Export Historical ECB Exchange Rates

Historical FX projects often begin with copied spreadsheets whose source, quote direction, and missing-day rules are unclear. The ECB Exchange Rates Scraper creates a repeatable export directly from the official data series and carries the observation metadata into every row.

Define the period before collecting

Choose currencies, frequency, start and end dates, and a result cap large enough for the interval. A calendar year of daily values needs fewer than 366 observations per currency because non-publication days are absent.

{"currencies":["USD","GBP","JPY"],"frequency":"D","startDate":"2025-01-01","endDate":"2025-12-31","maxResultsPerCurrency":300}

After the run, verify the earliest and latest dates and count rows by currency. Equal counts are common but should not be assumed without checking. Retain the status field because official series can identify observation conditions or revisions.

For long comparisons, monthly frequency can produce a smaller dataset that is easier to chart. Do not generate monthly points by arbitrarily selecting one daily row unless that is a documented business rule; request the ECB monthly series instead.

When joining rates to transactions, decide whether to use the transaction day, the latest prior published observation, or a period average. That policy belongs in the downstream analysis and should be recorded separately from source collection. Preserve source_url and the exact Actor input beside exported CSV or JSON files so an auditor can reproduce the pull.

This approach supports reconciliation and research while avoiding silent provider mixing. It remains reference data, not proof of the executable rate a bank offered on a transaction.