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docs: add reference index page
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docs/_config.yml

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sphinx:
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config:
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add_module_names: true
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nb_custom_formats:
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.Rmd:
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- jupytext.reads

docs/api/boards.rst

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Board
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=====
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Board Methods
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=============
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.. currentmodule:: pins
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docs/api/constructors.rst

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Board Constructors
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==================
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.. currentmodule:: pins
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.. autosummary::
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:toctree: api_card/
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~board_folder
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~board_local
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~board_temp
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~board_s3
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~board_rsconnect

docs/api/filesystem.rst

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docs/api/index.rst

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Reference
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=============
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Board Pin Methods
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-----------------
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.. table::
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:class: table-align-left
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=========================================== =======================================================
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:meth:`.pin_read`, :meth:`.pin_write` |read-write|
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:meth:`.pin_meta` |arrange|
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:meth:`.pin_download`, :meth:`.pin_upload` |select|
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:meth:`.pin_versions`, TODO complete |mutate|
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:meth:`.pin_list` |summarize|
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:meth:`.pin_search` |group_by|
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=========================================== =======================================================
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.. |read-write| replace:: Read and write objects to and from a board
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.. |arrange| replace:: Retrieve metadata for a pin
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.. |select| replace:: Upload and download files to and from a board
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.. |mutate| replace:: List, delete, and prune pin versions
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.. |summarize| replace:: List all pins
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.. |group_by| replace:: Search for pins
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Board Constructors
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------------------
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Boards abstract over different storage backends, making it easy to share data in a variety of ways.
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.. list-table::
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:class: table-align-left
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* - :func:`.board_folder`, :func:`board_local`
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- Use a local folder as a board
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* - :func:`.board_rsconnect`
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- Use RStudio Connect as a board
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* - :func:`.board_s3`
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- Use an S3 bucket as a board
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.. toctree::
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:maxdepth: 2
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constructors
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boards
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meta
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filesystem

docs/getting_started.Rmd

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name: venv-pins-python
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---
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```{python tags=c(), nbsphinx="hidden"}
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```{python tags=c("remove-input"), nbsphinx="hidden"}
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import pandas as pd
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pd.options.display.max_rows = 25
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```

docs/intro.md

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# Welcome
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```{image} logo.png
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:align: right
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:height: 139px
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:alt: pins, a library for organizing and sharing data.
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```
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The pins package publishes data, models, and other R 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 pin *boards*, including folders (to share on a networked drive or with services like DropBox), RStudio Connect, Amazon S3, Azure storage and ~Microsoft 365 (OneDrive and SharePoint)~.
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Pins can be automatically versioned, making it straightforward to track changes, re-run analyses on historical data, and undo mistakes.
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```python
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board <- board_rsconnect()
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from pins import board_rsconnect
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board = board_rsconnect()
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#> Connecting to RSC 1.9.0.1 at <https://connect.rstudioservices.com>
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board.pin_write(tidy_sales_data, "sales-summary", type = "rds")
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board.pin_write(tidy_sales_data, "sales-summary", type = "csv")
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#> Writing to pin 'hadley/sales-summary'
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```
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docs/logo.png

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pins/__init__.py

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# Imports ----
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from .boards import BaseBoard
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from .constructors import *
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from .cache import PinsCache, PinsUrlCache, cache_prune
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from .constructors import (
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board_deparse,
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board_folder,
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board_temp,
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board_local,
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board_github,
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board_urls,
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board_rsconnect,
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board_s3,
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)

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