Context

In this article, we are going to see how to embed the functions from the Harmonized Data Access API Python Client, in a R script.

But first, you need to install the HDA API Python Client: the latest version is already available in the JupyterHub WEkEO server, in the miniwekeolab environment. Otherwise, here you will find the procedure.

Set up

We will use the R package reticulate, built for calling Python functions inside a R code.

Install `reticulate`

Install the reticulate package from CRAN as follows:

install.packages("reticulate")

Python version

By default, reticulate uses the version of Python found in your PATH (e.g. Sys.which("python")).

The use_python() function enables you to specify an alternate version, for example:

library(reticulate)
use_python("/usr/local/bin/python")

The use_virtualenv() and use_condaenv() functions enable you to specify versions of Python in virtual or Conda environments, for example:

library(reticulate)
use_virtualenv("myenv")

📌Note: if you are in your personal environment, you can install the HDA package directly in R, by running: system("pip install hda")

Let's now see a practical example on how to use the HDA API.

R script

Step 1. Import module

As we mentioned above, we will need the reticulate R package to be imported:

library(reticulate)

# Import HDA Python module
hda <- import("hda")

Step 2. Credentials configuration

Afterwards, we must configure user's credentials. Two methods are available.

Method 1 (not regular users)

Configuration of the WEkEO credentials in the script:

# Configure user's credentials if .hdarc not existing
conf <- hda$Configuration(user = "username", password = "password")
hda_client <- hda$Client(config = conf)

Method 2 (regular users)

Create the .hdarc configuration file:

# Check if .hdarc is already existing in the path and create it if not
hdarc <- file.path("/Users/edimedio/.hdarc")
if (!file.exists(hdarc)) {
  USERNAME <- readline(prompt = "Enter your username: ")
  PASSWORD <- readline(prompt = "Enter your password: ")
  
  cat("url: https://wekeo-broker.apps.mercator.dpi.wekeo.eu/databroker\n",
      sprintf("user: %s\n", USERNAME),
      sprintf("password: %s\n", PASSWORD),
      file = hdarc)
}

# Call the .hdarc file
hda_client <- hda$Client()

Step 3. Define query and start download

Once the credentials are defined, we can set the query and run the download in the directory of choice (here path = "/data"):

# Select the parameters for the download
query <- list( 
  datasetId = "EO:EEA:DAT:CLMS_HRVPP_VPP",
  boundingBoxValues = list(
       list(
            name = "bbox",
            bbox = list(
                        1.1249375000000001,
                        42.5133734277223,
                        10.968140625000002,
                        48.4222938065848
                   )
            )
  ),
  dateRangeSelectValues = list(
       list(
            name = "temporal_interval",
            start = "2019-01-01T00:00:00.000Z",
            end = "2020-01-01T00:00:00.000Z"
            )
 ),
 stringChoiceValues = list(
        list(
            name = "productType",
            value = "TPROD"
            ),
       list(
            name = "productGroupId",
            value = "s1")
       ) 
)

# Send the request
matches <- hda_client$search(query)
print(matches)

# Download data in the path "data"
path <- "/data"
matches$download(path)