Quality Data API

Free Data Quality API

Check a dataset before you trust it. The quality endpoint returns an A-F score, coverage, critical issues, warnings and a link to the full HTML report.

Updated 2026-11-02 ? Data refreshed from the AlgoSpecial catalog.

617quality reports
A-Fscore grades
16automated checks
97 AXAUUSD M15 score

What the quality API checks

Every report audits the dataset for structural and market-data problems:

Structure

Duplicate timestamps, out-of-order rows, missing required columns and invalid calendar coverage.

Price integrity

OHLC violations, non-positive prices, flat bars and extreme returns.

Market realism

Unexpected gaps, weekend bars, zero or negative volume and spread anomalies.

The score starts at 100 and deducts points for critical errors and warnings. A critical issue can cap the grade at F. The report exposes the issue list rather than hiding it behind a single number.

Quality API response

Pass symbol and tf to the quality endpoint. The response includes:

FieldMeaning
scoreNumeric quality score from 0 to 100
gradeA, B, C, D or F
rows, start, endDataset coverage
checksCounts for duplicates, gaps, OHLC violations, volume, spread and more
issuesSeverity, check name, count and explanation
report_urlCanonical HTML report

Use the HTML report for a human-readable breakdown: all 617 quality reports.

How to read the A-F grades

  • A: structurally clean with no material issues; minor warnings may still exist.
  • B: good overall, with a small number of warnings worth reviewing.
  • C: inspect gaps, volume or spread issues before production use.
  • D: significant issues; use only after targeted cleaning.
  • F: critical issues present; do not use blindly.

The exact grade uses the weighted score plus issue severity, so two datasets with a similar score can receive different grades. A high score does not guarantee profitable backtests; it means the file is structurally cleaner, not that the strategy or broker execution is good.

When to call the quality API

Before a backtest

Reject or clean datasets with critical duplicates, OHLC errors or unusable gaps.

Before ML training

Check coverage and outlier counts so labels are not built on broken candles.

Before a data purchase

Compare the quality of two feeds before committing to either one.

Quality API limits

The quality endpoint shares the public rate limit: 60 requests per minute and 1,000 requests per day per IP. It returns JSON only. The full report download is available from each HTML report page.

Request examples

cURL - XAUUSD M15 quality report

curl "https://www.algospecial.com/api/data-quality.php?symbol=XAUUSD&tf=M15"

Python - gate a backtest on quality

import requests

r = requests.get(
    "https://www.algospecial.com/api/data-quality.php",
    params={"symbol": "XAUUSD", "tf": "M15"},
    timeout=30,
)
r.raise_for_status()
report = r.json()

if report["grade"] in ("D", "F") or report["critical_count"] > 0:
    raise SystemExit("Dataset needs cleaning before backtesting")

print(report["score"], report["grade"], report["report_url"])

All timestamps are broker server time. Some legacy forex exports return 0 for TickVolume and Spread because those fields were not present in the source feed.

Data Quality API FAQ

Is the data quality API free?

Yes. It uses the same public limits as the OHLC API: 60 requests per minute and 1,000 per day.

What does the score measure?

It measures structural data quality: duplicates, OHLC validity, gaps, outliers, volume, spread and related checks. It does not measure profitability.

Why is a dataset grade F?

A critical issue is present, such as duplicate timestamps, invalid OHLC, non-positive prices or a severe structural problem. Open the report for details.

Can I download the full report?

Yes. Each HTML quality report has a JSON download link, and the report API returns the canonical report URL.

Does a high grade guarantee good backtest results?

No. It only means the dataset is structurally cleaner. Strategy logic, spread, execution and market regime still determine results.

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