diff --git a/Project.toml b/Project.toml
index 9265238..240d97e 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "ArgoData"
 uuid = "9eb831cf-c491-48dc-bed4-6aca718df73c"
 authors = ["gaelforget <gforget@mit.edu>"]
-version = "0.1.22"
+version = "0.1.23"
 
 [deps]
 Bootstrap = "e28b5b4c-05e8-5b66-bc03-6f0c0a0a06e0"
@@ -16,6 +16,7 @@ Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 MeshArrays = "cb8c808f-1acf-59a3-9d2b-6e38d009f683"
 NCDatasets = "85f8d34a-cbdd-5861-8df4-14fed0d494ab"
+NetworkOptions = "ca575930-c2e3-43a9-ace4-1e988b2c1908"
 OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
@@ -24,19 +25,24 @@ YAML = "ddb6d928-2868-570f-bddf-ab3f9cf99eb6"
 
 [weakdeps]
 Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"
+CondaPkg = "992eb4ea-22a4-4c89-a5bb-47a3300528ab"
 Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
 PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
+PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
 
 [extensions]
 ArgoDataCondaExt = ["Conda"]
+ArgoDataCondaPkgExt = ["CondaPkg"]
 ArgoDataMakieExt = ["Makie"]
 ArgoDataPyCallExt = ["PyCall"]
+ArgoDataPythonCallExt = ["PythonCall"]
 
 [compat]
 Bootstrap = "2"
 CSV = "0.10"
 Climatology = "0.5"
 Conda = "1"
+CondaPkg = "0.2"
 DataFrames = "1"
 Downloads = "1"
 FTPClient = "1"
@@ -46,8 +52,10 @@ JLD2 = "0.4, 0.5"
 Makie = "0.21"
 MeshArrays = "0.3"
 NCDatasets = "0.12, 0.13, 0.14"
+NetworkOptions = "1"
 OrderedCollections = "1"
 PyCall = "1"
+PythonCall = "0.9"
 Statistics = "1"
 YAML = "0.4"
 julia = "1.9"
diff --git a/docs/Project.toml b/docs/Project.toml
index 374c16d..0f7b15f 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -1,9 +1,9 @@
 [deps]
 Climatology = "9e9a4d37-2d2e-41e3-8b85-f7978328d9c7"
-Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"
+CondaPkg = "992eb4ea-22a4-4c89-a5bb-47a3300528ab"
 Dataverse = "9c0b9be8-e31e-490f-90fe-77697562404d"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 MITgcm = "dce5fa8e-68ce-4431-a242-9469c69627a0"
 NCDatasets = "85f8d34a-cbdd-5861-8df4-14fed0d494ab"
 PlutoSliderServer = "2fc8631c-6f24-4c5b-bca7-cbb509c42db4"
-PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
+PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
diff --git a/docs/make.jl b/docs/make.jl
index 23a2107..7ed94c3 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -10,7 +10,7 @@ println(pth)
 run_argopy=false
 Sys.ARCH==:aarch64 ? run_argopy=false : nothing
 
-if run_argopy
+if false
   method="internal"
   if method=="external"
     tmpfile=joinpath(tempdir(),"pythonpath.txt")
diff --git a/docs/src/examples.md b/docs/src/examples.md
index 2305567..fed55d3 100644
--- a/docs/src/examples.md
+++ b/docs/src/examples.md
@@ -78,9 +78,18 @@ lst=Dataverse.file_list(doi)
 
 ## Argo via Python API
 
-The python library called [argopy](https://github.com/euroargodev/argopy#readme) provides more ways to access, manipulate, and visualize [Argo data](https://argopy.readthedocs.io/en/latest/what_is_argo.html#what-is-argo). The notebook below demonstrates how you can : 
+The python library called [argopy](https://github.com/euroargodev/argopy#readme) provides more ways to access, manipulate, and visualize [Argo data](https://argopy.readthedocs.io/en/latest/what_is_argo.html#what-is-argo). 
 
-1. install `argopy` into `Julia` via [Conda.jl](https://github.com/JuliaPy/Conda.jl#readme)
-2. use `argopy` from Julia via [PyCall.jl](https://github.com/JuliaPy/PyCall.jl#readme)
+```@example argopy
+using ArgoData, CondaPkg, PythonCall
+ArgoData.conda(:argopy)
+argopy=ArgoData.pyimport(:argopy)
+println(argopy.status())
+```
+
+```@example argopy
+ds_fetcher=argopy.DataFetcher().float(pylist([6902746, 6902747, 6902757, 6902766]))
+ds_points = ds_fetcher.to_xarray()
+```
 
