Metadata-Version: 2.3
Name: playa-pdf
Version: 0.2.4
Summary: PLAYA ain't a LAYout Analyzer
Project-URL: Homepage, https://dhdaines.github.io/playa
Author-email: David Huggins-Daines <dhd@ecolingui.ca>
License: MIT
Keywords: pdf parser,text mining
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Text Processing
Requires-Python: >=3.8
Description-Content-Type: text/markdown

# **P**LAYA-PDF is a **LA**z**Y** **A**nalyzer for **PDF** 🏖️

## About

There are already too many PDF libraries, unfortunately none of which
does everything that everybody wants it to do, and we probably don't
need another one. It is not recommended that you use this library for
anything at all, but if you were going to use it for something, it
would be specifically one of these things and nothing else:

1. Accessing the document catalog, page tree, structure tree, content
   streams, cross-reference table, XObjects, and other low-level PDF
   metadata.
2. Obtaining the absolute position and attributes of every character,
   line, path, and image in every page of a PDF.
   
If you just want to extract text from a PDF, there are a lot of better
and faster tools and libraries out there, see [these
benchmarks](https://github.com/py-pdf/benchmarks) for a summary (TL;DR
pypdfium2 is probably what you want, but pdfplumber does a nice job of
converting PDF to ASCII art).

The purpose of PLAYA is to provide an efficent, pure-Python and
Pythonic (for its author's definition of the term), lazy interface to
the internals of PDF files.

## Installation

Installing it should be really simple as long as you have Python 3.8
or newer:

    pipx install playa-pdf

Yes it's not just "playa".  Sorry about that.

## Usage

Do you want to get stuff out of a PDF?  You have come to the right
place!  Let's open up a PDF and see what's in it:

```python
pdf = playa.open("my_awesome_document.pdf")
raw_byte_stream = pdf.buffer
a_bunch_of_tokens = list(pdf.tokens)
a_bunch_of_indirect_objects = list(pdf)
```

The raw PDF tokens and objects are probably not terribly useful to
you, but you might find them interesting.  Note that these are
"indirect objects" where the actual object is accompanied by an object
number and generation number:

```python
for objid, genno, obj in pdf:
    ...
# or also
for obj in pdf:
    obj.objid, obj.genno, obj.obj
```

Also, these will only be the top-level objects and not those found
inside object streams (the streams are themselves indirect objects).
You can access all objects directly by indexing the PDF document:

```python
a_particular_object = pdf[42]
```

It probably has some pages.  How many?  What are their numbers/labels?
(they could be things like "xviii", 'a", or "42", for instance)

```python
npages = len(pdf.pages)
page_numbers = [page.label for page in pdf.pages]
```

What's in the table of contents?

```python
for entry in pdf.outlines:
    ...
```

If you are lucky it has a "logical structure tree".  The elements here
might even be referenced from the table of contents!  (or, they might
not... with PDF you never know)

```python
structure = pdf.structtree
for element in structure:
   for child in element:
       ...
```

Now perhaps we want to look at a specific page.  Okay!  You can also
look at its contents, more on that in a bit:

```python
page = pdf.pages[0]        # they are numbered from 0
page = pdf.pages["xviii"]  # but you can get them by label (a string)
page = pdf.pages["42"]  # or "logical" page number (also a string)
print(f"Page {page.label} is {page.width} x {page.height}")
```

## Accessing content

What are these "contents" of which you speak, which were surely
created by a Content Creator?  Well, you can look at the stream of
tokens or mysterious PDF objects:

```python
for token in page.tokens:
    ...
for object in page.contents:
    ...
```

But that isn't very useful, so you can also access actual textual and
graphical objects (if you wanted to, for instance, do layout
analysis).

```python
for item in page:
    ...
```

Because it is quite inefficient to expand, calculate, and copy every
possible piece of information, PLAYA gives you some options here.
Wherever possible this information can be computed lazily, but this
involves some more work on the user's part.

