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scripts for parsing raw reading list and citations file from Barnes & Noble, and creating reserves and purchase lists based on Alma holdings

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tufts-libraries-barnes-noble-reading-list

tufts-libraries-barnes-noble-reading-list

Title: Parse Barnes & Noble Reading Lists

Author: Henry Steele, Library Technology Services, Tufts University

parseBN.py:

**Purpose:**

-  Parse the raw output file Barnes & Noble provides, which is simply the text 
   output of a webpage, into a dataframe which can be exported to Excel and
   sent to Collections.

**Input:**

- raw output from Barnes & Noble, usually from a person named "Boon"
- the name of this file has always been "qprint.txt"

**Running:**

- execute the script in Python by python parseBN.py
- choose raw Barnes & Noble file in the file picker

**Output:**
- in script's main directory, there will be a file called "Cleaned Barnes and Noble File <date> .xls"
- this file will be one of the input files for the next phase of this process, using compare.py

compare.py

**Purpose:**
- Determine which titles from the list of Barnes & Noble readings
are not already in our collection (Tufts/Alma), to identify
titles for puchase in the AS&E Textbook Initiative

For each valid ISBN in the Barnes and Noble file, the script attempts
to retrieve the bib record for this record from our Alma SRU 
(Search/Retrieval by URL) endpoint.  
	
**Input:**

- output of parseBN.py "Cleaned Barnes and Noble File <date>.xls"
- course subset
  - this is the list of courses numbers that you wish to seek in
    in the Barnes and Noble

**Output:**

- Books We Have.xlsx
    - If a record is retrieved from SRU, then
      we have the item in Alma, and information about the item including MMS ID,
      title, and course information, go in this file
- Books to Order.xslx
    - Otherwise, the citation goes in this file, of thigns to be ordered

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