### Summary
Currently, the email partitioner removes only `=\n` characters during
the clearing process. However, email content sometimes contains `=\r\n`
characters, especially when read from file-like objects such as
`SpooledTemporaryFile` (the file type used in our API). This PR updates
the email partitioner to remove both `=\n` and `=\r\n` characters during
the clearing process.
### Testing
```
filename = "example-docs/eml/family-day.eml"
elements = partition_email(
filename=filename,
)
print(f"From filename: {elements[3].text}")
with open(filename, "rb") as test_file:
spooled_temp_file = tempfile.SpooledTemporaryFile()
spooled_temp_file.write(test_file.read())
spooled_temp_file.seek(0)
elements = partition_email(file=spooled_temp_file)
print(f"From spooled_temp_file: {elements[3].text}")
```
**Results:**
- on `main`
```
From filename: Make sure to RSVP!
From spooled_temp_file: Make sure to = RSVP!
```
- on `PR`
```
From filename: Make sure to RSVP!
From spooled_temp_file: Make sure to RSVP!
```
This PR aims to improve the organization and readability of our example
documents used in unit tests, specifically focusing on PDF and image
files.
### Summary
- Created two new subdirectories in the `example-docs` folder:
- `pdf/`: for all PDF example files
- `img/`: for all image example files
- Moved relevant PDF files from `example-docs/` to `example-docs/pdf/`
- Moved relevant image files from `example-docs/` to `example-docs/img/`
- Updated file paths in affected unit & ingest tests to reflect the new
directory structure
### Testing
All unit & ingest tests should be updated and verified to work with the
new file structure.
## Notes
Other file types (e.g., office documents, HTML files) remain in the root
of `example-docs/` for now.
## Next Steps
Consider similar reorganization for other file types if this structure
proves to be beneficial.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
**Summary**
Improve file-detection tests in preparation for additional work and bug
fixes.
**Additional Context**
- Add type annotations.
- Use mocks instead of `monkeypatch` in most cases and verify calls to
mock. This revealed a dozen broken tests, broken in that the mocks
weren't being called so a different code path than intended was being
exercised.
- Use `example_doc_path()` instead of hard-coded paths.
- Add actual test files for cases where they were being constructed in
temporary directories.
- Make test names consistent and more descriptive of behavior under
test.
**Summary**
Replace legacy HTML parser with recursive version that captures all
content and provides flexibility to add new metadata. It's also
substantially faster although that's just a happy side-effect.
**Additional Context**
The prior HTML parsing algorithm that makes up the core of HTML
partitioning was buggy and very difficult to reason about because it did
not conform to the inherently recursive structure of HTML. The new
version retains `lxml` as the performant and reliable base library but
uses `lxml`'s custom element classes to efficiently classify HTML
elements by their behaviors (block-item and inline (phrasing) primarily)
and give those elements the desired partitioning behaviors.
This solves a host of existing problems with content being skipped and
elements (paragraphs) being divided improperly, but also provides a
clear domain model for reasoning about its behavior and reliably
adjusting it to suit our existing and future purposes.
The parser's operation is recursive, closely modeling the recursive
structure of HTML itself. It's behaviors are based on the HTML Standard
and reliably produce proper and explainable results even for novel
cases.
Fixes#2325Fixes#2562Fixes#2675Fixes#3168Fixes#3227Fixes#3228Fixes#3230Fixes#3237Fixes#3245Fixes#3247Fixes#3255Fixes#3309
### BEHAVIOR DIFFERENCES
#### `emphasized_text_tags` encoding is changed:
- `<strong>` is encoded as `"b"` rather than `"strong"`.
- `<em>` is encoded as `"i"` rather than `"em"`.
- `<span>` is no longer recorded in `emphasized_text_tags` (because
without the CSS we can't tell whether it's used for emphasis or if so
what kind).
- nested emphasis (e.g. bold+italic) is encoded as multiple characters
("bi").
