use datahugger instead of url.

examples/sealevel-curve-extraction.jl

@@ -4,31 +4,32 @@ using Interpolations
 using DataFrames
 using CSV
 using HTTP
-#import OpenScienceFramework as OSF
+using PyCall
+dh = pyimport("datahugger")
+url = "https://osf.io/5yka4/" #url of the folder
+dh.get(url,"data/all-sealevel")
 
-function sealevel(url,name)
-    #=osf = OSF.Client(; token = alexa)  # put your OSF token here
-    proj = OSF.project(osf; title="CarbonKitten")
-    dir = OSF.directory(proj, "Analysis")
-    subdir = OSF.directory(dir, "CarboKitten")
-    subsubdir = OSF.directory(subdir, "OSF Storage")
-    file = OSF.file(subsubdir, name)
-    data = read(file)
-    url = OSF.url(file)
-    =#
-    headers = Dict("Authorization" => "Bearer $token")
-    response = HTTP.get(url,headers)# copy paste Sealelvel data from a database
-    data = split(String(response.body), "\n")
+function sealevel()  
+    #headers = Dict("Authorization" => "Bearer $token")
+    #response = HTTP.get(url)# copy paste Sealelvel data from a database
+    #data = split(String(response.body), "\n")
     #data_float64 = parse.(Float64, data)
-    CSV.write("data/all-sealevel/$name.csv", DataFrame(sl=data))
+    folder_path = "data/all-sealevel"
+    files = readdir(folder_path)
+    files = filter(x -> occursin(".txt", x), readdir(folder_path))
+
+    for file in files
+        file_path = joinpath(folder_path,file)
+        name, _ = splitext(file)
+        data = read(file_path, String)
+        CSV.write("data/all-sealevel/$name.csv", DataFrame(sl = data))
+    end
+
+    #CSV.write("data/all-sealevel/$name.csv", DataFrame(sl=data))
 end
 
-url = "https://osf.io/download/zntw8/"
 #local_path = "data/all-sealevel/sl.csv"
-name = "Auto000_Allo000_Stoch100V2"
-token = "the token";
-#localfile = "data/"
-sealevel(url,name) 
+sealevel() 
 #=t = 1 : 2500
 sl = sin.(2π .* t ./ 0.2)
 #file = open("data/all-sealevel/sl1.csv","w")