From b2fb644bb5c2290f86e28103c959d2b3a41b8b1e Mon Sep 17 00:00:00 2001
From: AndiMajore <andi.majore@googlemail.com>
Date: Thu, 23 Jun 2022 17:52:12 +0200
Subject: [PATCH] db init cleanup and significant speedup
---
data_drugstone/{ => Drugs}/drug-file.txt | 0
.../chembl_drug_gene_interactions_uniq.csv | 31234 ++++++++++++++++
.../drugbank_drug_gene_interactions_uniq.csv | 15923 ++++++++
drugstone/management/commands/populate_db.py | 84 +-
drugstone/management/includes/DataLoader.py | 23 +-
.../management/includes/DataPopulator.py | 194 +-
drugstone/views.py | 1 +
7 files changed, 47340 insertions(+), 119 deletions(-)
rename data_drugstone/{ => Drugs}/drug-file.txt (100%)
create mode 100644 data_drugstone/PDI/chembl_drug_gene_interactions_uniq.csv
create mode 100644 data_drugstone/PDI/drugbank_drug_gene_interactions_uniq.csv
diff --git a/data_drugstone/drug-file.txt b/data_drugstone/Drugs/drug-file.txt
similarity index 100%
rename from data_drugstone/drug-file.txt
rename to data_drugstone/Drugs/drug-file.txt
diff --git a/data_drugstone/PDI/chembl_drug_gene_interactions_uniq.csv b/data_drugstone/PDI/chembl_drug_gene_interactions_uniq.csv
new file mode 100644
index 0000000..533ba80
--- /dev/null
+++ b/data_drugstone/PDI/chembl_drug_gene_interactions_uniq.csv
@@ -0,0 +1,31234 @@
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diff --git a/data_drugstone/PDI/drugbank_drug_gene_interactions_uniq.csv b/data_drugstone/PDI/drugbank_drug_gene_interactions_uniq.csv
new file mode 100644
index 0000000..572366c
--- /dev/null
+++ b/data_drugstone/PDI/drugbank_drug_gene_interactions_uniq.csv
@@ -0,0 +1,15923 @@
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diff --git a/drugstone/management/commands/populate_db.py b/drugstone/management/commands/populate_db.py
index b2dd21a..2408eb3 100755
--- a/drugstone/management/commands/populate_db.py
+++ b/drugstone/management/commands/populate_db.py
@@ -2,7 +2,7 @@ from django.core.management.base import BaseCommand
import pandas as pd
from django.db import OperationalError, IntegrityError
-from drugstone.models import Protein, Drug, Tissue, ExpressionLevel, PPIDataset, PDIDataset, Disorder, PDisDataset
+from drugstone.models import Protein, Drug, Tissue, ExpressionLevel, PPIDataset, PDIDataset, Disorder, PDisDataset, DrDiDataset
from drugstone.models import ProteinProteinInteraction, ProteinDrugInteraction
from drugstone.management.includes.DataPopulator import DataPopulator
@@ -57,55 +57,6 @@ class DatabasePopulator:
self.delete_model(DrDiDataset)
- def populate_drug_model(self):
- print('Populating Drug model ...')
- drug_df = pd.read_csv(f'{self.data_dir}/data_drugstone/{self.drug_file}', delimiter='\t')
- for _, row in drug_df.iterrows():
- drug_id = row['drug_id']
- drug_name = row['drug_name']
- drug_status = row['drug_status']
- # links = row['links']
- Drug.objects.update_or_create(
- drug_id=drug_id,
- name=drug_name,
- status=drug_status,
- # links=links
- )
-
- print('Done!\n')
-
-
- def populate_exp_model(self):
- print('Populating Tissue and ExpressionLevel model ...')
