The PDFAnalyzer class¶
- class ferenda.PDFAnalyzer(pdf)¶
Create a analyzer for the given pdf file.
The primary purpose of an analyzer is to determine margins and other spatial metrics of a document, and identifiy common typographic styles for default text, title and headings. This is done by calling the metrics() method.
The analysis is done in several steps. The properties of all textboxes on each page is collected in several collections.Counter objects. These counters are then statistically analyzed in a series of functions to yield these metrics.
If different analyzis logic, or additional metrics, are desired, this class should be inherited and some methods/properties overridden.
Parameters: pdf (ferenda.PDFReader) – The pdf file to analyze.
- twopage = True¶
Whether or not the document is expected to have different margins depending on whether it’s a even or odd page.
- style_significance_threshold = 0.005¶
“The amount of use (as compared to the rest of the document that a style must have to be considered significant.
- header_significance_threshold = 0.002¶
The maximum amount (expressed as part of the entire text amount) of text that can occur on the top of the page for it to be considered part of the header.
The maximum amount (expressed as part of the entire text amount) of text that can occur on the bottom of the page for it to be considered part of the footer.
- frontmatter = 1¶
The amount of pages to be considered frontmatter, which might have different typography, special title font etc.
Attempts to distinguish different logical document (eg parts with differing pagesizes/margins/styles etc) within this PDF.
You should override this method if you want to provide your own document segmentation logic.
Returns: Tuples (startpage, pagecount) for the different identified documents Return type: list
- metrics(metricspath=None, plotpath=None, startpage=0, pagecount=None, force=False)¶
Calculate and return the metrics for this analyzer.
metrics is a set of named properties in the form of a dict. The keys of the dict can represent margins or other measurements of the document (left/right margins, header/footer etc) or font styles used in the document (eg. default, title, h1 – h3). Style values are in turn dicts themselves, with the keys ‘family’ and ‘size’.
- metricspath (str) – The path of a JSON file used as cache for the calculated metrics
- plotpath (str) – The path to write a PNG file with histograms for different values (for debugging).
- startpage (int) – starting page for the analysis
- startpage – number of pages to analyze (default: all available)
- force (bool) – Perform analysis even if cached JSON metrics exists.
The default implementation will try to find out values for the following metrics:
key description leftmargin position of left margin (for odd pages if twopage = True) rightmargin position of right margin (for odd pages if twopage = True) leftmargin_even position of left margin for even pages rightmargin_even position of right margin for right pages topmargin position of header zone bottommargin position of footer zone default style used for default text title style used for main document title (on front page) h1 style used for level 1 headings h2 style used for level 2 headings h3 style used for level 3 headings
Subclasses might add (or remove) from the above.
- textboxes(startpage, pagecount)¶
Generate a stream of (pagenumber, textbox) tuples consisting of all pages/textboxes from startpage to pagecount.
- count_horizontal_margins(startpage, pagecount)¶
Return a dict of Counter objects for all the horizontally oriented textbox properties (number of textboxes starting/ending at different positions).
The set of counters is determined by setup_horizontal_counters.
Create initial set of horizontal counters.
- count_horizontal_textbox(pagenumber, textbox, counters)¶
Add a single textbox to the set of horizontal counters.
- count_vertical_margins(startpage, pagecount)¶
- count_vertical_textbox(pagenumber, textbox, counters)¶
- count_styles(startpage, pagecount)¶
- count_styles_textbox(pagenumber, textbox, counters)¶
- analyze_styles(frontmatter_styles, rest_styles)¶
- drawboxes(outfilename, gluefunc=None, startpage=0, pagecount=None, counters=None, metrics=None)¶
Create a copy of the parsed PDF file, but with the textboxes created by gluefunc clearly marked, and metrics shown on the page.
This requires PyPDF2 and reportlab, which aren’t installed by default. Reportlab (3.*) only works on py27+ and py33+
- plot(filename, margincounters, stylecounters, metrics)¶
- plot_margins(subplots, margin_counters, metrics, pagewidth, pageheight)¶
- plot_styles(plot, stylecounters, metrics)¶