BioLabSim - Biotechnology Laboratory Simulator

# Setup the python virtual environment next to it. (use Python 3.8)
python3.8 -m venv py38-env

# Activate your environment. (Broad topic that depends on what software and OS is used)
source py38-env/bin/activate

# Clone the repository to a nearby folder.
git clone https://git.rwth-aachen.de/ulf.liebal/biolabsim.git repo-biolabsim

# Enter the newly cloned repository.
cd repo-biolabsim

# Install all required python libraries.
pip install -r requirements.txt

# See the Notebook for examples on how to use the library.

# Assuming you start at the project root directory.

# Enter the documentation directory.
cd docs

# Remove the old API documentation.
rm -ri ./api

# Generate the new reStructuredText files for the API documentation.
sphinx-apidoc --module-first -d 4 -o api ../biolabsim

# Generate the HTML from all documentation files.
make html

# Initial definition of a variable to store a probability
some_probability: float = 0

some_probability = 0.4      # Will work. The variable may receive fractional numbers.
some_probability = 0        # Will work. Integers are also numbers.

some_probability = "a lot"  # Error! The IDE will notify us about this bad assignment.
some_probability = "0.3"    # Error! This is still a string. No more conversion problems.

some_probability = -1.4     # Unfortunately this still works. Typing only defines simple types.

class BayesianNetworkNode :
    """
    Each class should document what it does. Ideally, it should have a single purpose.
    """

    # Probability that this node is true.
    true_prob: float

    # Probability that the node is false. Should be inverse of true probability.
    false_prob: float


    def __init__ ( self, true_prob: float ) :

        # Notice that constructor arguments may have the same name as properties.
        self.true_prob = true_prob

        # The constructor only uses necessary arguments to initialize all properties.
        self.false_prob = 1 - true_prob

# Use lower_case with underscores. Prefer distinct names to single letters.
num_strands = 2

# Constants are values embedded into the code. Use UPPER_CASE with underscores.
GOLDEN_RATIO = 1.6180


# Module names use lower_case and avoids underscore when possible.
import biolabsim.sequencing.evaluation


# Custom types use PascalCase.
from typing import Tuple, Literal
GeneBase = Literal['A','T','C','G']


# Functions use lower_case and typically start with a verb.
def complement_base ( base:GeneBase ) -> GeneBase :  # (input) -> output

    # Include most initilization on top of the method.
    orig_bases: List[GeneBase] = ['A','T','C','G']  # Common words may be shortened. orig = original
    comp_bases: List[GeneBase] = ['T','A','G','C']  # But spell it out in comments.  comp = complementary

    # Split your code into blocks of related operations. Provide a small summary of each block.
    # Comments should help outsiders to skim through the code and to explain programming decisions.
    found_orig_index = orig_bases.index(base)  # Avoid one-liners. Variable names provide context.
    return comp_bases[found_orig_index]


# Use simple types to construct more complex ones.
Codon = Tuple[ GeneBase, GeneBase, GeneBase ]


# Classes use PascalCase as well.
class AminoAcid :

    # Class properties use lower_case as well.
    gene_triplet : Codon


    # Constructors initialize the properties.
    def __init__ ( self, base1:GeneBase, base2:GeneBase, base3:GeneBase ) :
        self.gene_triplet = ( base1, base2, base3 )


    # Leave enough space between method definitions.
    def complement_triplet (self) -> Codon :
        return (                                       # Use multiple lines and more spacing if the
            complement_base( self.gene_triplet[0] ),   # code becomes too bulky.
            complement_base( self.gene_triplet[1] ),
            complement_base( self.gene_triplet[2] ),
        )