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Commit 3e598ebb authored by Arthur Le Bars's avatar Arthur Le Bars
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Delete workflow.py

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import os
from bioblend.galaxy import GalaxyInstance
from toolrunner import ToolRunner
import json
import logging
"""
Workflow creation for generation and visualization of data and analyses output
"""
class Workflow:
logging.basicConfig(level=logging.INFO)
def __init__(self, parameters_dict, instance, history_id):
self.history_id = history_id
self.instance = instance
self.parameters_dict = parameters_dict
self.genus = parameters_dict["genus"]
self.species = parameters_dict["species"]
self.strain = parameters_dict["strain"]
self.common = parameters_dict["common"]
self.performed = parameters_dict["performed by"]
self.genome_version = parameters_dict["genome version"]
self.ogs_version = parameters_dict["ogs version"]
self.sex = parameters_dict["sex"]
self.date = parameters_dict["date"]
self.custom_ga_file = None
self.custom_ga_file_path = None
self.preset_ga_file = None
self.sp_url = self.genus[0].lower() + self.genus[1:] + "_" + self.species
if self.strain != "":
self.abbr = self.genus[0].lower() + "_" + self.species + "_" + self.strain
self.full = "_".join([self.genus, self.species, self.strain, self.sex])
else:
self.abbr = self.genus[0].lower() + "_" + self.species
self.full = "_".join([self.genus, self.species, self.strain, self.sex])
self.workflow = None
def generate(self, working_directory, main_directory, workflow_name):
"""
Generation of a galaxy workflow using the defined parameters in the .json input file
Output format is a json dict
:param working_directory:
:param main_directory:
:return:
"""
# template workflow as a string
# template_workflow_str = '"{"uuid": "ea9c3050-416f-4098-a7ff-b05c952bcd73", "tags": [], "format-version": "0.1", "name": "test", "version": 2, "steps": {"0": {"tool_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_organism_delete_organisms/organism_delete_organisms/2.3.2", "tool_version": "2.3.2", "outputs": [{"type": "txt", "name": "results"}], "workflow_outputs": [{"output_name": "results", "uuid": "d9b75b03-49e7-4a81-a67c-eaf6a9671905", "label": null}], "input_connections": {}, "tool_state": "{\"__page__\": null, \"__rerun_remap_job_id__\": null, \"organism\": \"\\\"2\\\"\", \"psql_target\": \"{\\\"__current_case__\\\": 0, \\\"method\\\": \\\"remote\\\"}\"}", "id": 0, "tool_shed_repository": {"owner": "gga", "changeset_revision": "13da56fdaeb1", "name": "chado_organism_delete_organisms", "tool_shed": "toolshed.g2.bx.psu.edu"}, "uuid": "f70569bc-9ac0-441a-a2d8-b547086a5bdf", "errors": null, "name": "Chado organism delete", "post_job_actions": {}, "label": "$ORGADELETE", "inputs": [], "position": {"top": 362, "left": 200}, "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_organism_delete_organisms/organism_delete_organisms/2.3.2", "type": "tool"}, "1": {"tool_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_organism_add_organism/organism_add_organism/2.3.2", "tool_version": "2.3.2", "outputs": [{"type": "json", "name": "results"}], "workflow_outputs": [{"output_name": "results", "uuid": "8ca0b891-0f01-4787-9b7f-57105dc303b0", "label": null}], "input_connections": {}, "tool_state": "{\"comment\": \"\\\"\\\"\", \"__page__\": null, \"__rerun_remap_job_id__\": null, \"psql_target\": \"{\\\"__current_case__\\\": 0, \\\"method\\\": \\\"remote\\\"}\", \"common\": \"\\\"$COMMON\\\"\", \"genus\": \"\\\"$GENUS\\\"\", \"species\": \"\\\"$SPECIES\\\"\", \"abbr\": \"\\\"$ABBR\\\"\"}", "id": 