def update_reference_data(deployment_target):
"""DEPRECATED. Load reference data into mongodb.
Args:
deployment_target (string): value from DEPLOYMENT_TARGETS - eg. "minikube", "gcloud-dev", etc.
"""
check_kubernetes_context(deployment_target)
pod_name = get_pod_name('seqr', deployment_target=deployment_target)
if not pod_name:
raise ValueError(
"No 'seqr' pods found. Is the kubectl environment configured in this terminal? and have either of these pods been deployed?"
% locals())
# commented out because this is not loaded from settings backup
#run_in_pod(pod_name, "python2.7 -u manage.py update_all_reference_data --omim-key '$OMIM_KEY'" % locals(), verbose=True, print_command=True)
run_in_pod(pod_name, "mkdir -p /seqr/data/reference_data")
run_in_pod(
pod_name,
"wget -N https://storage.googleapis.com/seqr-reference-data/seqr-resource-bundle.tar.gz -O /seqr/data/reference_data/seqr-resource-bundle.tar.gz"
)
run_in_pod(
pod_name,
"tar xzf /seqr/data/reference_data/seqr-resource-bundle.tar.gz -C /seqr/data/reference_data",
verbose=True)
run_in_pod(pod_name,
"rm /seqr/data/reference_data/seqr-resource-bundle.tar.gz")
# load legacy resources
run_in_pod(pod_name, "python -u manage.py load_resources", verbose=True)
run_in_pod(pod_name, "python -u manage.py load_omim", verbose=True)
def deploy(deployment_target, components, output_dir=None, runtime_settings={}):
"""Deploy one or more components to the kubernetes cluster specified as the deployment_target.
Args:
deployment_target (string): value from DEPLOYMENT_TARGETS - eg. "minikube", "gcloud-dev", etc.
indentifying which cluster to deploy these components to
components (list): The list of component names to deploy (eg. "postgres", "phenotips" - each string must be in
constants.DEPLOYABLE_COMPONENTS). Order doesn't matter.
output_dir (string): path of directory where to put deployment logs and rendered config files
runtime_settings (dict): a dictionary of other key-value pairs that override settings file(s) values.
"""
if not components:
raise ValueError("components list is empty")
if components and "init-cluster" not in components:
check_kubernetes_context(deployment_target)
settings = prepare_settings_for_deployment(deployment_target, output_dir, runtime_settings)
# make sure namespace exists
if "init-cluster" not in components:
create_namespace(settings)
# call deploy_* functions for each component in "components" list, in the order that these components are listed in DEPLOYABLE_COMPONENTS
for component in DEPLOYABLE_COMPONENTS:
if component in components:
# only deploy requested components
func_name = "deploy_" + component.replace("-", "_")
f = globals().get(func_name)
if f is not None:
f(settings)
else:
raise ValueError("'deploy_{}' function not found. Is '{}' a valid component name?".format(func_name, component))
def deploy(deployment_target, components, output_dir=None, runtime_settings={}):
"""Deploy one or more components to the kubernetes cluster specified as the deployment_target.
Args:
deployment_target (string): value from DEPLOYMENT_TARGETS - eg. "minikube", "gcloud-dev", etc.
indentifying which cluster to deploy these components to
components (list): The list of component names to deploy (eg. "postgres", "phenotips" - each string must be in
constants.DEPLOYABLE_COMPONENTS). Order doesn't matter.
output_dir (string): path of directory where to put deployment logs and rendered config files
runtime_settings (dict): a dictionary of other key-value pairs that override settings file(s) values.
"""
if not components:
raise ValueError("components list is empty")
if components and "init-cluster" not in components:
check_kubernetes_context(deployment_target)
settings = prepare_settings_for_deployment(deployment_target, output_dir, runtime_settings)
# make sure namespace exists
if "init-cluster" not in components:
create_namespace(settings)
# call deploy_* functions for each component in "components" list, in the order that these components are listed in DEPLOYABLE_COMPONENTS
for component in DEPLOYABLE_COMPONENTS:
if component in components:
# only deploy requested components
func_name = "deploy_" + component.replace("-", "_")
f = globals().get(func_name)
if f is not None:
f(settings)
else:
raise ValueError("'deploy_{}' function not found. Is '{}' a valid component name?".format(func_name, component))
def load_example_project(deployment_target,
genome_version="37",
cpu_limit=None,
start_with_step=None):
"""Load example project
Args:
deployment_target (string): value from DEPLOYMENT_TARGETS - eg. "minikube", "gcloud-dev", etc.
genome_version (string): reference genome version - either "37" or "38"
"""
project_name = "1kg"
check_kubernetes_context(deployment_target)
pod_name = get_pod_name('seqr', deployment_target=deployment_target)
if not pod_name:
raise ValueError(
"No 'seqr' pod found. Is the kubectl environment configured in this terminal? and have either of these pods been deployed?"
