PyMARC examples

[Ivan M]

Hi, can anyone please in this group try to provide some PyMARC usage examples, from parsing MARC21 data to implementing those data to some final product for which you needed MARC21 data in the first place? Thanks! 

[Clara Turp]

Hi Ivan,

I have a few examples. Mostly parsing MARC data and modifying MARC records (adding fields). Should we share the full scripts or bits? Share from Github? Thanks!

[Jennifer Marie]

If you have examples of updating a mrc file, I'd really appreciate it if you could share. If you send a github link, that would be great.

Thanks,

Jennifer

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[Ivan M]

Hi, GitHub would be great. But the thing that kinda bugs me is why do you parse MARC data in the first place and what do you actually do with parsed data? I'm not that familiar with MARC format, it do seems a bit old, but still, for instance, if you work on some web app and your MARC data is essential part of your app's functionality, can't you just fetch MARC data from a database and use it to power your app?

[Geoffrey Spear]

For me, and I suspect many others, the most common use case would be to export bibliographic records from an ILS, transform them in some way (in my case, usually a cleanup by removing certain fields, or rewriting URLs because an e-resource vendor finally implemented HTTPS or changed their domain name), then load them back into the same ILS.

I also do a lot of cleanup of regular loads of vendor records before loading them at all. Many of them have predictable quality problems that a cataloguer used to fix by following a long set of manual steps in MARCEdit. Replacing this tedious work with python scripts saves a lot of time and also takes away human error while following the big list of steps.

[Clara Turp]

Similarly, I used pymarc on extracted bibliographic records. I wrote my scripts during a system migration. It was part of the clean up process and part of the fitting the new data requirements process.

I also use it when I need certain fields from a subset of the extracted records (post-migration clean up).

It's useful when you want to run a clean up project that you can't easily do in your ILS.

I'll put my scripts on Github and share the link Today.

Clara

[Clara Turp]

Here are the scripts. I'll take the time to write the read me file and explain what each script is suppose to do, but at least the scripts are there now.

https://github.com/ClaraTurp/PyMARCExamples

Thanks!

[Ivan M]

Great, thank you so much for the GitHub link!

Does anybody know is there a Facebook group regarding this topic, or any kind of ILS-datacleaning/datamanipulating social network community besides this Google group?

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[Jennifer Marie]

yes a giant thank you Clara. I don't know of any venue beyond this Google group. 

jennifer

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[Shirley Lincicum]

While not devoted exclusively to ILS datacleaning/datamanipulating, I'd encourage you to check out code4lib -  https://code4lib.org/  where many library developers gather, and questions/issues related to working with MARC data are periodically discussed in various chat channels  -  https://code4lib.org/irc/ -  on the Mailing list  https://lists.clir.org/cgi-bin/wa?A0=CODE4LIB and in the Journal - https://journal.code4lib.org/

I believe that an original/lead developer of pymarc is still a member of the code4lib community.

Shirley

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[Geoffrey Spear]

There's also a code4lib Slack that is possibly a bit better than IRC for more detailed (and slightly less ephemeral since you don't need to be connected constantly to see conversations, although the history is limited since we're using the free tier) technical conversations. 

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