- exp_df = pd.read_csv(f'{self.data_dir}/data_drugstone/{self.exp_file}', delimiter='\t')
-
- tissues_models = dict()
- for tissue_name in exp_df.columns.values[2:]:
- try:
- tissue_model = Tissue.objects.get(name=tissue_name)
- except Tissue.DoesNotExist:
- tissue_model = Tissue.objects.create(name=tissue_name)
- tissues_models[tissue_name] = tissue_model
-
- proteins_linked = 0
-
- for _, row in exp_df.iterrows():
- gene_name = row['Description']
-
- for protein_model in Protein.objects.filter(gene=gene_name).all():
- proteins_linked += 1
-
- for tissue_name, tissue_model in tissues_models.items():
- try:
- ExpressionLevel.objects.create(protein=protein_model,
- tissue=tissue_model,
- expression_level=row[tissue_name])
- except IntegrityError:
- pass
-
- print(f'Added {proteins_linked} expression levels!\n')
-
-
class Command(BaseCommand):
def add_arguments(self, parser):
@@ -139,6 +90,7 @@ class Command(BaseCommand):
pp = kwargs['protein_protein']
pd = kwargs['protein_drug']
+
db_populator = DatabasePopulator(data_dir=data_dir,
# protein_file=protein_file,
drug_file=drug_file,
@@ -152,8 +104,12 @@ class Command(BaseCommand):
db_populator.delete_models(model_list)
return
+ populator = DataPopulator()
+
if kwargs['drug_file'] is not None:
- db_populator.populate_drug_model()
+ print('Populating Drugs...')
+ n = DataPopulator.populate_drugs(populator)
+ print(f'Populated {n} Drugs.')
# if kwargs['protein_file'] is not None:
# db_poulator.populate_protein_model()
@@ -165,52 +121,54 @@ class Command(BaseCommand):
# db_poulator.populate_ppi_model()
if kwargs['exp_file'] is not None:
- db_populator.populate_exp_model()
+ print('Populating Expressions...')
+ n = DataPopulator.populate_expessions(populator)
+ print(f'Populated {n} Expressions.')
if kwargs['proteins'] is not None:
print('Populating Proteins...')
- n = DataPopulator.populate_proteins()
+ n = DataPopulator.populate_proteins(populator)
print(f'Populated {n} Proteins.')
print('Populating ENSG IDs...')
- n = DataPopulator.populate_ensg()
+ n = DataPopulator.populate_ensg(populator)
print(f'Populated {n} ENSG IDs.')
if kwargs['disorders'] is not None:
print('Populating Disorders...')
- n = DataPopulator.populate_disorders()
+ n = DataPopulator.populate_disorders(populator)
print(f'Populated {n} Disorders.')
if kwargs['protein_protein'] is not None:
print('Populating PPIs from STRING...')
- n = DataPopulator.populate_ppi_string()
+ n = DataPopulator.populate_ppi_string(populator)
print(f'Populated {n} PPIs from STRING.')
print('Populating PPIs from APID...')
- n = DataPopulator.populate_ppi_apid()
+ n = DataPopulator.populate_ppi_apid(populator)
print(f'Populated {n} PPIs from APID.')
print('Populating PPIs from BioGRID...')
- n = DataPopulator.populate_ppi_biogrid()
+ n = DataPopulator.populate_ppi_biogrid(populator)
print(f'Populated {n} PPIs from BioGRID.')
if kwargs['protein_drug'] is not None:
print('Populating PDIs from Chembl...')
- n = DataPopulator.populate_pdi_chembl()
+ n = DataPopulator.populate_pdi_chembl(populator)
print(f'Populated {n} PDIs from Chembl.')
print('Populating PDIs from DGIdb...')
- n = DataPopulator.populate_pdi_dgidb()
+ n = DataPopulator.populate_pdi_dgidb(populator)
print(f'Populated {n} PDIs from DGIdb.')
print('Populating PDIs from DrugBank...')
- n = DataPopulator.populate_pdi_drugbank()
+ n = DataPopulator.populate_pdi_drugbank(populator)
print(f'Populated {n} PDIs from DrugBank.')
if kwargs['protein_disorder'] is not None:
print('Populating PDis associations from DisGeNET...')
