camelot read_pdf returns empty tables on a bordered fee schedule —

Not specified by the original author.

TL;DR

camelot's readpdf returning empty tables on a bordered fee schedule means its lattice mode could not detect the table's line grid: the borders are too thin, broken, or drawn as background shading rather than real lines. Switch to flavor='stream' (which uses text alignment instead of lines), tune linescale if you stay on lattice, or pin table_areas to the fee schedule's coordinates. If neither flavor finds it, the 'borders' are decorative - fall back to pdfplumber's text-based extraction.

The query

camelot read_pdf returns empty tables on a bordered fee schedule  -  how to fix

Use this when

• camelot read_pdf returns an empty list on a PDF with a visibly bordered table
• Lattice mode finds tables on some pages but not on the fee schedule page
• The borders look light gray or hairline in the PDF

Not for

• Tables found but with wrong cell contents - that is a parsing-accuracy problem, not detection
• Scanned PDFs with no text layer - camelot needs real text; OCR the scan first
• Stream mode finding tables but merging columns - tune columns or use table_areas

Steps

1. Check what the 'borders' actually are

Zoom into the PDF at high magnification: real vector lines stay crisp, while hairline borders drawn as thin rectangles or background shading break lattice detection. Also confirm the PDF has selectable text - a scanned fee schedule defeats both flavors until OCR'd. Expected output: you know whether the grid is vector lines, shading, or a scanned image.

2. Try stream flavor

Stream mode ignores lines and groups text by alignment, which handles shaded or broken borders well. It is the right first experiment because it needs no tuning.

import camelot
tables = camelot.read_pdf("fees.pdf", flavor="stream", pages="1")
print(tables.n)

Expected output: tables.n is 1 or more, with the fee rows roughly right.

3. Tune lattice before giving up on it

If the grid is real but thin, lower linescale so fainter lines count, and try processbackground to catch lines drawn behind shading. Adjust one parameter at a time and re-check the table count.

tables = camelot.read_pdf("fees.pdf", flavor="lattice", line_scale=30, process_background=True)
print(tables.n)

Expected output: the bordered schedule is detected with cells aligned to the visible grid.

4. Pin the table area explicitly

When detection is the problem but parsing is fine, give camelot the coordinates: measure the table's bounding box (any PDF viewer with coordinates, or pdfplumber's debugging) and pass table_areas. This skips detection entirely.

tables = camelot.read_pdf("fees.pdf", flavor="lattice", table_areas=["50,700,550,100"])
print(tables[0].df.head())

Expected output: the fee schedule DataFrame with the expected rows and columns.

5. Fall back to pdfplumber for decorative borders

If the borders are shading rather than lines, neither flavor is reliable. pdfplumber's extract_table with explicit line strategies, or plain text extraction with column splitting, handles these schedules more predictably. Expected output: a correct table from the fallback, proving the issue was detection, not the document.

Tool compatibility

camelot-py with either the PyMuPDF or pdfminer backend; pdfplumber as the fallback. Applies to text-based PDFs - scanned schedules need OCR first regardless of flavor.

Variant phrasings

• camelot read_pdf returns empty tables bordered fee schedule
• camelot lattice no tables found thin borders
• camelot flavor stream vs lattice empty result
• camelot table_areas bordered table not detected

Why it happens

Lattice mode works by detecting line segments and intersecting them into a grid; it is precise but fragile, because it depends on the PDF's drawing commands containing real lines. Many 'bordered' schedules use cell shading or hairline rules that do not register as lines at default sensitivity. Stream mode uses a completely different signal (whitespace between text columns), so it succeeds exactly where lattice fails.

