Python library for using the UNICORE REST API

pip install pyunicore==0.15.2


PyUNICORE, a Python library for using UNICORE and UFTP

This library covers the UNICORE REST API, making common tasks like file access, job submission and management, workflow submission and management more convenient, and integrating UNICORE features better with typical Python usage.

The full, up-to-date documentation of the REST API can be found here

In addition, this library contains code for using UFTP (UNICORE FTP) for filesystem mounts with FUSE, a UFTP driver for PyFilesystem and a UNICORE implementation of a Dask Cluster

This project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement Nos. 720270, 785907 and 945539 (Human Brain Project SGA 1, 2 and 3)

See LICENSE file for licensing information


Install from PyPI with

pip install -U pyunicore

Additional extra packages may be required for your use case:

  • Using the UFTP fuse driver requires "fusepy"
  • Using UFTP with pyfilesystem requires "fs"
  • Creating JWT tokens signed with keys requires the "cryptography" package

You can install (one or more) extras with pip:

pip install -U pyunicore[crypto,fs,fuse]


Creating a client for a UNICORE site

import pyunicore.client as uc_client
import pyunicore.credentials as uc_credentials
import json

base_url = "https://localhost:8080/DEMO-SITE/rest/core"

# authenticate with username/password
credential = uc_credentials.UsernamePassword("demouser", "test123")

client = uc_client.Client(credential, base_url)
print(json.dumps(, indent = 2))

Run a job and read result files

my_job = {'Executable': 'date'}

job = uc_client.new_job(job_description=my_job, inputs=[])
print(json.dumps(, indent = 2))

job.poll() # wait for job to finish

work_dir = job.working_dir
print(json.dumps(, indent = 2))

stdout = work_dir.stat("/stdout")
print(json.dumps(, indent = 2))
content = stdout.raw().read()

Connect to a Registry and list all registered services

registry_url = "https://localhost:8080/REGISTRY/rest/registries/default_registry"

# authenticate with username/password
credential = uc_credentials.UsernamePassword("demouser", "test123")

r = uc_client.Registry(credential, registry_url)

Further reading

More examples for using PyUNICORE can be found in the "integration-tests" folder in the source code repository.

UFTP examples

Using UFTP for PyFilesystem

You can create a PyFilesystem FS object either directly in code, or implicitely via a URL.

The convenient way is via URL:

from fs import open_fs
fs_url = "uftp://demouser:test123@localhost:9000/rest/auth/TEST:/data"
uftp_fs = open_fs(fs_url)

The URL format is


The FS driver supports three types of authentication

  • Username/Password - give username and password
  • SSH Key - give username and the identity parameter, where identity is the filename of a private key. Specify the password if needed to load the private key
  • Bearer token - give the token value via the token parameter

(note: the SSH key authentication using this library requires UFTP Auth server 2.7.0 or later)

Mounting remote filesystems via UFTP

PyUNICORE contains a FUSE driver based on fusepy, allowing you to mount a remote filesystem via UFTP. Mounting is a two step process,

  • authenticate to an Auth server, giving you the UFTPD host/port and one-time password
  • run the FUSE driver

The following code example gives you the basic idea:

import pyunicore.client as uc_client
import pyunicore.credentials as uc_credentials
import pyunicore.uftp as uc_uftp
import pyunicore.uftpfuse as uc_fuse

_auth = "https://localhost:9000/rest/auth/TEST"
_base_dir = "/opt/shared-data"
_local_mount_dir = "/tmp/mount"

# authenticate
cred = uc_credentials.UsernamePassword("demouser", "test123")
uftp = uc_uftp.UFTP(uc_client.Transport(cred), _auth, _base_dir)
_host, _port, _password  = uftp.authenticate()

# run the fuse driver
fuse = uc_fuse.FUSE(
uc_fuse.UFTPDriver(_host, _port, _password), _local_mount_dir, foreground=False, nothreads=True)

Tunneling / port forwarding

Opens a local server socket for clients to connect to, where traffic gets forwarded to a service on a HPC cluster login (or compute) node. This feature requires UNICORE 9.1.0 or later on the server side.

