import json
import os
import sys

# This example, provided for comparison with w5_metagenomics.py,
# contains the code required to run the metagenomics workflow
# *without* BioBlend.

URL = os.getenv("GALAXY_URL", "https://orione.crs4.it").rstrip("/")
API_URL = f"{URL}/api"
API_KEY = os.getenv("GALAXY_API_KEY", "YOUR_API_KEY")
if API_KEY == "YOUR_API_KEY":
    sys.exit("API_KEY not set, see the README.txt file")

# Clone the galaxy git repository and replace
# YOUR_GALAXY_PATH with the clone's local path in the following code, e.g.:
#   cd /tmp
#   git clone https://github.com/galaxyproject/galaxy
#   GALAXY_PATH = '/tmp/galaxy'

GALAXY_PATH = "YOUR_GALAXY_PATH"
sys.path.insert(1, os.path.join(GALAXY_PATH, "scripts/api"))
import common  # noqa: E402,I100,I202

# Select "W5 - Metagenomics" from published workflows

workflow_name = "W5 - Metagenomics"
workflows = common.get(API_KEY, f"{API_URL}/workflows?show_published=True")
w = [_ for _ in workflows if _["published"] and _["name"] == workflow_name]
assert len(w) == 1
w = w[0]

# Import the workflow to user space

data = {"workflow_id": w["id"]}
iw = common.post(API_KEY, f"{API_URL}/workflows/import", data)
iw_details = common.get(API_KEY, f"{API_URL}/workflows/{iw['id']}")

# Select the "Orione SupMat" library

library_name = "Orione SupMat"
libraries = common.get(API_KEY, f"{API_URL}/libraries")
filtered_libraries = [_ for _ in libraries if _["name"] == library_name]
assert len(filtered_libraries) == 1
library = filtered_libraries[0]

# Select the "/Metagenomics/MetagenomicsDataset.fq" dataset

ds_name = "/Metagenomics/MetagenomicsDataset.fq"
contents = common.get(API_KEY, f"{API_URL}/libraries/{library['id']}/contents")
ld = [_ for _ in contents if _["type"] == "file" and _["name"] == ds_name]
assert len(ld) == 1
ld = ld[0]

# Select the blastn step

ws = [_ for _ in iw_details["steps"].values() if _["tool_id"] and "blastn" in _["tool_id"]]
assert len(ws) == 1
ws = ws[0]
tool_id = ws["tool_id"]

# Get (a copy of) the parameters dict for the selected step

ws_parameters = ws["tool_inputs"].copy()
for k, v in ws_parameters.items():
    ws_parameters[k] = json.loads(v)

# Run the workflow on a new history with the selected dataset
# as input, setting the BLAST db to "16SMicrobial-20131106"

history_name = f"{workflow_name} output"
ws_parameters["db_opts"]["database"] = "16SMicrobial-20131106"
data = {
    "workflow_id": iw["id"],
    "parameters": {tool_id: {"db_opts": ws_parameters["db_opts"]}},
}
assert len(iw_details["inputs"]) == 1
input_step_id = iw_details["inputs"].keys()[0]
data["ds_map"] = {input_step_id: {"src": "ld", "id": ld["id"]}}
data["history"] = history_name
r_dict = common.post(API_KEY, f"{API_URL}/workflows", data)

print(f"Running workflow: {iw['name']} [{iw['id']}]")
print(f"Output history: {history_name} [{r_dict['history']}]")