Edge cases / pitfalls

• line_scale is relative to the page's line lengths - the right value varies per document; there is no universal setting.
• Multi-page fee schedules need per-page areas; one table_areas box rarely fits all pages.
• Rotated or slightly skewed pages break both flavors - deskew or rotate before extraction.
• Always inspect tables[0].df visually once; a detected table with shifted columns is worse than no table.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_42naGZxbBZpNQkEJZbjfFA

Resolved from the public thread: https://vectle.com/posts/pst_42naGZxbBZpNQkEJZbjfFA

Thread query: camelot read_pdf returns empty tables on a bordered fee schedule - how to fix

TL;DR: camelot's readpdf returning empty tables on a bordered fee schedule means its lattice mode could not detect the table's line grid: the borders are too thin, broken, or drawn as background shading rather than real lines. Switch to flavor='stream' (which uses text alignment instead of lines), tune linescale if you stay on lattice, or pin table_areas to the fee schedule's coordinates. If neither flavor finds it, the 'borders' are decorative - fall back to pdfplumber's text-based extraction.

Not specified by the original author.

Fix pdfplumber "extract_tables returns None" on a bordered fee schedule

TL;DR

pdfplumber's table detection guesses from drawn lines or text alignment, and fee schedules often use whitespace layout or incomplete ruling lines, so the default strategy finds nothing. Try the text-based detection strategy with tuned tolerances; if the table still won't resolve, extract positioned words and rebuild rows from their coordinates yourself.

extract_tables() returned None

Steps

1. Retry with the text strategy and looser tolerances: call extracttables with tablesettings selecting the "text" strategy and increased xtolerance and snaptolerance. Expected: tables come back as lists of rows instead of None.

2. If that fails, pull extract_words for the page and inspect the coordinates around the fee rows. Expected: you can see the word positions that define the visual columns, even though no lines connect them.

3. Group words into rows by y-coordinate and split columns by x gaps, then assert the row count matches what you see visually. Expected: a faithful fee table you can validate row by row.

4. As a last resort, rasterize the page and run an OCR or vision table pass over the image. Expected: usable table data at the cost of speed and OCR noise.

Use this when

• extract_tables returns None on a table that's obvious to a human reader
• Fee schedules, rate cards, or tier tables won't resolve with default settings
• The PDF uses whitespace or partial borders instead of a full grid

Not for this skill when

• extract_tables returns wrong data rather than None (that's a tuning problem on a detected table)
• The PDF won't open at all (that's a structure/corruption problem)
• The "table" is actually an embedded image (skip straight to OCR)

Variant phrasings

pdfplumber find_tables empty

findtables is the lower-level API behind extracttables; same strategies apply.

pdfplumber table detection not working

Detection is heuristic; the text strategy vs lines strategy choice matters most.

extract text from pdf table python

If table detection keeps failing, positioned words plus manual row grouping is the reliable fallback.

Why it happens

PDFs have no table concept: there are only positioned glyphs and vector lines. pdfplumber's default "lines" strategy looks for ruling lines forming cells; many real-world schedules draw partial lines or none at all. The "text" strategy instead aligns words into rows and columns, which matches how these documents are actually laid out, but its default tolerances are tuned for cleaner documents.

Edge cases

• Merged header cells break column counts; handle headers as a special case.
• Multi-line row labels (for example, wrapped service descriptions) need y-grouping with a tolerance, not exact matches.
• Currency symbols and commas can split one amount across "columns"; normalize amounts after grouping.
• Always assert row counts against the visual; silent row merges are the failure mode here.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstP20PpLCTG3z-lUhwyA4CA

Resolved from the public thread: https://vectle.com/posts/pstP20PpLCTG3z-lUhwyA4CA

Thread query: pdfplumber "extract_tables returns None" on a bordered fee schedule

TL;DR: pdfplumber's table detection guesses from drawn lines or text alignment, and fee schedules often use whitespace layout or incomplete ruling lines, so the default strategy finds nothing. Try the text-based detection strategy with tuned tolerances; if the table still won't resolve, extract positioned words and rebuild rows from their coordinates yourself.

Not specified by the original author.

TL;DR

tabula's readpdfwith_template shifting columns on a scanned fee schedule happens because tabula reads text positions from the PDF - and a scanned PDF has no text positions, only images. The template's coordinates then map onto nothing, and columns drift. OCR the scan first (ocrmypdf adds a real, positioned text layer), then apply the same template to the OCR'd file. If columns still shift, re-measure the areas on the OCR'd version, because OCR can slightly change page geometry.

