#!/usr/bin/python
# -*- coding: utf-8 -*-
import bioblend
import bioblend.galaxy.objects
from bioblend import galaxy
import argparse
import os
import subprocess
import logging
import sys
import yaml
import re
from gga_autoload.gga_load_data import metadata_generator
"""
deploy_stacks.py
Usage: $ python3 deploy_stacks.py -i example.yml [OPTIONS]
"""
def parse_input(input_file):
"""
Parse the yml input file to extract data to create the SpeciesData objects
Return a list of dictionaries. Each dictionary contains data tied to a species
:param input_file:
:return:
"""
parsed_sp_dict_list = []
if str(input_file).endswith("yml") or str(input_file).endswith("yaml"):
logging.debug("Input format used: YAML")
else:
logging.critical("Error, please input a YAML file")
sys.exit()
with open(input_file, 'r') as stream:
try:
yaml_dict = yaml.safe_load(stream)
for k, v in yaml_dict.items():
if k == "config":
pass
parsed_sp_dict_list.append(v)
except yaml.YAMLError as exit_code:
logging.critical(exit_code + " (YAML input file might be incorrect)")
sys.exit()
return parsed_sp_dict_list
class RunWorkflow:
"""
Run a workflow into the galaxy instance's history of a given species
"""
def __init__(self, parameters_dictionary):
self.parameters_dictionary = parameters_dictionary
self.species = parameters_dictionary["description"]["species"]
self.genus = parameters_dictionary["description"]["genus"]
self.strain = parameters_dictionary["description"]["strain"]
self.sex = parameters_dictionary["description"]["sex"]
self.common = parameters_dictionary["description"]["common_name"]
self.date = datetime.today().strftime("%Y-%m-%d")
self.origin = parameters_dictionary["description"]["origin"]
self.performed = parameters_dictionary["data"]["performed_by"]
if parameters_dictionary["data"]["genome_version"] == "":
self.genome_version = "1.0"
else:
self.genome_version = parameters_dictionary["data"]["genome_version"]
if parameters_dictionary["data"]["ogs_version"] == "":
self.ogs_version = "1.0"
else:
self.ogs_version = parameters_dictionary["data"]["ogs_version"]
self.genus_lowercase = self.genus[0].lower() + self.genus[1:]
self.genus_uppercase = self.genus[0].upper() + self.genus[1:]
self.species_folder_name = "_".join([self.genus_lowercase, self.species, self.strain, self.sex])
self.full_name = " ".join([self.genus_uppercase, self.species, self.strain, self.sex])
self.abbreviation = " ".join([self.genus_lowercase[0], self.species, self.strain, self.sex])
self.genus_species = self.genus_lowercase + "_" + self.species
self.instance_url = "http://scratchgmodv1:8888/sp/" + self.genus_lowercase + "_" + self.species + "/galaxy/"
# Testing with localhost/scratchgmodv1
self.instance = None
self.history_id = None
self.library_id = None
self.script_dir = os.path.dirname(os.path.realpath(sys.argv[0]))
self.main_dir = None
self.species_dir = None
self.org_id = None
self.genome_analysis_id = None
self.ogs_analysis_id = None
self.tool_panel = None
self.datasets = dict()
self.source_files = dict()
self.workflow_name = None
self.metadata = dict()
self.api_key = "master"
if parameters_dictionary["data"]["parent_directory"] == "" or parameters_dictionary["data"]["parent_directory"] == "/path/to/closest/parent/dir":
self.source_data_dir = "/projet/sbr/phaeoexplorer/" # Testing path for phaeoexplorer data
else:
self.source_data_dir = parameters_dictionary["data"]["parent_directory"]
# Directory/subdirectories where data files are located (fasta, gff, ...)
self.do_update = False
# Update the instance (in histories corresponding to the input) instead of creating a new one
self.api_key = "master"
# API key used to communicate with the galaxy instance. Cannot be used to do user-tied actions
self.species_name_regex_litteral = "(?=\w*V)(?=\w*A)(?=\w*R)(?=\w*I)(?=\w*A)(?=\w*B)(?=\w*L)(?=\w*E)\w+" # Placeholder re
def get_species_history_id(self):
"""
Set and return the current species history id in its galaxy instance
:return:
"""
histories = self.instance.histories.get_histories(name=str(self.full_name))
self.history_id = histories[0]["id"]
self.instance.histories.show_history(history_id=self.history_id)
return self.history_id
def create_species_history(self):
histories = self.instance.histories.get_histories(name=str(self.full_name))
print("\n" + str(histories) + "\n" + self.full_name + "\n")
if not histories:
self.instance.histories.create_history(name="FOO")
print("Created history!")
def get_instance_attributes(self):
"""
retrieves instance attributes:
- working history ID
- libraries ID (there should only be one library!)
