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Copy file name to clipboardExpand all lines: docs/getting_started.Rmd
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The pins package helps you publish data sets, models, and other Python objects, making it easy to share them across projects and with your colleagues.
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You can pin objects to a variety of "boards", including local folders (to share on a networked drive or with DropBox), RStudio connect, Amazon S3,
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Google Cloud Storage, and more.
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Google Cloud Storage, Azure Datalake, and more.
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This vignette will introduce you to the basics of pins.
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```{python}
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-`type = "csv"` uses `to_csv()` from pandas to create a `.csv` file. CSVs can read by any application, but only support simple columns (e.g. numbers, strings, dates), can take up a lot of disk space, and can be slow to read.
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-`type = "joblib"` uses `joblib.dump()` to create a binary python data file. See the [joblib docs](https://joblib.readthedocs.io/en/latest/) for more information.
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-`type = "arrow"` uses `pyarrow` to create an arrow/feather file. [Arrow](https://arrow.apache.org) is a modern, language-independent, high-performance file format designed for data science. Not every tool can read arrow files, but support is growing rapidly.
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🚧 Data formats TODO 🚧
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-`type = "arrow"` uses `arrow::write_feather()` to create an arrow/feather file. [Arrow](https://arrow.apache.org) is a modern, language-independent, high-performance file format designed for data science. Not every tool can read arrow files, but support is growing rapidly.
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-`type = "json"` uses `jsonlite::write_json()` to create a `.json` file. Pretty much every programming language can read json files, but they only work well for nested lists.
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After you've pinned an object, you can read it back with `pin_read()`:
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```
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The pins package publishes data, models, and other Python objects, making it easy to share
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You can pin objects to a variety of pin *boards*, including folders (to share on a networked drive or with services like DropBox), RStudio Connect, Amazon S3, and Google Cloud Storage.
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You can pin objects to a variety of pin *boards*, including folders (to share on a networked drive or with services like DropBox), RStudio Connect, Amazon S3, Google Cloud Storage, and Azure Datalake.
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Pins can be automatically versioned, making it straightforward to track changes, re-run analyses on historical data, and undo mistakes.
You can easily control who gets to access the data using the RStudio Connect permissions pane.
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The pins package also includes boards that allow you to share data on services like Amazon's S3 (`board_s3()`) and Google Cloud Storage (`board_gcs()`).
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The pins package also includes boards that allow you to share data on services like
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Amazon's S3 (`board_s3()`), Google Cloud Storage (`board_gcs()`), and Azure Datalake (`board_azure()`).
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Learn more in [getting started](getting_started.Rmd).
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