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"""module contains the code all related to datasets"""
import json
from unittest import mock
from typing import Optional
from typing import List
from dataclasses import dataclass
import requests
from gn3.experimental_db import database_connector
from gn3.settings import GN2_BASE_URL
def retrieve_trait_sample_data(dataset,
trait_name: str,
group_species_id=None,) -> List:
"""given the dataset id and trait_name fetch the\
sample_name,value from the dataset"""
# should pass the db as arg all do a setup
(dataset_name, dataset_id, dataset_type) = (dataset.get("name"), dataset.get(
"id"), dataset.get("type"))
dataset_query = get_query_for_dataset_sample(dataset_type)
results = []
sample_query_values = {
"Publish": (trait_name, dataset_id),
"Geno": (group_species_id, trait_name, dataset_name),
"ProbeSet": (trait_name, dataset_name)
}
if dataset_query:
formatted_query = dataset_query % sample_query_values[dataset_type]
results = fetch_from_db_sample_data(formatted_query, mock.Mock())
return results
def fetch_from_db_sample_data(formatted_query: str, database_instance) -> List:
"""this is the function that does the actual fetching of\
results from the database"""
cursor = database_instance.cursor()
_conn = database_connector
# conn, cursor = database_connector()
# cursor = conn.cursor()
cursor.execute(formatted_query)
results = cursor.fetchall()
cursor.close()
return results
def get_query_for_dataset_sample(dataset_type) -> Optional[str]:
"""this functions contains querys for\
getting sample data from the db depending in
dataset"""
dataset_query = {}
pheno_query = """
SELECT
Strain.Name, PublishData.value, PublishSE.error,NStrain.count, Strain.Name2
FROM
(PublishData, Strain, PublishXRef, PublishFreeze)
left join PublishSE on
(PublishSE.DataId = PublishData.Id AND PublishSE.StrainId = PublishData.StrainId)
left join NStrain on
(NStrain.DataId = PublishData.Id AND
NStrain.StrainId = PublishData.StrainId)
WHERE
PublishXRef.InbredSetId = PublishFreeze.InbredSetId AND
PublishData.Id = PublishXRef.DataId AND PublishXRef.Id = %s AND
PublishFreeze.Id = %s AND PublishData.StrainId = Strain.Id
Order BY
Strain.Name
"""
geno_query = """
SELECT
Strain.Name, GenoData.value, GenoSE.error, "N/A", Strain.Name2
FROM
(GenoData, GenoFreeze, Strain, Geno, GenoXRef)
left join GenoSE on
(GenoSE.DataId = GenoData.Id AND GenoSE.StrainId = GenoData.StrainId)
WHERE
Geno.SpeciesId = %s AND Geno.Name = %s AND GenoXRef.GenoId = Geno.Id AND
GenoXRef.GenoFreezeId = GenoFreeze.Id AND
GenoFreeze.Name = %s AND
GenoXRef.DataId = GenoData.Id AND
GenoData.StrainId = Strain.Id
Order BY
Strain.Name
"""
probeset_query = """
SELECT
Strain.Name, ProbeSetData.value, ProbeSetSE.error, NStrain.count, Strain.Name2
FROM
(ProbeSetData, ProbeSetFreeze,
Strain, ProbeSet, ProbeSetXRef)
left join ProbeSetSE on
(ProbeSetSE.DataId = ProbeSetData.Id AND ProbeSetSE.StrainId = ProbeSetData.StrainId)
left join NStrain on
(NStrain.DataId = ProbeSetData.Id AND
NStrain.StrainId = ProbeSetData.StrainId)
WHERE
ProbeSet.Name = '%s' AND ProbeSetXRef.ProbeSetId = ProbeSet.Id AND
ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND
ProbeSetFreeze.Name = '%s' AND
ProbeSetXRef.DataId = ProbeSetData.Id AND
ProbeSetData.StrainId = Strain.Id
Order BY
Strain.Name
"""
dataset_query["Publish"] = pheno_query
dataset_query["Geno"] = geno_query
dataset_query["ProbeSet"] = probeset_query
return dataset_query.get(dataset_type)
@dataclass
class Dataset:
"""class for creating datasets"""
name: Optional[str] = None
dataset_type: Optional[str] = None
dataset_id: int = -1
def create_mrna_tissue_dataset(dataset_name, dataset_type):
"""an mrna assay is a quantitative assessment(assay) associated\
with an mrna trait.This used to be called probeset,but that term\
only referes specifically to the afffymetrix platform and is\
far too speficified"""
return Dataset(name=dataset_name, dataset_type=dataset_type)
def dataset_type_getter(dataset_name, redis_instance=None) -> Optional[str]:
"""given the dataset name fetch the type\
of the dataset this in turn enables fetching\
the creation of the correct object could utilize\
redis for the case"""
results = redis_instance.get(dataset_name, None)
if results:
return results
return fetch_dataset_type_from_gn2_api(dataset_name)
def fetch_dataset_type_from_gn2_api(dataset_name):
"""this function is only called when the\
the redis is empty and does have the specificied\
dataset_type"""
# should only run once
dataset_structure = {}
map_dataset_to_new_type = {
"Phenotypes": "Publish",
"Genotypes": "Geno",
"MrnaTypes": "ProbeSet"
}
data = json.loads(requests.get(
GN2_BASE_URL + "/api/v_pre1/gen_dropdown", timeout=5).content)
_name = dataset_name
for species in data['datasets']:
for group in data['datasets'][species]:
for dataset_type in data['datasets'][species][group]:
for dataset in data['datasets'][species][group][dataset_type]:
# assumes the first is dataset_short_name
short_dataset_name = next(
item for item in dataset if item != "None" and item is not None)
dataset_structure[short_dataset_name] = map_dataset_to_new_type.get(
dataset_type, "MrnaTypes")
return dataset_structure
def dataset_creator_store(dataset_type):
"""function contains key value pairs for\
the function need to be called to create\
each dataset_type"""
dataset_obj = {
"ProbeSet": create_mrna_tissue_dataset
}
return dataset_obj[dataset_type]
def create_dataset(dataset_type=None, dataset_name: str = None):
"""function for creating new dataset temp not implemented"""
if dataset_type is None:
dataset_type = dataset_type_getter(dataset_name)
dataset_creator = dataset_creator_store(dataset_type)
results = dataset_creator(
dataset_name=dataset_name, dataset_type=dataset_type)
return results
def fetch_dataset_sample_id(samplelist: List, database, species: str) -> dict:
"""fetch the strain ids from the db only if\
it is in the samplelist"""
# xtodo create an in clause for samplelist
strain_query = """
SELECT Strain.Name, Strain.Id FROM Strain, Species
WHERE Strain.Name IN {}
and Strain.SpeciesId=Species.Id
and Species.name = '{}'
"""
database_cursor = database.cursor()
database_cursor.execute(strain_query.format(samplelist, species))
results = database_cursor.fetchall()
return dict(results)
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