## Dictionary-based API

If, on the other hand, **you** are lazy, then you can just use
`page.layout`, which will flatten everything for you into a friendly
dictionary representation (but it is a
[`TypedDict`](https://typing.readthedocs.io/en/latest/spec/typeddict.html#typeddict))
which, um, looks a lot like what `pdfplumber` gives you, except in the
coordinate space defined previously.

```python
for dic in page.layout:
    print("it is a {dic['object_type']} at ({dic['x0']}", {dic['y0']}))
    print("    the color is {dic['stroking_color']}")
    print("    the text is {dic['text']}")
    print("    it is in MCS {dic['mcid']} which is a {dic['tag']}")
    print("    it is also in Form XObject {dic['xobjid']}")
```

This is for instance quite useful for doing "Artificial Intelligence",
or if you like wasting time and energy for no good reason, but I
repeat myself.  For instance, you can write `page.layout` to a CSV file:

```python
writer = DictWriter(outfh, fieldnames=playa.fieldnames)
writer.writeheader()
for dic in pdf.layout:
    writer.writerow(dic)
```

you can also create a Pandas DataFrame:

```python
df = pandas.DataFrame.from_records(pdf.layout)
```

or a Polars DataFrame or LazyFrame:

```python
df = polars.DataFrame(pdf.layout, schema=playa.schema)
```

If you have more specific needs or want better performance, then read on.

## An important note about coordinate spaces

Wait, what is this "absolute position" of which you speak, and which
PLAYA gives you?  It's important to understand that there is no
definition of "device space" in the PDF standard, and I quote (PDF 1.7
sec 8.3.2.2):

> A particular device’s coordinate system is called its device
space. The origin of the device space on different devices can fall in
different places on the output page; on displays, the origin can vary
depending on the window system. Because the paper or other output
medium moves through different printers and imagesetters in different
directions, the axes of their device spaces may be oriented
differently.

You may immediately think of CSS when you hear the phrase "absolute
position" and this is exactly what PLAYA gives you as its default
device space, specifically:

- Units are default user space units (1/72 of an inch).
- `(0, 0)` is the top-left corner of the page, as defined by its
  `MediaBox` after rotation is applied.
- Coordinates increase from the top-left corner of the page towards
  the bottom-left corner.

However, for compatibility with `pdfminer.six`, you can also pass
`space="page"` to `playa.open`.  In this case, `(0, 0)` is the
bottom-left corner of the page as defined by the `MediaBox`, after
rotation, and coordinates increase from the bottom-left corner of the
page towards the top-right, as they do in PDF user space.

If you don't care about absolute positioning, you can use
`space="user"`, which may be somewhat faster in the future (currently
it isn't).  In this case, no translation or rotation of the default
user space is done (in other words any values of `MediaBox` or
`Rotate` in the page dictionary are simply ignored).

## Lazy object API

Fundamentally you may just want to know *what* is *where* on the page,
and PLAYA has you covered there (note that the bbox is normalized, and
in the aforementioned interpretation of "device space"):

```python
for obj in page:
    print(f"{obj.object_type} at {obj.bbox}")
    left, top, right, bottom = obj.bbox
    print(f"  top left is {left, top}")
    print(f"  bottom right is {right, botom}")
```

Another important piece of information (which `pdfminer.six` does not
really handle) is the relationship between layout and logical
structure, done using *marked content sections*:

```python
for obj in page:
    print(f"{obj.object_type} is in marked content section {obj.mcs.mcid}")
    print(f"    which is tag {obj.mcs.tag.name}")
    print(f"    with properties {obj.mcs.tag.props}")
```

The `mcid` here is the same one referenced in elements of the
structure tree as shown above (but remember that `tag` has nothing to
do with the structure tree element, because Reasons).  A marked
content section does not necessarily have a `mcid` or `props`, but it
will *always* have a `tag`.

PDF also has the concept of "marked content points". PLAYA suports
these with objects of `object_type == "tag"`.  The tag name and
properties are also accessible via the `mcs` attribute.

### Form XObjects

A PDF page may also contain "Form XObjects" which are like tiny
embedded PDF documents (they have nothing to do with fillable forms).
The lazy API (because it is lazy) **will not expand these for you**
which may be a source of surprise.  You can identify them because they
have `object_type == "xobject"`.  The layout objects inside them are
accessible by iteration, as with pages (but **not** documents):

```python
for obj in page:
    if obj.object_type == "xobject":
        for item in obj:
            ...
```

You can also iterate over them in the page context with `page.xobjects`:

```python
for xobj in page.xobjects:
    for item in xobj:
        ...
```

Exceptionally, these have a few more features than the ordinary
`ContentObject` - you can look at their raw stream contents as well as
the tokens, and you can also see raw, mysterious PDF objects with
`contents`.

