def get_colors(obs, factors, as_df=True):
v_colors = dict()
for f in factors:
v = obs.loc[:, f]
d = OrderedDict(zip(sorted(v.unique()), colors[f]))
v_colors[f] = pd.Series(v.map(d).values, index=v.index)
return v_colors if not as_df else pd.DataFrame(v_colors)
def expand_range(value):
""" receive a value in form a-d,x-y,z and return list of expanded values.
Note, all remap functions expect strings so the expanded range will
also be a list of strings.
if unable to expand range then return list with original value
"""
try:
result = []
for v in list(set(value.split(","))):
r1 = re.search(RANGE_REGEX, v)
if r1 is None:
result.append(v)
continue
start = int(r1.group("s"))
end = int(r1.group("e"))
if start > end:
for i in range(end, start + 1):
result.append("%d" % i)
else:
for i in range(start, end + 1):
result.append("%d" % i)
return sorted(set(result))
except Exception as e:
logger.warn("failed to expand range (%s): %s" % (value, e))
return ["%s" % value]
def __init__(self, game, network, train_directory):
self.game = game
env_name = '%sNoFrameskip-v4' % game
env = gym.make(env_name)
#env = gym.wrappers.Monitor(env, '/tmp/temp_%s' % game, mode='evaluation', force=True)
vb_file = os.path.join(train_directory, "vb.npy")
vb = np.load(vb_file)
parameters_file = sorted(os.listdir(train_directory))[-3]
self.policy = Policy(env, network, "elu")
parameters_path = os.path.join(train_directory, parameters_file)
print('Using parameters file %s \n' % parameters_path)
with open(parameters_path, 'rb') as f:
parameters = pickle.load(f)['parameters']
self.policy.set_parameters(parameters)
self.policy.set_vb(vb)
def gen_format_all(self, usage):
"""
generates string for format all
"""
format_string = " "
core_strings = []
for core, usage in usage.items():
if core == 'usage_cpu' and self.exclude_average:
continue
elif core == 'usage':
continue
core = core.replace('usage_', '')
string = self.formatter.vformat(self.format_all, (),
{'core': core, 'usage': usage})
core_strings.append(string)
core_strings = sorted(core_strings)
return format_string.join(core_strings)
def gen_format_all(self, usage):
"""
generates string for format all
"""
format_string = " "
core_strings = []
for core, usage in usage.items():
if core == 'usage_cpu' and self.exclude_average:
continue
elif core == 'usage':
continue
core = core.replace('usage_', '')
string = self.formatter.format(format_string=self.format_all,
core=core,
usage=usage)
core_strings.append(string)
core_strings = sorted(core_strings)
return format_string.join(core_strings)
# subsample
ds = ds.sample(n=n_cells if n_cells < ds.shape[0] else ds.shape[0],
replace=False).loc[:, genes]
# sort by timepoint, patient
d = data.obs.loc[ds.index].sort_values(['patient_id', 'timepoint'])
ds = ds.loc[d.index, :]
colors = list()
for f, cmap in [
('patient_id', 'tab20'),
('timepoint', 'tab20'),
# ('cell_type', 'tab20')
]:
q = data.obs.loc[ds.index, f]
qq = sorted(q.unique())
m = dict(zip(qq, range(len(qq))))
cmap = plt.get_cmap(cmap)
colors.append(cmap([m[x] for x in q]))
g = sns.clustermap(ds.T.dropna().T,
row_cluster=False,
row_colors=colors,
metric="euclidean",
xticklabels=False,
yticklabels=False,
cbar_kws={"label": "Expression\n(Z-score)"},
cmap="RdBu_r",
center=0,
robust=True)
g.ax_heatmap.set_xlabel("Genes (n = {})".format(ds.shape[1]))
def search_entries(entries,
regex,
ignore_case=False,
sort_reg=None,
sort_neg=False,
retro_option=False,
retro_space=False,
retro_month=False,
