---
title: "How to build a document scanner with OCR in Python"
canonical_url: "https://www.nutrient.io/blog/creating-a-document-scanner-with-ocr-in-python/"
md_url: "https://www.nutrient.io/blog/creating-a-document-scanner-with-ocr-in-python.md"
last_updated: "2026-08-06T08:09:21.355Z"
description: "Build a document scanner in Python that runs OCR on scanned PDFs and images using the Nutrient DWS Processor API — full setup and code."
---

This blog post shows how to build a document scanner in Python using the [Nutrient DWS Processor API](https://www.nutrient.io/api/pdf-ocr-api/). You’ll use its optical character recognition ([OCR](https://www.nutrient.io/guides/dws-processor/tools-and-api/pdf-ocr-api.md)) endpoint to detect text in scanned documents and turn them into searchable PDFs.

## Prerequisites

Before you start, make sure you have:

- [Python 3](https://www.python.org/downloads/)

- A Nutrient API key — [sign up for a free account](https://www.nutrient.io/guides/dws-processor/getting-started.md) to get one

The Processor API is a hosted service, so there’s nothing to install or run locally beyond Python and an HTTP client.

## Setting up the project

The examples use the Python [`requests`](https://docs.python-requests.org/en/master/) library, but any HTTP client works.

Install `requests`:

```sh

python3 -m pip install requests

```

Create a folder for the project with two subfolders — `input_documents` for the files you want to scan and `processed_documents` for the results — and a `scanner.py` file for your code.

## Calling the Processor API from Python

The OCR endpoint accepts a `multipart/form-data` request: the file to process, plus a `data` field containing a JSON configuration. Authentication is a bearer token — your API key.

Add the following to `scanner.py`:

```python

import requests
import json

response = requests.request(
    "POST",
    "https://api.nutrient.io/processor/ocr",
    headers={
        "Authorization": "Bearer your_api_key_here"
    },
    files={
        "file": open("input_documents/photo.pdf", "rb")
    },
    data={
        "data": json.dumps({
            "language": "english"
        })
    },
    stream=True,
)

if response.ok:
    with open("processed_documents/outfile.pdf", "wb") as outfile:
        for chunk in response.iter_content(chunk_size=8096):
            outfile.write(chunk)
else:
    print(f"Got error reply: {response.text}")

```

Replace `your_api_key_here` with your API key.

A few things to note about the request:

- `files` carries the document to scan. The key (`file`) is the field name the API expects; the value is the opened file.

- `data` carries the OCR configuration as a JSON-encoded string. Here it has a single `language` entry telling the API which language to recognize.

- `stream=True` lets you write the response — the processed PDF — to disk in chunks rather than holding it all in memory.

The response body is the processed PDF, written back to disk.

## Making the script reusable

The last step is to let the script run OCR on any file by accepting input and output paths as arguments:

```python

import sys
import json
import requests

if len(sys.argv) < 3:
    print(f"Usage: {sys.argv[0]} <input_pdf> <output_pdf>")
    sys.exit(0)

input_path = sys.argv[1]
output_path = sys.argv[2]

response = requests.request(
    "POST",
    "https://api.nutrient.io/processor/ocr",
    headers={
        "Authorization": "Bearer your_api_key_here"
    },
    files={
        "file": open(input_path, "rb")
    },
    data={
        "data": json.dumps({
            "language": "english"
        })
    },
    stream=True,
)

if response.ok:
    with open(output_path, "wb") as outfile:
        for chunk in response.iter_content(chunk_size=8096):
            outfile.write(chunk)
else:
    print(f"Got error reply: {response.text}")

```

Now run the script against a scanned PDF:

```sh

python3 scanner.py input_documents/photo.pdf processed_documents/outfile.pdf

```

Open the resulting file and select the text to confirm it was recognized.![An image of a PDF showing selected text](@/assets/images/blog/2022/creating-a-document-scanner-with-ocr-in-python/selected-text-pdf.png)

The API also accepts image files as input, so you can scan a photo the same way:

```sh

python3 scanner.py input_documents/photo.png processed_documents/image_outfile.pdf

```

The result is a searchable PDF.

## Summary

In this post, you learned how to call the Nutrient DWS Processor API from Python, run OCR on a document or image, and save the searchable result. To go further, see the [OCR API guide](https://www.nutrient.io/guides/dws-processor/tools-and-api/pdf-ocr-api.md) or explore the full [PDF API tools](https://www.nutrient.io/api/). To try it yourself, [sign up for a free account](https://www.nutrient.io/guides/dws-processor/getting-started.md) and grab an API key.
---

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