From c49719bd2fdb4fe709e33733fbe9469241c9ed9a Mon Sep 17 00:00:00 2001 From: LuisDVA Date: Thu, 5 Sep 2024 10:18:01 -0600 Subject: [PATCH 1/4] add logo --- README.Rmd | 2 +- man/figures/logo.png | Bin 0 -> 151220 bytes 2 files changed, 1 insertion(+), 1 deletion(-) create mode 100644 man/figures/logo.png diff --git a/README.Rmd b/README.Rmd index 5bee8243..91a07085 100644 --- a/README.Rmd +++ b/README.Rmd @@ -31,7 +31,7 @@ local({ Sys.setenv(DUCKPLYR_OUTPUT_ORDER = TRUE) ``` -# duckplyr +# duckplyr [![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental) diff --git a/man/figures/logo.png b/man/figures/logo.png new file mode 100644 index 0000000000000000000000000000000000000000..fa3750d648801961e4d2dbe03b204cce9737b998 GIT binary patch literal 151220 zcmaHU2|ShQ`~E9azSUq_l`KiRBrAW$hC|kDEXi^C&QG}U@?hoVcFsHCv0b9vyAlhf8BZ5Tco?O&|StMrjMm2dHe3|*~3b?Pk!sF z{NuiVOx2^|@&~&byM4TtzKEL 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z66YqVhP0y#nJQoQ7hcO((&>Fg;#{|sHREJ3!I353Y-c2&DGj|jBBt15cXM!{E7of{ z`WI*wWL9BjLh-%B$_wy=n1WV;>s0c9D^11^T8gO-Qda}Pwl!TM)BZn?QilZH+>_)c zi0&}~H_s}D{x5{0s6a(jh!g+Cp@2{zLm!6P*`ABolU~?xd){aZ6a8&oVpMrc^N5)A z=+=@@&DOX>Q%eA{Y%`p&nv zw^xkJ_sm6#uZO=>23DTkT@YOix(=-2sRg@H!gJ9$6&1(v<0Lp{{ zBitg=&$%1E9BuGnmJFQyS*bPNI6P(3ig3U{{BoM87bn9;&TJ?RjAc(@Jkr@v=X zLQMDh$HV9>fOzW~sel1b2#hNKLbj_P<2D+cd$24bI(p1~w5wDEBw|>fi6Qch9nDC8OFPGSF&m%6J*th%OkBprb Gzy3d0BaSKn literal 0 HcmV?d00001 From 780743d8d40eab716af1616c0d47318d37cd247e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kirill=20M=C3=BCller?= Date: Wed, 25 Sep 2024 08:49:30 +0200 Subject: [PATCH 2/4] Add logo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8b163b69..aae95381 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ -# duckplyr +# duckplyr From a1a02ec45acb30fc6efc50d5fce561546593ca02 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kirill=20M=C3=BCller?= Date: Wed, 25 Sep 2024 08:49:58 +0200 Subject: [PATCH 3/4] Render with duckdb 1.1.0 --- README.md | 90 ++++++++++++++++++++++++++++++++----------------------- 1 file changed, 52 insertions(+), 38 deletions(-) diff --git a/README.md b/README.md index aae95381..f98eb0ce 100644 --- a/README.md +++ b/README.md @@ -41,7 +41,7 @@ Or from [GitHub](https://github.com/) with: There are two ways to use duckplyr. -1. To enable duckplyr for individual data frames, use [`duckplyr::as_duckplyr_tibble()`](https://tidyverse.github.io/duckplyr/reference/as_duckplyr_tibble.html) as the first step in your pipe, without attaching the package. +1. To enable duckplyr for individual data frames, use [`duckplyr::as_duckplyr_tibble()`](https://tidyverse.github.io/duckplyr/reference/as_duckplyr_df.html) as the first step in your pipe, without attaching the package. 2. By calling [`library(duckplyr)`](https://tidyverse.github.io/duckplyr/), it overwrites dplyr methods and is automatically enabled for the entire session without having to call `as_duckplyr_tibble()`. To turn this off, call `methods_restore()`. The examples below illustrate both methods. See also the companion [demo repository](https://github.com/Tmonster/duckplyr_demo) for a use case with a large dataset. @@ -50,14 +50,14 @@ The examples below illustrate both methods. See also the companion [demo reposit This example illustrates usage of duckplyr for individual data frames. -Use [`duckplyr::as_duckplyr_tibble()`](https://tidyverse.github.io/duckplyr/reference/as_duckplyr_tibble.html) to enable processing with duckdb: +Use [`duckplyr::as_duckplyr_tibble()`](https://tidyverse.github.io/duckplyr/reference/as_duckplyr_df.html) to enable processing with duckdb:

 out <-
   palmerpenguins::penguins %>%
   # CAVEAT: factor columns are not supported yet
   mutate(across(where(is.factor), as.character)) %>%
-  duckplyr::as_duckplyr_tibble() %>%
+  duckplyr::as_duckplyr_tibble() %>%
   mutate(bill_area = bill_length_mm * bill_depth_mm) %>%
   summarize(.by = c(species, sex), mean_bill_area = mean(bill_area)) %>%
   filter(species != "Gentoo")
@@ -77,86 +77,100 @@ duckdb is responsible for eventually carrying out the operations. Despite the la explain() #> ┌───────────────────────────┐ #> │ ORDER_BY │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ -#> │ ORDERS: │ +#> │ ──────────────────── │ #> │ dataframe_42_42 │ #> │ 42.___row_number ASC │ -#> └─────────────┬─────────────┘ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ FILTER │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ -#> │r_base::!=(species, 'Gentoo│ -#> │ ') │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ -#> │ EC: 34 │ -#> └─────────────┬─────────────┘ +#> │ ──────────────────── │ +#> │ "r_base::!="(species, │ +#> │ 'Gentoo') │ +#> │ │ +#> │ ~34 Rows │ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ PROJECTION │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ #> │ #0 │ #> │ #1 │ #> │ #2 │ #> │ #3 │ -#> └─────────────┬─────────────┘ +#> │ │ +#> │ ~172 Rows │ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ STREAMING_WINDOW │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ +#> │ Projections: │ #> │ ROW_NUMBER() OVER () │ -#> └─────────────┬─────────────┘ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ ORDER_BY │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ -#> │ ORDERS: │ +#> │ ──────────────────── │ #> │ dataframe_42_42 │ #> │ 42.___row_number ASC │ -#> └─────────────┬─────────────┘ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ HASH_GROUP_BY │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ +#> │ Groups: │ #> │ #0 │ #> │ #1 │ +#> │ │ +#> │ Aggregates: │ #> │ min(#2) │ #> │ mean(#3) │ -#> └─────────────┬─────────────┘ +#> │ │ +#> │ ~172 Rows │ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ PROJECTION │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ #> │ species │ #> │ sex │ #> │ ___row_number │ #> │ bill_area │ -#> └─────────────┬─────────────┘ +#> │ │ +#> │ ~344 Rows │ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ PROJECTION │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ #> │ #0 │ #> │ #1 │ #> │ #2 │ #> │ #3 │ -#> └─────────────┬─────────────┘ +#> │ │ +#> │ ~344 Rows │ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ STREAMING_WINDOW │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ +#> │ Projections: │ #> │ ROW_NUMBER() OVER () │ -#> └─────────────┬─────────────┘ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ PROJECTION │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ #> │ species │ #> │ sex │ #> │ bill_area │ -#> └─────────────┬─────────────┘ +#> │ │ +#> │ ~344 Rows │ +#> └─────────────┬─────────────┘ #> ┌─────────────┴─────────────┐ #> │ R_DATAFRAME_SCAN │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ ──────────────────── │ #> │ data.frame │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ +#> │ │ +#> │ Projections: │ #> │ species │ #> │ bill_length_mm │ #> │ bill_depth_mm │ #> │ sex │ -#> │ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ -#> │ EC: 344 │ +#> │ │ +#> │ ~344 Rows │ #> └───────────────────────────┘ All data frame operations are supported. Computation happens upon the first request. @@ -169,13 +183,13 @@ All data frame operations are supported. Computation happens upon the first requ #> --------------------- #> Projection [species as species, sex as sex, mean_bill_area as mean_bill_area] #> Order [___row_number ASC] -#> Filter [!=(species, 'Gentoo')] +#> Filter ["!="(species, 'Gentoo')] #> Projection [species as species, sex as sex, mean_bill_area as mean_bill_area, row_number() OVER () as ___row_number] #> Projection [species as species, sex as sex, mean_bill_area as mean_bill_area] #> Order [___row_number ASC] #> Aggregate [species, sex, min(___row_number), mean(bill_area)] #> Projection [species as species, island as island, bill_length_mm as bill_length_mm, bill_depth_mm as bill_depth_mm, flipper_length_mm as flipper_length_mm, body_mass_g as body_mass_g, sex as sex, "year" as year, bill_area as bill_area, row_number() OVER () as ___row_number] -#> Projection [species as species, island as island, bill_length_mm as bill_length_mm, bill_depth_mm as bill_depth_mm, flipper_length_mm as flipper_length_mm, body_mass_g as body_mass_g, sex as sex, "year" as year, *(bill_length_mm, bill_depth_mm) as bill_area] +#> Projection [species as species, island as island, bill_length_mm as bill_length_mm, bill_depth_mm as bill_depth_mm, flipper_length_mm as flipper_length_mm, body_mass_g as body_mass_g, sex as sex, "year" as year, "*"(bill_length_mm, bill_depth_mm) as bill_area] #> r_dataframe_scan(0xdeadbeef) #> #> --------------------- @@ -238,13 +252,13 @@ Querying the number of rows also starts the computation: #> --------------------- #> Projection [species as species, sex as sex, mean_bill_area as mean_bill_area] #> Order [___row_number ASC] -#> Filter [!=(species, 'Gentoo')] +#> Filter ["!="(species, 'Gentoo')] #> Projection [species as species, sex as sex, mean_bill_area as mean_bill_area, row_number() OVER () as ___row_number] #> Projection [species as species, sex as sex, mean_bill_area as mean_bill_area] #> Order [___row_number ASC] #> Aggregate [species, sex, min(___row_number), mean(bill_area)] #> Projection [species as species, island as island, bill_length_mm as bill_length_mm, bill_depth_mm as bill_depth_mm, flipper_length_mm as flipper_length_mm, body_mass_g as body_mass_g, sex as sex, "year" as year, bill_area as bill_area, row_number() OVER () as ___row_number] -#> Projection [species as species, island as island, bill_length_mm as bill_length_mm, bill_depth_mm as bill_depth_mm, flipper_length_mm as flipper_length_mm, body_mass_g as body_mass_g, sex as sex, "year" as year, *(bill_length_mm, bill_depth_mm) as bill_area] +#> Projection [species as species, island as island, bill_length_mm as bill_length_mm, bill_depth_mm as bill_depth_mm, flipper_length_mm as flipper_length_mm, body_mass_g as body_mass_g, sex as sex, "year" as year, "*"(bill_length_mm, bill_depth_mm) as bill_area] #> r_dataframe_scan(0xdeadbeef) #> #> --------------------- @@ -298,7 +312,7 @@ The first time the package encounters an unsupported function, data type, or ope
 palmerpenguins::penguins %>%
-  duckplyr::as_duckplyr_tibble() %>%
+  duckplyr::as_duckplyr_tibble() %>%
   transmute(bill_area = bill_length_mm * bill_depth_mm) %>%
   head(3)
 #> The duckplyr package is configured to fall back to dplyr when it encounters an