- n=DataPopulator.populate_pdis_disgenet()
+ n=DataPopulator.populate_pdis_disgenet(populator)
print(f'Populated {n} PDis associations from DisGeNET.')
if kwargs['drug_disorder'] is not None:
print('Populating DrDi indications from DrugBank...')
- n=DataPopulator.populate_drdis_drugbank()
+ n=DataPopulator.populate_drdis_drugbank(populator)
print(f'Populated {n} DrDi associations from DrugBank.')
diff --git a/drugstone/management/includes/DataLoader.py b/drugstone/management/includes/DataLoader.py
index eb65ac5..8fa0d2a 100755
--- a/drugstone/management/includes/DataLoader.py
+++ b/drugstone/management/includes/DataLoader.py
@@ -4,6 +4,8 @@ import json
class DataLoader:
PATH_PROTEINS = 'data_drugstone/Proteins/'
+ PATH_DRUGS = 'data_drugstone/Drugs/'
+ PATH_EXPR = 'data_drugstone/'
PATH_DISORDERS = 'data_drugstone/Disorders/'
PATH_PDI = 'data_drugstone/PDI/'
PATH_PPI = 'data_drugstone/PPI/'
@@ -16,15 +18,20 @@ class DataLoader:
# Disorders
DISORDERS_MONDO = 'disorders.tsv'
+ #Drugs
+ DRUG_FILE = 'drug-file.txt'
+
+ #Expressions
+ EXPR_FILE = 'gene_tissue_expression.gct'
# Protein-Protein-Interactions
PPI_APID = 'apid_9606_Q2.txt'
PPI_BIOGRID = 'BIOGRID-ORGANISM-Homo_sapiens-3.5.187.mitab.txt'
PPI_STRING = 'string_interactions.csv'
# Protein-Drug-Interactions
- PDI_CHEMBL = 'chembl_drug_gene_interactions.csv'
+ PDI_CHEMBL = 'chembl_drug_gene_interactions_uniq.csv'
PDI_DGIDB = 'DGIdb_drug_gene_interactions.csv'
- PDI_DRUGBANK = 'drugbank_drug_gene_interactions.csv'
+ PDI_DRUGBANK = 'drugbank_drug_gene_interactions_uniq.csv'
# Protein-Disorder-Interaction
PDi_DISGENET = 'disgenet-protein_disorder_association.tsv'
@@ -59,6 +66,14 @@ class DataLoader:
df = pd.read_csv(f'{DataLoader.PATH_PROTEINS}{DataLoader.PROTEINS_COVEX}')
df['entrez_id'] = df['entrez_id'].map(DataLoader._clean_entrez)
return df
+ @staticmethod
+ def load_drugs()-> pd.DataFrame:
+ return pd.read_csv(f'{DataLoader.PATH_DRUGS}{DataLoader.DRUG_FILE}', sep='\t')
+
+ @staticmethod
+ def load_expressions() -> pd.DataFrame:
+ return pd.read_csv(f'{DataLoader.PATH_EXPR}{DataLoader.EXPR_FILE}', sep='\t')
+
@staticmethod
def load_disorders() -> pd.DataFrame:
@@ -206,7 +221,7 @@ class DataLoader:
Returns:
pd.DataFrame: columns "drug_id" and "protein_ac"
"""
- return pd.read_csv(f'{DataLoader.PATH_PDI}{DataLoader.PDI_CHEMBL}', index_col=0)
+ return pd.read_csv(f'{DataLoader.PATH_PDI}{DataLoader.PDI_CHEMBL}')
@staticmethod
def load_pdis_disgenet() -> pd.DataFrame:
@@ -244,6 +259,6 @@ class DataLoader:
Returns:
pd.DataFrame: columns "drug_id" and "entrez_id"
"""
- df = pd.read_csv(f'{DataLoader.PATH_PDI}{DataLoader.PDI_DRUGBANK}', index_col=0).dropna()
+ df = pd.read_csv(f'{DataLoader.PATH_PDI}{DataLoader.PDI_DRUGBANK}').dropna()
df['entrez_id'] = df['entrez_id'].map(DataLoader._clean_entrez)
return df
diff --git a/drugstone/management/includes/DataPopulator.py b/drugstone/management/includes/DataPopulator.py
index f66b19d..2b101ed 100755
--- a/drugstone/management/includes/DataPopulator.py
+++ b/drugstone/management/includes/DataPopulator.py
@@ -1,10 +1,39 @@
+from collections import defaultdict
+
from drugstone.management.includes.DataLoader import DataLoader
import drugstone.models as models
class DataPopulator:
+ proteins = dict()
+ uniprot_to_ensembl = dict()
+ gene_name_to_ensembl = defaultdict(lambda: set())
+ # protein_name_to_ensembl = dict()
+ disorders = dict()
+ drugs = dict()
+
+ def init_proteins(self):
+ if len(self.proteins) == 0:
+ print("Generating protein maps...")
