The presentation by Katharine Frazier discusses using Python to enhance library workflows, particularly focusing on automating repetitive tasks and data manipulation. It introduces various Python libraries such as Pandas for data handling, Selenium for web automation, and FuzzyWuzzy for string matching, and emphasizes project-based learning. Attendees are encouraged to consider their own library project needs and explore how Python can improve efficiency and accuracy in their operations.

1. Here’s What Python Does
for Us: What Can it Do for
Your Library?
Katharine Frazier
NC State University Libraries

2. The following presentation is being shared
with EBSCO’s permission. Certain functions
shown in the slides will only be available to
GOBI customers.

3. ● Large public university
(>34,000 FTE)
● STEM-focused
● Collections & Research
Strategy department

4. Getting Started
Identifying project opportunities
Learning & implementing Python

5. Diving In
Automating web interactions (GOBI)
Automating data manipulation
Spreading the word about code

6. Your Turn!
How do YOU want to use Python to improve
your workflows?

7. Getting Started

8. The most important step:
Realizing there’s a problem.

9. Example:
Time-consuming
monthly reports!

11. ● Not very accurate
● Limited to just one type of
search at a time
● Searching by ISBN is no good!

12. ● Getting better…
● Requires users to repeatedly
navigate back to standard search

13. Results are not
ordered by date or
edition, and include
duplicative items

15. 1. Search for and identify matches in GOBI
2. Select only same or newer editions
3. Add purchase information to reports
...and do it faster!

16. Identifying solutions
not in plain sight

17. “Python is good for repetitive work, and
working with large sets of data
programmatically instead of by hand.”

19. I want to do this task today... There’s a Python library for that!
Data manipulation Pandas
Web automation Selenium
Spreadsheet writing OpenPyxl/Pandas
String matching Fuzzywuzzy

20. Project-Based Learning

25. The learning never
stops!

26. Let’s see a demo!

27. 1. Takes a list of items (holdings data) and
searches GOBI for matches
2. Grabs the price, binding, year of publication for
each match
3. Selects newest edition, matches to original list
of holdings data

28. Diving in

30. Pandas: a library for creating and
manipulating dataframes, reading
from and writing to files (.xlsx, .csv)

31. Selenium: a library for automating
web interactions

32. Requests: a function for navigating
to web pages using Selenium
ex: browser.get(‘http://www.lib.ncsu.edu)

33. Fuzzywuzzy: a module for creating
fuzzy (inexact) string matches

34. Re: a module for creating regular
expressions (search pattern)
text = “Pub date: 2019”
output = re.search(“d{4}”, text)

35. Xlsxwriter: a module for creating
Excel documents within Python

41. ● Use regular expressions to find desired values
● Use fuzzy string matching to identify title matches
● Send matching title information to lists

42. ● Create DataFrame from dictionary
● Create sub-frames for print and ebook options

43. ● Sort each DataFrame by descending date
● Drop duplicates: keep only the newest copy
available

44. ● Merge print and ebook DataFrames
● This results in one DataFrame with both print and
ebook purchase information, and only one option
for each title

45. Spreading the
word about
code projects

46. Sharing with the library community
● Code4Lib listserv
● Conferences (MDLS, Internet
Librarian, etc…)
● LITA, technology groups

47. Licensing code
● MIT License
● General Public License (GPL)
● Apache License
● https://choosealicense.com/licenses/

48. Your Turn!

49. Think about...
● Your own project needs
● What types of Python activities (data
manipulation, automation) would help?

50. Idea Generation…
● Code4Lib Journal
● Library Carpentry
● PyPi.org
● StackOverflow

51. How do YOU want to use Python to
improve your workflows?

52. Thank you!
Katharine Frazier | kfrazie2@ncsu.edu
https://github.com/kchasefray/GOBI_Searching