1, "tool_shed_repository": {"owner": "gga", "changeset_revision": "0f4956cec445", "name": "chado_organism_add_organism", "tool_shed": "toolshed.g2.bx.psu.edu"}, "uuid": "24f0e175-f932-4e48-8b42-a53d9a432d5e", "errors": null, "name": "Chado organism add", "post_job_actions": {}, "label": "$ORGADD", "inputs": [], "position": {"top": 361, "left": 467.5}, "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_organism_add_organism/organism_add_organism/2.3.2", "type": "tool"}, "2": {"tool_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_add_analysis/analysis_add_analysis/2.3.2", "tool_version": "2.3.2", "outputs": [{"type": "json", "name": "results"}], "workflow_outputs": [{"output_name": "results", "uuid": "8fa0e728-8803-4800-93b4-70f906f95f87", "label": null}], "input_connections": {}, "tool_state": "{\"__page__\": null, \"name\": \"\\\"$GENOME\\\"\", \"sourceuri\": \"\\\"\\\"\", \"sourcename\": \"\\\"\\\"\", \"__rerun_remap_job_id__\": null, \"programversion\": \"\\\"\\\"\", \"psql_target\": \"{\\\"__current_case__\\\": 0, \\\"method\\\": \\\"remote\\\"}\", \"sourceversion\": \"\\\"\\\"\", \"program\": \"\\\"$PERFORMEDBY\\\"\", \"algorithm\": \"\\\"\\\"\", \"date_executed\": \"\\\"\\\"\", \"description\": \"\\\"\\\"\"}", "id": 2, "tool_shed_repository": {"owner": "gga", "changeset_revision": "3a1f3c9b755b", "name": "chado_analysis_add_analysis", "tool_shed": "toolshed.g2.bx.psu.edu"}, "uuid": "76cbbd55-f1ac-4e48-be3c-c7bbda5add4c", "errors": null, "name": "Chado analysis add", "post_job_actions": {}, "label": "$ADDGENOME", "inputs": [], "position": {"top": 307, "left": 690}, "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_add_analysis/analysis_add_analysis/2.3.2", "type": "tool"}, "3": {"tool_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_add_analysis/analysis_add_analysis/2.3.2", "tool_version": "2.3.2", "outputs": [{"type": "json", "name": "results"}], "workflow_outputs": [{"output_name": "results", "uuid": "5e7da027-0723-4077-8885-2dbe51cb5dda", "label": null}], "input_connections": {}, "tool_state": "{\"__page__\": null, \"name\": \"\\\"$OGS\\\"\", \"sourceuri\": \"\\\"\\\"\", \"sourcename\": \"\\\"\\\"\", \"__rerun_remap_job_id__\": null, \"programversion\": \"\\\"\\\"\", \"psql_target\": \"{\\\"__current_case__\\\": 0, \\\"method\\\": \\\"remote\\\"}\", \"sourceversion\": \"\\\"\\\"\", \"program\": \"\\\"$PERFORMEDBY\\\"\", \"algorithm\": \"\\\"\\\"\", \"date_executed\": \"\\\"\\\"\", \"description\": \"\\\"\\\"\"}", "id": 3, "tool_shed_repository": {"owner": "gga", "changeset_revision": "3a1f3c9b755b", "name": "chado_analysis_add_analysis", "tool_shed": "toolshed.g2.bx.psu.edu"}, "uuid": "4d1ffee4-00b2-445d-b630-b7b774c17873", "errors": null, "name": "Chado analysis add", "post_job_actions": {}, "label": "$ADDOGS", "inputs": [], "position": {"top": 395, "left": 697}, "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_add_analysis/analysis_add_analysis/2.3.2", "type": "tool"}, "4": {"tool_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_feature_load_fasta/feature_load_fasta/2.3.2", "tool_version": "2.3.2", "outputs": [{"type": "json", "name": "results"}], "workflow_outputs": [{"output_name": "results", "uuid": "737dddc9-ae1b-463d-99fa-d9176053594d", "label": null}], "input_connections": {}, "tool_state": "{\"do_update\": \"\\\"false\\\"\", \"relationships\": \"{\\\"__current_case__\\\": 0, \\\"rel_type\\\": \\\"none\\\"}\", \"ext_db\": \"{\\\"db\\\": \\\"\\\", \\\"re_db_accession\\\": \\\"\\\"}\", \"analysis_id\": \"\\\"4\\\"\", \"re_uniquename\": \"\\\"\\\"\", \"match_on_name\": \"\\\"false\\\"\", \"__page__\": null, \"__rerun_remap_job_id__\": null, \"psql_target\": \"{\\\"__current_case__\\\": 