+ for protein in models.Protein.objects.all():
+ self.proteins[protein.entrez]=protein
+ self.uniprot_to_ensembl[protein.uniprot_code] = protein.entrez
+ self.gene_name_to_ensembl[protein.gene].add(protein.entrez)
+ # self.protein_name_to_ensembl[protein.protein_name] = protein.entrez
+
+ def init_drugs(self):
+ if len(self.drugs)== 0:
+ print("Generating drug map...")
+ for drug in models.Drug.objects.all():
+ self.drugs[drug.drug_id]=drug
- def populate_proteins() -> int:
+ def init_disorders(self):
+ if len(self.disorders) == 0:
+ print("Generating disorder map...")
+ for disorder in models.Disorder.objects.all():
+ self.disorders[disorder.mondo_id]=disorder
+
+ def populate_proteins(self) -> int:
""" Populates the Protein table in the django database.
Handles loading the data and passing it to the django database
@@ -12,18 +41,20 @@ class DataPopulator:
int: Count of how many proteins were added
"""
df = DataLoader.load_proteins()
- proteins = list()
for _, row in df.iterrows():
- proteins.append(models.Protein(
+ self.proteins[row['entrez_id']] = models.Protein(
uniprot_code=row['protein_ac'],
gene=row['gene_name'],
entrez=row['entrez_id'],
protein_name=row['protein_name'])
- )
- models.Protein.objects.bulk_create(proteins)
- return len(proteins)
+ self.uniprot_to_ensembl[row['protein_ac']] = row['entrez_id']
+ self.gene_name_to_ensembl[row['gene_name']].add(row['entrez_id'])
+ # self.protein_name_to_ensembl[row['protein_name']] = row['entrez_id']
+
+ models.Protein.objects.bulk_create(self.proteins.values())
+ return len(self.proteins)
- def populate_disorders() -> int:
+ def populate_disorders(self) -> int:
""" Populates the Disorder table in the django database.
Handles loading the data and passing it to the django database
@@ -31,17 +62,63 @@ class DataPopulator:
int: Count of how many disorders were added
"""
df = DataLoader.load_disorders()
- bulk = list()
for _, row in df.iterrows():
- bulk.append(models.Disorder(
+ self.disorders[row['mondo_id']] = models.Disorder(
mondo_id=row['mondo_id'],
label=row['label'],
icd10=row['icd10']
- ))
- models.Disorder.objects.bulk_create(bulk)
+ )
+ models.Disorder.objects.bulk_create(self.disorders.values())
+ return len(self.disorders)
+
+ def populate_drugs(self):
+ df = DataLoader.load_drugs()
+ for _, row in df.iterrows():
+ drug_id = row['drug_id']
+ drug_name = row['drug_name']
+ drug_status = row['drug_status']
+ self.drugs[drug_id] = models.Drug(
+ drug_id=drug_id,
+ name=drug_name,
+ status=drug_status)
+ models.Drug.objects.bulk_create(self.drugs.values())
+ return len(self.drugs)
+
+ def populate_expessions(self):
+ self.init_proteins()
+ df = DataLoader.load_expressions()
+
+ tissues_models = dict()
+ for tissue_name in df.columns.values[2:]:
+ try:
+ tissue_model = models.Tissue.objects.get(name=tissue_name)
+ except models.Tissue.DoesNotExist:
+ tissue_model = models.Tissue.objects.create(name=tissue_name)
+ tissues_models[tissue_name] = tissue_model
+
+ proteins_linked = 0
+ unique = set()
+ bulk = list()
+
+ for _, row in df.iterrows():
+ gene_name = row['Description']
+
+ for protein_id in self.gene_name_to_ensembl[gene_name]:
+ protein_model = self.proteins[protein_id]
+ proteins_linked += 1
+
+ for tissue_name, tissue_model in tissues_models.items():
+ id = f"{tissue_name}_{protein_id}"
+ if id in unique:
+ continue
+ unique.add(id)
+ bulk.append(models.ExpressionLevel(protein=protein_model,
+ tissue=tissue_model,
+ expression_level=row[tissue_name]))
+ models.ExpressionLevel.objects.bulk_create(bulk)
return len(bulk)
- def populate_ensg() -> int:
+ def populate_ensg(self) -> int:
""" Populates the Ensembl-Gene table in the django database.