You can use this feature in two ways

  • in your own applications via the pyunicore.client.Job class.
  • you can also open a tunnel from the command line using the 'pyunicore.forwarder' module

Here is an example for a command line tool invocation:

python3 -m pyunicore.forwarder  --token <your_auth_token> \
   $JOB_URL/forward-port?port=REMOTE_PORT \

Your application can now connect to "localhost:4322" but all traffic will be forwarded to port 8000 on the login node.


python3 -m pyunicore.forwarder --help

for all options.

Dask cluster implementation (experimental)

PyUNICORE provides an implementation of a Dask Cluster, allowing to run the Dask client on your local host (or in a Jupyter notebook in the Cloud), and have the Dask scheduler and workers running remotely on the HPC site.

A basic usage example:

import pyunicore.client as uc_client
import pyunicore.credentials as uc_credentials
import pyunicore.dask as uc_dask

# Create a UNICORE client for accessing the HPC cluster
base_url = "https://localhost:8080/DEMO-SITE/rest/core"
credential = uc_credentials.UsernamePassword("demouser", "test123")
submitter = uc_client.Client(credential, base_url)

# Create the UNICORECluster instance

uc_cluster = uc_dask.UNICORECluster(
   queue = "batch",
   project = "my-project",

# Start two workers
uc_cluster.scale(2, wait_for_startup=True)

# Create a Dask client connected to the UNICORECluster

from dask.distributed import Client
dask_client = Client(uc_cluster, timeout=120)

That's it! Now Dask will run its computations using the scheduler and workers started via UNICORE on the HPC site.

Convert a CWL job to UNICORE

PyUNICORE provides a tool to convert a CWL CommanLineTool and input into a UNICORE job file. Given the following YAML files that describe a CommandLineTool wrapper for the echo command and an input file:

# echo.cwl

cwlVersion: v1.2

class: CommandLineTool
baseCommand: echo

    type: string
      position: 1

outputs: []
# hello_world.yml

message: "Hello World"

A UNICORE job file can be generated using the following command:

unicore-cwl-runner echo.cwl hello_world.yml > hello_world.u


The pyunicore.helpers module provides a set of higher-level APIs:

  • Connecting to
    • a Registry (pyunicore.helpers.connect_to_registry).
    • a site via a Registry URL (pyunicore.helpers.connect_to_site_from_registry).
    • a site via its core URL (pyunicore.helpers.connect_to_site).
  • Defining descriptions as a dataclass and easily converting to a dict as required by pyunicore.client.Client.new_job via a to_dict() method:
    • for pyunicore.client.Client.new_job()
    • pyunicore.helpers.workflows.Description for pyunicore.client.WorkflowService.new_workflow()
  • All possible job statuses that may be returned by the jobs API (pyunicore.helpers.JobStatus).
  • Defining a workflow description

Connecting to a Registry

import json
import pyunicore.credentials as uc_credentials
import pyunicore.helpers as helpers

registry_url = "https://localhost:8080/REGISTRY/rest/registries/default_registry"

credentials = uc_credentials.UsernamePassword("demouser", "test123")

client = helpers.connection.connect_to_registry(
print(json.dumps(, indent=2))

Connecting to a site via a Registry

import json
import pyunicore.credentials as uc_credentials
import pyunicore.helpers as helpers

registry_url = "https://localhost:8080/REGISTRY/rest/registries/default_registry"
site = "DEMO-SITE"

credentials = uc_credentials.UsernamePassword("demouser", "test123")

client = helpers.connection.connect_to_site_from_registry(
print(json.dumps(, indent=2))

Connecting to a site directly

import json
import pyunicore.credentials as uc_credentials
import pyunicore.helpers as helpers

site_url = "https://localhost:8080/DEMO-SITE/rest/core"

credentials = uc_credentials.UsernamePassword("demouser", "test123")

client = helpers.connection.connect_to_site(
    site_api_url=site_url ,
print(json.dumps(, indent=2))

Defining a job or workflow

from pyunicore import helpers

client = ...

resources =
job =


This works analogously for pyunicore.helpers.workflows.


  1. Fork the repository

  2. Install the development dependencies

    pip install -r requirements-dev.txt
  3. Install pre-commit hooks

    pre-commit install