def produce_report(self):
"""Produce a report of the batch jobs."""
s3_prefix = 'reading_results/%s/logs/%s/' % (self.basename,
self._job_queue)
logger.info("Producing batch report for %s, from prefix %s." %
(self.basename, s3_prefix))
s3 = boto3.client('s3')
file_tree = get_s3_file_tree(s3, bucket_name, s3_prefix)
logger.info("Found %d relevant files." % len(file_tree))
stat_files = {
'git_info.txt': (self._handle_git_info, self._report_git_info),
'timing.txt': (self._handle_timing, self._report_timing),
'raw_tuples.pkl': (None, None),
'hist_data.pkl': (self._handle_hist_data, self._report_hist_data),
'sum_data.pkl': (self._handle_sum_data, self._report_sum_data)
}
stat_aggs = {}
for stat_file, (handle_stats, report_stats) in stat_files.items():
logger.info("Aggregating %s..." % stat_file)
# Prep the data storage.
my_agg = {}
# Get a list of the relevant files (one per job).
file_paths = file_tree.get_paths(stat_file)
logger.info("Found %d files for %s." %
(len(file_paths), stat_file))
# Aggregate the data from all the jobs for each file type.
for sub_path, file_entry in file_paths:
s3_key = file_entry['key']
ref = sub_path[0]
file = s3.get_object(Bucket=bucket_name, Key=s3_key)
file_bytes = file['Body'].read()
if handle_stats is not None:
handle_stats(ref, my_agg, file_bytes)
if report_stats is not None and len(my_agg):
report_stats(my_agg)
stat_aggs[stat_file] = my_agg
for end_type, jobs in self.run_record.items():
self.reporter.add_text('Jobs %s: %d' % (end_type, len(jobs)),
section='Totals')
s3_prefix = 'reading_results/%s/' % self.basename
fname = self.reporter.make_report()
with open(fname, 'rb') as f:
s3.put_object(Bucket=bucket_name,
Key=s3_prefix + fname,
Body=f.read())
s3.put_object(Bucket=bucket_name,
Key=s3_prefix + 'stat_aggregates_%s.pkl' % self.time_tag,
Body=pickle.dumps(stat_aggs))
return file_tree, stat_aggs
def sort_s3_files_by_last_mod(bucket,
prefix,
time_delta=None,
extension=None,
unsigned=True,
reverse=False,
w_dt=False):
"""Return a list of s3 object keys sorted by their LastModified date on S3
Parameters
----------
bucket : str
s3 bucket to look for keys in
prefix : str
The prefix to use for the s3 keys
time_delta : Optional[datetime.timedelta]
If used, should specify how far back the to look for files on s3.
Default: None
extension : Optional[str]
If used, limit keys to those with the matching file extension.
Default: None.
unsigned : bool
If True, use unsigned s3 client. Default: True.
reverse : bool
Reverse the sort order of the returned s3 files. Default: False.
w_dt : bool
If True, return list with datetime object along with key as tuple
(key, datetime.datetime). Default: False.
Returns
-------
list
A list of s3 keys. If w_dt is True, each item is a tuple of
(key, datetime.datetime) of the LastModified date.
"""
if time_delta is None:
time_delta = timedelta() # zero timedelta
s3 = get_s3_client(unsigned)
n_hours_ago = datetime.utcnow() - time_delta
file_tree = get_s3_file_tree(s3,
bucket,
prefix,
date_cutoff=n_hours_ago,
with_dt=True)
key_list = sorted(list(file_tree.get_leaves()),
key=lambda t: t[1],
reverse=reverse)
if extension:
return [
t if w_dt else t[0] for t in key_list if t[0].endswith(extension)
]
else:
return key_list if w_dt else [t[0] for t in key_list]
def get_latest_pa_stmt_dump():
s3_cli = get_s3_client(False)
# Get file key
dump_name = 'full_pa_stmts.pkl'
file_tree = get_s3_file_tree(s3=s3_cli,
bucket=DUMPS_BUCKET,
prefix=DUMPS_PREFIX,
with_dt=True)
# Get all keys for dump_name
keys = [key for key in file_tree.gets('key') if key[0].endswith(dump_name)]
keys.sort(key=itemgetter(1)) # Sorts ascending by datetime
return load_pickle_from_s3(s3_cli, keys[-1][0], DUMPS_BUCKET)
def get_latest_sif_s3(get_mesh_ids: bool = False) \
-> Union[Tuple[Any, str], Tuple[Tuple[Any, str], Tuple[Any, str]]]:
necc_files = [mngr.name for mngr in dumpers]
if get_mesh_ids:
necc_files.append(StatementHashMeshId.name)
s3 = get_s3_client(unsigned=False)
tree = get_s3_file_tree(s3,
bucket=DUMPS_BUCKET,
