README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# tidypass

<!-- badges: start -->
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
<!-- badges: end -->

A tidy R interface to the [Postpass](https://github.com/woodpeck/postpass-ops) service. Allows you to use dplyr syntax to retrieve OpenStreetMap data using [`{dbplyr}`](https://dbplyr.tidyverse.org/). Postpass is a nice alternative to [Overpass Turbo](https://overpass-turbo.eu/) that is faster and more versatile because it uses a Postgres database in the background.

## Installation

You can install the development version of tidypass from [GitHub](https://github.com/) with:

``` r
# install.packages("pak")
pak::pak("jslth/tidypass")
```

## Example

This is a basic example which extracts all fast food restaurants in Karlsruhe along with their stated cuisine. Generally, only the four columns can be accessed directly (`tags`, `osm_id`, `osm_type`, and `geom`) and all other features have to be extracted from the tags list using the `%->>%` operator.

```{r example}
library(tidypass)
library(dplyr, warn.conflicts = FALSE)
library(sf, quietly = TRUE)

# Boundaries of Karlsruhe
bbox <- st_as_sfc(st_bbox(c(
  xmin = 8.34,
  xmax = 8.46,
  ymin = 48.97,
  ymax = 49.03
)))

pp_tbl("point") |>
    filter(tags %->>% 'amenity' == "fast_food" & geom %&&% !!pg_bbox(bbox)) |>
    transmute(cuisine = tags %->>% "cuisine", name = tags %->>% 'name', geom) |>
    collect()
```