retro_full=False,
retro_deletion=False):
"""
loop through entries list and print each full entry that matches regex
"""
results = []
logging.debug("regex: %s, ignore_case: %r, negative: %r" %
(regex, ignore_case, sort_neg))
start = time.time()
matches = 0
if ignore_case and regex is not None:
for e in entries:
matched = False
if re.search(regex, e, re.IGNORECASE):
matches += 1
matched = True
if (matched and not sort_neg) or (not matched and sort_neg):
results.append(e)
elif regex is not None:
for e in entries:
matched = False
if re.search(regex, e):
matches += 1
matched = True
if (matched and not sort_neg) or (not matched and sort_neg):
results.append(e)
else:
# get all entries
results = entries
logging.debug("search time: %s" % td(start, time.time()))
logging.debug("search matches: %d" % matches)
if len(results) == 0:
logging.debug("no results to print")
return
# sort the 'filtered' results into final result list
final_results = []
if sort_reg is not None:
logging.debug("sort_reg: %s" % sort_reg)
sort_match_count = 0
start = time.time()
ts_results_default = [] # catch all if we don't match any results
ts_results = {}
for r in results:
r1 = re.search(sort_reg, r)
if r1 is not None:
sort_match_count += 1
m = r1.group("m")
if m not in ts_results:
ts_results[m] = []
ts_results[m].append(r)
else:
ts_results_default.append(r)
# final results is combined ts_results_default and sorted results
final_results = ts_results_default
for k in sorted(ts_results):
final_results += ts_results[k]
logging.debug("sort attribute time: %s" % td(start, time.time()))
logging.debug("sort attribute matches: %d" % sort_match_count)
else:
final_results = results
# print all results (peek first for suppot for retro_peek)
if retro_option:
retro_peek = results[0].splitlines()[0]
if "# aaaModLR" in retro_peek:
new_results = aaa_entry_parse(final_results, retro_full)
elif "# eventRecord" in retro_peek:
new_results = event_entry_parse(final_results, retro_full)
elif "# faultRecord" in retro_peek:
new_results = fault_entry_parse(final_results, retro_full,
retro_deletion)
else:
logging.error("Unable to Determine Record Type")
new_results = final_results
if retro_space:
new_results = space_option(new_results)
for e in new_results:
if retro_month:
print(letter_month(e))
else:
print(e)
# normal non-retro printing
else:
for r in final_results:
print("".join(r))
def execute_snapshot(snapshot_id):
""" perform snapshot operation for provided fabric name and definition name.
The snapshot will be stored in config["DATA_DIR"]. The progress of the
collection and final result are saved to the database.
format of snapshot:
snapshot.<fabric-name>.<date>.tgz
/md5checksum checksum of bundle.tgz
/bundle.tgz
/snapshot.json snapshot object attributes
/definition.json
/node-X note, node-0 is for global objects
/<classname.json> per-object class collection
"""
from ..utils import (get_app_config, format_timestamp, pretty_print)
logger.debug("execute snapshot for: %s" % snapshot_id)
config = get_app_config()
src = config.get("TMP_DIR", "/tmp/")
dst = config.get("DATA_DIR", "/tmp/")
reg = "topology/pod-[0-9]+/node-(?P<node>[0-9]+)(/|$)"
reg = re.compile(reg)
# verify that snapshot object exists, if not abort since no way to alert
# user of final result
ts = time.time()
apic = None
s = Snapshots.load(_id=snapshot_id)
if not s.exists():
logger.warn("snapshot %s not found" % snapshot_id)
return
filename = "snapshot.%s.%s.tgz" % (s.fabric, format_timestamp(ts,
