diff --git a/main.py b/main.py
index 7b06b6c940a38294c15f155b30f26c06693ea688..fa23d7905b0bbf0f15d4b9c16f340559122c2fc8 100644
--- a/main.py
+++ b/main.py
@@ -5,9 +5,9 @@ import argparse
import os
import sys
import subprocess
+import logging
+import re
import json
-import urllib3 as ul
-from chado import ChadoInstance
from workflow import Workflow
from toolrunner import ToolRunner
"""
@@ -17,22 +17,12 @@ python3 ~/PycharmProjects/ggauto/gga_load_data/main.py ~/PycharmProjects/ggauto/
"""
-class Autoload:
- """
- TODO: turn main into an object
- """
- def __init__(self, json_in):
- self.json_in = json_in
-
- def main(self):
- return None
-
-
def main():
parser = argparse.ArgumentParser(description="Input genus, species, strain, version")
parser.add_argument("json", type=str, help="Input JSON file")
parser.add_argument("--just-load", help="Only load data into galaxy, does not create nor run analyses in galaxy")
+ parser.add_argument("-v", "--verbose", help="Increase output verbosity")
# CLI stuff
# parser.add_argument("--name", help="Sample species name, format: genus-species",type=str)
@@ -42,6 +32,8 @@ def main():
user_arguments = parser.parse_args()
+ logging.basicConfig(level=logging.INFO)
+
# List that will hold all dicts from the JSON input file, containing parameters for each species
sp_dict_list = []
@@ -81,17 +73,20 @@ def main():
# Test adress, change to abims-gga.sb-roscoff.fr/sp/ in production
instance_url = "http://localhost/sp/" + genus_lower + "_" + species + "/galaxy/"
- print("Species: " + genus + " " + species + " (" + common + ")"
- "\nStrain: " + strain +
- "\nAccessing instance " + instance_url)
+ print("Species: " + genus + " " + species + " (" + common + ")" +
+ "\nStrain: " + strain +
+ "\nAccessing instance " + instance_url)
- # Connect to the galaxy instance of the current species TODO: API key connection issues
+ # Connect to the galaxy instance of the current species TODO: connection issues (galaxy side)
gi = galaxy.GalaxyInstance(url=instance_url,
key="3b36455cb16b4d0e4348e2c42f4bb934",
email="alebars@sb-roscoff.fr",
password="pouet",
verify=True)
+ # admin_email = os.environ.get('GALAXY_DEFAULT_ADMIN_USER', 'admin@galaxy.org')
+ # admin_pass = os.environ.get('GALAXY_DEFAULT_ADMIN_PASSWORD', 'admin')
+
"""
This part creates the current species directory and go to it
If it already exists, just move to it
@@ -118,22 +113,62 @@ def main():
# password="****")
# Check connection to the current instance
+ print("Testing connection to the galaxy instance")
try:
hl = gi.histories.get_histories()
except bb.ConnectionError:
- print("Cannot connect to GGA instance @ " + instance_url)
+ print("Cannot connect to galaxy instance @ " + instance_url)
else:
- print("Successfully connected to instance " + instance_url)
+ print("Successfully connected to galaxy instance @ " + instance_url)
- # TODO: FTP stuff to retrieve the datasets (used in testing, not needed for production)
+ # TODO: FTP/symlink stuff to retrieve the datasets + change headers in pep.fasta
+ setup_data_libraries_cl = "docker-compose exec galaxy /tool_deps/_conda/bin/python /opt/setup_data_libraries.py"
# try:
# os.mkdir("./src_data")
# except FileExistsError:
# print("src_data folder already exists for " + genus_species_strain)
+ # print("Loading data into galaxy...")