Also maps the added ensg entries to the corresponding proteins.
Handles loading the data and passing it to the django database
@@ -49,22 +126,24 @@ class DataPopulator:
Returns:
int: Count of how many ensg-protein relations were added
"""
+ self.init_proteins()
data = DataLoader.load_ensg()
bulk = list()
for entrez, ensg_list in data.items():
- protein = models.Protein.objects.get(entrez=entrez)
+ protein = self.proteins[entrez]
for ensg in ensg_list:
bulk.append(models.EnsemblGene(name=ensg, protein=protein))
models.EnsemblGene.objects.bulk_create(bulk)
return len(bulk)
- def populate_ppi_string() -> int:
+ def populate_ppi_string(self) -> int:
""" Populates the Protein-Protein-Interactions from STRINGdb
Handles loading the data and passing it to the django database
Returns:
int: Count of how many interactions were added
"""
+ self.init_proteins()
df = DataLoader.load_ppi_string()
dataset, _ = models.PPIDataset.objects.get_or_create(
name='STRING',
@@ -75,9 +154,9 @@ class DataPopulator:
for _, row in df.iterrows():
try:
# try fetching proteins
- protein_a = models.Protein.objects.get(entrez=row['entrez_a'])
- protein_b = models.Protein.objects.get(entrez=row['entrez_b'])
- except models.Protein.DoesNotExist:
+ protein_a = self.proteins[row['entrez_a']]
+ protein_b = self.proteins[row['entrez_b']]
+ except KeyError:
# continue if not found
continue
try:
@@ -92,13 +171,14 @@ class DataPopulator:
models.ProteinProteinInteraction.objects.bulk_create(bulk)
return len(bulk)
- def populate_ppi_apid() -> int:
+ def populate_ppi_apid(self) -> int:
""" Populates the Protein-Protein-Interactions from Apid
Handles loading the data and passing it to the django database
Returns:
int: Count of how many interactions were added
"""
+ self.init_proteins()
df = DataLoader.load_ppi_apid()
dataset, _ = models.PPIDataset.objects.get_or_create(
name='APID',
@@ -109,9 +189,9 @@ class DataPopulator:
for _, row in df.iterrows():
try:
# try fetching proteins
- protein_a = models.Protein.objects.get(uniprot_code=row['from_protein_ac'])
- protein_b = models.Protein.objects.get(uniprot_code=row['to_protein_ac'])
- except models.Protein.DoesNotExist:
+ protein_a = self.proteins[self.uniprot_to_ensembl[row['from_protein_ac']]]
+ protein_b = self.proteins[self.uniprot_to_ensembl[row['to_protein_ac']]]
+ except KeyError:
# continue if not found
continue
try:
@@ -121,18 +201,18 @@ class DataPopulator:
to_protein=protein_b
))
except models.ValidationError:
- # duplicate
continue
models.ProteinProteinInteraction.objects.bulk_create(bulk)
return len(bulk)
- def populate_ppi_biogrid() -> int:
+ def populate_ppi_biogrid(self) -> int:
""" Populates the Protein-Protein-Interactions from BioGRID
Handles loading the data and passing it to the django database
Returns:
int: Count of how many interactions were added
"""
+ self.init_proteins()
df = DataLoader.load_ppi_biogrid()
dataset, _ = models.PPIDataset.objects.get_or_create(
name='BioGRID',
@@ -143,9 +223,10 @@ class DataPopulator:
for _, row in df.iterrows():
try:
# try fetching proteins
- protein_a = models.Protein.objects.get(entrez=row['entrez_a'])