0, \\\"method\\\": \\\"remote\\\"}\", \"re_name\": \"\\\"\\\"\", \"fasta\": \"{\\\"__class__\\\": \\\"RuntimeValue\\\"}\", \"wait_for\": \"{\\\"__class__\\\": \\\"RuntimeValue\\\"}\", \"organism\": \"\\\"2\\\"\", \"sequence_type\": \"\\\"contig\\\"\"}", "id": 4, "tool_shed_repository": {"owner": "gga", "changeset_revision": "1421dbc33a92", "name": "chado_feature_load_fasta", "tool_shed": "toolshed.g2.bx.psu.edu"}, "uuid": "3d417ced-fc48-4c04-8a92-fdb7b9fecafc", "errors": null, "name": "Chado load fasta", "post_job_actions": {}, "label": "$LOADFASTA", "inputs": [{"name": "fasta", "description": "runtime parameter for tool Chado load fasta"}, {"name": "wait_for", "description": "runtime parameter for tool Chado load fasta"}], "position": {"top": 306, "left": 933.5}, "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_feature_load_fasta/feature_load_fasta/2.3.2", "type": "tool"}}, "annotation": "", "a_galaxy_workflow": "true"}"'
# TODO: store workflow as a var instead of file (once it runs smoothly)
os.chdir(path=working_directory)
self.preset_ga_file = main_directory + "Galaxy-Workflow-" + workflow_name + ".ga"
if self.strain != "":
self.custom_ga_file = "_".join([self.genus, self.species, self.strain]) + "_workflow.ga"
self.custom_ga_file_path = os.path.abspath(self.custom_ga_file)
# print("Workflow file @ " + self.custom_ga_file_path)
else:
self.custom_ga_file = "_".join([self.genus, self.species]) + "_workflow.ga"
self.custom_ga_file_path = os.path.abspath(self.custom_ga_file)
# print("Workflow file @ " + self.custom_ga_file_path)
with open(self.preset_ga_file, 'r') as ga_in_file:
ga_in = str(ga_in_file.readlines())
print(ga_in)
ga_in = ga_in.replace('{\\\\\\\\\\\\"unique_id\\\\\\\\\\\\": \\\\\\\\\\\\"UNIQUE_ID\\\\\\\\\\\\"}',
str('{\\\\\\\\\\\\"unique_id\\\\\\\\\\\\": \\\\\\\\\\\\"' + self.genus + " " + self.species) + '\\\\\\\\\\\\"')
ga_in = ga_in.replace('\\\\\\\\\\\\"name\\\\\\\\\\\\": \\\\\\\\\\\\"NAME\\\\\\\\\\\\"',
str('\\\\\\\\\\\\"name\\\\\\\\\\\\": \\\\\\\\\\\\"' + self.genus.lower()[0] + self.species) + '\\\\\\\\\\\\"')
ga_in = ga_in.replace("\\\\", "\\") # to restore the correct amount of backslashes in the workflow string before import
# ga_in = ga_in.replace("\\\\\\\\\\\\", "\\\\\\")
ga_in = ga_in.replace('http://localhost/sp/genus_species/feature/Genus/species/mRNA/{id}',
"http://localhost/sp/" + self.genus.lower()[0] + self.genus[1:] + "_" + self.species + "/feature/" + self.genus + "/mRNA/{id}")
# ga_in = ga_in.replace('"index\\\": \\\"false', '"index\\\": \\\"true')
# workflow_name = '"name": "' + self.full + '"'
# ga_in = ga_in.replace('"name": "preset_workflow"', '"name": "preset_workflow"')
# print(workflow_name)
ga_in = ga_in[2:-2] # if the line under doesn't outputs a correct json
# ga_in = ga_in[:-2] # if the line above doesn't outputs a correct json
self.workflow = ga_in
# print(ga_in)
return ga_in
def set_main_workflow_parameters(self, datasets):
"""
Test function
:return:
"""
# TODO: move tool calls to main/autoload
toolrunner = ToolRunner(parameters_dict=self.parameters_dict, instance=self.instance, history=self.history_id)
toolrunner.add_organism()
toolrunner.add_ogs()
toolrunner.add_genome()
org_id: str = None
genome_analysis_id: str = None
ogs_analysis_id: str = None
org = toolrunner.get_organism()
org_job_out = org["outputs"][0]["id"]
org_json_output = self.instance.datasets.download_dataset(dataset_id=org_job_out)
try:
org_output = json.loads(org_json_output)[0]
org_id = str(org_output["organism_id"]) # needs to be str to be recognized by the chado tool
global_org_id = org_id
except IndexError:
logging.info("No organism matching " + self.full + " exists in the Chado database")
ogs_analysis = toolrunner.get_ogs_analysis()
ogs_analysis_job_out = ogs_analysis["outputs"][0]["id"]