- `emphasized_text_contents` is broken on emphasis-change boundaries,
like:
```html
`<p>foo <b>bar <i>baz</i> bada</b> bing</p>`
```
produces:
```json
{
"emphasized_text_contents": ["bar", "baz", "bada"],
"emphasized_text_tags": ["b", "bi", "b"]
}
```
whereas previously it would have produced:
```json
{
"emphasized_text_contents": ["bar baz bada", "baz"],
"emphasized_text_tags": ["b", "i"]
}
```
#### `<pre>` text is preserved as it appears in the html
Except that a leading newline is removed if present (has to be in
position 0 of text). Also, a trailing newline is stripped but only if it
appears in the very last position ([-1]) of the `<pre>` text. Old parser
stripped all leading and trailing whitespace.
Result is that:
```html
<pre>
foo
bar
baz
</pre>
```
parses to `"foo\nbar\nbaz"` which is the same result produced for:
```html
<pre>foo
bar
baz</pre>
```
This equivalence is the same behavior exhibited by a browser, which is
why we did the extra work to make it this way.
#### Whitespace normalization
Leading and trailing whitespace are removed from element text, just as
it is removed in the browser. Runs of whitespace within the element text
are reduced to a single space character (like in the browser). Note this
means that `\t`, `\n`, and ` ` are replaced with a regular space
character. All text derived from elements is whitespace normalized
except the text within a `<pre>` tag. Any leading or trailing newline is
trimmed from `<pre>` element text; all other whitespace is preserved
just as it appeared in the HTML source.
#### `link_start_indexes` metadata is no longer captured. Rationale:
- It was frequently wrong, often `-1`.
- It was deprecated but then added back in a community PR.
- Maintaining it across any possible downstream transformations (e.g.
chunking) would be expensive and almost certainly lead to wrong values
as distant code evolves.
- It is complex to compute and recompute when whitespace is normalized,
adding substantial complexity to the code and reducing readability and
maintainability
#### `<br/>` element is replaced with a single newline (`"\n"`)
but that is usually replaced with a space in `Element.text` when it is
normalized. The newline is preserved within a `<pre>` element.
- Related: _No paragraph-break on `<br/><br/>`_
#### Empty `h1..h6` elements are dropped.
HTML heading elements (`<h1..h6>`) are "skipped" (do not generate a
`Title` element) when they contain no text or contain only whitespace.
---------
Co-authored-by: scanny <scanny@users.noreply.github.com>
**Summary**
Allow registration of a custom sub-partitioner that extracts images from
a DOCX paragraph.
**Additional Context**
- A custom image sub-partitioner must implement the
`PicturePartitionerT` interface defined in this PR. Basically have an
`.iter_elements()` classmethod that takes the paragraph and generates
zero or more `Image` elements from it.
- The custom image sub-partitioner must be registered by passing the
class to `register_picture_partitioner()`.
- The default image sub-partitioner is `_NullPicturePartitioner` that
does nothing.
- The registered picture partitioner is called once for each paragraph.
Allows introduction of form extraction in the future - sets up the
FormKeysValues element & format, puts in an empty function call in the
partition_pdf_or_image pipeline.
**Summary**
In preparation for adding more tests related to image extraction,
improve the `partition_odt()` test suite:
- Add type annotations to type-check clean on strict mode.
- Improve test names.
- Simplify tests where possible.
- Remove a couple duplicated tests
**Summary**
In preparation for adding more tests related to image extraction,
improve the `partition_doc()` test suite:
- Remove redundant DOCX -> DOC file conversions on most tests.
- Add type annotations to type-check clean on strict mode.
- Improve test names.
- Simplify tests where possible.
- Remove one duplicated test
Speed was roughly doubled: 24 tests in 20s -> 23 tests in 8s.
**Summary**
The CSV delimiter-sniffer requires whole lines to properly detect the
delimiter character. Limiting bytes read produced partial lines when
lines were very long. Limit bytes but read whole lines.
Fixes#2643.
Pass the parameters `include_slide_notes` and `include_page_breaks` to
`partition_pptx` from `partition_ppt`.