- protein_b = models.Protein.objects.get(entrez=row['entrez_b'])
- except models.Protein.DoesNotExist:
+ protein_a = self.proteins[row['entrez_a']]
+ protein_b = self.proteins[row['entrez_b']]
+ except KeyError:
+ # TODO update error
# continue if not found
continue
try:
@@ -160,13 +241,15 @@ class DataPopulator:
models.ProteinProteinInteraction.objects.bulk_create(bulk)
return len(bulk)
- def populate_pdi_chembl() -> int:
+ def populate_pdi_chembl(self) -> int:
""" Populates the Protein-Drug-Interactions from Chembl
Handles Loading the data and passing it to the django database
Returns:
int: Count of how many interactions were added
"""
+ self.init_proteins()
+ self.init_drugs()
df = DataLoader.load_pdi_chembl()
dataset, _ = models.PDIDataset.objects.get_or_create(
name='ChEMBL',
@@ -176,15 +259,14 @@ class DataPopulator:
bulk = list()
for _, row in df.iterrows():
try:
- # try fetching protein
- protein = models.Protein.objects.get(uniprot_code=row['protein_ac'])
- except models.Protein.DoesNotExist:
+ protein = self.proteins[self.uniprot_to_ensembl[row['protein_ac']]]
+ except KeyError:
# continue if not found
continue
try:
# try fetching drug
- drug = models.Drug.objects.get(drug_id=row['drug_id'])
- except models.Drug.DoesNotExist:
+ drug = self.drugs[row['drug_id']]
+ except KeyError:
# continue if not found
continue
bulk.append(models.ProteinDrugInteraction(
@@ -195,13 +277,15 @@ class DataPopulator:
models.ProteinDrugInteraction.objects.bulk_create(bulk)
return len(bulk)
- def populate_pdis_disgenet() -> int:
+ def populate_pdis_disgenet(self,) -> int:
""" Populates the Protein-Disorder-Interactions from DisGeNET
Handles Loading the data and passing it to the django database
Returns:
int: Count of how many interactions were added
"""
+ self.init_proteins()
+ self.init_disorders()
df = DataLoader.load_pdis_disgenet()
dataset, _ = models.PDisDataset.objects.get_or_create(
name='DisGeNET',
@@ -212,14 +296,14 @@ class DataPopulator:
for _, row in df.iterrows():
try:
# try fetching protein
- protein = models.Protein.objects.get(uniprot_code=row['protein_name'])
- except models.Protein.DoesNotExist:
+ protein = self.proteins[self.uniprot_to_ensembl[row['protein_name']]]
+ except KeyError:
# continue if not found
continue
try:
# try fetching drug
- disorder = models.Disorder.objects.get(mondo_id=row['disorder_name'])
- except models.Disorder.DoesNotExist:
+ disorder = self.disorders[str(int(row['disorder_name']))]
+ except KeyError:
# continue if not found
continue
bulk.append(models.ProteinDisorderAssociation(
@@ -231,13 +315,15 @@ class DataPopulator:
models.ProteinDisorderAssociation.objects.bulk_create(bulk)
return len(bulk)
- def populate_drdis_drugbank() -> int:
+ def populate_drdis_drugbank(self) -> int:
""" Populates the Drug-Disorder-Indications from DrugBank
Handles Loading the data and passing it to the django database
Returns:
int: Count of how many edges were added
"""
+ self.init_drugs()
+ self.init_disorders()
df = DataLoader.load_drdis_drugbank()
dataset, _ = models.DrDiDataset.objects.get_or_create(
name='DrugBank',
@@ -248,14 +334,14 @@ class DataPopulator:
for _, row in df.iterrows():
try:
# try fetching protein
- drug = models.Drug.objects.get(drug_id=row['drugbank_id'])
- except models.Drug.DoesNotExist:
+ drug = self.drugs[row['drugbank_id']]
+ except KeyError:
# continue if not found
continue
try:
# try fetching drug
- disorder = models.Disorder.objects.get(mondo_id=row['mondo_id'])
- except models.Disorder.DoesNotExist:
+ disorder = self.disorders[str(int(row['mondo_id']))]
+ except KeyError:
# continue if not found
continue
bulk.append(models.DrugDisorderIndication(
@@ -266,13 +352,15 @@ class DataPopulator:
models.DrugDisorderIndication.objects.bulk_create(bulk)
return len(bulk)
- def populate_pdi_dgidb() -> int:
+ def populate_pdi_dgidb(self) -> int:
""" Populates the Protein-Drug-Interactions from DGIdb
Handles Loading the data and passing it to the django database
Returns:
int: Count of how many interactions were added
"""
+ self.init_proteins()
+ self.init_drugs()
df = DataLoader.load_pdi_dgidb()
dataset, _ = models.PDIDataset.objects.get_or_create(
name='DGIdb',
@@ -283,14 +371,14 @@ class DataPopulator:
for _, row in df.iterrows():
try:
# try fetching protein
- protein = models.Protein.objects.get(entrez=row['entrez_id'])
- except models.Protein.DoesNotExist:
+ protein = self.proteins[row['entrez_id']]
+ except KeyError:
# continue if not found
continue
try:
# try fetching drug
- drug = models.Drug.objects.get(drug_id=row['drug_id'])
- except models.Drug.DoesNotExist:
+ drug = self.drugs[row['drug_id']]
+ except KeyError:
# continue if not found
continue
bulk.append(models.ProteinDrugInteraction(
@@ -301,13 +389,15 @@ class DataPopulator:
models.ProteinDrugInteraction.objects.bulk_create(bulk)
return len(bulk)
- def populate_pdi_drugbank() -> int:
+ def populate_pdi_drugbank(self) -> int:
""" Populates the Protein-Drug-Interactions from Drugbank
Handles Loading the data and passing it to the django database
Returns:
int: Count of how many interactions were added
"""
+ self.init_proteins()
+ self.init_drugs()
df = DataLoader.load_pdi_drugbank()
dataset, _ = models.PDIDataset.objects.get_or_create(
name='DrugBank',
@@ -318,14 +408,14 @@ class DataPopulator:
for _, row in df.iterrows():
try:
# try fetching protein
- protein = models.Protein.objects.get(entrez=row['entrez_id'])
- except models.Protein.DoesNotExist:
+ protein = self.proteins[row['entrez_id']]
+ except KeyError:
# continue if not found
continue
try:
# try fetching drug
- drug = models.Drug.objects.get(drug_id=row['drug_id'])
- except models.Drug.DoesNotExist:
+ drug = self.drugs[row['drug_id']]
+ except KeyError:
# continue if not found
continue
bulk.append(models.ProteinDrugInteraction(
diff --git a/drugstone/views.py b/drugstone/views.py
index 6381476..6491d09 100755
--- a/drugstone/views.py
+++ b/drugstone/views.py
@@ -78,6 +78,7 @@ class ProteinDrugInteractionView(APIView):
def get(self, request) -> Response:
if request.query_params.get('proteins'):
+ print("getting drugs for proteins")
protein_ac_list = json.loads(request.query_params.get('proteins'))
proteins = list(Protein.objects.filter(uniprot_code__in=protein_ac_list).all())
else:
--
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