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Simplified OpenJDK11 instructions for Windows
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pachadotdev committed Apr 29, 2024
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Expand Up @@ -34,12 +34,12 @@ You need do this before installing rJava or attempting to use tabulapdf. More on

tabulapdf is not available on CRAN, but it can be installed from rOpenSci's
R-Universe:
```{r eval = FALSE}
```r
install.packages("tabulapdf", repos = c("https://ropensci.r-universe.dev", "https://cloud.r-project.org"))
```

To install the latest development version:
```{r eval = FALSE}
```r
if (!require(remotes)) install.packages("remotes")

# on 64-bit Windows
Expand All @@ -53,127 +53,161 @@ remotes::install_github(c("ropensci/tabulapdf"))

The main function, `extract_tables()` provides an R clone of the Tabula command line application:

```{r eval = FALSE}
library("tabulapdf")
```r
library(tabulapdf)
f <- system.file("examples", "data.pdf", package = "tabulapdf")
out1 <- extract_tables(f)
str(out1)
## List of 4
## $ : chr [1:32, 1:10] "mpg" "21.0" "21.0" "22.8" ...
## $ : chr [1:7, 1:5] "Sepal.Length " "5.1 " "4.9 " "4.7 " ...
## $ : chr [1:7, 1:6] "" "145 " "146 " "147 " ...
## $ : chr [1:15, 1] "supp" "VC" "VC" "VC" ...
out1[[1]]

# # A tibble: 32 × 11
# mpg cyl disp hp drat wt qsec vs am gear carb
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
# 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
# 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
# 4 21.4 6 258 110 3.08 3.21 19.4 1 0 3 1
# 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
# 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
# 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
# 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
# 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
# 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
# # ℹ 22 more rows
# # ℹ Use `print(n = ...)` to see more rows
```

By default, it returns the most table-like R structure available: a matrix. It can also write the tables to disk or attempt to coerce them to data.frames using the `output` argument. It is also possible to select tables from only specified pages using the `pages` argument.

```{r eval = FALSE}
out2 <- extract_tables(f, pages = 1, guess = FALSE, output = "data.frame")
str(out2)
## List of 1
## $ :'data.frame': 33 obs. of 13 variables:
## ..$ X : chr [1:33] "Mazda RX4 " "Mazda RX4 Wag " "Datsun 710 " "Hornet 4 Drive " ...
## ..$ mpg : num [1:33] 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
## ..$ cyl : num [1:33] 6 6 4 6 8 6 8 4 4 6 ...
## ..$ X.1 : int [1:33] NA NA NA NA NA NA NA NA NA NA ...
## ..$ disp: num [1:33] 160 160 108 258 360 ...
## ..$ hp : num [1:33] 110 110 93 110 175 105 245 62 95 123 ...
## ..$ drat: num [1:33] 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
## ..$ wt : num [1:33] 2.62 2.88 2.32 3.21 3.44 ...
## ..$ qsec: num [1:33] 16.5 17 18.6 19.4 17 ...
## ..$ vs : num [1:33] 0 0 1 1 0 1 0 1 1 1 ...
## ..$ am : num [1:33] 1 1 1 0 0 0 0 0 0 0 ...
## ..$ gear: num [1:33] 4 4 4 3 3 3 3 4 4 4 ...
## ..$ carb: int [1:33] 4 4 1 1 2 1 4 2 2 4 ...
By default, it returns a list of tibbles. It can also write the tables to disk
or attempt to coerce them to a list of matrices using the `output` argument. It
is also possible to select tables from only specified pages using the `pages`
argument.

