# Shopify CSV Import Audit — ImportCheck (`myrakibo/shopify-csv-import-audit`) Actor

Check product CSV files before Shopify imports. Find supported header, variant and update risks with row-level findings and a JSON report. No store access or automatic edits.

- **URL**: https://apify.com/myrakibo/shopify-csv-import-audit.md
- **Developed by:** [Myrakibo](https://apify.com/myrakibo) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.50 / completed csv audit

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

## Shopify CSV Import Audit

Check a Shopify product CSV before importing it. Paste your CSV and select whether you intend to create or update products. Receive a JSON audit report and a table of findings with row numbers, column names, severity, and explanations.

The tool checks the file you provide. It does not connect to your Shopify store, import products, change records, or rewrite the CSV. It is an independent tool, not affiliated with or endorsed by Shopify.

### Input

- `csvText`: inline CSV text, with comma separators and standard quoted fields. URLs are not accepted as an input source.
- `mode`: `create` for new products or `update` for an intended update.
- Limits: 10 MiB of UTF-8 text and 50,000 data records, excluding the header. A quoted multiline cell remains part of a single record.

Example (deliberately reuses SKU `00123` across two different products):

```json
{
  "csvText": "Title,URL handle,SKU,Price\nExample shirt,example-shirt,00123,19.95\nExample cap,example-cap,00123,12.95\n",
  "mode": "create"
}
```

Expect one `SKU_REUSED` warning on CSV row 3. This asks you to review the reuse; it does not mean Shopify universally forbids it. An excerpt of the expected report is:

```json
{
  "summary": { "status": "review", "analysisComplete": true, "dataRows": 2, "warnings": 1 },
  "issues": [{ "row": 3, "column": "SKU", "code": "SKU_REUSED", "severity": "warning" }]
}
```

A successful audit with no findings has an empty default dataset. Read the canonical `REPORT` in the run's key-value store for the complete summary, supported checks, and limitations.

### Checks and results

The audit checks supported current and legacy header names, required fields, explicit variant options, duplicate rows, conflicting identifiers, selected price/inventory/boolean/status formats, and conditional update risks. It also reports malformed CSV and inconsistent column counts. Every report includes the exact supported checks and limitations. Findings currently use French explanations; their stable codes support automated processing.

Read `REPORT` in the run's key-value store for the canonical JSON report. Open the default dataset for a table of retained findings, exportable as JSON, CSV, or Excel. A report can be complete while identifying errors that need correction. A clean report is not a guarantee of a successful Shopify import.

The report retains at most 1,000 findings. Check `summary.truncated`, the total counts, and the retained count. Findings identify logical CSV records and source text lines. Spreadsheet exports prepend an apostrophe to text beginning with a formula marker, including after whitespace; `spreadsheetEscapedFields` identifies changed export fields. The canonical JSON report retains the original finding text.

### Pricing

USD 0.50 for one completed audit report, regardless of how many findings it contains. A completed audit with business-rule errors is still a completed report. Rejected input, an unparseable CSV, a size/record-limit failure, or a failure to persist the results does not trigger the completed-audit event. No charge is applied per finding or per CSV row. Check the Store pricing panel before starting the run.

### Limitations and data handling

This is a partial pre-import audit based on documented CSV rules. It cannot compare against your existing products, verify store-specific settings, determine whether an image is accessible, or validate rights to use content. It makes no requests to URLs contained in the CSV. Review the report and test your import on a small sample before applying broad changes.

CSV values are kept as strings during analysis; leading zeros are not converted to numbers. The original CSV is excluded from the output report but remains in the run input stored by Apify. Submit product data you are authorized to process; do not include customer, payment, or credential data. Data retention and access follow your Apify run/storage settings.

Rules reference: [Shopify product CSV documentation](https://help.shopify.com/en/manual/products/import-export/using-csv).

# Actor input Schema

## `csvText` (type: `string`):

CSV content, not a URL. The example deliberately reuses SKU 00123 across two products to demonstrate an audit finding. Do not submit customer or payment data. The submitted text becomes part of the run input stored by Apify; it is not included again in the report.

## `mode` (type: `string`):

Choose whether the CSV is intended to create new products or update existing products.

## Actor input object example

```json
{
  "csvText": "Title,URL handle,SKU,Price\nExample shirt,example-shirt,00123,19.95\nExample cap,example-cap,00123,12.95\n",
  "mode": "create"
}
```

# Actor output Schema

## `report` (type: `string`):

No description

## `issues` (type: `string`):

No description

# 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 = {
    "csvText": `Title,URL handle,SKU,Price
Example shirt,example-shirt,00123,19.95
Example cap,example-cap,00123,12.95`,
    "mode": "create"
};

// Run the Actor and wait for it to finish
const run = await client.actor("myrakibo/shopify-csv-import-audit").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 = {
    "csvText": """Title,URL handle,SKU,Price
Example shirt,example-shirt,00123,19.95
Example cap,example-cap,00123,12.95
""",
    "mode": "create",
}

# Run the Actor and wait for it to finish
run = client.actor("myrakibo/shopify-csv-import-audit").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 '{
  "csvText": "Title,URL handle,SKU,Price\\nExample shirt,example-shirt,00123,19.95\\nExample cap,example-cap,00123,12.95\\n",
  "mode": "create"
}' |
apify call myrakibo/shopify-csv-import-audit --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,myrakibo/shopify-csv-import-audit"
        }
    }
}
```

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/ErjHlgoC0H2ZSJvsX/builds/ZihBXRDxRfNAMF663/openapi.json