add sample to fetch API by points in CSV (#349)

* add sample to fetch API by points in CSV

* add link to another example in doc

docs/src/developer/api/guide/access-api-using-r.md

@@ -51,6 +51,7 @@ This tutorial demonstrates how to download a NetCDF file from GAP API, save it l
 
     - You can download the full code from [here](https://github.com/kartoza/tomorrownow_gap/blob/main/examples/sample.R).
     - Once you have downloaded the sample code, then you can open the file from RStudio (File -> Open File).
+    - Other example [fetch by points](https://github.com/kartoza/tomorrownow_gap/blob/main/examples/sample_points.R) is to show an example fetching the data by list of point from CSV file.
 
 2. **Set the username and password**
 

examples/sample.R

@@ -36,9 +36,6 @@ query_params <- list(
     # location_name = ''
 )
 
-# Define user agent of the request
-user_agent_string <- "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36"
-
 # Set the output file path
 output_file <- "data.nc"
 
@@ -47,7 +44,7 @@ response <- GET(
     url = base_url,
     authenticate(username, password),
     query = query_params,
-    add_headers(`User-Agent` = user_agent_string),
+    user_agent("httr"),
     write_disk(output_file, overwrite = TRUE)
 )
 # Check the response

examples/sample_points.R

@@ -0,0 +1,81 @@
+# library for HTTP request
+library(httr)
+
+# working directory for output data
+# NOTE: on windows, the path should use double backslashes ("\\")
+working_dir <- '~/Documents/gap_data'
+dir.create(working_dir, showWarnings = FALSE)
+
+# GAP API Base URL
+base_url <- 'https://tngap.sta.do.kartoza.com/api/v1/measurement/'
+
+# Set your username and password
+username <- ''
+password <- ''
+
+# the csv has columns: locationId,latitude,longitude
+csv_file_path <- file.path(working_dir, 'points.csv')
+
+# Load CSV into a DataFrame
+input_points <- read.csv(csv_file_path, header = TRUE)
+
+# Initialize an empty list to store dataframes
+dataframes <- list()
+
+for (i in 1:nrow(input_points)) {
+    # Define the request parameters
+    query_params <- list(
+        # product type and attribute list can be viewed in
+        # https://kartoza.github.io/tomorrownow_gap/developer/api/guide/measurement/#gap-input-data-table
+        product = 'cbam_historical_analysis',
+        # comma separated string (without space)
+        attributes = 'max_temperature,min_temperature',
+        # start and end dates in format YYYY-MM-DD
+        start_date = '2020-01-01',
+        end_date = '2020-01-03',
+        # available output type: json, csv, netcdf
+        # Note that json output is only for single location query
+        output_type = 'csv',
+        # area bounding box (long min, lat min, long max, lat max)
+        # bbox = '33.9, -4.67, 41.89, 5.5'
+        # for single point query, we can use lat and lon parameters
+        lat = input_points$latitude[i],
+        lon = input_points$longitude[i]
+        # for custom polygon/bounding box, you can upload a shapefile and provides the location_name
+        # location_name = ''
+    )
+
+    # Set the output file path
+    output_file <- file.path(working_dir, paste0("data", "_lat", input_points$latitude[i], "_lon", input_points$longitude[i], ".csv"))
+    print(output_file)
+
+    # Trigger the API call
+    response <- GET(
+        url = base_url,
+        authenticate(username, password),
+        query = query_params,
+        user_agent("httr"),
+        write_disk(output_file, overwrite = TRUE)
+    )
+    # Check the response
+    if (status_code(response) == 200) {
+        cat("File downloaded successfully as", output_file, "\n")
+
+        # Load the CSV into a dataframe
+        df <- read.csv(output_file)
+
+        # add locationId to the df
+        df$locationId <- input_points$locationId[i]
+
+        # Add the dataframe to the list
+        dataframes[[i]] <- df
+
+        # Clean up the temporary file if needed
+        # unlink(output_file)
+    } else {
+        cat("Failed to download. HTTP Status Code:", status_code(response), "\n")
+        cat(content(response, as = "text"))
+    }
+}
+
+print(dataframes)