ogs_analysis_json_output = self.instance.datasets.download_dataset(dataset_id=ogs_analysis_job_out)
try:
ogs_analysis_output = json.loads(ogs_analysis_json_output)[0]
ogs_analysis_id = str(ogs_analysis_output["analysis_id"]) # needs to be str to be recognized by the chado tool
global_ogs_id = ogs_analysis_id
except IndexError:
logging.info("No matching OGS analysis exists in the Chado database")
genome_analysis = toolrunner.get_genome_analysis()
genome_analysis_job_out = genome_analysis["outputs"][0]["id"]
genome_analysis_json_output = self.instance.datasets.download_dataset(dataset_id=genome_analysis_job_out)
try:
genome_analysis_output = json.loads(genome_analysis_json_output)[0]
genome_analysis_id = str(genome_analysis_output["analysis_id"]) # needs to be str to be recognized by the chado tool
global_genome_id = genome_analysis_id
except IndexError:
logging.info("No matching genome analysis exists in the Chado database")
params = dict()
params["0"] = {}
params["1"] = {}
params["2"] = {}
params["3"] = {}
params["4"] = {"organism": org_id,
"analysis_id": genome_analysis_id,
"do_update": "true"} # the do_update parameter is to prevent assertion errors when loading the file, should always be set to "true"
params["5"] = {"organism": org_id,
"analysis_id": ogs_analysis_id,
}
params["6"] = {"organism_id": org_id}
params["7"] = {"analysis_id": ogs_analysis_id}
params["8"] = {"analysis_id": genome_analysis_id}
params["9"] = {"organism_id": org_id}
return params
def set_jbrowse_workflow_parameters(self):
params = dict()
params["0"] = {}
params["1"] = {}
# jbrowse tools parameters are inside nested dictionaries, read tool inputs before adding or modifying anything
# problem is with Jbrowse add organism --> the parameters are nested
params["2"] = {} # {"jbmenu": {"menu_url": "http://localhost/sp/undaria_pinnatifida/feature/Undaria/pinnatifida/mRNA/{id}"}} # {"menu_url": "/".join(["http://localhost/sp", self.sp_url, "feature", self.genus, self.species, "mRNA", "{id}"])}}
params["3"] = {}
# params["3"] = {"name": " ".join([self.genus, self.species + self.strain + "male"]),
# "unique_id": self.genus.lower()[0] + self.species}
# params["3"] = {"name": [{"name": str(self.genus + " " + self.species),
# "unique_id": str(self.genus.lower()[0] + self.species)}]}
def set_datamap(self):
gi = self.instance
def dict_port(self):
"""
Import workflow into a galaxy instance from a json dict
:return:
"""
try:
self.instance.workflows.import_workflow_dict(workflow_dict=self.workflow)
except ConnectionError:
return False
return True
def port(self):
"""
Import workflow into a galaxy instance from a local file
:return:
"""
try:
self.instance.workflows.import_workflow_from_local_path(self.custom_ga_file_path)
except ConnectionError:
return False
else:
return True
def get_workflow_name(self):
"""
Name of the imported workflow
:return:
"""
return str("preset_workflow")
def show(self):
"""
Print the instance's main workflow to stdout (dict form)
:return:
"""
workflow_id = self.instance.workflows.get_workflows()[0]['id']
return logging.info(self.instance.workflows.show_workflow(workflow_id=workflow_id))
def store(self):
"""
Store the instance's workflow
:return:
"""
workflow_id = self.instance.workflows.get_workflows()[0]['id']
return workflow_id
def delete(self):
"""
Delete custom workflow
:return:
"""
return None
def run(self, datamap, params):
"""
Run the custom workflow into a galaxy instance
Input datasets in the form of a list
Params
:return:
"""
return None
# def add_step(self, step_position, description, name):
# """
# TODO: add a step to the workflow (data loading into chado for example)
#
# :param workflow:
# :return:
# """
# return None
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