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368 | def run_pipe(
name: str, path_name: Optional[str] = None,
run_dj_obj: Optional[Run] = None, cli: bool = True,
debug: bool = False, user: Optional[User] = None, full_rerun: bool = False,
prev_ui_status: str = 'END'
) -> bool:
'''
Main function to run the pipeline.
Args:
name:
The name of the pipeline run (p_run.name).
path_name:
The path of the directory of the pipeline run (p_run.path),
defaults to None.
run_dj_obj:
The Run object of the pipeline run, defaults to None.
cli:
Flag to signify whether the pipeline run has been run via the UI
(False), or the command line (True). Defaults to True.
debug:
Flag to signify whether to enable debug verbosity to the logging
output. Defaults to False.
user:
The User of the request if made through the UI. Defaults to None.
full_rerun:
If the run already exists, a complete rerun will be performed which
will remove and replace all the previous results.
prev_ui_status:
The previous status through the UI. Defaults to 'END'.
Returns:
Boolean equal to `True` on a successful completion.
Raises:
CommandError: Raised if error occurs during processing.
PipelineConfigError: Raised if an error is found in the pipeline
config.
'''
path = run_dj_obj.path if run_dj_obj else path_name
# set up logging for running pipeline from UI
if not cli:
# set up the logger for the UI job
root_logger = logging.getLogger('')
if debug:
root_logger.setLevel(logging.DEBUG)
f_handler = logging.FileHandler(
os.path.join(path, timeStamped('log.txt')),
mode='w'
)
f_handler.setFormatter(root_logger.handlers[0].formatter)
root_logger.addHandler(f_handler)
pipeline = Pipeline(
name=run_dj_obj.name if run_dj_obj else name,
config_path=os.path.join(path, 'config.yaml'),
validate_config=False, # delay validation
)
# Create the pipeline run in DB
p_run, flag_exist = get_create_p_run(
pipeline.name,
pipeline.config["run"]["path"],
)
# backup the last successful outputs.
# if the run is being run again and the last status is END then the
# user is highly likely to be attempting to add images. Making the backups
# now from a guaranteed successful run is safer in case of problems
# with the config file below that causes an error.
if flag_exist:
if cli and p_run.status == 'END':
backup_parquets(p_run.path)
elif not cli and prev_ui_status == 'END':
backup_parquets(p_run.path)
# validate run configuration
try:
pipeline.config.validate(user=user)
except PipelineConfigError as e:
if debug:
traceback.print_exc()
logger.exception('Config error:\n%s', e)
msg = f'Config error:\n{e}'
# If the run is already created (e.g. through UI) then set status to
# error
pipeline.set_status(p_run, 'ERR')
raise CommandError(msg) if cli else PipelineConfigError(msg)
# clean up pipeline images and forced measurements for re-runs
# Scenarios:
# A. Complete Re-run: If the job is marked as successful then backup
# old parquets and proceed to remove parquets along with forced
# extractions from the database.
# B. Additional Run on successful run: Backup parquets, remove current
# parquets and proceed.
# C. Additional Run on errored run: Do not backup parquets, just delete
# current.
# D. Running on initialised run that errored and is still the init run.
# Flag on the pipeline object on whether the addition mode is on or off.
pipeline.add_mode = False
pipeline.previous_parquets = {}
prev_config_exists = False
try:
if not flag_exist:
# check for and remove any present .parquet (and .arrow) files
parquets = (
glob.glob(os.path.join(p_run.path, "*.parquet"))
# TODO Remove arrow when arrow files are no longer needed.
+ glob.glob(os.path.join(p_run.path, "*.arrow"))
+ glob.glob(os.path.join(p_run.path, "*.bak"))
)
for parquet in parquets:
os.remove(parquet)
# copy across config file at the start
logger.debug("Copying temp config file.")
create_temp_config_file(p_run.path)
else:
# Check if the status is already running or queued. Exit if this is
# the case.
if p_run.status in ['RUN', 'RES']:
logger.error(
"The pipeline run requested to process already has a "
"running or restoring status! Performing no actions. "
"Exiting."
)
return True
# copy across config file at the start
logger.debug("Copying temp config file.")
create_temp_config_file(p_run.path)
# Check if there is a previous run config and back up if so
if os.path.isfile(
os.path.join(p_run.path, 'config_prev.yaml')
):
prev_config_exists = True
shutil.copy(
os.path.join(p_run.path, 'config_prev.yaml'),
os.path.join(p_run.path, 'config.yaml.bak')
)
logger.debug(f'config_prev.yaml exists: {prev_config_exists}')
# Check for an error status and whether any previous config file
# exists - if it doesn't exist it means the run has failed during
# the first run. In this case we want to clear anything that has
# gone on before so to do that `complete-rerun` mode is activated.
if not prev_config_exists:
if cli and p_run.status == "ERR":
full_rerun = True
elif not cli and prev_ui_status == "ERR":
full_rerun = True
logger.debug(f'Full re-run: {full_rerun}')
# Check if the run has only been initialised, if so we don't want
# to do any previous run checks or cleaning.
if p_run.status == 'INI':
initial_run = True
# check if coming from UI
elif cli is False and prev_ui_status == 'INI':
initial_run = True
else:
initial_run = False
if initial_run is False:
parquets = (
glob.glob(os.path.join(p_run.path, "*.parquet"))
