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Validate a report with dpm-xl

dpm-xbrl reads a report and checks how the file is written. Whether the values are right, for example that a total equals the sum of its parts, is decided by the EBA validation rules, written in DPM-XL. The sibling package dpm-xl parses and evaluates those rules.

The two packages are independent: neither depends on the other. You connect them with a small DataProvider that answers dpm-xl's queries for table, row and column cells from the facts that dpm-xbrl reads. The mapping from a datapoint code to its table, row and column comes from the DPM release of the taxonomy.

The dpm-xl documentation has the full, tested walk-through: from an XBRL report to explained failures. It reads a report with read_report, binds its facts to a provider through an explicit datapoint mapping, evaluates rules with dpm-xl's columnar engine, falls back to the reference engine where the columnar engine does not support a rule, and explains each failure.

What dpm-xbrl gives the provider

  • Report.facts, each with datapoint, template, keys and value (see the fact model). For large reports, read the tables as frames instead and hand the frames to dpm-xl's columnar engine.
  • Report.filing_indicators, keyed by template code, for dpm-xl's table_reported. Map a table file to its filing indicator as described in table codes and filing indicators.
  • Report.parameters (such as refPeriod and baseCurrency) and Report.decimals_parameters, for dpm-xl's parameter.
from dpmxbrl import read_report

report = read_report("report.zip")
print(report.parameters["refPeriod"], report.filing_indicators["C_26.00"])
print([(fact.datapoint, fact.value) for fact in report.facts_for_template("C_26.00")])

2025-12-31 True
[('dp457468', '56058000'), ('dp32024', '92592000'), ('dp32026', '86911000'), ('dp32025', '0.71')]

Values are strings as written; convert numbers with the decimals parameter that applies to their data type before evaluating rules.