator.py 192.168.0.1

Usage interactively (no argument):

python utils/ip_validator.py
# Then input an IP when prompted

Example output:

The address '192.168.0.1' is a valid IPv4 address.