```r
out2 <- extract_tables(f, pages = 1, guess = FALSE, output = "tibble")
out2[[1]]

# # A tibble: 32 × 11
# mpg cyl disp hp drat wt qsec vs am gear carb
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
# 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
# 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
# 4 21.4 6 258 110 3.08 3.21 19.4 1 0 3 1
# 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
# 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
# 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
# 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
# 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
# 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
# # ℹ 22 more rows
# # ℹ Use `print(n = ...)` to see more rows
```

It is also possible to manually specify smaller areas within pages to look for tables using the `area` and `columns` arguments to `extract_tables()`. This facilitates extraction from smaller portions of a page, such as when a table is embeded in a larger section of text or graphics.
It is also possible to manually specify smaller areas within pages to look for
tables using the `area` and `columns` arguments to `extract_tables()`. This
facilitates extraction from smaller portions of a page, such as when a table is
embeded in a larger section of text or graphics.

Another function, `extract_areas()` implements this through an interactive style in which each page of the PDF is loaded as an R graphic and the user can use their mouse to specify upper-left and lower-right bounds of an area. Those areas are then extracted auto-magically (and the return value is the same as for `extract_tables()`). Here's a shot of it in action:
Another function, `extract_areas()` implements this through an interactive style
in which each page of the PDF is loaded as an R graphic and the user can use
their mouse to specify upper-left and lower-right bounds of an area. Those areas
are then extracted auto-magically (and the return value is the same as for
`extract_tables()`). Here's a shot of it in action:

![extract_areas()](https://i.imgur.com/USTyQl7.gif)

`locate_areas()` handles the area identification process without performing the extraction, which may be useful as a debugger.
`locate_areas()` handles the area identification process without performing the
extraction, which may be useful as a debugger.

`extract_text()` simply returns text, possibly separately for each (specified) page:
`extract_text()` simply returns text, possibly separately for each (specified)
page:

```{r eval = FALSE}
```r
out3 <- extract_text(f, page = 3)
cat(out3, sep = "\n")
## len supp dose
## 4.2 VC 0.5
## 11.5 VC 0.5
## 7.3 VC 0.5
## 5.8 VC 0.5
## 6.4 VC 0.5
## 10.0 VC 0.5
## 11.2 VC 0.5
## 11.2 VC 0.5
## 5.2 VC 0.5
## 7.0 VC 0.5
## 16.5 VC 1.0
## 16.5 VC 1.0
## 15.2 VC 1.0
## 17.3 VC 1.0
## 22.5 VC 1.0
## 3

# len supp dose
# 4.20 VC 0.50
# 11.50 VC 0.50
# 7.30 VC 0.50
# 5.80 VC 0.50
# 6.40 VC 0.50
# 10.00 VC 0.50
# 11.20 VC 0.50
# 11.20 VC 0.50
# 5.20 VC 0.50
# 7.00 VC 0.50
# 16.50 VC 1.00
# 16.50 VC 1.00
# 15.20 VC 1.00
# 17.30 VC 1.00
# 22.50 VC 1.00
```

Note that for large PDF files, it is possible to run up against Java memory constraints, leading to a `java.lang.OutOfMemoryError: Java heap space` error message. Memory can be increased using `options(java.parameters = "-Xmx16000m")` set to some reasonable amount of memory.
Note that for large PDF files, it is possible to run up against Java memory
constraints, leading to a `java.lang.OutOfMemoryError: Java heap space` error
message. Memory can be increased using `options(java.parameters = "-Xmx16000m")`
set to some reasonable amount of memory.

Some other utility functions are also provided (and made possible by the Java [Apache PDFBox library](https://pdfbox.apache.org/)):
Some other utility functions are also provided (and made possible by the Java
[Apache PDFBox library](https://pdfbox.apache.org/)):

- `extract_text()` converts the text of an entire file or specified pages into an R character vector.
- `extract_text()` converts the text of an entire file or specified pages into
an R character vector.
- `split_pdf()` and `merge_pdfs()` split and merge PDF documents, respectively.
- `extract_metadata()` extracts PDF metadata as a list.
- `get_n_pages()` determines the number of pages in a document.
- `get_page_dims()` determines the width and height of each page in pt (the unit used by `area` and `columns` arguments).
- `get_page_dims()` determines the width and height of each page in pt (the
unit used by `area` and `columns` arguments).
- `make_thumbnails()` converts specified pages of a PDF file to image files.