+ # try:
+ # setup_data_libraries = subprocess.Popen(setup_data_libraries_cl.split(), stdout=subprocess.PIPE)
+ # print("Output from setup_data_libraries.py")
+ # print(setup_data_libraries.communicate())
+ # except bb.ConnectionError:
+ # print("Cannot load data into container for " + genus_species_strain)
+ # break
+ # else:
+ # print("Data successfully loaded into docker container for " + genus_species_strain)
# else:
# print("src_data folder created for " + genus_species_strain)
- #
+ # try:
+ # setup_data_libraries = subprocess.Popen(setup_data_libraries_cl.split(), stdout=subprocess.PIPE)
+ # print("Output from setup_data_libraries.py")
+ # print(setup_data_libraries.communicate())
+ # except bb.ConnectionError:
+ # print("Cannot load data into container for " + genus_species_strain)
+ # break
+ # else:
+ # print("Data successfully loaded into docker container for " + genus_species_strain)
+
+ genome_dir, annotation_dir = None, None
+ for d in [i[0] for i in os.walk(os.getcwd() + "/src_data")]:
+ if "annotation/" in d:
+ annotation_dir = d
+ annotation_dir_files = [f for f in os.listdir(d) if os.path.isfile(os.path.join(d, f))]
+ print("src_data annotation file(s):")
+ print(str('\t' + file) for file in annotation_dir_files)
+ elif "genome/" in d:
+ genome_dir = d
+ genome_dir_files = [f for f in os.listdir(d) if os.path.isfile(os.path.join(d, f))]
+ print("src_data genome file(s):")
+ print(str('\t' + file) for file in genome_dir_files)
+
+
+
+
+ modify_pep_headers = ["sh /usr/local/genome2/mmo/scripts/phaeoexplorer/phaeoexplorer-change_pep_fasta_header.sh"]
+
+
# TODO: load the data into the current species directory and load it into galaxy instance
# setup_data_libraries_cl = \
# "docker-compose exec galaxy /tool_deps/_conda/bin/python /opt/setup_data_libraries.py"
@@ -150,7 +185,7 @@ def main():
# generate workflow file and run it in the galaxy instance
- gi.histories.create_history(name=str(genus_species_strain + "_" + genome_version))
+ # gi.histories.create_history(name=str(genus_species_strain + "_" + genome_version))
hi = gi.histories.get_histories(name=str(genus_species_strain + "_" + genome_version))
hi_id = hi[0]["id"]
li = gi.libraries.get_libraries() # only one library
@@ -186,7 +221,7 @@ def main():
for k2, v2 in sub_folder_content.items():
for e in v2:
if type(e) == dict:
- # TODO: manage several files of the same type
+ # TODO: manage several files of the same type and versions
if e["name"].endswith("transcripts-gff.fa"):
datasets["transcripts_file"] = e["ldda_id"]
print("\t\t" + e["name"] + ": " + e["ldda_id"])
@@ -196,6 +231,9 @@ def main():
elif e["name"].endswith(".gff"):
datasets["gff_file"] = e["ldda_id"]
print("\t\t" + e["name"] + ": " + e["ldda_id"])
+ elif e["name"].endswith("MALE"):
+ datasets["gff_file"] = e["ldda_id"]
+ print("\t\t" + e["name"] + ": " + e["ldda_id"])
current_hi_id = gi.histories.get_current_history()["id"]
print("History ID: " + current_hi_id)
@@ -204,76 +242,80 @@ def main():
gi.histories.upload_dataset_from_library(history_id=current_hi_id, lib_dataset_id=datasets["transcripts_file"])
gi.histories.upload_dataset_from_library(history_id=current_hi_id, lib_dataset_id=datasets["proteins_file"])
- # Delete Homo sapiens from Chado database
- toolrunner = ToolRunner(parameters_dict=sp_dict, instance=gi, history=current_hi_id)
- sapiens_id = None
- sapiens = toolrunner.get_sapiens_id()
- sapiens_job_out = sapiens["outputs"][0]["id"]
- sapiens_json_output = gi.datasets.download_dataset(dataset_id=sapiens_job_out)
- try:
- sapiens_output = json.loads(sapiens_json_output)[0]