 👉 [Notebook](../Argo_argopy.html) 👈 [(code)](https://raw.githubusercontent.com/euroargodev/ArgoData.jl/master/examples/Argo_argopy.jl)
diff --git a/ext/ArgoDataCondaPkgExt.jl b/ext/ArgoDataCondaPkgExt.jl
new file mode 100644
index 0000000..cf77647
--- /dev/null
+++ b/ext/ArgoDataCondaPkgExt.jl
@@ -0,0 +1,14 @@
+module ArgoDataCondaPkgExt
+
+using CondaPkg, ArgoData
+
+function ArgoData.conda(flag=:argopy)
+    if flag==:argopy
+        CondaPkg.add("xarray",version=">=0.18,<2024.3")
+        CondaPkg.add("argopy")
+    else
+        error("unknown option")
+    end
+end
+
+end
diff --git a/ext/ArgoDataPythonCallExt.jl b/ext/ArgoDataPythonCallExt.jl
new file mode 100644
index 0000000..d945aef
--- /dev/null
+++ b/ext/ArgoDataPythonCallExt.jl
@@ -0,0 +1,23 @@
+module ArgoDataPythonCallExt
+
+using PythonCall, ArgoData
+import ArgoData: NetworkOptions
+
+function ArgoData.pyimport(flag=:argopy)
+    if flag==:argopy
+#        @py import ssl
+#        p=ssl.get_default_verify_paths()
+#        string(p.cafile)
+#        println(cafile)
+        cafile=NetworkOptions.ca_roots_path()
+        ENV["SSL_CERT_FILE"] = cafile
+        PythonCall.pyimport("argopy")
+#        withenv("SSL_CERT_FILE"=>cafile) do
+#            PythonCall.pyimport("argopy")
+#        end
+    else
+        @warn "unknown flag value   "
+    end
+end
+
+end
diff --git a/src/ArgoData.jl b/src/ArgoData.jl
index 810e263..dcad204 100644
--- a/src/ArgoData.jl
+++ b/src/ArgoData.jl
@@ -10,11 +10,14 @@ include("GDAC.jl")
 include("MITprof.jl")
 include("MITprofAnalysis.jl")
 
+import NetworkOptions
+
 export GDAC, ArgoTools, GriddedFields
 export MITprof, MITprofAnalysis, MITprofStat
 export ProfileNative, ProfileStandard, MITprofStandard
 
-conda(dev::String) = conda(:pyargo)
-pyimport(dev::String) = pyimport(:pyargo)
+function conda end
+function pyimport end
+function CondaPkgDev end
 
 end # module
diff --git a/test/Project.toml b/test/Project.toml
index b359f3a..2dacd82 100644
--- a/test/Project.toml
+++ b/test/Project.toml
@@ -1,10 +1,10 @@
 [deps]
 Climatology = "9e9a4d37-2d2e-41e3-8b85-f7978328d9c7"
-Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"
+CondaPkg = "992eb4ea-22a4-4c89-a5bb-47a3300528ab"
 MITgcm = "dce5fa8e-68ce-4431-a242-9469c69627a0"
 MeshArrays = "cb8c808f-1acf-59a3-9d2b-6e38d009f683"
 NCDatasets = "85f8d34a-cbdd-5861-8df4-14fed0d494ab"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
-PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
+PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
diff --git a/test/runtests.jl b/test/runtests.jl
index 0a747fc..291616e 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -1,35 +1,22 @@
 
-run_argopy=false
-Sys.ARCH==:aarch64 ? run_argopy=false : nothing
-method="external"
-
-if run_argopy
-  if method=="external"
-    tmpfile=joinpath(tempdir(),"pythonpath.txt")
-    run(pipeline(`which python`,tmpfile)) 
-    ENV["PYTHON"]=readline(tmpfile)
-  else #internal python path
-    ENV["PYTHON"]=""
-  end
-  using Pkg; Pkg.build("PyCall")
-  using PyCall, Conda
-end
-
-##
-
 using ArgoData, MeshArrays, Test
 using Climatology, MITgcm
 
 ENV["DATADEPS_ALWAYS_ACCEPT"]=true
 clim_path=Climatology.MITPROFclim_download()
-readdir(clim_path)
+
+run_argopy=true
+Sys.ARCH==:aarch64 ? run_argopy=false : nothing
 
 if run_argopy
+  using PythonCall, CondaPkg
   @testset "argopy" begin
     ArgoData.conda(:argopy)
+    println(CondaPkg.status())
     argopy=ArgoData.pyimport(:argopy)
+    println(argopy.status())
 
-    ds_fetcher=argopy.DataFetcher().float([6902746, 6902747, 6902757, 6902766])
+    ds_fetcher=argopy.DataFetcher().float(pylist([6902746, 6902747, 6902757, 6902766]))
     ds_points = ds_fetcher.to_xarray()
     ds_profiles = ds_points.argo.point2profile()