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examples Update (#8) May 8, 2019

Quick user guide

Golemrpc is a python client that allows you to use Golem Network without need to install it. This is lightweight client, easy to use and serviceless. It requires only to install python packages.

Usually, one needs to run full Golem node in order to participate in and use Golem Network. Golemrpc allows you to connect to specified Golem node that operates on your behalf in Golem Network. This way you can request your tasks and the remote Golem node handles networking and protocol. It handles even payments so you do not need to have any ETH and/or GNT. You need to provide a script that connects to the remote Golem node and requests tasks - see our examples.

First of all, you need to know your remote Golem node. You cannot connect to a random one. Contact the Golem node's administrator and obtain

  1. IP address and port,
  2. node's certificate that authenticates it, the .pem file,
  3. access ticket that authenticates you, the .tck file.

Optionally, you can run your own local Golem node - see below for setup details.

System requirements:

  1. Windows, Linux, Mac.
  2. Python3 installed.

Before running examples, perform one time installation.

pip3 install golemrpc

Take one of our examples: or Copy the example script, .pem file and .tck file to a working directory. If you want to use raspa, you need to copy raspa_data directory to the working directory also. If you want to use dummy task, you need to create my_input.txt file in the working directory and write some human readable text as test data. Now edit the script and update connection data:

rpc = RPCComponent(

Now you can run the script


After a while, you will see an output: some number in the case of raspa example, or your text preceded by 'myprefix_string' in the case of dummy task.


Golemrpc is a python package allowing communication with a (remote) Golem node. Connection handling, golem task state handling, resources upload and results retrieval are handled automatically for the user. This package has been created mainly for RASPA2 use case, but it also works with basic blender rendering tasks (see examples).

RASPA2 tasks are submitted to Golem in the form of Python functions and args dictionary, e.g.:

def raspa_task(args):
    '''Task to compute provider side.
    It is possible to import RASPA2 package on provider side because
    this package is preinstalled in a docker environment we are about
    to use (dockerhub golemfactory/glambda:1.3).
    import RASPA2
    import pybel

    mol = pybel.readstring('cif', args['mol'])

    return RASPA2.get_helium_void_fraction(mol)

It is called RASPA2, however generic Python functions are equally acceptable.


User must have access to a Golem node (branch glambda0.3) with a public IP address and ports forwarded (e.g. AWS hosted). By having access, we mean possessing SSL certificate and CLI secret files required to establish a connection. For typical Golem installation, these are stored in $golem_datadir/crossbar directory.


Golemrpc allows users to make task requests without having to install Golem client and take care of port forwarding, GNT purchase etc. Library handles user defined tasks by communicating with Golem over RPC (remote procedure call) interface. This Golem node will be requesting tasks to P2P network on user's behalf. Requesting node can be hosted by anyone, anywhere, etc., for instance, on the AWS EC2 instance.

Golem node running locally, i.e., as localhost, is also supported, but by default, this library will handle input/output files transfers over TCP. To disable it and take advantage of sharing the filesystem with Golem node, use remote argument in RPCComponent class.


Use package installer for Python3.6:

pip3 install golemrpc

User guide

Basic example

First set up a logging module:

import logging

Then create and start an RPCComponent:

from golemrpc.rpccomponent import RPCComponent
rpc = RPCComponent(

It will spawn a separate thread that will handle communication with Golem on Now define a dummy_task function to compute on Golem provider's machine:

def dummy_task(args):
    return 1 + args['b']

Create a golemrpc CreateTask message with task type GLambda (an abbreviation for Golem Lambda, a type of task that takes serialized Python function and dictionary as input and sends them to the provider for computation. For more information about messages and events see this):

message = {
    'type': 'CreateTask',
    'task': {
        'type': 'GLambda',
        'options': {
            'method': dummy_task,
            'args': {'b': 2},

Send it to RPCComponent:

Now poll the RPC message queue for new events. First expected event is TaskCreatedEvent:

task_created_event = rpc.poll(timeout=None)

It contains task_idassigned to this particular task by the requesting Golem node. One can use it to keep track of tasks in case there are more than one being computed at a time. Second message coming from RPCComponent should be TaskResults containing filepaths to actual results:

task_results = rpc.poll(timeout=None)

By default there are three files listed in TaskResults message: result.json, stderr.log and stdout.log. Result returned by dummy_task function is serialized to a result.json of form:

    "data": 3,

If there are any errors in user supplied function the JSON object will contain error key:

    "error": "Some error message"

Pick result file, load it and verify the results:

import json

result_json_file = None

for f in task_results['results']:
    if f.endswith('result.json'):
        result_json_file = f

with open(result_json_file, 'r') as f:
    result_json = json.load(f)
assert result_json['data'] == (1 + 2)

Big input files

By default, CreateTask message cannot exceed 0.5MB. One must use resources task's field instead of function args in order to supply bigger file inputs. Files listed in resources will be saved in /golem/resources directory (with the path structure preserved) which is accessible from the user supplied function, e.g.:

def echo_task(args):
    my_input = None
    with open('/golem/resources/my_input.txt') as f:
        my_input =
    return my_input

is valid if followed by message:

message = {
    'type': 'CreateTask',
    'task': {
        'type': 'GLambda',
        'options': {
            'method': echo_task,
        'resources': ['my_input.txt']

Custom output files

There is no size limit for result.json file although one might want to use format different than JSON. To get back the results in a custom format, you have to write them to a file in /golem/output directory. Every file in this directory will be packed and sent back to you if it is listed in outputs field of CreateTask message, e.g.:

def echo_task(args):
    with open('/golem/resources/my_input.txt', 'r') as fin,\
         open('/golem/output/my_output.txt', 'w') as fout:

will create my_output.txt result file and send it back to the user when created by message:

import os
message = {
    'type': 'CreateTask',
    'task': {
        'type': 'GLambda',
        'options': {
            'method': echo_task,
            'outputs': ['my_output.txt']
        'resources': ['{cwd}/my_input.txt'.format(cwd=os.getcwd())]

Local Golem nodes setup

First of all, in main Golem repository golemfactory/golem branch glambda0.3 required for GLambda tasks to work is not yet merged into develop. One has to install Golem from source using glambda0.3 branch. See Golem instructions for running from source.

Further steps assume that user has successfully installed Golem from source, and has GOLEM_DIR variable defined.

Set up two Golem nodes:

# Node listening on port 61000, requestor.
python $GOLEM_DIR/ --datadir=$HOME/datadir1 --password=node1 --accept-terms --rpc-address=localhost:61000	
# Node listening on port 61001, provider.
python $GOLEM_DIR/ --datadir=$HOME/datadir2 --password=node2 --accept-terms --rpc-address=localhost:61001 --peer=localhost:40102

Now, if 1st node acts as a requestor, one should use CLI secret and SSL cert from $HOME/datadir1/crossbar/rpc_cert.pem and $HOME/datadir1/crossbar/secrets/golemcli.tck.


For more information regarding task requesting see our examples.

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