% locals())
run_in_pod(
pod_name,
"wget -N https://storage.googleapis.com/seqr-reference-data/test-projects/1kg.ped"
% locals())
#run_in_pod(pod_name, "gsutil cp %(ped)s ." % locals())
# TODO call APIs instead?
run_in_pod(
pod_name,
"python2.7 -u -m manage create_project -p '1kg.ped' '%(project_name)s'"
% locals(),
verbose=True)
if genome_version == "37":
vcf_filename = "1kg.vcf.gz"
elif genome_version == "38":
vcf_filename = "1kg.liftover.GRCh38.vep.vcf.gz"
else:
raise ValueError("Unexpected genome_version: %s" % (genome_version, ))
load_dataset(
deployment_target,
project_name=project_name,
genome_version=genome_version,
sample_type="WES",
dataset_type="VARIANTS",
cpu_limit=cpu_limit,
start_with_step=start_with_step,
vcf=
"https://storage.googleapis.com/seqr-reference-data/test-projects/%(vcf_filename)s"
% locals())
def redeploy(deployment_target, components):
if not components:
raise ValueError("components list is empty")
check_kubernetes_context(deployment_target)
# call redeploy_* functions for each component in "components" list, in the order that these components are listed in DEPLOYABLE_COMPONENTS
for component in DEPLOYABLE_COMPONENTS:
if component in components:
# only deploy requested components
func_name = "redeploy_" + component.replace("-", "_")
f = globals().get(func_name)
if f is not None:
f(deployment_target)
else:
raise ValueError(
"'redeploy_{}' function not found. Is '{}' a valid component name?".format(func_name, component))
def load_example_project(deployment_target, genome_version="37", cpu_limit=None, start_with_step=None):
"""Load example project
Args:
deployment_target (string): value from DEPLOYMENT_TARGETS - eg. "minikube", "gcloud-dev", etc.
genome_version (string): reference genome version - either "37" or "38"
"""
project_name = "1kg"
check_kubernetes_context(deployment_target)
pod_name = get_pod_name('seqr', deployment_target=deployment_target)
if not pod_name:
raise ValueError("No 'seqr' pod found. Is the kubectl environment configured in this terminal? and have either of these pods been deployed?" % locals())
run_in_pod(pod_name, "wget -N https://storage.googleapis.com/seqr-reference-data/test-projects/1kg.ped" % locals())
#run_in_pod(pod_name, "gsutil cp %(ped)s ." % locals())
# TODO call APIs instead?
run_in_pod(pod_name, "python2.7 -u -m manage create_project -p '1kg.ped' '%(project_name)s'" % locals(), verbose=True)
if genome_version == "37":
vcf_filename = "1kg.vcf.gz"
elif genome_version == "38":
vcf_filename = "1kg.liftover.GRCh38.vep.vcf.gz"
else:
raise ValueError("Unexpected genome_version: %s" % (genome_version,))
load_dataset(
deployment_target,
project_name=project_name,
genome_version=genome_version,
sample_type="WES",
dataset_type="VARIANTS",
cpu_limit=cpu_limit,
start_with_step=start_with_step,
vcf="https://storage.googleapis.com/seqr-reference-data/test-projects/%(vcf_filename)s" % locals())
def update_reference_data(deployment_target):
"""DEPRECATED. Load reference data into mongodb.
Args:
deployment_target (string): value from DEPLOYMENT_TARGETS - eg. "minikube", "gcloud-dev", etc.
"""
check_kubernetes_context(deployment_target)
pod_name = get_pod_name('seqr', deployment_target=deployment_target)
if not pod_name:
raise ValueError("No 'seqr' pods found. Is the kubectl environment configured in this terminal? and have either of these pods been deployed?" % locals())
# commented out because this is not loaded from settings backup
#run_in_pod(pod_name, "python2.7 -u manage.py update_all_reference_data --omim-key '$OMIM_KEY'" % locals(), verbose=True, print_command=True)
run_in_pod(pod_name, "mkdir -p /seqr/data/reference_data")
run_in_pod(pod_name, "wget -N https://storage.googleapis.com/seqr-reference-data/seqr-resource-bundle.tar.gz -O /seqr/data/reference_data/seqr-resource-bundle.tar.gz")
run_in_pod(pod_name, "tar xzf /seqr/data/reference_data/seqr-resource-bundle.tar.gz -C /seqr/data/reference_data", verbose=True)
run_in_pod(pod_name, "rm /seqr/data/reference_data/seqr-resource-bundle.tar.gz")
# load legacy resources
run_in_pod(pod_name, "python -u manage.py load_resources", verbose=True)
run_in_pod(pod_name, "python -u manage.py load_omim", verbose=True)