Ever chase a CSV through a series of emails or had to decide between data-final.csv and data-final-final.csv?
Pins (both for R & Python) is a package that a bunch of people at the Data Science Hangout wish they knew about earlier. It allows you to publish and share objects (data, models, etc.) across projects and with your colleagues.
Pins package (R) - pins.rstudio.com/
Pins package (Python) - pypi.org/project/pins/
Timestamps:
1:15 - Posit Team Overview
2:18 - Introduction to pins (scenarios where you might want to consider using pins)
4:42 - Installing pins
6:24 - Workflow #1: Pinning an R Object to Posit Connect (from RStudio)
10:23 - Workflow #2: Pinning a Python Object to Posit Connect (from JupyterLab)
15:19 - Workflow #3: Reading in a Python pin in an R Session
16:07 - Workflow #4: Reading an R pin into a Python session
17:50 - Workflow #5: Pin versioning
21:50 - Workflow #6: Automating the pin writing process (through job scheduling on Connect)
Helpful resources:
Q&A for this session on August 30th: kzitem.info8hc9ck1ZNLE
Blog post on pinning an R dataset to Posit Connect: posit.co/blog/pins-posit-conn...
Many people find this useful for:
1. Scheduling reports that need to be updated with the newest data each week
2. Reusing data across multiple projects or content (Shiny app, Jupyter Notebook, Quarto doc, etc.)
We host these end-to-end workflow demos on the last Wednesday of every month. No registration is required to attend - simply add it to your calendar using this link: pos.it/team-demo
If you ever have ideas for topics or questions about them, please let us know in the comments.
Негізгі бет How to keep data up-to-date with 6 pins workflows (aka avoid data-final.csv & data-final-final.csv)
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