Observed since 20 Oct, 21:14 UTC
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aftermarket
Analytical engine for aftermarket asset depreciation, secondary market valuation, and condition-based pricing.
An analytical engine for calculating aftermarket asset depreciation, secondary market valuation, and condition-based pricing. Designed for e-commerce recommerce platforms, ERP systems, and insurance tech.
🔗 GitHub Repository: https://github.com/rylse/aftermarket
pip install aftermarket
from datetime import date
from aftermarket import Asset, AftermarketValuation
# Initialize a purchased asset (e.g., electronics, vehicles, equipment)
laptop = Asset(
purchase_price=2000.0,
purchase_date=date(2024, 1, 1),
category_depreciation_rate=0.25 # 25% annual value drop
)
# 1. Calculate fundamental depreciated value (Declining Balance method)
current_value = AftermarketValuation.declining_balance_value(laptop, current_date=date(2026, 1, 1))
print(f"Base Depreciated Value: ${current_value}") # $1125.0
# 2. Adjust for actual physical condition on the secondary market
listing_price = AftermarketValuation.estimate_market_price(current_value, condition="good")
print(f"Recommended Aftermarket Listing: ${listing_price}") # $843.75
This package is currently in Alpha version. It is under active development and the API may evolve to support more complex depreciation schedules. We are open to collaboration! If you want to support the project, suggest features, or contribute code, feel free to contact us at hello@rylse.com or open an issue/PR on our GitHub repository.
This software is provided by Rylse Solutions strictly "as is" and for informational/computational purposes only. It does not constitute financial, accounting, tax, or legal advice. The valuation models provided are theoretical mathematical estimates and do not guarantee actual market performance, resale value, or compliance with local accounting standards (e.g., GAAP, IFRS).
Rylse Solutions, its authors, and contributors assume zero liability for any financial losses, business decisions, data inaccuracies, or damages resulting from the use of this library. Always consult certified financial professionals or appraisers before making monetary decisions.
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Declarations describe requirements; they are not a resolved dependency graph.
bdist_wheel · 4.25 KB · Python py3
sdist · 4.2 KB · Python source
Observed since 20 Oct, 21:14 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package_version:f8540bcbb3c9c3eae733101eac1ca2ebab20822bef6ab739d0d42a9a82ff180f