def rpPipeline():
with tempfile.TemporaryDirectory() as tmpdir:
params = json.load(request.files['params'])
rp2_file = os.path.join(tmpdir, 'rp2_file.csv')
with open(rp2_file, 'wb') as fo:
fo.write(request.files['rp2_file'].read())
rp2paths_compounds_file = os.path.join(tmpdir,
'rp2paths_compounds_file.csv')
with open(rp2paths_compounds_file, 'wb') as fo:
fo.write(request.files['rp2paths_compounds_file'].read())
rp2paths_pathways_file = os.path.join(tmpdir, 'rp2paths_pathways_file')
with open(rp2paths_pathways_file, 'wb') as fo:
fo.write(request.files['rp2paths_pathways_file'].read())
gem_file = os.path.join(tmpdir, 'gem_file.sbml')
with open(gem_file, 'wb') as fo:
fo.write(request.files['gem_file'].read())
rpcollection_file = os.path.join(tmpdir, 'rpcollection.tar.xz')
rpre_status = rpReader.rp2ToCollection(rp2_file,
rp2paths_compounds_file,
rp2paths_pathways_file,
rpcollection_file,
rpcache=GLOBAL_RPCACHE)
rpeq_status = rpEquilibrator.runCollection(
rpcollection_file,
rpcollection_file,
ph=float(params['ph']),
ionic_strength=float(params['ionic_strength']),
temp_k=float(params['temp_k']),
rpcache=GLOBAL_RPCACHE)
rpfba_status = rpFBA.runCollection(rpcollection_file,
gem_file,
rpcollection_file,
num_workers=params['num_workers'],
keep_merged=params['keep_merged'],
del_sp_pro=params['del_sp_pro'],
del_sp_react=params['del_sp_react'],
rpcache=GLOBAL_RPCACHE)
if params['taxo_id'] == None:
#if you cannot find the annotation then try to recover it from the GEM file
rpsbml_gem = rpSBML(model_name='tmp', path=gem_file)
params['taxo_id'] = rpsbml_gem.readTaxonomy()
rpsel_status = rpSelenzyme.runCollection(
rpcollection_file,
params['taxo_id'],
rpcollection_file,
uniprot_aa_length=SELENZYME_UNIPROT_AA_LENGTH,
data_dir=SELENZYNE_DATA_DIR,
pc=SELENZYME_PC,
rpcache=GLOBAL_RPCACHE)
rpglo_status = rpGlobalScore.runCollection(rpcollection_file,
rpcollection_file,
rpcache=GLOBAL_RPCACHE)
rpcollection_file.seek(0)
return send_file(rpcollection_file,
as_attachment=True,
attachment_filename='rpcollection.tar.xz',
mimetype='application/x-tar')
def rpSelenzymeService():
with tempfile.TemporaryDirectory() as tmpdir:
########### file in ####################
rpcollection_file = os.path.join(tmpdir, 'rpcollection.tar.xz')
try:
with open(rpcollection_file, 'wb') as fo:
fo.write(request.files['rpcollection_file'].read())
except KeyError as e:
app.logger.error('A required file is missing: ' + str(e))
return Response('A required file is missing: ' + str(e),
status=400)
########## Parameters ###################
try:
params = json.load(request.files['data'])
except ValueError as e:
app.logger.error('One or more parameters are malformed: ' + str(e))
return Response('One or more parameters are malformed: ' + str(e),
status=400)
except KeyError as e:
app.logger.error('One or more of the parameters are missing: ' +
str(e))
return Response('One or more of the parameters are missing: ' +
str(e),
status=400)
try:
taxo_id = int(params['taxo_id'])
except KeyError:
app.logger.info(
'No taxo_id passed. Setting to default to E.Coli (83333)')
taxo_id = 83333
except ValueError:
app.logger.warning(
'taxo_id is not recognised. Setting to default E.Coli (83333)')
taxo_id = 83333
status = rpSelenzyme.runCollection(
rpcollection_file,
taxo_id,
rpcollection_file,
is_cleanup=False,
uniprot_aa_length=SELENZYME_UNIPROT_AA_LENGTH,
data_dir=SELENZYNE_DATA_DIR,
pc=SELENZYME_PC,
rpcache=GLOBAL_RPCACHE)
#rpcollection_file.seek(0)
if not status:
app.logger.error(
'rpSelenzyme has encountered a problem.... please investigate futher'
)
return Response(
'rpSelenzyme has encountered a problem.... please investigate futher',
status=400)
return send_file(rpcollection_file,
as_attachment=True,
attachment_filename='rpcollection.tar.xz',