Also update the .ppt example doc we use for testing so it has slide
notes and a PageBreak (and second page)
This pull request add metrics that are calculated based on
table_as_cells instead of text_as_html. This change is required for
comprehensive metrics calculation, as previously every colspan or
rowspan predicted was considered to be an incorrect predicted (even if
it was correct prediction)
This change has to be merged after
https://github.com/Unstructured-IO/unstructured/pull/2892 which
introduces table_as_cells field
**Summary**
The DOCX format allows a table row to start late and/or end early,
meaning cells at the beginning or end of a row can be omitted. While
there are legitimate uses for this capability, using it in practice is
relatively rare. However, it can happen unintentionally when adjusting
cell borders with the mouse. Accommodate this case and generate accurate
`.text` and `.metadata.text_as_html` for these tables.
This PR attempts to fix a memory issue, which resulted in errors like
this: https://github.com/Unstructured-IO/unstructured/issues/2931
The root cause seems to be in how ListItems are being combined, not in
how hashes or parent IDs are updated.
When `assign_and_map_hash_ids()` is called and elements (or elements'
metadata) do not have unique memory addresses, then updating the
parent_id of one element will also overwrite the parent_id of some other
element.
---------
Co-authored-by: cragwolfe <crag@unstructured.io>
Part two of: https://github.com/Unstructured-IO/unstructured/pull/2842
Main changes compared to part one:
* hash computation includes element's sequence number on page, page
number, document filename and its text
* there are more test for deterministic behavior of IDs returned by
partitioning functions + their uniqueness (guaranteed at the document
level, and high probability across multiple documents)
This PR addresses the following issue:
https://github.com/Unstructured-IO/unstructured/issues/2461
**Summary**
Delegate partitioning of PPTX Picture (image, to a first approximation)
shapes to a distinct sub-partitioner and allow the default picture
sub-partitioner to be replaced at run-time by one of the user's
choosing.
**Reviewers:** Likely quicker to review commit-by-commit.
**Summary**
In preparation for adding a PPTX `Picture` shape _sub-partitioner_,
extract management of PPTX partitioning-run options to a separate
`_PptxPartitioningOptions` object similar to those used in chunking and
XLSX partitioning. This provides several benefits:
- Extract code dealing with applying defaults and computing derived
values from the main partitioning code, leaving it less cluttered and
focused on the partitioning algorithm itself.
- Allow the options set to be passed to helper objects, prominently
including sub-partitioners, without requiring a long list of parameters
or requiring the caller to couple itself to the particular option values
the helper object requires.
- Allow options behaviors to be thoroughly and efficiently tested in
isolation.
### Summary
Detects headers and footers when using `partition_pdf` with the fast
strategy. Identifies elements that are positioned in the top or bottom
5% of the page as headers or footers. If no coordinate information is
available, an element won't be detected as a header or footer.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: MthwRobinson <MthwRobinson@users.noreply.github.com>
This PR adds new table evaluation metrics prepared by @leah1985
The metrics include:
- `table count` (check)
- `table_level_acc` - accuracy of table detection
- `element_col_level_index_acc` - accuracy of cell detection in columns
- `element_row_level_index_acc` - accuracy of cell detection in rows
- `element_col_level_content_acc` - accuracy of content detected in
columns
- `element_row_level_content_acc` - accuracy of content detected in rows
TODO in next steps:
- create a minimal dataset and upload to s3 for ingest tests
- generate and add metrics on the above dataset to
`test_unstructured_ingest/metrics`
Reported bug: Text from docx shapes is not included in the `partition`
output.
Fix: Extend docx partition to search for text tags nested inside
structures responsible for creating the shape.
---------
Co-authored-by: Filip Knefel <filip@unstructured.io>
**Reviewers:** It may be easier to review each of the two commits
separately. The first adds the new `_SubtableParser` object with its
unit-tests and the second one uses that object to replace the flawed
existing subtable-parsing algorithm.
**Summary**
There are a cluster of bugs in `partition_xlsx()` that all derive from
flaws in the algorithm we use to detect "subtables". These are
encountered when the user wants to get multiple document-elements from
each worksheet, which is the default (argument `find_subtable = True`).
This PR replaces the flawed existing algorithm with a `_SubtableParser`
object that encapsulates all that logic and has thorough unit-tests.