- datasets IDs
:return:
"""
histories = self.instance.histories.get_histories(name=str(self.full_name))
self.history_id = histories[0]["id"]
logging.debug("history ID: " + self.history_id)
libraries = self.instance.libraries.get_libraries() # normally only one library
self.library_id = self.instance.libraries.get_libraries()[0]["id"] # project data folder/library
logging.debug("library ID: " + self.history_id)
instance_source_data_folders = self.instance.libraries.get_folders(library_id=self.library_id)
folders_ids = {}
current_folder_name = ""
for i in instance_source_data_folders:
for k, v in i.items():
if k == "name":
folders_ids[v] = 0
current_folder_name = v
if k == "id":
folders_ids[current_folder_name] = v
logging.info("Folders and datasets IDs: ")
self.datasets = dict()
for k, v in folders_ids.items():
logging.info("\t" + k + ": " + v)
if k == "/genome":
sub_folder_content = self.instance.folders.show_folder(folder_id=v, contents=True)
for k2, v2 in sub_folder_content.items():
for e in v2:
if type(e) == dict:
if e["name"].endswith(".fa"):
self.datasets["genome_file"] = e["ldda_id"]
logging.info("\t\t" + e["name"] + ": " + e["ldda_id"])
elif k == "/annotation/" + self.genus_species:
sub_folder_content = self.instance.folders.show_folder(folder_id=v, contents=True)
for k2, v2 in sub_folder_content.items():
for e in v2:
if type(e) == dict:
# TODO: manage several files of the same type and manage versions
if e["name"].endswith("transcripts-gff.fa"):
self.datasets["transcripts_file"] = e["ldda_id"]
logging.info("\t\t" + e["name"] + ": " + e["ldda_id"])
elif e["name"].endswith("proteins.fasta"):
self.datasets["proteins_file"] = e["ldda_id"]
logging.info("\t\t" + e["name"] + ": " + e["ldda_id"])
elif e["name"].endswith(".gff"):
self.datasets["gff_file"] = e["ldda_id"]
logging.info("\t\t" + e["name"] + ": " + e["ldda_id"])
elif e["name"].endswith("MALE"):
self.datasets["gff_file"] = e["ldda_id"]
logging.info("\t\t" + e["name"] + ": " + e["ldda_id"])
def init_instance(self):
"""
Galaxy instance startup in preparation for running workflows
- remove Homo sapiens from the chado database.
- add organism and analyses into the chado database --> separate
- get any other existing organisms IDs before updating the galaxy instance --> separate
TODO: move the library and analysis/data stuff to a separate function
:return:
"""
self.connect_to_instance()
self.get_species_history_id()
histories = self.instance.histories.get_histories(name=str(self.full_name))
# Create the first history
if not histories:
self.instance.histories.create_history(name=str(self.full_name))
self.history_id = histories[0]["id"]
logging.debug("history ID: " + self.history_id)
# libraries = self.instance.libraries.get_libraries() # routine check: one library
# self.library_id = self.instance.libraries.get_libraries()[0]["id"] # project data folder/library
logging.debug("library ID: " + self.history_id)
instance_source_data_folders = self.instance.libraries.get_folders(library_id=self.library_id)
# Delete Homo sapiens from Chado database
logging.debug("Getting 'Homo sapiens' ID in instance's chado database")
get_sapiens_id_job = self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_organism_get_organisms/organism_get_organisms/2.3.2",
history_id=self.history_id,
tool_inputs={"genus": "Homo", "species": "sapiens"})
get_sapiens_id_job_output = get_sapiens_id_job["outputs"][0]["id"]
get_sapiens_id_json_output = self.instance.datasets.download_dataset(dataset_id=get_sapiens_id_job_output)
try:
logging.debug("Deleting Homo 'sapiens' in the instance's chado database")
get_sapiens_id_final_output = json.loads(get_sapiens_id_json_output)[0]
sapiens_id = str(
get_sapiens_id_final_output["organism_id"]) # needs to be str to be recognized by the chado tool
self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_organism_delete_organisms/organism_delete_organisms/2.3.2",
history_id=self.history_id,
tool_inputs={"organism": str(sapiens_id)})
except bioblend.ConnectionError:
logging.debug("Homo sapiens isn't in the instance's chado database")
except IndexError:
logging.debug("Homo sapiens isn't in the instance's chado database")
pass
# TODO: the following actions should be done in a separate function (in case if the user wants to do everything him/herself -- for EOSC)
# Add organism (species) to chado
logging.info("Adding organism to the instance's chado database")
