There is a problem running workflow using api

Hi!I have a problem using bioblend’s documentation.I want the workflow to end and my whole program to end, but my code still has problems. When my workflow is still running, my program shows completion. Help me check what’s wrong.Here is all my code:

from bioblend.galaxy import GalaxyInstance
from gooey import Gooey, GooeyParser
import os
from typing import (
import logging
import time
from bioblend import (
from bioblend.galaxy.client import Client
    from bioblend.galaxy import GalaxyInstance

log = logging.getLogger(__name__)
INVOCATION_TERMINAL_STATES = {"cancelled", "failed", "scheduled"}

class InvocationClient(Client):
    gi: "GalaxyInstance"
    module = "invocations"

@Gooey(dump_build_config=True, program_name="MetaWin", default_size=(1400, 1000), timing_options={'show_time_remaining': True, 'hide_time_remaining_on_complete': False})
def main():
    desc = "MetaWin is a macro-genomic analysis tool based on Windows. Its workflow includes quality control, read trimming, assembly, binning, gene prediction, and functional annotation."

    my_cool_parser = GooeyParser(description=desc)

        "Input1 forward", help="Input1 forward(e.g. _r1.fastq.gz)", widget="FileSaver")
        "Input1 reverse", help="Input1 reverse(e.g. _r1.fastq.gz)", widget="FileSaver")
    my_cool_parser.add_argument('-k', '--Kraken Database',
                                choices=['Silva', 'RDP', 'Greengenes','Standard','Prebuilt Refseq indexes'],
                                help="Select a Kraken2 database (default: Standard)",
    my_cool_parser.add_argument('-c', '--Confidence', default=0,
                                help="Confidence score threshold. Must be in [0, 1] (default: 0)", dest='Confidence',

        "-e", "--error", action="store_true", help="Stop process on error (default: No)")
    args = my_cool_parser.parse_args()
    input_files = args.__dict__["Input1 forward"]
    Input1_forward = args.__dict__["Input1 forward"]
    Input1_reverse = args.__dict__["Input1 reverse"]
    input_dir = os.path.dirname(input_files)
    output_dir = os.path.join(input_dir, "output")
    if not os.path.exists(output_dir):

    galaxy_url = ''
    api_key = 'c962d3fae66664a11ba60297ef0d1b84'
    gi = GalaxyInstance(url=galaxy_url, key=api_key)

    history_name = 'MetaWin Results'
    history_id = gi.histories.create_history(name=history_name)['id']

    dataset_1 =, history_id=history_id, file_type='fastqsanger.gz')
    dataset_1_id = dataset_1['outputs'][0]['id']

    dataset_2 =, history_id=history_id, file_type='fastqsanger.gz')
    dataset_2_id = dataset_2['outputs'][0]['id']

    collection_payload = {
        'collection_type': 'list:paired',
        'name': 'Paired Collection',
        'element_identifiers': [
                'collection_type': 'paired',
                'name': 'first_element',
                'src': 'new_collection',
                'element_identifiers': [
                        'name': 'forward',
                        'src': 'hda',
                        'id': dataset_1_id
                    }, {
                        'src': 'hda',
                        'id': dataset_2_id

    uploaded_collection = gi.histories.create_dataset_collection(history_id, collection_payload)
    inputs = {
        'Collection of paired reads': {'src': 'hdca', 'id': uploaded_collection['id']}

    workflow_id = '7efde95b640dbea9'
    invocation = gi.workflows.invoke_workflow(workflow_id, inputs=inputs, inputs_by="name")

    def wait_for_invocation(gi: GalaxyInstance, invocation_id: str, maxwait: float = 12000, interval: float = 3, check: bool = True):
       time_left = maxwait
       while True:
          invocation = gi.invocations.show_invocation(invocation_id)
          state = invocation["state"]
          if state in INVOCATION_TERMINAL_STATES:
            if check and state != "scheduled":
                raise Exception(f"Invocation {invocation_id} is in terminal state {state}")
            return invocation
          if time_left > 0:
  "Invocation {invocation_id} is in non-terminal state {state}. Will wait {time_left} more s")
            time.sleep(min(time_left, interval))
            time_left -= interval
            raise TimeoutException(
                f"Invocation {invocation_id} is still in non-terminal state {state} after {maxwait} s"
        wait_for_invocation(gi, invocation['id'])
    except TimeoutException as e:
        log.error(f"Timeout waiting for workflow invocation to complete: {e}")
    datasets = gi.histories.show_history(history_id, contents=True)
    for dataset in datasets:
        dataset_id = dataset['id']
        dataset_name = dataset['name']
        output_file = os.path.join(output_dir, dataset_name)
        gi.datasets.download_dataset(dataset_id, file_path=output_file, use_default_filename=False)

if __name__ == '__main__':

Hi @chenqiang
a workflow is considered “scheduled” when Galaxy has created all the history items / jobs that the workflow is supposed to run.
This is not the same as all these jobs being finished. You’d have to use additional parts of bioblend like the histories API if what you want to know is whether the jobs scheduled as part of the invocation are completed.

As an aside, but an important one:
You’ve copy/pasted your account’s API key as part of your code meaning anybody can use that to impersonate you on
What you should do immediately is reset that key!
To avoid this issue in the future, it’s best to read the API key from an environment variable (in Python with os.getenv), and to source that variable from a file that’s only accessible by you. That way the key will never appear in your code snippets nor command line examples.

Hi!Thank you for your reply.I want to know whether the assignment arranged as a call has been completed, so I can use the histories api, but I don’t see it in the API document of bioblend. Can you try to write it according to my code?

No time for doing so, unfortunately. Try to follow the link I provided and study, for example, the get_status method of the gi object.

Consolidating into I made an error when I used bioblend's api to download the output