Dynamic Pricing API Reference

This page documents the API for the business KPIs module in Pypulate.

Dynamic Pricing Module

This module provides functions for calculating dynamic pricing adjustments.

PricingRule

A class for managing custom pricing rules.

This class provides methods for: - Adding custom pricing rules - Applying custom pricing rules - Managing rule metadata

__init__()

Initialize the PricingRule class.

add_rule(rule_name, calculation_function, description='')

Add a custom pricing rule.

Parameters:

Name	Type	Description	Default
rule_name	str	Name of the custom pricing rule	required
calculation_function	callable	Function that implements the custom pricing logic	required
description	str	Description of the pricing rule	''

apply_rule(rule_name, *args, **kwargs)

Apply a custom pricing rule.

Parameters:

Name	Type	Description	Default
rule_name	str	Name of the custom pricing rule	required
*args	Any	Arguments to pass to the custom pricing function	()
**kwargs	Any	Arguments to pass to the custom pricing function	()

Returns:

Type	Description
float	Price calculated using the custom rule

Raises:

Type	Description
KeyError	If the specified rule_name doesn't exist

get_rule_description(rule_name)

Get the description of a pricing rule.

Parameters:

Name	Type	Description	Default
rule_name	str	Name of the pricing rule	required

Returns:

Type	Description
str	Description of the pricing rule

Raises:

Type	Description
KeyError	If the specified rule_name doesn't exist

list_rules()

List all available pricing rules and their descriptions.

Returns:

Type	Description
dict	Dictionary of rule names and their descriptions

apply_dynamic_pricing(base_price, demand_factor, competition_factor, seasonality_factor=1.0, min_price=None, max_price=None)

Calculate dynamically adjusted price based on market factors.

Parameters:

Name	Type	Description	Default
base_price	float	Base price before adjustments	required
demand_factor	float	Demand multiplier (1.0 is neutral)	required
competition_factor	float	Competition multiplier (1.0 is neutral)	required
seasonality_factor	float	Seasonal adjustment factor	1.0
min_price	float	Minimum price floor	None
max_price	float	Maximum price ceiling	None

Returns:

Type	Description
float	Dynamically adjusted price

Examples:

>>> apply_dynamic_pricing(100.0, 1.2, 0.9, 1.1)
118.8  # 100.0 * 1.2 * 0.9 * 1.1
>>> apply_dynamic_pricing(100.0, 1.5, 0.8, min_price=90.0, max_price=150.0)
120.0  # 100.0 * 1.5 * 0.8, bounded by min/max