self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_organism_add_organism/organism_add_organism/2.3.2",
history_id=self.history_id,
tool_inputs={"abbr": self.abbreviation,
"genus": self.genus,
"species": self.species,
"common": self.common})
# Add OGS analysis to chado
logging.info("Adding OGS analysis to the instance's chado database")
self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_add_analysis/analysis_add_analysis/2.3.2",
history_id=self.history_id,
tool_inputs={"name": self.genus + " " + self.species + " OGS" + self.ogs_version,
"program": "Performed by Genoscope",
"programversion": str("OGS" + self.ogs_version),
"sourcename": "Genoscope",
"date_executed": self.date})
# Add genome analysis to chado
logging.info("Adding genome analysis to the instance's chado database")
self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_add_analysis/analysis_add_analysis/2.3.2",
history_id=self.history_id,
tool_inputs={"name": self.genus + " " + self.species + " genome v" + self.genome_version,
"program": "Performed by Genoscope",
"programversion": str("genome v" + self.genome_version),
"sourcename": "Genoscope",
"date_executed": self.date})
self.get_organism_and_analyses_ids()
logging.info("Finished initializing instance")
def run_workflow(self, workflow_name, workflow_parameters, datamap):
"""
Run the "main" workflow in the galaxy instance
- import data to library
- load fasta and gff
- sync with tripal
- add jbrowse + organism
- fill in the tripal views
TODO: map tool name to step id
:param workflow_name:
:param workflow_parameters:
:param datamap:
:return:
"""
logging.debug("running workflow: " + str(workflow_name))
workflow_ga_file = self.main_dir + "Galaxy-Workflow-" + workflow_name + ".ga"
if self.strain != "":
custom_ga_file = "_".join([self.genus, self.species, self.strain]) + "_workflow.ga"
custom_ga_file_path = os.path.abspath(custom_ga_file)
else:
custom_ga_file = "_".join([self.genus, self.species]) + "_workflow.ga"
custom_ga_file_path = os.path.abspath(custom_ga_file)
with open(workflow_ga_file, 'r') as ga_in_file:
workflow = str(ga_in_file.readlines())
# ugly fix for the jbrowse parameters
workflow = workflow.replace('{\\\\\\\\\\\\"unique_id\\\\\\\\\\\\": \\\\\\\\\\\\"UNIQUE_ID\\\\\\\\\\\\"}',
str('{\\\\\\\\\\\\"unique_id\\\\\\\\\\\\": \\\\\\\\\\\\"' + self.genus + " " + self.species) + '\\\\\\\\\\\\"')
workflow = workflow.replace('\\\\\\\\\\\\"name\\\\\\\\\\\\": \\\\\\\\\\\\"NAME\\\\\\\\\\\\"',
str('\\\\\\\\\\\\"name\\\\\\\\\\\\": \\\\\\\\\\\\"' + self.genus.lower()[0] + self.species) + '\\\\\\\\\\\\"')
workflow = workflow.replace("\\\\", "\\") # to restore the correct amount of backslashes in the workflow string before import
# test
workflow = workflow.replace('http://localhost/sp/genus_species/feature/Genus/species/mRNA/{id}',
"http://localhost/sp/" + self.genus_lowercase+ "_" + self.species + "/feature/" + self.genus + "/mRNA/{id}")
# production
# workflow = workflow.replace('http://localhost/sp/genus_species/feature/Genus/species/mRNA/{id}',
# "http://abims--gga.sb-roscoff.fr/sp/" + self.genus_lowercase + "_" + self.species + "/feature/" + self.genus + "/mRNA/{id}")
workflow = workflow[2:-2] # if the line under doesn't output a correct json
# workflow = workflow[:-2] # if the line above doesn't output a correct json
workflow_dict = json.loads(workflow)
self.instance.workflows.import_workflow_dict(workflow_dict=workflow_dict)
self.workflow_name = workflow_name
workflow_attributes = self.instance.workflows.get_workflows(name=self.workflow_name)
workflow_id = workflow_attributes[0]["id"]
show_workflow = self.instance.workflows.show_workflow(workflow_id=workflow_id)
logging.debug("Workflow ID: " + workflow_id)
logging.debug("Inputs:")
logging.debug(show_workflow["Inputs"])
self.instance.workflows.invoke_workflow(workflow_id=workflow_id,
history_id=self.history_id,
params=workflow_parameters,
inputs=datamap,
inputs_by="")
self.instance.workflows.delete_workflow(workflow_id=workflow_id)
def get_organism_and_analyses_ids(self):
"""
Retrieve current organism ID and OGS and genome chado analyses IDs (needed to run some tools as Tripal/Chado
doesn't accept organism/analyses names as valid inputs
:return:
"""
# Get the ID for the current organism in chado
org = self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_organism_get_organisms/organism_get_organisms/2.3.2",