msec=True))
filename = get_unique_filename(dst, filename)
src = "%s/%s" % (src, re.sub("\.tgz$", "", filename))
# update snapshot state with error message and error status
def fail(msg="", cleanup=True):
if len(msg) > 0: s.error = msg
s.status = "error"
s.total_time = abs(time.time() - ts)
logger.debug("snapshot %s failed: %s" % (s._id, s.error))
if not s.save():
logger.warn("failed to save snapshot %s state" % s._id)
if cleanup: tmp_cleanup()
return
# clean up working directory
def tmp_cleanup():
if os.path.isdir(src):
logger.debug("cleanup directory %s" % src)
try:
shutil.rmtree(src)
except Exception as e:
logger.warn("failed to cleanup directory(%s): %s" % (src, e))
else:
logger.debug("cleanup directory %s not found" % src)
if apic is not None: apic.close()
# update snapshot progress percentage
def progress(i, total):
abort_snapshot() # check for abort signal before progress update
if total > 0: p = round(i / (1.0 * total), 2)
else: p = 0
s.progress = p
s.total_time = abs(time.time() - ts)
if not s.save():
logger.warn("failed to save snapshot %s state" % s._id)
return
# user can force snapshot execution to stop by deleting the object
# abort_snapshot is checked at a regular interval. If snapshot was deleted
# then perform cleanup and return True, else return False
def abort_snapshot():
_s = Snapshots.load(_id=s._id)
if not _s.exists():
logger.debug("snapshot %s has been deleted, aborting" % s._id)
tmp_cleanup()
raise Exception("snapshot operation %s aborted" % s._id)
# write dict data to specified path
def json_write(path, data):
if not re.search("\.json$", path): path = "%s.json" % path
if not os.path.exists(os.path.dirname(path)):
os.makedirs(os.path.dirname(path))
logger.debug("saving to %s" % (path))
with open("%s" % path, "w") as f:
json.dump(data, f)
# init progress, error, status
s.nodes = []
s.fabric_domain = ""
s.progess = 0.0
s.filename = ""
s.filesize = 0
s.start_time = ts
s.total_time = 0
s.wait_time = 0
s.error = ""
s.status = "running"
s.save()
try:
# setup working directory to store collection outputs
if os.path.exists(src):
return fail("tmp directory already exists: %s" % src,
cleanup=False)
os.makedirs(src)
# get definition managed_objects to collect
d = Definitions.load(definition=s.definition)
if not d.exists():
return fail("unable to read definition: %s" % s.definition)
managed_objects = d.get_managed_objects()
# ensure all required objects are within definition. If not add them
for r in Remap.REQUIRED_MANAGED_OBJECTS:
if r not in managed_objects:
logger.debug("adding required mo to definition: %s" % r)
mo = ManagedObjects(classname=r)
mo.analyzer = "exclude"
managed_objects[mo.classname] = mo.to_json()
# create apic session
apic = aci_utils.get_apic_session(s.fabric)
if apic is None: return fail("unable to connect to %s apic" % s.fabric)
ret = aci_utils.get_class(apic, "infraCont")
if ret is not None and len(ret)>0 and "infraCont" in ret[0] and \
"attributes" in ret[0]["infraCont"] and \
"fbDmNm" in ret[0]["infraCont"]["attributes"]:
s.fabric_domain = ret[0]["infraCont"]["attributes"]["fbDmNm"]
complete_count = 0
for classname in managed_objects:
complete_count += 1
o = managed_objects[classname]
if len(o["classname"]) == 0:
logger.warn("%s ignoring empty classname %s" %
(s.definition, o["classname"]))
continue
_t = time.time()
response_classes = []
logger.debug("getting data for class %s" % o["classname"])
if o["pseudo"]:
# for pseudo mo, collect each of the classnames defined in the
# corresponding customer analyzer. If no customer analyzer then
# no objects will be collected...
if o["analyzer"] in ManagedObjects.ANALYZERS and \
"classnames" in ManagedObjects.ANALYZERS[o["analyzer"]]:
ret = []
for ac in ManagedObjects.ANALYZERS[
o["analyzer"]]["classnames"]:
order = "%s.%s" % (ac, "dn") # static to dn for now
sret = aci_utils.get_class(apic, ac, orderBy=order)
if sret is not None:
ret += sret
response_classes.append(ac)
elif len(o["uri"]) > 0:
ret = aci_utils.get(apic, o["uri"])
response_classes.append(o["classname"])
else:
order = "%s.%s" % (o["classname"], o["key"])
ret = aci_utils.get_class(apic, o["classname"], orderBy=order)
response_classes.append(o["classname"])
s.wait_time += abs(time.time() - _t)
# if failed to get object, might not exists on current version of
# code. just continue
if ret is None:
progress(complete_count, len(managed_objects) + 1)
continue
# need to parse each received object and group based on node-id
cc_match = None # cache expected response_classes value (usually the
# same for all objects expect for pseudo case)
nodes = {}
for c in ret:
node = "0"
if type(c) is dict and len(c) >= 1:
cc = None
# check for each possible response_class in returned object
if cc_match is not None and cc_match in c:
cc = c[cc_match]
else:
for rclass in response_classes:
if rclass in c:
cc_match = rclass
cc = c[cc_match]
break
else:
# check if 'children' is present and first level
# child has corresponding object. before child
# check, try to extract node-id (i.e., stats
# object node-id from original parent object)
tc = c[c.keys()[0]]
if "attributes" in tc and "dn" in tc[
"attributes"]:
r = reg.search(tc["attributes"]["dn"])
if r is not None: node = r.group("node")
if "children" in tc:
for child in tc["children"]:
if rclass in child:
cc = child[rclass]
c = child
break
if cc is None:
logger.debug("failed to extract data for %s from %s" %
(o["classname"], c))
continue
if type(cc) is dict and len(
cc) >= 1 and "attributes" in cc:
if "dn" in cc["attributes"]:
r = reg.search(cc["attributes"]["dn"])
if r is not None: node = r.group("node")
if node not in nodes: nodes[node] = []
if node not in s.nodes: s.nodes.append(node)
nodes[node].append(c)
continue
logger.debug("skipping unsupported object: %s" % c)
# for each node, write results to file
for n in nodes:
json_write("%s/node-%s/%s" % (src, n, o["classname"]),
nodes[n])
# check for abort and then update progress
progress(complete_count, len(managed_objects) + 1)
# sort nodes before saving
s.nodes = sorted(s.nodes)
json_write("%s/snapshot" % src, s.to_json())
json_write("%s/definition" % src, {
"definition": s.definition,
"managed_objects": managed_objects
})
# bundle all files
ret = aci_utils.run_command("cd %s ; tar -zcvf bundle.tgz ./*" % src)
if ret is None: return fail("failed to create snapshot bundle")
# get md5 for bundle
md5 = aci_utils.get_file_md5("%s/bundle.tgz" % src)
if md5 is None: return fail("failed to calculate bundle md5")
json_write("%s/md5checksum" % src, {"md5checksum": md5})
# create final bundle with bundle.tgz and md5checksum.json
cmd = "cd %s ; tar --force-local -zcvf %s " % (src, filename)
cmd += "./bundle.tgz ./md5checksum.json"
if aci_utils.run_command(cmd) is None:
return fail("failed to create snapshot bundle")
# to prevent race condition of 'delete' operation during compression,
# perform one last abort check before moving complete file to dst
abort_snapshot()
# create the directory if not present
if not os.path.isdir(dst): os.makedirs(dst)
# move final bundle to dst directory and cleanup tmp directory
if aci_utils.run_command("mv %s/%s %s/" % (src, filename, dst)):
return fail("failed to save snapshot bundle")
tmp_cleanup()
# after everything is complete, update progress to 100% and complete
s.progress = 1.0
s.status = "complete"
s.filename = "%s/%s" % (dst, filename)
s.filesize = os.path.getsize("%s/%s" % (dst, filename))
s.total_time = abs(time.time() - ts)
if not s.save(): logger.warn("failed to save snapshot status")
logger.debug("snapshot %s complete: %s " % (snapshot_id, s))
except Exception as e:
logger.debug(traceback.format_exc())
fail("unexpected error occurred: %s" % e)
def gen_gif(path_in,
pattern='.*',
fn_out='movie.gif',
duration=0.5,
file_range=None,
repeat={},
path_out=None,
user_confirm=True):
"""Generate a gif from a collection of images in a given directory.
