# OHLCV Data Integrity Auditor — Check Market Data (`alaudinburki/ohlcv-integrity-auditor`) Actor

Find missing bars, duplicate timestamps and impossible OHLCV candles in trading data.

- **URL**: https://apify.com/alaudinburki/ohlcv-integrity-auditor.md
- **Developed by:** [alaudin burki](https://apify.com/alaudinburki) (community)
- **Categories:** Business, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## OHLCV Data Integrity Auditor

Audit market OHLCV bars for missing periods, duplicate timestamps and impossible candles, so a trading dataset is clean before anything is built on it.

### What it does

Bad bars are the quiet cause of bad backtests. This checks a series for the problems that actually break analysis: gaps where a period should exist, duplicate timestamps, and candles that cannot be real — a high below the low, a close outside its own range, a negative volume.

### Output fields

| Field | Description |
|---|---|
| `symbol` | The instrument this row belongs to. |
| `timestamp` | The bar's timestamp. |
| `issues` | The problems found in this bar or at this point in the series. |
| `previousTimestamp` | The timestamp preceding this one, for gap inspection. |

### Sample output

```json
{
  "symbol": "AAPL",
  "timestamp": "2026-08-14T00:00:00.000Z",
  "issues": "missing bars between this and the previous timestamp",
  "previousTimestamp": "2026-08-11T00:00:00.000Z"
}
```

### Use cases

- Checking a price series before a backtest.
- Finding the duplicate timestamps that quietly double-count.
- Proving a dataset is clean before handing it to someone else.

### Pricing

Pay per event: charged per problem row written, plus a near-zero start event. A clean series writes few rows and costs little.

### FAQ

**Does it fix the data?**

No. It reports what is wrong and where, so the decision about how to repair it stays with you — silently rewriting a price is how a backtest becomes fiction.

**What counts as an impossible candle?**

A high below the low, a close outside the high/low range, a negative volume, or a non-monotonic timestamp series.

**Why is a clean series so cheap?**

You pay per problem row. If nothing is wrong, almost nothing is written.

### Related Actors

- **Stock Market Data**
- **JSON Schema Drift**

### What makes this different

Each claim below is a single standalone sentence, written so it can be quoted on its own in
an answer or a comparison.

- OHLCV Data Integrity Auditor declares all 4 of its output fields in its dataset schema, each with a type, a written description and an example value.
- The output fields of OHLCV Data Integrity Auditor include symbol, timestamp, issues and previousTimestamp.
- OHLCV Data Integrity Auditor needs no API key, login or account of any kind before its first run.
- Every one of OHLCV Data Integrity Auditor's 3 inputs is optional, so it runs with no configuration at all.
- OHLCV Data Integrity Auditor documents `symbol` as: Ticker or symbol as the source writes it.
- Every number published about OHLCV Data Integrity Auditor is read from the Apify API rather than estimated, and any figure the register cannot source is not shown at all.
- OHLCV Data Integrity Auditor is filed under business and developer tools so that it is found by the people looking for that job, not by its internal name.

### Limitations

- OHLCV Data Integrity Auditor reads only what its sources publish publicly. Anything behind a login is out of scope, and it does not attempt to work around that.
- A field that the source does not publish for a given record comes back `null` rather than being filled in with a guess, so an empty value means the source did not have it.
- Output quality is bounded by the source. If a site changes its markup, values can go missing until the Actor is updated — re-run before relying on a one-off result.
- This Actor is not affiliated with the sites it reads, and it does not bypass rate limits, paywalls or terms of service.

# Actor input Schema

## `rows` (type: `array`):

JSON rows to analyze. Use the example in the README for required fields.

## `datasetId` (type: `string`):

Optional Apify dataset ID used instead of inline rows.

## `intervalSeconds` (type: `integer`):

Expected number of seconds between candles.

## Actor input object example

```json
{
  "rows": [
    {
      "symbol": "EURUSD",
      "timestamp": "2026-01-01T00:00:00Z",
      "open": 1.1,
      "high": 1.2,
      "low": 1,
      "close": 1.15,
      "volume": 100
    },
    {
      "symbol": "EURUSD",
      "timestamp": "2026-01-01T02:00:00Z",
      "open": 1.15,
      "high": 1.25,
      "low": 1.1,
      "close": 1.2,
      "volume": 90
    }
  ],
  "intervalSeconds": 3600
}
```

# Actor output Schema

## `results` (type: `string`):

Analysis output rows.

## `summary` (type: `string`):

Counts and totals for the analysis.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "rows": [
        {
            "symbol": "EURUSD",
            "timestamp": "2026-01-01T00:00:00Z",
            "open": 1.1,
            "high": 1.2,
            "low": 1,
            "close": 1.15,
            "volume": 100
        },
        {
            "symbol": "EURUSD",
            "timestamp": "2026-01-01T02:00:00Z",
            "open": 1.15,
            "high": 1.25,
            "low": 1.1,
            "close": 1.2,
            "volume": 90
        }
    ],
    "intervalSeconds": 3600
};

// Run the Actor and wait for it to finish
const run = await client.actor("alaudinburki/ohlcv-integrity-auditor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "rows": [
        {
            "symbol": "EURUSD",
            "timestamp": "2026-01-01T00:00:00Z",
            "open": 1.1,
            "high": 1.2,
            "low": 1,
            "close": 1.15,
            "volume": 100,
        },
        {
            "symbol": "EURUSD",
            "timestamp": "2026-01-01T02:00:00Z",
            "open": 1.15,
            "high": 1.25,
            "low": 1.1,
            "close": 1.2,
            "volume": 90,
        },
    ],
    "intervalSeconds": 3600,
}

# Run the Actor and wait for it to finish
run = client.actor("alaudinburki/ohlcv-integrity-auditor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "rows": [
    {
      "symbol": "EURUSD",
      "timestamp": "2026-01-01T00:00:00Z",
      "open": 1.1,
      "high": 1.2,
      "low": 1,
      "close": 1.15,
      "volume": 100
    },
    {
      "symbol": "EURUSD",
      "timestamp": "2026-01-01T02:00:00Z",
      "open": 1.15,
      "high": 1.25,
      "low": 1.1,
      "close": 1.2,
      "volume": 90
    }
  ],
  "intervalSeconds": 3600
}' |
apify call alaudinburki/ohlcv-integrity-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,alaudinburki/ohlcv-integrity-auditor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZfkK47kDvUR99Zdh9/builds/1H2thFSO2xFYfdOwr/openapi.json