File size: 3,384 Bytes
362a075 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | # SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
#
# SPDX-License-Identifier: Apache-2.0
import io
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
from haystack import Document, component, logging
from haystack.components.converters.utils import get_bytestream_from_source, normalize_metadata
from haystack.dataclasses import ByteStream
logger = logging.getLogger(__name__)
@component
class CSVToDocument:
"""
Converts CSV files to Documents.
By default, it uses UTF-8 encoding when converting files but
you can also set a custom encoding.
It can attach metadata to the resulting documents.
### Usage example
```python
from haystack.components.converters.csv import CSVToDocument
converter = CSVToDocument()
results = converter.run(sources=["sample.csv"], meta={"date_added": datetime.now().isoformat()})
documents = results["documents"]
print(documents[0].content)
# 'col1,col2\now1,row1\nrow2row2\n'
```
"""
def __init__(self, encoding: str = "utf-8"):
"""
Creates a CSVToDocument component.
:param encoding:
The encoding of the csv files to convert.
If the encoding is specified in the metadata of a source ByteStream,
it overrides this value.
"""
self.encoding = encoding
@component.output_types(documents=List[Document])
def run(
self,
sources: List[Union[str, Path, ByteStream]],
meta: Optional[Union[Dict[str, Any], List[Dict[str, Any]]]] = None,
):
"""
Converts a CSV file to a Document.
:param sources:
List of file paths or ByteStream objects.
:param meta:
Optional metadata to attach to the documents.
This value can be either a list of dictionaries or a single dictionary.
If it's a single dictionary, its content is added to the metadata of all produced documents.
If it's a list, the length of the list must match the number of sources, because the two lists will
be zipped.
If `sources` contains ByteStream objects, their `meta` will be added to the output documents.
:returns:
A dictionary with the following keys:
- `documents`: Created documents
"""
documents = []
meta_list = normalize_metadata(meta, sources_count=len(sources))
for source, metadata in zip(sources, meta_list):
try:
bytestream = get_bytestream_from_source(source)
except Exception as e:
logger.warning("Could not read {source}. Skipping it. Error: {error}", source=source, error=e)
continue
try:
encoding = bytestream.meta.get("encoding", self.encoding)
data = io.BytesIO(bytestream.data).getvalue().decode(encoding=encoding)
except Exception as e:
logger.warning(
"Could not convert file {source}. Skipping it. Error message: {error}", source=source, error=e
)
continue
merged_metadata = {**bytestream.meta, **metadata}
document = Document(content=data, meta=merged_metadata)
documents.append(document)
return {"documents": documents}
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