prefix=DUMPS_PREFIX,
with_dt=True)
# Find all pickles and jsons
keys = [
key for key in tree.gets('key') if key[0].endswith(('.pkl', '.json'))
]
# Sort newest first
keys.sort(key=lambda t: t[1], reverse=True)
# Get keys of those pickles
keys_in_latest_dir = \
[k[0] for k in keys if any(nfl in k[0] for nfl in necc_files)]
# Map key to resource
necc_keys = {}
for n in necc_files:
for k in keys_in_latest_dir:
# check name then alt name
if n in k:
# Save and continue to next file in necc_files
necc_keys[n] = k
break
logger.info(f'Latest files: {", ".join([f for f in necc_keys.values()])}')
df = load_pickle_from_s3(s3, key=necc_keys[Sif.name], bucket=DUMPS_BUCKET)
sif_date = _get_date_from_s3_key(necc_keys[Sif.name])
if get_mesh_ids:
mid = load_pickle_from_s3(s3,
key=necc_keys[StatementHashMeshId.name],
bucket=DUMPS_BUCKET)
meshids_date = _get_date_from_s3_key(
necc_keys[StatementHashMeshId.name])
return (df, sif_date), (mid, meshids_date)
return df, sif_date
def get_logs_from_s3(folder=None, cached=True, past_days=None):
"""Download logs from S3 and save into a local folder
Parameters
----------
folder : str
The directory where to put the processed reports
cached : str
Look for already existing folders and skip those that exist
past_days : int|datetime.datetime
Either an integer or an instance of a datetime.datetime object
specifying the number of days into the past to download logs for.
If nothing is specified (default), all logs are downloaded.
Default: None.
Returns
-------
dir_set : set
A set containing the dir paths of all the requested logs
"""
s3 = get_s3_client(unsigned=False)
if past_days:
days_ago = past_days if isinstance(past_days, datetime) else\
((datetime.utcnow() - timedelta(days=past_days)).replace(
tzinfo=timezone.utc) if isinstance(past_days, int) else None)
else:
days_ago = None
tree = get_s3_file_tree(s3, 'cwc-hms', 'bob_ec2_logs', days_ago)
keys = tree.gets('key')
# Here we only get the tar.gz files which contain the logs for the
# facilitator + the json file (if present) of the user data
logger.info('Total number of objects: %d ' % len(keys))
logger.info('Total number of images found: %d' %
len([k for k in keys if 'image' in k]))
keys = [key for key in keys if key.startswith('bob_ec2_logs/')
and key.endswith(('.tar.gz', '.json', '.log'))]
logger.info('Number of archives: %d' % len(keys))
fname_patt = re.compile(
'([\w:-]+?)_(\w+?)_(\w+?_\w+?)_(.*).(tar\.gz|json|\.log)'
)
dir_set = set()
for key in tqdm.tqdm(keys):
fname = os.path.basename(key)
m = fname_patt.match(fname)
if m is None:
logger.warning("File name %s failed to match %s. Skipping..."
% (fname, fname_patt))
continue
image_id, cont_hash, cont_name, resource_name, suffix = m.groups()
head_dir_path = '%s_%s_%s' % (image_id.replace(':', '-'), cont_name,
cont_hash)
dir_set.add(head_dir_path)
if folder:
head_dir_path = os.path.join(folder, head_dir_path)
if not os.path.exists(head_dir_path):
os.makedirs(head_dir_path, exist_ok=True)
if resource_name == 'bioagent_images':
outpath = head_dir_path
else:
outpath = os.path.join(head_dir_path, 'log.txt')
if cached and os.path.exists(outpath) and\
not key.endswith(('.json', '.log')):
continue
tgz_file_name = key.split('/')[-1]
tgz_file = os.path.join(head_dir_path, tgz_file_name)
res = s3.get_object(Bucket='cwc-hms', Key=key)
# byte_stream = BytesIO(res['Body'].read())
byte_stream = res['Body'].read()
with open(tgz_file, 'wb') as tf:
tf.write(byte_stream)
# Re-open file
if tgz_file.endswith(('.json', '.log')):
continue
with open(tgz_file, 'rb') as file_byte_stream:
with tarfile.open(None, 'r', fileobj=file_byte_stream) as tarf:
if resource_name == 'bioagent_images':
tarf.extractall(outpath)
else:
outpaths = tarf.getnames()
facls = [n for n in outpaths if
n.endswith('facilitator.log')]
if not facls:
logger.info('No facilitator.log found for %s' % key)
continue
facl = facls[0]
efo = tarf.extractfile(facl)
log_txt = efo.read().decode('utf-8')
with open(outpath, 'w') as fh:
fh.write(log_txt)
return dir_set