From e4a78642180bfe08176393e8faf5b703c4f6cdc5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Kirill=20M=C3=BCller?= 
Date: Wed, 25 Sep 2024 08:46:34 +0200
Subject: [PATCH 4/4] Fix link

---
 DESCRIPTION | 2 +-
 README.md   | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index d0a0a6fd..75db521f 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -13,7 +13,7 @@ Description: A drop-in replacement for 'dplyr', powered by 'DuckDB' for performa
     Also defines a set of generics that provide a low-level
     implementer's interface for the high-level user interface of 'dplyr'.
 License: MIT + file LICENSE
-URL: https://tidyverse.github.io/duckplyr, https://github.com/tidyverse/duckplyr
+URL: https://duckplyr.tidyverse.org, https://github.com/tidyverse/duckplyr
 BugReports: https://github.com/tidyverse/duckplyr/issues
 Depends: 
     R (>= 4.1.0)
diff --git a/README.md b/README.md
index f98eb0ce..25233f1f 100644
--- a/README.md
+++ b/README.md
@@ -42,7 +42,7 @@ Or from [GitHub](https://github.com/) with:
 There are two ways to use duckplyr.
 
 1.  To enable duckplyr for individual data frames, use [`duckplyr::as_duckplyr_tibble()`](https://tidyverse.github.io/duckplyr/reference/as_duckplyr_df.html) as the first step in your pipe, without attaching the package.
-2.  By calling [`library(duckplyr)`](https://tidyverse.github.io/duckplyr/), it overwrites dplyr methods and is automatically enabled for the entire session without having to call `as_duckplyr_tibble()`. To turn this off, call `methods_restore()`.
+2.  By calling [`library(duckplyr)`](https://duckplyr.tidyverse.org), it overwrites dplyr methods and is automatically enabled for the entire session without having to call `as_duckplyr_tibble()`. To turn this off, call `methods_restore()`.
 
 The examples below illustrate both methods. See also the companion [demo repository](https://github.com/Tmonster/duckplyr_demo) for a use case with a large dataset.
 
@@ -218,7 +218,7 @@ After the computation has been carried out, the results are available immediatel
 
 This example illustrates usage of duckplyr for all data frames in the R session.
 
-Use [`library(duckplyr)`](https://tidyverse.github.io/duckplyr/) or [`duckplyr::methods_overwrite()`](https://tidyverse.github.io/duckplyr/reference/methods_overwrite.html) to overwrite dplyr methods and enable processing with duckdb for all data frames:
+Use [`library(duckplyr)`](https://duckplyr.tidyverse.org) or [`duckplyr::methods_overwrite()`](https://tidyverse.github.io/duckplyr/reference/methods_overwrite.html) to overwrite dplyr methods and enable processing with duckdb for all data frames:
 
 
 duckplyr::methods_overwrite()
@@ -367,7 +367,7 @@ The dbplyr package is a dplyr backend that connects to SQL databases, and is des
 This package also provides generics, for which other packages may then implement methods.
 
 
-library(duckplyr)
+library(duckplyr)
 #>  Overwriting dplyr methods with duckplyr methods.
 #>  Turn off with `duckplyr::methods_restore()`.