- sapiens_id = str(sapiens_output["organism_id"]) # needs to be str to be recognized by the chado tool
- toolrunner.delete_sapiens(hs_id=sapiens_id)
- except bb.ConnectionError:
- print("Homo sapiens isn't in the database")
+ # ---------------------------------------------------------------------
+ # Galaxy instance interaction
+ # ---------------------------------------------------------------------
- # Workflow generation
+ # # Delete Homo sapiens from Chado database
+ # toolrunner = ToolRunner(parameters_dict=sp_dict, instance=gi, history=current_hi_id)
+ # sapiens = toolrunner.get_sapiens_id()
+ # sapiens_job_out = sapiens["outputs"][0]["id"]
+ # sapiens_json_output = gi.datasets.download_dataset(dataset_id=sapiens_job_out)
+ # try:
+ # sapiens_output = json.loads(sapiens_json_output)[0]
+ # sapiens_id = str(sapiens_output["organism_id"]) # needs to be str to be recognized by the chado tool
+ # toolrunner.delete_sapiens(hs_id=sapiens_id)
+ # except bb.ConnectionError:
+ # print("Homo sapiens isn't in the database")
+ # except IndexError:
+ # pass
+ #
+ # # Workflow generation
workflow = Workflow(parameters_dict=sp_dict, instance=gi, history_id = current_hi_id)
- wf_dict_json = workflow.generate(working_directory=wd, main_directory=main_dir, workflow_name="preset_workflow")
-
- tools = gi.tools.get_tool_panel() # tools panel -> alternative to wf
- # print(tools)
-
- wf_dict = json.loads(wf_dict_json) # doesn't work with eval()
-
- gi.workflows.import_workflow_dict(workflow_dict=wf_dict)
- wf_name = workflow.get_workflow_name()
- wf_attr = gi.workflows.get_workflows(name=wf_name)
- wf_id = wf_attr[0]["id"]
- wf_show = gi.workflows.show_workflow(workflow_id=wf_id)
- print("Workflow ID: " + wf_id)
-
- toolrunner = ToolRunner(parameters_dict=sp_dict, instance=gi, history=current_hi_id)
- # toolrunner.purge_organisms()
-
- # wf_o = bbo.Workflow(wf_dict=wf_dict, gi=gi)
-
- wf_params = workflow.set_main_workflow_parameters(datasets=datasets)
- print("Inputs:")
- print(wf_show["inputs"])
-
- datamap = dict()
- datamap["0"] = {"src": "hda", "id": datasets["genome_file"]}
- datamap["1"] = {"src": "hda", "id": datasets["gff_file"]}
- datamap["2"] = {"src": "hda", "id": datasets["proteins_file"]}
- datamap["3"] = {"src": "hda", "id": datasets["transcripts_file"]}
+ # wf_dict_json = workflow.generate(working_directory=wd, main_directory=main_dir, workflow_name="preset_workflow")
+ #
+ # tools = gi.tools.get_tool_panel() # tools panel -> alternative to wf
+ # # print(tools)
+ #
+ # wf_dict = json.loads(wf_dict_json) # doesn't work with eval()
+ #
+ # gi.workflows.import_workflow_dict(workflow_dict=wf_dict)
+ # wf_name = workflow.get_workflow_name()
+ # wf_attr = gi.workflows.get_workflows(name=wf_name)
+ # wf_id = wf_attr[0]["id"]
+ # wf_show = gi.workflows.show_workflow(workflow_id=wf_id)
+ # print("Workflow ID: " + wf_id)
+ #
+ # toolrunner = ToolRunner(parameters_dict=sp_dict, instance=gi, history=current_hi_id)
+ # # toolrunner.purge_organisms()
+ #
+ # # wf_o = bbo.Workflow(wf_dict=wf_dict, gi=gi)
+ #
+ # wf_params = workflow.set_main_workflow_parameters(datasets=datasets)
+ # # print("Inputs:")
+ # # print(wf_show["inputs"])
+ #
+ # datamap = dict()
+ # datamap["0"] = {"src": "hda", "id": datasets["genome_file"]}
+ # datamap["1"] = {"src": "hda", "id": datasets["gff_file"]}
+ # datamap["2"] = {"src": "hda", "id": datasets["proteins_file"]}
+ # datamap["3"] = {"src": "hda", "id": datasets["transcripts_file"]}
#
# gi.workflows.invoke_workflow(workflow_id=wf_id,
# history_id=current_hi_id,
# params=wf_params,
# inputs=datamap)
+ # gi.workflows.delete_workflow(workflow_id=wf_id)
+ #
+ # datamap = dict()