path_in: path of input images
pattern regular expression matching file to include in gif
fn_out filename for output gif
duration duration between frames in seconds
file_range replaces "{number}" in pattern with re matching a range of numbers
repeat dict of frame numbers and the number of times those frames should be repeated
path_out directory to write gif to
"""
assert os.path.isdir(path_in)
if path_out is None:
path_out = path_in
assert os.path.isdir(path_out)
if (file_range is not None) and ('{range}' in fn_out):
fn_out.format(range='{}-{}'.format(file_range[0], file_range[1]))
if file_range is not None:
assert '{number}' in pattern, 'Include "{number}" in pattern when using file range'
pattern = pattern.format(number=regexp_range(*file_range))
filenames = fn_filter(path_in, pattern)
filenames = sorted(filenames)
nframes = len(filenames)
assert nframes > 0, 'No frames to create gif from'
if -1 in repeat.keys(
): # If repeating final frame, replace '-1' with index
repeat[nframes - 1] = repeat[-1]
repeat.pop(-1)
if user_confirm:
print('{} frames will be combined into gif in: {}'.format(
nframes, os.path.join(path_in, fn_out)))
if nframes < 60:
pprint(filenames)
choice = input('Proceed? [y/n]: ')
if not choice == 'y':
print('gif was not produced')
return ## return from function without renaming
with imageio.get_writer(os.path.join(path_out, fn_out),
mode='I',
format='GIF-FI',
duration=0.12) as writer: # duration = 0.4
for i, filename in enumerate(filenames):
image = imageio.imread(os.path.join(path_in, filename))
writer.append_data(image)
if repeat is not None and i in repeat.keys():
for j in np.arange(repeat[i]):
writer.append_data(image)
print('Wrote gif containing {} frames to: {}'.format(
nframes, os.path.join(path_in, fn_out)))
def execute_compare(compare_id):
""" perform comparison between two snapshots """
logger.debug("execute compare for: %s" % compare_id)
ts = time.time()
c = Compare.load(_id=compare_id)
if not c.exists():
logger.warn("compare object %s not found" % compare_id)
return
# init progress, error, status to block second process from running
c.progess = 0.0
c.start_time = ts
c.total_time = 0
c.error = ""
c.status = "running"
c.save()
# delete any previous CompareResults
CompareResults.delete(_filters={"compare_id":c._id})
# create a working directory to extract objects
config = get_app_config()
tmp = config.get("TMP_DIR", "/tmp/")
tmp = "%s/compare.%s.%s" % (tmp, c._id, int(ts))
# update state with error message and error status
def fail(msg="", cleanup=True):
if len(msg)>0: c.error = msg
c.status = "error"
c.total_time = abs(time.time() - ts)
logger.debug("compare %s failed: %s" % (c._id, c.error))
if not c.save(): logger.warn("failed to save compare %s state"%c._id)
if cleanup: tmp_cleanup()
return
# clean up working directory
def tmp_cleanup():
if os.path.isdir(tmp):
logger.debug("cleanup directory %s" % tmp)
try: shutil.rmtree(tmp)
except Exception as e:
logger.warn("failed to cleanup directory(%s): %s"%(tmp,e))
else: logger.debug("cleanup directory %s not found" % tmp)
# update snapshot progress percentage
def progress(i, total):
abort_compare() # check for abort signal before progress update
if total>0: p = round(i/(1.0*total), 2)
else: p = 0
if p > 1: p = 1
c.progress = p
c.total_time = abs(time.time() - ts)
if not c.save(): logger.warn("failed to save compare %s state"%c._id)
logger.debug("progress %s/%s = %s" % (i, total, p))
return
# user can force compare execution to stop by deleting the object
# abort_compare is checked at a regular interval. If compare was deleted
# then perform cleanup and return True, else return False
def abort_compare():
_s = Compare.load(_id=c._id)
if not _s.exists() or _s.status == "abort":
logger.debug("compare object %s has been aborted"%c._id)
tmp_cleanup()
raise Exception("compare operation %s aborted" % c._id)
# return dict representation of json in provided filename
def get_json_data(fname):
with open(fname, "r") as f:
return json.load(f)
