Menotexport v1.5.1

Remove pandas dependency

Also fix the issue that when a field fetched is a sequence (e.g. first names), and the sequence
has duplicates, the duplicates were removed, which could result in wrong author list.

Menotexport v1.5.0

Fix multiple attachment issue:
When a document has more than one attachments (e.g. supplementary materials that go along a paper), now the export puts respective highlights and notes to each attached PDF, while summarizing annotations from all attachments to the exported txt file.

Quite some changes under the hood to implement the change, resulting in cleaner code, but unfortunately not so much of speed up.

Fetch side-bar notes (aka "General notes") correctly.

Some minor fixes, including excluding the comma ":" from output folder name, as it's an illegal symbol in Windows and Mac systems.

Menotexport v1.4.4

add custom template
fix autorename function

Menotexport v1.4.3

Fix the tag list issue in anaconda build

Menotexport v1.4.2

Fix parent id 0 bug.
Fix tags as nested list bug.

Menotexport v1.4.1

Add conda install option

Menotexport version1.4

Added:

• Export to .bib and .ris files.
• New colors in the highlighted texts in exported PDFs.
• Support for nested Mendeley folders.
• Bug fixes.

Menotexport version1.1

• Supports both command line and gui usage.
• Allows specifying a folder to work on.
• Improved line break detection. Fewer erroneous '......' are inserted.
• Various minor fixes.

Menotexport command line version

Menotexport

Menotexport (Mendeley-Note-Export) extracts highlights and notes from your Mendeley database

What does this do?

Menotexport.py is a simple python solution to help extracts annotations (highlighted
texts and sticky notes) you made in the build-in PDF reader of Mendeley.

Mendeley is a desktop and web program for managing and sharing research
papers. It offers free desktop clients for Windows, OSX and Linux. But the
software is not open source, and their support team has been real slow in responding
to customers feature requests, some of which has been proposed by many for YEARS.
This tool aims at solving the following:

1. Bulk export annotated PDFs.

Annotations (highlights and notes) made inside Mendeley are saved not directly onto
the relevant PDFs, but to a separate database file. Therefore these annotations can
not be viewered in another PDF reader other than Mendeley itself.

The native but awkward solution to export a PDF with its annotations is: in
Mendeley, open that PDF in the Mendeley PDF reader, go to Files -> Export PDF
with annotations. However to export all your collections, this has to be repeated
manually for each individual PDF in your library.

This script can bulk export all PDFs with annotations to a given folder, and
the annotations are readable by other PDF softwares. NOTE that PDFs with no annotations
are not exported.

2. Extract annotation texts.

To extract texts from the highlights and sticky notes in a PDF, other than
Copy-n-Paste one by one, some softwares offer an automated solution.

skim on OSX has the functionality to produce a summary of all annotations.

Some versions of Foxit Reader can do that (on windows, not on the Linux version, not sure about Mac).

Pro versions of Adobe Reader may have that too.

Most of the PDF readers in Linux do not have that functionality. (Let me know if you find one).

This tool could extract the texts from the highlights and notes in the PDFs in Mendeley
to a plain text file, and format the information in a sensible structure.

Usage

python menotexport.py [-h] [-e] [-m] [-n] [-w] [-s] dbfile outputdir

where

• -h: Show help messages.
• -e: Bulk export PDFs to a folder given by outputdir.
• -m: Extract markups (highlighted texts).
• -n: Extract notes.
• -w: Do not overwrite existing files in outputdir. Default to overwrite.
• -s: Save extracted texts to a separate txt file for each PDF. Default to
  save all texts to a single file.
• dbfile: Absolute path to the Mendeley database file. In Linux systems default location is
  ~/.local/share/data/Mendeley\ Ltd./Mendeley\ Desktop/your_email@www.mendeley.com.sqlite
• outputdir: folder to save outputs.
• If -s, texts for each PDF is saved to Anno_PDFTITLE.txt (if both -m and
  -n are given), or to Highlights_PDFTITLE.txt or Notes_PDFTITLE.txt (if
  either -m or -n is given).
• If not -s, save extracted texts from all PDFs to Mendeley_annotations.txt
  (if both -m and -n are given), or to Mendeley_highlights.txt or
  Mendeley_notes.txt (if either -m or -n is given).
• If not -s, also generate another txt Mendeley_annotations_by_tags.txt where
  information is grouped by tags.

Example:

To bulk export, extract and save to separate txt files:

python menotexport.py -emns dbfile outputdir

Caveats and further notes

• The bulk PDF export works with quite good accuracy, most highlights and notes are
  reproduced as they should be.
• Note extraction works with quite good accruacy.
• Highlight extraction accuracy is compromised, due to the inherent nature of the PDF
  format. Not all texts are correctly extracted, and the order they appear in the output
  may not be exactly the same as in the PDFs (top-down, left-right). DO proof read afterwards.
• Highlighted texts from a single "block" of texts are treated as one record/entry. A "block" of
  texts is a continuous chunk of texts in the PDF, could be a whole paragraph, a single
  line separated from others, or a single isolated word. This ambiguity is again due to the inherent
  nature of PDF format. Again proof read the results.
• Citationkeys and tags are added to the extracted texts to facilitate further information
  processes, both can be editted in Mendeley.
• If choose to save all annotations to a single file, the programme also re-structure the extracted texts
  and organize them by their tags before saving to a separate file. Pieces of texts from a PDF that isn't taged are given
  a tag of @None.
• Possible follow-ups one can do: re-format the extracted txts to PDFs, docs or sync into
  your Evernote account, will probably implement these in a later version.

Dependencies

Developed in python2.7. Haven't tested in python 3.

It requires the following packages:

• PyPDF2
• sqlite3
• pandas
• pdfminer
• numpy

It further incorporate (with minor adjustments) the pdfannotation.py file from
the Menextract2pdf project.

Platform/OS

The software is tested on Linux, should also run on Mac.
Will create a windows version later.

Versions

• 0.1 first release

Licence

The script is distributed under the GPLv3. The pdfannotations.py file is
LGPLv3.

Related projects

• Mendeley2Zotero
• Adios_Mendeley
• Menextract2pdf