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Process multiple documents efficiently and export results in JSON, HTML, Markdown, text, doctags, and YAML formats.
Overview
This example demonstrates:
- Batch processing multiple PDF files
- Exporting to multiple formats simultaneously
- Handling conversion errors gracefully
- Generating page images for HTML output
Basic Batch Conversion
from pathlib import Path
import json
import yaml
from docling_core.types.doc import ImageRefMode
from docling.datamodel.base_models import ConversionStatus, InputFormat
from docling.datamodel.pipeline_options import PdfPipelineOptions
from docling.document_converter import DocumentConverter, PdfFormatOption
input_doc_paths = [
Path("data/pdf/doc1.pdf"),
Path("data/pdf/doc2.pdf"),
Path("data/pdf/doc3.pdf"),
]
# Configure pipeline to generate page images for HTML
pipeline_options = PdfPipelineOptions()
pipeline_options.generate_page_images = True
doc_converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
}
)
# Convert all documents
conv_results = doc_converter.convert_all(
input_doc_paths,
raises_on_error=False, # Continue processing even if some fail
)
Process Results
Iterate through conversion results and check status.
Export Successful Documents
Save each document in multiple formats using helper methods.
Handle Errors
Log failures and partial successes for debugging.
output_dir = Path("scratch")
output_dir.mkdir(parents=True, exist_ok=True)
for conv_res in conv_results:
if conv_res.status == ConversionStatus.SUCCESS:
doc_filename = conv_res.input.file.stem
# Export using helper methods
conv_res.document.save_as_json(
output_dir / f"{doc_filename}.json",
image_mode=ImageRefMode.PLACEHOLDER,
)
conv_res.document.save_as_html(
output_dir / f"{doc_filename}.html",
image_mode=ImageRefMode.EMBEDDED,
)
conv_res.document.save_as_markdown(
output_dir / f"{doc_filename}.md",
image_mode=ImageRefMode.PLACEHOLDER,
)
conv_res.document.save_as_markdown(
output_dir / f"{doc_filename}.txt",
image_mode=ImageRefMode.PLACEHOLDER,
strict_text=True,
)
conv_res.document.save_as_doctags(
output_dir / f"{doc_filename}.doctags.txt"
)
# Export to YAML
with (output_dir / f"{doc_filename}.yaml").open("w") as fp:
fp.write(yaml.safe_dump(conv_res.document.export_to_dict()))
elif conv_res.status == ConversionStatus.PARTIAL_SUCCESS:
print(f"Partial success: {conv_res.input.file}")
for item in conv_res.errors:
print(f" Error: {item.error_message}")
else:
print(f"Failed: {conv_res.input.file}")
conv_res.document.save_as_json(
output_dir / f"{doc_filename}.json",
image_mode=ImageRefMode.PLACEHOLDER,
)
Set pipeline_options.generate_page_images = True to include page images in HTML exports.
Error Handling
The batch conversion tracks:
- Success count: Fully converted documents
- Partial success count: Documents with warnings
- Failure count: Failed conversions
success_count = 0
failure_count = 0
partial_success_count = 0
for conv_res in conv_results:
if conv_res.status == ConversionStatus.SUCCESS:
success_count += 1
elif conv_res.status == ConversionStatus.PARTIAL_SUCCESS:
partial_success_count += 1
else:
failure_count += 1
print(f"Processed {success_count + partial_success_count + failure_count} docs")
print(f"Failures: {failure_count}")
print(f"Partial: {partial_success_count}")