### Installing Java on Windows with Chocolatey
## Installing Java on Windows with Chocolatey

In Power Shell prompt, install Chocolately if you don't already have it.

In command prompt, install Chocolately if you don't already have it:
Run `Get-ExecutionPolicy`. If it returns `Restricted`, then run `Set-ExecutionPolicy AllSigned` or `Set-ExecutionPolicy Bypass -Scope Process`. Then, install Chocolatey by running the following command:

```
@powershell -NoProfile -ExecutionPolicy Bypass -Command "iex ((new-object net.webclient).DownloadString('https://chocolatey.org/install.ps1'))" && SET PATH=%PATH%;%ALLUSERSPROFILE%\chocolatey\bin
Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
```

Then, install java using the following command:
Install java using the following command:

```
choco install openjdk11
```

You may also need to then set the `JAVA_HOME` environment variable to the path to your Java installation (e.g., `C:\Program Files\Java\jdk-11\bin`). This can be done:

1. within R using `Sys.setenv(JAVA_HOME = "C:/Program Files/Java/jdk-11/bin")` (note slashes), or
2. from command prompt using the `setx` command: `setx JAVA_HOME C:\Program Files\Java\jdk-11\bin`, or
3. from PowerShell, using the .NET framework: `[Environment]::SetEnvironmentVariable("JAVA_HOME", "C:\Program Files\Java\jdk-11\bin", "User")`, or
4. from the Start Menu, via `Control Panel » System » Advanced » Environment Variables` ([instructions here](http://superuser.com/a/284351/221772)).

You should now be able to safely open R, and use rJava and tabulapdf. Note,
however, that some users report that rather than setting this variable, they
instead need to delete it (e.g., with `Sys.setenv(JAVA_HOME = "")`), so if the
above instructions fail, that is the next step in troubleshooting.

From PowerShell, you should see something like this after running `java -version`:
You should now be able to safely open R, and use rJava and tabulapdf. From
PowerShell, you should see something like this after running `java -version`:

```
OpenJDK Runtime Environment (build 11.0.22+7-post-Ubuntu-0ubuntu222.04.1)
OpenJDK 64-Bit Server VM (build 11.0.22+7-post-Ubuntu-0ubuntu222.04.1, mixed mode, sharing)
```

### Troubleshooting
## Troubleshooting

### Mac OS and Linux

We tested with OpenJDK version 11. The package is configured to ask for that
version of Java. If you have a different version of Java installed, you may need
to change the `JAVA_HOME` environment variable to point to the correct version.

You need to ensure that R has been installed with Java support. This can often
be fixed by running `R CMD javareconf` on the command line (possibly with
`sudo`).

Some notes for troubleshooting common installation problems:
### Windows

- On Mac OS and Linux, we tested with OpenJDK version 11. The package is configure to ask for that version of Java. If you have a different version of Java installed, you may need to change the `JAVA_HOME` environment variable to point to the correct version. You need to ensure that R has been installed with Java support. This can often be fixed by running `R CMD javareconf` on the command line (possibly with `sudo`, etc. depending on your system setup).
- On Windows, make sure you have permission to write to and install packages to your R directory before trying to install the package. This can be changed from "Properties" on the right-click context menu. Alternatively, you can ensure write permission by choosing "Run as administrator" when launching R (again, from the right-click context menu).
Make sure you have permission to write to and install packages to your R
directory before trying to install the package. This can be changed from
"Properties" on the right-click context menu. Alternatively, you can ensure
write permission by choosing "Run as administrator" when launching R (again,
from the right-click context menu).

## Meta

* Please [report any issues or bugs](https://github.com/ropensci/tabulapdf/issues).
* License: MIT
* Get citation information for `tabulapdf` in R doing `citation(package = 'tabulapdf')`
* License: Apache

[![rofooter](http://ropensci.org/public_images/github_footer.png)](http://ropensci.org)
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