Analyzing Financial Ratios Using the Finance Toolkit Ratios Module

Financial ratios are how you compare companies that are nothing alike in size. Apple and Walmart both report hundreds of billions in revenue, but they make money in completely different ways, and the raw numbers hide that. Ratios put them on the same scale.

The Finance Toolkit is an open-source Python package that calculates more than 50 of them from a company’s financial statements, using transparent formulas you can check yourself. This post walks through its Ratios Module, using four companies: Apple (AAPL), Amazon (AMZN), Meta (META), and Walmart (WMT).

What the Ratios Module Covers

The module groups its ratios into five categories. Each one answers a different question about a business:

• Efficiency: how well the company turns its resources into revenue.
• Liquidity: whether it can pay the bills coming due in the next year.
• Profitability: how much of each dollar of revenue it keeps.
• Solvency: whether it can carry its debt over the long run.
• Valuation: what the market is paying for its earnings.

The full list is in the reference at the end of this post. Here are the patterns that stand out across the four companies:

• Walmart turns its assets over fastest. It generated more than $2.50 of sales for every dollar of assets in 2023, about double Apple and Amazon.
• Meta is the most liquid. It led on both the current ratio and the quick ratio every year, with a current ratio above 5 in 2020.
• Apple’s return on equity is extreme. Above 170% in 2022 and 2023, largely because years of buybacks have shrunk its shareholder equity.
• Amazon’s 2022 is an outlier everywhere. A net loss that year turned its ROA, ROE, and P/E negative.

Setting Up the Ratios Module

Install the package, then initialize the Toolkit with the tickers you want to compare. It pulls statements from Financial Modeling Prep, so you’ll need a free API key from them.

# Install the financetoolkit package using pip
pip install financetoolkit -U

# Import the Toolkit
from financetoolkit import Toolkit

# Set up API access to FMP
API_KEY = "FINANCIAL_MODELING_PREP_API_KEY"

# Initialize the Toolkit with company tickers
companies = Toolkit(
    ["AAPL", "AMZN", "META", "WMT"], api_key=API_KEY, start_date="2005-01-01"
)

Every ratio is then one method call away. The tables below show the Toolkit’s output for 2020 through 2024. Walmart’s fiscal year ends in January, so its numbers land a year later than the others, which is why only Walmart has a 2024 value.

Profitability

Return on Assets (ROA)

ROA measures how much profit a company earns from everything it owns.

ROA = Net Income / Average Total Assets

roa_ratios = companies.ratios.get_return_on_assets()
print(roa_ratios)

Apple held steady around 28% from 2021 on. Amazon dipped below zero in 2022, and Walmart’s low ROA is the flip side of a business built on thin margins and huge volume.

Return on Equity (ROE)

ROE measures the profit generated on the money shareholders have invested.

ROE = Net Income / Average Shareholders' Equity

roe_ratios = companies.ratios.get_return_on_equity()
print(roe_ratios)

An ROE above 100% is a reminder to read a ratio alongside its inputs. Apple has spent hundreds of billions buying back its own stock, which shrinks shareholders’ equity. A smaller denominator pushes ROE up even when net income is flat.

Liquidity

Current Ratio

The current ratio compares what a company can turn into cash within a year to what it owes within a year. Above 1 means current assets cover current liabilities.

Current Ratio = Current Assets / Current Liabilities

current_ratio = companies.ratios.get_current_ratio()
print(current_ratio)

Quick Ratio

The quick ratio, also called the acid-test ratio, is stricter. It drops inventory, which can take months to sell, and asks whether the most liquid assets alone cover short-term debts.

Quick Ratio = (Current Assets - Inventory) / Current Liabilities

quick_ratio = companies.ratios.get_quick_ratio()
print(quick_ratio)

Meta leads on both measures by a wide margin: it carries a lot of cash and almost no inventory. Walmart is the opposite. Its quick ratio sits near 0.2 because so much of its current assets is merchandise on shelves. For a retailer that sells inventory as fast as Walmart does, that isn’t a warning sign the way it would be for a slower business.

Efficiency

Asset Turnover Ratio

Asset turnover measures how many dollars of sales a company generates for each dollar of assets.

Asset Turnover Ratio = Net Sales / Average Total Assets

asset_turnover = companies.ratios.get_asset_turnover_ratio()
print(asset_turnover)

Walmart’s turnover climbed every year, reaching 2.61 in 2024. Meta sits at the bottom for the opposite reason: its business runs on data centers and intangible assets that are expensive to build but don’t scale sales the way store shelves do.

Solvency

Debt-to-Equity Ratio

Debt-to-equity compares how much of a company is financed by borrowing versus by shareholders. Higher means more leverage, which amplifies both gains and losses.

Debt-to-Equity Ratio = Total Debt / Total Shareholders' Equity

debt_to_equity = companies.ratios.get_debt_to_equity_ratio()
print(debt_to_equity)

Like ROE, this ratio is sensitive to buybacks. When a company retires shares, equity shrinks and debt-to-equity rises, even if it hasn’t borrowed a dollar more.

Valuation

Price-to-Earnings (P/E) Ratio

P/E is what investors pay for each dollar of a company’s earnings. A high P/E usually means the market expects strong growth.

P/E Ratio = Market Price per Share / Earnings per Share

pe_ratio = companies.ratios.get_price_earnings_ratio()
print(pe_ratio)

Amazon’s 2022 value of -314 isn’t a typo. When earnings are negative, P/E turns negative and stops being meaningful. That’s a good example of why a ratio needs context: on its own, it would look like a data error.

Ratio Reference

The Ratios Module includes far more than the ratios above. Here is the full set by category, with the formula behind each one.

Efficiency Ratios

Liquidity Ratios

Profitability Ratios

Solvency Ratios

Valuation Ratios

Takeaways

• One method call per ratio. Once the Toolkit is initialized, comparing companies on any of 50+ ratios takes a single line.
• Ratios only make sense against peers and against time. Walmart’s quick ratio of 0.2 looks alarming alone and ordinary for a big-box retailer.
• Read the inputs, not just the output. Apple’s ROE above 170% and Amazon’s P/E of -314 are both correct, and both would mislead anyone who didn’t check what drove them.

From here, try the Toolkit on companies you follow, and pair the numbers with what ratios can’t capture: competitive position, market trends, and where growth will come from. The Finance Toolkit documentation covers every ratio in detail.