Overview

Convert between 150+ currencies using real-time rates, with date-based historical conversions. It supports batch processing, locale-aware formatting, and CSV workflows, while caching rates to minimize API usage.

How This Skill Works

Relies on forex-python to fetch current and historical exchange rates and uses pandas for CSV input/output and data handling. It can process multiple amounts in a single run and caches rates to reduce unnecessary API calls for efficiency.

When to Use It

• Travel budgeting and price comparisons across currencies.
• International invoicing or expense reports requiring batch conversions.
• CSV-based data enrichment by converting currency columns.
• Auditing or analyzing historical exchange rates for a specific date.
• Locale-aware reporting that formats numbers per region.

Quick Start

1. Step 1: Install dependencies: pip install forex-python>=1.8 pandas>=2.0.0
2. Step 2: Run a simple conversion: python currency_converter.py --amount 100 --from USD --to EUR
3. Step 3: Process a CSV file: python currency_converter.py --file amounts.csv --from_col usd --to EUR --output converted.csv

Best Practices

• Use explicit ISO currency codes (e.g., USD, EUR) for inputs.
• When using historical rates, specify the exact date for accuracy.
• Enable rate caching to reduce API calls in repeated runs.
• Validate and align CSV columns before processing.
• Test formatting with your target locale to ensure correct currency symbols and separators.

Example Use Cases

• Convert 100 USD to EUR using the current rate.
• Convert 250 GBP to JPY on 2023-08-15.
• Process amounts.csv to convert a USD column to EUR and save as converted.csv.
• Format outputs for en_US locale in a expense report.
• Batch-convert a list of multi-currency amounts in a single run.

Frequently Asked Questions