**Additional Context**
This is a summary of the failure cases. There are a few other cases but
they're closely related and this was enough evidence and scope for my
purposes. This PR fixes all these bugs:
```python
#
# -- ✅ CASE 1: There are no leading or trailing single-cell rows.
# -> this subtable functions never get called, subtable is emitted as the only element
#
# a b -> Table(a, b, c, d)
# c d
# -- ✅ CASE 2: There is exactly one leading single-cell row.
# -> Leading single-cell row emitted as `Title` element, core-table properly identified.
#
# a -> [ Title(a),
# b c Table(b, c, d, e) ]
# d e
# -- ❌ CASE 3: There are two-or-more leading single-cell rows.
# -> leading single-cell rows are included in subtable
#
# a -> [ Table(a, b, c, d, e, f) ]
# b
# c d
# e f
# -- ❌ CASE 4: There is exactly one trailing single-cell row.
# -> core table is dropped. trailing single-cell row is emitted as Title
# (this is the behavior in the reported bug)
#
# a b -> [ Title(e) ]
# c d
# e
# -- ❌ CASE 5: There are two-or-more trailing single-cell rows.
# -> core table is dropped. trailing single-cell rows are each emitted as a Title
#
# a b -> [ Title(e),
# c d Title(f) ]
# e
# f
# -- ✅ CASE 6: There are exactly one each leading and trailing single-cell rows.
# -> core table is correctly identified, leading and trailing single-cell rows are each
# emitted as a Title.
#
# a -> [ Title(a),
# b c Table(b, c, d, e),
# d e Title(f) ]
# f
# -- ✅ CASE 7: There are two leading and one trailing single-cell rows.
# -> core table is correctly identified, leading and trailing single-cell rows are each
# emitted as a Title.
#
# a -> [ Title(a),
# b Title(b),
# c d Table(c, d, e, f),
# e f Title(g) ]
# g
# -- ✅ CASE 8: There are two-or-more leading and trailing single-cell rows.
# -> core table is correctly identified, leading and trailing single-cell rows are each
# emitted as a Title.
#
# a -> [ Title(a),
# b Title(b),
# c d Table(c, d, e, f),
# e f Title(g),
# g Title(h) ]
# h
# -- ❌ CASE 9: Single-row subtable, no single-cell rows above or below.
# -> First cell is mistakenly emitted as title, remaining cells are dropped.
#
# a b c -> [ Title(a) ]
# -- ❌ CASE 10: Single-row subtable with one leading single-cell row.
# -> Leading single-row cell is correctly identified as title, core-table is mis-identified
# as a `Title` and truncated.
#
# a -> [ Title(a),
# b c d Title(b) ]
```
### Summary
Closes#2489, which reported an inability to process `.p7s` files. PR
implements two changes:
- If the user selected content type for the email is not available and
there is another valid content type available, fall back to the other
valid content type.
- For signed message, extract the signature and add it to the metadata
### Testing
```python
from unstructured.partition.auto import partition
filename = "example-docs/eml/signed-doc.p7s"
elements = partition(filename=filename) # should get a message about fall back logic
print(elements[0]) # "This is a test"
elements[0].metadata.to_dict() # Will see the signature
```
.heic files are an image filetype we have not supported.
#### Testing
```
from unstructured.partition.image import partition_image
png_filename = "example-docs/DA-1p.png"
heic_filename = "example-docs/DA-1p.heic"
png_elements = partition_image(png_filename, strategy="hi_res")
heic_elements = partition_image(heic_filename, strategy="hi_res")
for i in range(len(heic_elements)):
print(heic_elements[i].text == png_elements[i].text)
```
---------
Co-authored-by: christinestraub <christinemstraub@gmail.com>
The code makes edit to the `measure_text_extraction_accuracy` function
to allows dir of txt as well as json. The function also takes input
`output_type` to be either "json" or "txt" only, and checks if the files
under given directory/list contains only specified file type or not.
To test this feature, run the following code:
```PYTHONPATH=. python unstructured/ingest/evaluate.py measure-text-extraction-accuracy-command --output_dir <clean-text-path> --source_dir <cct-label-path> --output_type txt```
Closes#2302.