### Graphics state

You may also wish to know what color an object is, and other aspects of
what PDF refers to as the *graphics state*, which is accessible
through `obj.gstate`.  This is a mutable object, and since there are
quite a few parameters in the graphics state, PLAYA does not create a
copy of it for every object in the layout - you are responsible for
saving them yourself if you should so desire.  This is not
particularly onerous, because the parameters themselves are immutable:

```python
for obj in page:
    print(f"{obj.object_type} at {obj.bbox} is:")
    print(f"    {obj.gstate.scolor} stroking color")
    print(f"    {obj.gstate.ncolor} non-stroking color")
    print(f"    {obj.gstate.dash} dashing style")
    my_stuff = (obj.dash, obj.gstate.scolor, obj.gstate.ncolor)
    other_stuff.append(my_stuff)  # it's safe there
```

For compatbility with `pdfminer.six`, PLAYA, even though it is not a
layout analyzer, can do some basic interpretation of paths.  Again,
this is lazy.  If you don't care about them, you just get objects with
`object_type` of `"path"`, which you can ignore.  PLAYA won't even
compute the bounding box (which isn't all that slow, but still).  If
you *do* care, then you have some options.  You can look at the actual
path segments in user space (fast):

```python
for seg in path.raw_segments:
   print(f"segment: {seg}")
```

Or in PLAYA's "device space" (not so fast):

```python
for seg in path.segments:
   print(f"segment: {seg}")
```

This API doesn't try to interpret paths for you.  You only get
`PathSegment`s.  But for convenience you can get them grouped by
subpaths as created using the `m` or `re` operators:

```python
for subpath in path:
   for seg in subpath.segments:
       print(f"segment: {seg}")
```

### Text Objects

Since most PDFs consist primarily of text, obviously you may wish to
know something about the actual text (or the `ActualText`, which you
can sometimes find in `obj.mcs.tag.props["ActualText"]`).  This is
more difficult than it looks, as fundamentally PDF just positions
arbitrarily numbered glyphs on a page, and the vast majority of PDFs
embed their own fonts, using *subsetting* to include only the glyphs
actually used.

Whereas `pdfminer.six` would break down text objects into their
individual glyphs (which might or might not correspond to characters),
this is not always what you want, and moreover it is computationally
quite expensive.  So PLAYA, by default, does not do this.  If you
don't need to know the actual bounding box of a text object, then
don't access `obj.bbox` and it won't be computed.  If you don't need
to know the position of each glyph but simply want the Unicode
characters, then just look at `obj.chars`.

Also, a lot of PDFs, especially ones produced by OCR, don't organize
text objects in any meaningful fashion, so you will want to actually
look at the glyphs.  This becomes a matter of iterating over the item,
giving you, well, more items, which are the individual glyphs:

```python
for glyph in item:
    print("Glyph has CID {glyph.cid} and Unicode {glyph.text}")
```

By default PLAYA, following the PDF specification, considers the
grouping of glyphs into strings irrelevant by default.  I *might*
consider separating the strings in the future.

PDF has the concept of a *text state* which determines some aspects of
how text is rendered.  You can obviously access this though
`glyph.textstate` - note that the text state, like the graphics state,
is mutable, so you will have to copy it or save individual parameters
that you might care about.

PLAYA doesn't guarantee that text objects come at you in anything
other than the order they occur in the file (but it does guarantee
that).

In some cases might want to look at the abovementioned `ActualText`
attribute to reliably extract text, particularly if the PDF was
created by certain versions of LibreOffice, but in their infinite
wisdom, Adobe made `ActualText` a property of *marked content
sections* and not *text objects*, so you may be out of luck if you
want to actually match these characters to glyphs.  Sorry, I don't
write the standards.

## Conclusion

As mentioned earlier, if you really just want to do text extraction,
there's always pdfplumber, pymupdf, pypdfium2, pikepdf, pypdf, borb,
etc, etc, etc.

## Acknowledgement

This repository obviously includes code from `pdfminer.six`.  Original
license text is included in
[LICENSE](https://github.com/dhdaines/playa/blob/main/LICENSE).  The
license itself has not changed!