mimetype='application/x-tar')
def rpSelenzyme():
with tempfile.TemporaryDirectory() as tmpdir:
rpcollection_file = os.path.join(tmpdir, 'rpcollection.tar.xz')
with open(rpcollection_file, 'wb') as fo:
fo.write(request.files['rpcollection_file'].read())
status = rpSelenzyme.runCollection(
rpcollection_file,
params['taxo_id'],
rpcollection_file,
uniprot_aa_length=SELENZYME_UNIPROT_AA_LENGTH,
data_dir=SELENZYNE_DATA_DIR,
pc=SELENZYME_PC,
rpcache=GLOBAL_RPCACHE)
rpcollection_file.seek(0)
return send_file(rpcollection_file,
as_attachment=True,
attachment_filename='rpcollection.tar.xz',
mimetype='application/x-tar')
taxo_id = model_taxo_id[s]
except IndexError:
logging.error('Index error in lines: ' + str(lines))
continue
except FileNotFoundError:
logging.error('Cannot find the file')
continue
except KeyError:
logging.error('KeyError for ' + str(s))
continue
if not taxo_id:
logging.error('Taxonomy id has not been defined')
continue
rpsel_status = rpSelenzyme.runCollection(
rpcollection_file,
taxo_id,
rpcollection_file,
cache_path=selenzyme_cache_file,
rpcache=global_rpcache)
if not rpsel_status:
logging.error('Problem running rpSelenzyme')
continue
logging.info('---------- rpGlobalScore -----')
rpglo_status = rpGlobalScore.runCollection(rpcollection_file,
rpcollection_file,
rpcache=global_rpcache)
if not rpglo_status:
logging.error('Problem running rpGlobalScore')
continue
################ generate the various netowrk JSON and SBML JSON #####
logging.info('------------ JSON ----------')
rpSBML.batchAsDict(rpcollection_file)
def rpPipelineService():
with tempfile.TemporaryDirectory() as tmpdir:
########### file in ################
rp2_file = os.path.join(tmpdir, 'rp2_file.csv')
rp2paths_compounds_file = os.path.join(tmpdir,
'rp2paths_compounds_file.csv')
rp2paths_pathways_file = os.path.join(tmpdir, 'rp2paths_pathways_file')
gem_file = os.path.join(tmpdir, 'gem_file.sbml')
try:
with open(rp2_file, 'wb') as fo:
fo.write(request.files['rp2_file'].read())
with open(rp2paths_compounds_file, 'wb') as fo:
fo.write(request.files['rp2paths_compounds_file'].read())
with open(rp2paths_pathways_file, 'wb') as fo:
fo.write(request.files['rp2paths_pathways_file'].read())
with open(gem_file, 'wb') as fo:
fo.write(request.files['gem_file'].read())
except KeyError as e:
app.logger.error('A required file is missing: ' + str(e))
return Response('A required file is missing: ' + str(e),
status=400)
############ parameters ##########
try:
params = json.load(request.files['data'])
except ValueError as e:
app.logger.error('One or more parameters are malformed: ' + str(e))
return Response('One or more parameters are malformed: ' + str(e),
status=400)
except KeyError as e:
app.logger.error('One or more of the parameters are missing: ' +
str(e))
return Response('One or more of the parameters are missing: ' +
str(e),
status=400)
try:
ph = float(params['ph'])
except KeyError:
app.logger.info('No ph passed. Setting to default to 7.5')
ph = 7.5
except ValueError:
app.logger.warning('ph is not recognised. Setting to default 7.5')
ph = 7.5
try:
temp_k = float(params['temp_k'])
except KeyError:
app.logger.info('No temp_k passed. Setting to default to 298.15')
temp_k = 298.15
except ValueError:
app.logger.warning(
'temp_k is not recognised. Setting to default 298.15')
temp_k = 298.15
try:
ionic_strength = float(params['ionic_strength'])
except KeyError:
app.logger.info(
'No ionic_strength passed. Setting to default to 200.0')
ionic_strength = 200.0
except ValueError:
app.logger.warning(
'ionic_strength is not recognised. Setting to default 200.0')
ionic_strength = 200.0
try:
num_workers = int(params['num_workers'])
except KeyError:
app.logger.info('No num_workers passed. Setting to default to 1')
num_workers = 1
except ValueError:
app.logger.warning(
'num_workers is not recognised. Setting to default 1')
num_workers = 1
try:
keep_merged = bool(params['keep_merged'])
except KeyError:
app.logger.info(
'No keep_merged passed. Setting to default to True')
keep_merged = True
except ValueError:
app.logger.warning(
'keep_merged is not recognised. Setting to default True')
keep_merged = True
try:
del_sp_pro = bool(params['del_sp_pro'])
except KeyError:
app.logger.info(
'No del_sp_pro passed. Setting to default to False')
del_sp_pro = False
except ValueError:
app.logger.warning(
'del_sp_pro is not recognised. Setting to default False')
del_sp_pro = False
try:
del_sp_react = bool(params['del_sp_react'])
except KeyError:
app.logger.info(
'No del_sp_react passed. Setting to default to False')
del_sp_react = False
except ValueError:
app.logger.warning(
'del_sp_react is not recognised. Setting to default False')
del_sp_react = False
try:
taxo_id = int(params['taxo_id'])
except KeyError:
app.logger.info(
'No taxo_id passed. Setting to default to None to try and recover from GEM SBML'
)
taxo_id = None
except ValueError:
app.logger.warning(
'taxo_id is not recognised. Setting to default None to try to recover from GEM SBML'
)
taxo_id = None
rpcollection_file = os.path.join(tmpdir, 'rpcollection.tar.xz')
rpre_status = rpReader.rp2ToCollection(rp2_file,
rp2paths_compounds_file,
rp2paths_pathways_file,
rpcollection_file,
rpcache=GLOBAL_RPCACHE)
if not rpre_status:
app.logger.error(
'rpReader has encountered a problem.... please investigate futher'
)
return Response(
'rpReader has encountered a problem.... please investigate futher',
status=400)
rpeq_status = rpEquilibrator.runCollection(
rpcollection_file,
rpcollection_file,
ph=ph,
ionic_strength=ionic_strength,
temp_k=temp_k,
rpcache=GLOBAL_RPCACHE)
if not rpeq_status:
app.logger.error(
'rpEquilibrator has encountered a problem.... please investigate futher'
)
return Response(
'rpEquilibrator has encountered a problem.... please investigate futher',
status=400)
rpfba_status = rpFBA.runCollection(rpcollection_file,
gem_file,
rpcollection_file,
num_workers=num_workers,
keep_merged=keep_merged,
del_sp_pro=del_sp_pro,
del_sp_react=del_sp_react,
rpcache=GLOBAL_RPCACHE)
if not rpfba_status:
app.logger.error(
'rpFBA has encountered a problem.... please investigate futher'
)
return Response(
'rpFBA has encountered a problem.... please investigate futher',
status=400)
if taxo_id == None:
#if you cannot find the annotation then try to recover it from the GEM file
rpsbml_gem = rpSBML(model_name='tmp', path=gem_file)
taxo_id = rpsbml_gem.readTaxonomy()
logging.info('The taxonomy_id is ' + str(taxo_id))
try:
taxo_id = taxo_id[0]
except IndexError:
app.logger.error(
'Could not retreive the taxonomy id and none was passed')
return Response(
'Could not retreive the taxonomy id and none was passed',
status=400)
rpsel_status = rpSelenzyme.runCollection(
rpcollection_file,
taxo_id,
rpcollection_file,
is_cleanup=False,
uniprot_aa_length=SELENZYME_UNIPROT_AA_LENGTH,
data_dir=SELENZYNE_DATA_DIR,
pc=SELENZYME_PC,
rpcache=GLOBAL_RPCACHE)
if not rpsel_status:
app.logger.error(
'rpSelenzyme has encountered a problem.... please investigate futher'
)
return Response(
'rpSelenzyme has encountered a problem.... please investigate futher',
status=400)
rpglo_status = rpGlobalScore.runCollection(rpcollection_file,
rpcollection_file,
rpcache=GLOBAL_RPCACHE)
if not rpglo_status:
app.logger.error(
'rpGlobalScore has encountered a problem.... please investigate futher'
)
return Response(
'rpGlobalScore has encountered a problem.... please investigate futher',
status=400)
#rpcollection_file.seek(0)
return send_file(rpcollection_file,
as_attachment=True,
attachment_filename='rpcollection.tar.xz',
mimetype='application/x-tar')