# TODO Remove arrow when arrow files are no longer needed.
+ glob.glob(os.path.join(p_run.path, "*.arrow"))
)
if full_rerun:
logger.info(
'Cleaning up pipeline run before re-process data'
)
p_run.image_set.clear()
logger.info(
'Cleaning up forced measurements before re-process data'
)
remove_forced_meas(p_run.path)
for parquet in parquets:
os.remove(parquet)
# remove bak files
bak_files = glob.glob(os.path.join(p_run.path, "*.bak"))
if bak_files:
for bf in bak_files:
os.remove(bf)
# remove previous config if it exists
if prev_config_exists:
os.remove(os.path.join(p_run.path, 'config_prev.yaml'))
# reset epoch_based flag
with transaction.atomic():
p_run.epoch_based = False
p_run.save()
else:
# Before parquets are started to be copied and backed up, a
# check is run to see if anything has actually changed in
# the config
config_diff = pipeline.config.check_prev_config_diff()
if config_diff:
logger.info(
"The config file has either not changed since the"
" previous run or other settings have changed such"
" that a new or complete re-run should be performed"
" instead. Performing no actions. Exiting."
)
os.remove(os.path.join(p_run.path, 'config_temp.yaml'))
pipeline.set_status(p_run, 'END')
return True
if pipeline.config.epoch_based != p_run.epoch_based:
logger.info(
"The 'epoch based' setting has changed since the"
" previous run. A complete re-run is required if"
" changing to epoch based mode or vice versa."
)
os.remove(os.path.join(p_run.path, 'config_temp.yaml'))
pipeline.set_status(p_run, 'END')
return True
pipeline.add_mode = True
for i in [
'images', 'associations', 'sources', 'relations',
'measurement_pairs'
]:
pipeline.previous_parquets[i] = os.path.join(
p_run.path, f'{i}.parquet.bak')
except Exception as e:
logger.error('Unexpected error occurred in pre-run steps!')
pipeline.set_status(p_run, 'ERR')
logger.exception('Processing error:\n%s', e)
raise CommandError(f'Processing error:\n{e}')
if pipeline.config["run"]["suppress_astropy_warnings"]:
warnings.simplefilter("ignore", category=AstropyWarning)
logger.info("VAST Pipeline version: %s", pipeline_version)
logger.info(
"Source finder: %s",
pipeline.config["measurements"]["source_finder"]
)
logger.info("Using pipeline run '%s'", pipeline.name)
logger.info(
"Source monitoring: %s",
pipeline.config["source_monitoring"]["monitor"]
)
# log the list of input data files for posterity
inputs = pipeline.config["inputs"]
input_image_list = [
image
for image_list in inputs["image"].values()
for image in image_list
]
input_selavy_list = [
selavy
for selavy_list in inputs["selavy"].values()
for selavy in selavy_list
]
input_noise_list = [
noise
for noise_list in inputs["noise"].values()
for noise in noise_list
]
if "background" in inputs.keys():
input_background_list = [
background
for background_list in inputs["background"].values()
for background in background_list
]
else:
input_background_list = ["N/A", ] * len(input_image_list)
for image, selavy, noise, background in zip(
input_image_list, input_selavy_list, input_noise_list, input_background_list
):
logger.info(
"Matched inputs - image: %s, selavy: %s, noise: %s, background: %s",
image,
selavy,
noise,
background,
)
stopwatch = StopWatch()
# run the pipeline operations
try:
# check if max runs number is reached
pipeline.check_current_runs()
# run the pipeline
pipeline.set_status(p_run, 'RUN')
pipeline.process_pipeline(p_run)
# Create arrow file after success if selected.
if pipeline.config["measurements"]["write_arrow_files"]:
create_measurements_arrow_file(p_run)
if pipeline.config["variability"]["pair_metrics"]:
create_measurement_pairs_arrow_file(p_run)
except Exception as e:
# set the pipeline status as error
pipeline.set_status(p_run, 'ERR')
logger.exception('Processing error:\n%s', e)
raise CommandError(f'Processing error:\n{e}')
# copy across config file now that it is successful
logger.debug("Copying and cleaning temp config file.")
shutil.copyfile(
os.path.join(p_run.path, 'config_temp.yaml'),
os.path.join(p_run.path, 'config_prev.yaml'))
os.remove(os.path.join(p_run.path, 'config_temp.yaml'))
# set the pipeline status as completed
pipeline.set_status(p_run, 'END')
logger.info(
'Total pipeline processing time %.2f sec',
stopwatch.reset()
)
return True
|