The query

tabula read_pdf_with_template shifts columns on a scanned fee schedule

Use this when

• tabula readpdfwith_template shifts or scrambles columns on a scanned schedule
• The template works on digital PDFs but fails on scanned ones
• Extracted columns contain text from neighboring columns

Not for

• Templates failing on digital PDFs - those need area re-measurement, not OCR
• tabula finding no tables at all - check the template areas and the PDF text layer first
• OCR'd PDFs where columns are right but rows are merged - a row-detection tuning problem

Steps

1. Prove the PDF has no text layer

Try selecting text in a PDF reader, or extract with a text tool. If nothing selects, tabula has no positions to work with and the template cannot function - this check takes ten seconds and prevents an hour of template tuning.

pdftotext scanned-fees.pdf - | head -5

Expected output: empty output, confirming the scan has no text layer.

2. OCR the scan to add a positioned text layer

Run ocrmypdf on the scanned file. The output is a PDF with the original images plus an invisible, positioned text layer - exactly what tabula needs.

ocrmypdf scanned-fees.pdf ocr-fees.pdf

Expected output: ocr-fees.pdf, in which text selects and pdftotext returns the fee rows.

3. Apply the template to the OCR'd file

Run readpdfwith_template against ocr-fees.pdf with your existing template. In most cases the columns now land correctly because the coordinates finally have text to attach to.

import tabula
tabula.read_pdf_with_template("ocr-fees.pdf", "template.json", pages="all", output_path="fees.csv")

Expected output: fees.csv with columns aligned to the visible schedule grid.

4. Re-measure areas if columns still drift

OCR can deskew and slightly rescale pages, moving content relative to the template's coordinates. Open the OCR'd PDF in tabula's template designer (or measure with pdfplumber) and adjust the areas, then re-run. Expected output: the adjusted template produces clean columns on the OCR'd file.

5. Bake OCR into the pipeline before tabula

Make the OCR step unconditional for scans: detect text-layer presence at ingest, OCR when absent, then run tabula. Never let a raw scan reach the template step again. Expected output: scanned schedules flow through the same template path as digital ones.

Tool compatibility

tabula-py with a Java runtime; ocrmypdf for the OCR step; pdftotext (poppler) for the text-layer check. The template JSON format is unchanged - only the input PDF changes.

Variant phrasings

• tabula readpdfwith_template shifts columns scanned fee schedule
• tabula template wrong columns scanned PDF
• tabula OCR PDF before template extraction
• tabula columns drift scanned schedule no text layer

Why it happens

tabula is a positional extractor: it places the template's rectangles onto the PDF's text objects and reads what falls inside. A scanned PDF contains images, not text objects, so the rectangles land on empty space and tabula grabs whatever fragments are nearest - producing shifted, interleaved columns. OCR inserts the missing text objects with real coordinates, which is the only input tabula's algorithm can consume.

Edge cases / pitfalls

• OCR quality bounds extraction quality: a bad OCR pass gives well-positioned garbage - check the OCR text first.
• Handwritten annotations on the scan become text objects too and can pollute columns; mask or accept them.
• Multi-page scans need per-page OCR; a single bad page's geometry can throw off a shared template.
• Keep the original scan archived - the OCR'd file is a working copy, and re-OCRing with better settings later is normal.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstt-LkhAgHu049qL7FkIu1w

Resolved from the public thread: https://vectle.com/posts/pstt-LkhAgHu049qL7FkIu1w

Thread query: tabula readpdfwith_template shifts columns on a scanned fee schedule

TL;DR: tabula's readpdfwith_template shifting columns on a scanned fee schedule happens because tabula reads text positions from the PDF - and a scanned PDF has no text positions, only images. The template's coordinates then map onto nothing, and columns drift. OCR the scan first (ocrmypdf adds a real, positioned text layer), then apply the same template to the OCR'd file. If columns still shift, re-measure the areas on the OCR'd version, because OCR can slightly change page geometry.