### Summary
- add functionality to get a Base64 encoded string from a PIL image
- store base64 encoded image data in two metadata fields: `image_base64`
and `image_mime_type`
- update the "image element filter" logic to keep all image elements in
the output if a user specifies image extraction
### Testing
```
from unstructured.partition.pdf import partition_pdf
elements = partition_pdf(
filename="example-docs/embedded-images-tables.pdf",
strategy="hi_res",
extract_element_types=["Image", "Table"],
extract_to_payload=True,
)
```
or
```
from unstructured.partition.auto import partition
elements = partition(
filename="example-docs/embedded-images-tables.pdf",
strategy="hi_res",
pdf_extract_element_types=["Image", "Table"],
pdf_extract_to_payload=True,
)
```
closes#816
## Description
Added functionality for `partition_email` to automatically decode base64
text before passing it to `partition_text` or `partition_html`.
Also adds base64 encoded email text test cases.
Closes#2218. When a csv has commas in its content, and the delimiter is
something else, Pandas may throw an error. We can sniff the csv and get
the correct delimiter to pass to Pandas. To verify, try partitioning the
file in the linked bug.
### Summary
Add a procedure to repair PDF when the PDF structure is invalid for
`PDFminer` to process.
This PR handles two cases of `PSSyntaxError Invalid dictionary
construct: ...`:
* PDFminer open entire document and create pages generator on
`PDFPage.get_pages(fp)`: [sentry log
example](https://unstructuredio.sentry.io/issues/4655715023/?alert_rule_id=14681339&alert_type=issue¬ification_uuid=d8db4cf4-686f-4504-8a22-74a79a8e966f&project=4505909127086080&referrer=slack)
* PDFminer's interpreter process a single page on
`interpreter.process_page(page)`: [sentry log
example](https://unstructuredio.sentry.io/issues/4655898781/?referrer=slack¬ification_uuid=0d929d48-f490-4db8-8dad-5d431c8460bc&alert_rule_id=14681339&alert_type=issue)
**Additional tech details:**
* Add new dependency `pikepdf` in `requirements/extra-pdf-image.in`,
which is used for repairing PDF.
* Add new denpendenct `pypdf` in `requirements/extra-pdf-image.in`,
which is used to find the error page from entire document by reading the
PDF file again (can't find a way to split pdf in PDFminer).
* Refactor the `is null` check for `get_uris_from_annots`, since the
root cause is that `get_uris` passed a None `annots` to
`get_uris_from_annots`, so the Null check should happen in `get_uris`.
* Add more type protection in `get_uris_from_annots` when using any
`PDFObjRef.resolve()` as `dict` (it could still be a `PDFObjRef`). This
should fix :
* https://github.com/Unstructured-IO/unstructured/issues/1922 where
`annotation_dict` is a `PDFObjRef`
* https://github.com/Unstructured-IO/unstructured/issues/1921 where
`rect` is a `PDFObjRef`
### Test
Added three test files (both are larger than 500 KB) for unittests to
test:
* Repair entire doc
* Repair one page
* Reprocess failure after repairing one page (just return the elements
before error page in this case).
* Also seems like splitting the document into smaller pages could fix
this problem, but not sure why. For example, I saw error from reprocess
in the whole
[cancer.pdf](https://github.com/Unstructured-IO/unstructured/files/13461616/cancer.pdf)
doc, but no error when i split the pdf by error page....
* tested if i can repair the entire doc again in this case, saw other
error which means repairing is not helping imo
* PDFminer can process the whole doc after pikepdf only repaired the
entire doc in the first place, but we can't repair by pages in this way
---------
Co-authored-by: cragwolfe <crag@unstructured.io>
A DOCX header or footer is a so-called "story part" meaning like the
document body (which is also a story part) it can contain both
paragraphs and tables. The implementation of `Header.text` and
`Footer.text` gather only the paragraphs.
Add a new method to extract all content from a header or footer,
including table content, suitable for use as the `.text` attribute of
that element.
Fixes#2126.
**Summary.** The `python-docx` table API is designed for _uniform_
tables (no merged cells, no nested tables). Naive processing of DOCX
tables using this API produces duplicate text when the table has merged
cells. Add a more sophisticated parsing method that reads only "root"
cells (those with an actual `<tc>` element) and skip cells spanned by a
merge.
