jsvine/pdfplumber

What it does

You give it a file path, or bytes, or a file object, and a password if the file has one. It exposes every object on each page as a list you can read: characters, lines, rectangles, curves, images, annotations and links, each with its coordinates. On top of that it extracts text, words and tables. Table finding has four strategies in each direction — ruled lines, strict lines, text alignment, or boundaries you give it yourself — and twenty settings to tune them. There is also a command-line mode that writes CSV, JSON or plain text. The debugging view renders a page as an image at 72 dots per inch and draws the lines, intersections and table boundaries it detected on top, which is how you work out why a table came out wrong. What it does not do is stated plainly in the README: it "works best on machine-generated, rather than scanned, PDFs", it has no text recognition for scans, it does not create or modify PDFs at all, it does not rebuild the content of images, and it has no interface for form fields.

Why it matters

Who it suits. Anyone who regularly gets data as a PDF and types it out again. Bank statements, invoices, government reports and published tables are the usual cases, and this is the tool that gets them into rows and columns. It also suits anyone debugging a table extraction that another library got wrong, because the picture it draws shows you what the computer actually saw. Skip it if your documents are scans or photographs, because there is no text recognition here at all, and skip it if you need to write PDFs rather than read them.

Verdict. Worth twenty minutes today on a document you have already given up on once. pip install pdfplumber and four lines of Python gets you the first table, and the debugging image is what makes the second one work. Three honest limits. It is slower than the alternatives, and the README says so itself, naming pymupdf/PyMuPDF as substantially faster. On a large document its per-page caching "can use a lot of memory", released by closing each page. And several features, including layout-preserving text extraction and search, are marked experimental. For scans you need text recognition first, and Edition 27 covered ocrmypdf/OCRmyPDF, which makes a scan searchable and then hands it to a tool like this one. A note on checking: the usual mirror this report uses for code dates refused this repository on three attempts, so currency here rests on its release of 15 June 2026, confirmed at the package registry, and on a test list that includes Python 3.14.