+ # datamap["0"] = {"src": "hda", "id": datasets["genome_file"]}
+ # datamap["1"] = {"src": "hda", "id": datasets["proteins_file"]}
#
- gi.workflows.delete_workflow(workflow_id=wf_id)
-
- datamap = dict()
- datamap["0"] = {"src": "hda", "id": datasets["genome_file"]}
- datamap["1"] = {"src": "hda", "id": datasets["proteins_file"]}
-
wf_dict_json = workflow.generate(working_directory=wd, main_directory=main_dir, workflow_name="jbrowse")
wf_dict = json.loads(wf_dict_json) # doesn't work with eval()
-
- gi.workflows.import_workflow_dict(workflow_dict=wf_dict)
- wf_attr = gi.workflows.get_workflows(name="jbrowse")
- wf_id = wf_attr[0]["id"]
- wf_show = gi.workflows.show_workflow(workflow_id=wf_id)
- print("Jbrowse workflow ID: " + wf_id)
- wf_params = workflow.set_jbrowse_workflow_parameters()
-
- gi.workflows.invoke_workflow(workflow_id=wf_id,
- history_id=current_hi_id,
- params=wf_params,
- inputs=datamap)
- gi.workflows.delete_workflow(workflow_id=wf_id)
+ #
+ # gi.workflows.import_workflow_dict(workflow_dict=wf_dict)
+ # wf_attr = gi.workflows.get_workflows(name="jbrowse")
+ # wf_id = wf_attr[0]["id"]
+ # wf_show = gi.workflows.show_workflow(workflow_id=wf_id)
+ # print("Jbrowse workflow ID: " + wf_id)
+ # wf_params = workflow.set_jbrowse_workflow_parameters()
+ #
+ # gi.workflows.invoke_workflow(workflow_id=wf_id,
+ # history_id=current_hi_id,
+ # params=wf_params,
+ # inputs=datamap)
+ # gi.workflows.delete_workflow(workflow_id=wf_id)
# remove active instance history for testing, purge configured @ ~/config/galaxy.yml.docker_sample
# gi.histories.delete_history(history_id=current_hi_id, purge=True)
diff --git a/workflow.py b/workflow.py
index 16fff714022cdb69ad00ca3f394c4973c1c15ef7..90cf75fe7a7a75f4cbc345a3d868a4c43af8f00e 100644
--- a/workflow.py
+++ b/workflow.py
@@ -2,6 +2,7 @@ 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
"""
@@ -9,6 +10,8 @@ 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
@@ -59,18 +62,22 @@ class Workflow:
# 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())
+ ga_in = ga_in.replace('{\\\\\\\\\\\\"unique_id\\\\\\\\\\\\": \\\\\\\\\\\\"UNIQUEID\\\\\\\\\\\\"}',
+ 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('"name": "NAME"', str('"name": "' + self.genus.lower()[0] + self.species) + '"')
- ga_in = ga_in.replace('{"unique_id": "UNIQUEID"}', str('{"unique_id": "' + self.genus + " " + self.species) + '"')
+ ga_in = ga_in.replace("\\\\\\\\\\\\", "\\\\\\")
ga_in = ga_in.replace('http://localhost/sp/undaria_pinnatifida/feature/Undaria/pinnatifida/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]
+ 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):
@@ -98,7 +105,7 @@ class Workflow:
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:
- print("No organism matching " + self.full + " exists in the Chado database")
+ 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"]
@@ -108,7 +115,7 @@ class Workflow:
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:
- print("No matching OGS analysis exists in the Chado database")
+ 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"]
@@ -118,7 +125,7 @@ class Workflow:
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:
- print("No matching genome analysis exists in the Chado database")
+ logging.info("No matching genome analysis exists in the Chado database")
params = dict()
params["0"] = {}
@@ -194,7 +201,7 @@ class Workflow:
:return:
"""
workflow_id = self.instance.workflows.get_workflows()[0]['id']
- return print(self.instance.workflows.show_workflow(workflow_id=workflow_id))
+ return logging.info(self.instance.workflows.show_workflow(workflow_id=workflow_id))
def store(self):
"""