In the process, abandon use of the `tabulate` package for this job
(which is also designed for uniform tables) and remove the whitespace
padding it adds for visual alignment of columns. Separate the text for
each cell with a single newline ("\n").
Since it's little extra trouble, add support for nested tables such that
their text also contributes to the `Table.text` string.
The new `._iter_table_texts()` method will also be used for parsing
tables in headers and footers (where they are frequently used for layout
purposes) in a closely following PR.
Fixes#2106.
Page breaks can and often do occur within a paragraph. The full text of
the paragraph is attributed to the page (number) the paragraph starts
on.
Improve page-break fidelity such that a paragraph containing a
page-break is split into two elements, one containing the text before
the page-break and the other the text after. Emit the `PageBreak`
element between these two and assign the correct page-number (n and n+1
respectively) to the two textual elements.
This functionality is largely provided upstream by the new `python-docx`
v1.0.0 release (1.0.0 from 0.8.11 because it drops Python 2 support).
That version also makes obsolete the "include hyperlink text in
`Paragraph.text` monkey patch that we had maintained up to now. Remove
that monkey-patch.
Closes#2059.
We've found some pdfs that throw an error in pdfminer. These files use a
ICCBased color profile but do not include an expected value `N`. As a
workaround, we can wrap pdfminer and drop any colorspace info, since we
don't need to render the document.
To verify, try to partition the document in the linked issue.
```
elements = partition(filename="google-2023-environmental-report_condensed.pdf", strategy="fast")
```
---------
Co-authored-by: cragwolfe <crag@unstructured.io>
Closes#2027
Tables or pages that contain only numbers are returned as floats in a
pandas.DataFrame when the image or page is converted from
`.image_to_data()`. An AttributeError was raised downstream when trying
to `.strip()` the floats. This update converts those floats if needed
and otherwise strips the text.
Testing (note: the document used for testing is new, so you will have to
copy it to the main branch in order to see that this snippet raises an
AttributeError on the main branch, but works on this branch)
```
from unstructured.partition.pdf import partition_pdf
filename = "example-docs/all-number-table.pdf"
partition_pdf(filename, strategy="ocr_only")
```
---------
Co-authored-by: cragwolfe <crag@unstructured.io>
Page breaks are reliably indicated by `w:lastRenderedPageBreak` elements
present in the document XML. Page breaks are NOT reliably indicated by
"hard" page-breaks inserted by the author and when present are redundant
to a `w:lastRenderedPageBreak` element so cause over-counting if used.
Use rendered page-breaks only.
A DOCX document that has no sections can still contain one or more
tables. Such files are never created by Word but Word can open them just
fine. These can be and are generated by other applications.
Use the newly-added `Document.iter_inner_content()` method added
upstream in `python-docx` to capture both paragraphs and tables from a
section-less DOCX document.
This generalizes the fix for MS Teams chat-transcripts (an example of
sectionless-docx) implemented in #1825.
In DOCX, like HTML, a table cell can itself contain a table. This is not
uncommon and is typically used for formatting purposes.
When a DOCX table is nested, create nested HTML tables to reflect that
structure and create a plain-text table with captures all the text in
nested tables, formatting it as a reasonable facsimile of a table.
This implements the solution described and spiked in PR #1952.
---------
Co-authored-by: Bruno Bornsztein <bruno.bornsztein@gmail.com>
### Summary
Click decorated functions cannot (properly) be called outside of the
click interface. This makes it difficult to reuse the setup
functionality in measure_text_edit_distance or
measure_element_type_accuracy. This PR removes the click decoration and
separates it into a wrapper function purely to execute the command.
### Technical Details
- Changed as suggested in [this StackOverflow
post](https://stackoverflow.com/questions/40091347/call-another-click-command-from-a-click-command)
response
- The locations of these now distinct functions are separate: the
`_command` click-decorated functions stay in ingest/evaluate.py, and the
core functions measure_text_edit_distance and
measure_element_type_accuracy are moved into the unstructured/metrics/
folder (which is a more logical location for them).