history_id=self.history_id,
tool_inputs={"genus": self.genus, "species": self.species})
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]
self.org_id = str(org_output["organism_id"]) # id needs to be a str to be recognized by chado tools
except IndexError:
logging.debug("no organism matching " + self.full_name + " exists in the instance's chado database")
# Get the ID for the OGS analysis in chado
ogs_analysis = self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_get_analyses/analysis_get_analyses/2.3.2",
history_id=self.history_id,
tool_inputs={"name": self.genus + " " + self.species + " OGS" + self.ogs_version})
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]
self.ogs_analysis_id = str(ogs_analysis_output["analysis_id"])
except IndexError:
logging.debug("no matching OGS analysis exists in the instance's chado database")
# Get the ID for the genome analysis in chado
genome_analysis = self.instance.tools.run_tool(
tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_analysis_get_analyses/analysis_get_analyses/2.3.2",
history_id=self.history_id,
tool_inputs={"name": self.genus + " " + self.species + " genome v" + self.genome_version})
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]
self.genome_analysis_id = str(genome_analysis_output["analysis_id"])
except IndexError:
logging.debug("no matching genome analysis exists in the instance's chado database")
def connect_to_instance(self):
"""
TODO: move in init/access
TODO: password
Test the connection to the galaxy instance for the current organism
Exit if it cannot connect to the instance
"""
self.instance = galaxy.GalaxyInstance(url=self.instance_url, email="gga@sb-roscoff.fr", password="password",
verify=False)
logging.info("Connecting to the galaxy instance ...")
try:
self.instance.histories.get_histories()
self.tool_panel = self.instance.tools.get_tool_panel()
except bioblend.ConnectionError:
logging.critical("Cannot connect to galaxy instance @ " + self.instance_url)
sys.exit()
else:
logging.info("Successfully connected to galaxy instance @ " + self.instance_url)
self.instance.histories.create_history(name="FOO")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Automatic data loading in containers and interaction "
"with galaxy instances for GGA"
", following the protocol @ "
"http://gitlab.sb-roscoff.fr/abims/e-infra/gga")
parser.add_argument("input",
type=str,
help="Input file (yml)")
parser.add_argument("-v", "--verbose",
help="Increase output verbosity",
action="store_false")
args = parser.parse_args()
if args.verbose:
logging.basicConfig(level=logging.DEBUG)
else:
logging.basicConfig(level=logging.INFO)
logging.info("Start")
sp_dict_list = parse_input(args.input)
for sp_dict in sp_dict_list:
o = RunWorkflow(parameters_dictionary=sp_dict)
o.main_dir = os.path.abspath(args.dir)
if args.init_instance:
logging.info(" Initializing the galaxy instance")
o.init_instance()
o.get_instance_attributes()
# metadata[genus_species_strain_sex]["initialized"] = True
if args.load_data:
logging.info("Loading data into galaxy")
# o.load_data()
# metadata[genus_species_strain_sex]["data_loaded_in_instance"] = True
if args.run_main:
logging.info("Running main workflow")
o.get_organism_and_analyses_ids()
workflow_parameters = dict()
workflow_parameters["0"] = {}
workflow_parameters["1"] = {}
workflow_parameters["2"] = {}
workflow_parameters["3"] = {}
workflow_parameters["4"] = {"organism": al.org_id,
"analysis_id": al.genome_analysis_id,
"do_update": "true"}
workflow_parameters["5"] = {"organism": al.org_id,
"analysis_id": al.ogs_analysis_id}
workflow_parameters["6"] = {"organism_id": al.org_id}
workflow_parameters["7"] = {"analysis_id": al.ogs_analysis_id}
workflow_parameters["8"] = {"analysis_id": al.genome_analysis_id}
workflow_parameters["9"] = {"organism_id": al.org_id}
workflow_parameters["10"] = {}
workflow_parameters["11"] = {}
o.datamap = dict()
o.datamap["0"] = {"src": "hda", "id": al.datasets["genome_file"]}
o.datamap["1"] = {"src": "hda", "id": al.datasets["gff_file"]}
o.datamap["2"] = {"src": "hda", "id": al.datasets["proteins_file"]}
o.datamap["3"] = {"src": "hda", "id": al.datasets["transcripts_file"]}
o.run_workflow(workflow_name="main", workflow_parameters=workflow_parameters, datamap=al.datamap)
# metadata[genus_species_strain_sex]["workflows_run"] = metadata[genus_species_strain_sex]["workflows_run"].append("main")