* Run `make cmap` and `git add pdfminer/cmap`.
* Modify MANIFEST.in not to include cmaprsrc dir in the sdist package.
* Add pdfminer/cmap/README.txt to include license in the sdist package.
* Remove installation guide specific to CJK languages from README.md.
As stated in the PDF specification ISO 32000-1, table in Annex D.2 Latin Character Set and Encodings page 653 to 656 (available here: http://www.adobe.com/content/dam/Adobe/en/devnet/acrobat/pdfs/PDF32000_2008.pdf):
"The SPACE character shall also be encoded as 312 in MacRomanEncoding and as 240 in WinAnsiEncoding. This duplicate code shall signify a nonbreaking space; it shall be typographically the same as (U+003A) SPACE."
The duplicate key was missing, therefore PDFMiner was returning the string "(cid:160)".
This fix adds the duplicate key in latin_enc.py
glyphlist.py does not need to be modified as it already contains a key for non breaking space https://github.com/lucanaso/pdfminer/blob/master/pdfminer/glyphlist.py#L2755.
Sorry, changes should have been more atomic.
*In pdf2txt.py:*
* Re-wrote main function to use argparse instead of optparse.
* Manually tested in Py2/Py3 to get partial consistency.
* Errors abound including Tags mode, but most modes weren't working at all in Py3 anyway.
* Py2 mode *probably* unchanged, cannot find any bugs yet...
* Kept old main function for posterity, for now.
*In utils:*
* Added a few compatibility functions (some string hax required chardet, new dependency):
- make_compat_bytes(in_str)-> (py3->bytes | py2->str)
- make_compat_str(in_str)-> (str)
- compatible_encode_method(bytesorstring, encoding, erraction)-> (str)
*In pdfdevice:*
* To handle different output filetypes in Py3, injected lots of calls to new utils methods,
as well as some six.PYX checks and logic. These changes are largely responsible for
enhanced Py2/Py3 consistency.
*In converter:*
* To handle output filetypes in Py2, injected a few checks and fixes particularly around the
py2 `str.encode` method and its *assumed* usual use-analogies in Py3.
This commit finds horizontal neighbors in a horizonal line and merges them together into a single horizontal line if necessary. This leads to much better text extraction if the PDF was created in a funky way.
For example (test case coming), I have seen PDFs which are written almost like vertical columns, but the text is entirely horizontal.