- Initial test added for measure_text_edit_distance
### Test
`sh ./test_unstructured_ingest/evaluation-metrics.sh text-extraction`
functionality is unchanged.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: shreyanid <shreyanid@users.noreply.github.com>
Co-authored-by: Trevor Bossert <37596773+tabossert@users.noreply.github.com>
- This PR adds a function to check if a piece of text only contains a
bullet (no text) to prevent creating an empty element.
- Also fixed a test that had a typo.
*Reviewer:* May be quicker to review commit by commit as they are quite
distinct and well-groomed to each focus on a single clean-up task.
Clean up odds-and-ends in the docx partitioner in preparation for adding
nested-tables support in a closely following PR.
1. Remove obsolete TODOs now in GitHub issues, which is probably where
they belong in future anyway.
2. Remove local DOCX "workaround" code that has been implemented
upstream and is now obsolete.
3. "Clean" the docx tests, introducing strict typing, extracting a
fixture or two, and generally tightening things up.
4. Extract docx-local versions of
`unstructured.partition.common.convert_ms_office_table_to_text()` which
will be the base for adding nested-table support. More information on
why this is required in that commit.
Courtesy @phowat, created a branch in the repo to make some changes and
merge quickly.
Closes#1486.
* **Fixes issue where tables from markdown documents were being treated
as text** Problem: Tables from markdown documents were being treated as
text, and not being extracted as tables. Solution: Enable the `tables`
extension when instantiating the `python-markdown` object. Importance:
This will allow users to extract structured data from tables in markdown
documents.
#### Testing:
On `main` run the following (run `git checkout fix/md-tables --
example-docs/simple-table.md` first to grab the example table from this
branch)
```python
from unstructured.partition.md import partition_md
elements = partition_md("example-docs/simple-table.md")
print(elements[0].category)
```
Output should be `UncategorizedText`. Then run the same code on this
branch and observe the output is `Table`.
---------
Co-authored-by: cragwolfe <crag@unstructured.io>
- add helper to run inference over an image or pdf of table and compare
it against a ground truth csv file
- this metric generates a similarity score between 1 and 0, where 1 is
perfect match and 0 is no match at all
- add example docs for testing
- NOTE: this metric is only relevant to table structure detection.
Therefore the input should be just the table area in an image/pdf file;
we are not evaluating table element detection in this metric
This PR resolves#1816
- current docx partition assumes all contents are in sections
- this is not true for MS Teams chat transcript exported to docx
- now the code checks if there are sections or not; if not then iterate
through the paragraphs and partition contents in the paragraphs
Fixes recursion limit error that was being raised when partitioning
Excel documents of a certain size.
Previously we used a recursive method to find subtables within an excel
sheet. However this would run afoul of Python's recursion depth limit
when there was a contiguous block of more than 1000 cells within a
sheet. This function has been updated to use the NetworkX library which
avoids Python recursion issues.
* Updated `_get_connected_components` to use `networkx` graph methods
rather than implementing our own algorithm for finding contiguous groups
of cells within a sheet.
* Added a test and example doc that replicates the `RecursionError`
prior to the change.
* Added `networkx` to `extra_xlsx` dependencies and `pip-compile`d.
#### Testing:
The following run from a Python terminal should raise a `RecursionError`
on `main` and succeed on this branch:
```python
import sys
from unstructured.partition.xlsx import partition_xlsx
old_recursion_limit = sys.getrecursionlimit()
try:
sys.setrecursionlimit(1000)
filename = "example-docs/more-than-1k-cells.xlsx"
partition_xlsx(filename=filename)
finally:
sys.setrecursionlimit(old_recursion_limit)
```
Note: the recursion limit is different in different contexts. Checking
my own system, the default in a notebook seems to be 3000, but in a
terminal it's 1000. The documented Python default recursion limit is
1000.
### Summary
Closes#1534 and #1535
Detects document language using `langdetect` package.
Creates new kwargs for user to set the document language (`languages`)
or detect the language at the element level instead of the default
document level (`detect_language_per_element`)
---------
Co-authored-by: shreyanid <42684285+shreyanid@users.noreply.github.com>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: Coniferish <Coniferish@users.noreply.github.com>
Co-authored-by: cragwolfe <crag@unstructured.io>
Co-authored-by: Austin Walker <austin@unstructured.io>