# load snapshot1 (s1) and snapshot2 (s2) along with definition in compare object
s1 = Snapshots.load(_id=c.snapshot1)
s2 = Snapshots.load(_id=c.snapshot2)
d = Definitions.load(definition=c.definition)
classnames = []
if not s1.exists(): return fail("snapshot %s not found" % c.snapshot1)
if not s2.exists(): return fail("snapshot %s not found" % c.snapshot2)
if not s1.status=="complete":
return fail("snapshot %s not complete"%c.snapshot1)
if not s2.status=="complete":
return fail("snapshot %s not complete"%c.snapshot2)
if not d.exists():
logger.debug("unknown definition provided in compare request: '%s'", c.definition)
else:
classnames = d.get_managed_objects()
try:
# create tmp directory for extracting files
if os.path.exists(tmp):
return fail("tmp directory already exists: %s"%tmp, cleanup=False)
logger.debug("make directory: %s" % tmp)
os.makedirs(tmp)
# extract snaphots to tmp directories
for index, s in enumerate([s1, s2]):
td = "%s/%s/%s" % (tmp, index, s._id)
logger.debug("make directory: %s" % td)
os.makedirs(td)
if not os.path.exists(s.filename):
return fail("snapshot file %s not found" % s.filename)
shutil.copy(s.filename, td)
fname = s.filename.split("/")[-1]
# extract snapshot contents
cmd = "cd %s ; tar --force-local -zxf %s" % (td, fname)
if aci_utils.run_command(cmd) is None:
return fail("failed to extract snapshot %s" % s.id)
for f in ["bundle.tgz", "md5checksum.json"]:
if not os.path.exists("%s/%s" % (td, f)):
return fail("snapshot %s missing required file %s"%(s.id,f))
# check bundle against md5
embedded = get_json_data("%s/md5checksum.json" % td)["md5checksum"]
md5 = aci_utils.get_file_md5("%s/bundle.tgz" % td)
if md5 is None or md5!=embedded:
return fail("snapshot %s invalid md5(%s) expected(%s)" % (
s.id, md5, embedded))
# extract bundle
cmd = "cd %s ; tar -zxf %s" % (td, "bundle.tgz")
if aci_utils.run_command(cmd) is None:
return fail("failed to extract bundle %s" % s.id)
# get the union of the list of classes from both s1 and s2 definitions,
# use the managed_object definition from s2 (should always be the same)
# use the definition in s2 for list of objects, attributes, and flags
# if the classname is not present in definition from s1 then skip it
js1 = get_json_data("%s/0/%s/definition.json" % (tmp, s1._id))
js2 = get_json_data("%s/1/%s/definition.json" % (tmp, s2._id))
if len(js1)==0: return fail("invalid definition in snapshot %s"%s1._id)
if len(js2)==0: return fail("invalid definition in snapshot %s"%s2._id)
s1_classes = [cn for cn in js1["managed_objects"].keys()]
managed_objects = {}
for classname in js2["managed_objects"]:
if classname not in s1_classes:
logger.debug("skipping %s not in snapshot1" % classname)
continue
managed_objects[classname] = js2["managed_objects"][classname]
# build list of all nodes (join of s1 and s2 nodes)
nodes =[ int(x) for x in sorted(list(set().union(s1.nodes, s2.nodes)))]
# create pool to perform work
pool = Pool(processes=config.get("MAX_POOL_SIZE", 4))
filtered_nodes = []
for n in nodes:
if len(c.nodes)==0 or n in c.nodes: filtered_nodes.append(n)
# build out work that needs to be completed
class_work = [] # list of classes to perform 'class' work
analyzer_work = [] # list of customer analyzers to work
for classname in managed_objects:
mo = managed_objects[classname]
if len(classnames)>0 and classname not in classnames: continue
if mo["analyzer"]=="" or mo["analyzer"]=="default": class_work.append(classname)
for analyzer in ManagedObjects.ANALYZERS:
# skip empty analyzer and default analyzer as they are 'class-work'
if len(analyzer)==0 or analyzer=="default": continue
# if a filter is set on the comparison for specific classname, then
# ensure should be the name of the analyzer
if len(classnames)==0 or analyzer in classnames: analyzer_work.append(analyzer)
# think of progress as the sum of all tasks that need to be completed.
# one task for each class in 'class_work' per node plus
# one task for each analyzer in 'analyzer_work' per node plus
# two task per node to for remapping (one for each snapshot)
total_progress =len(class_work)*len(filtered_nodes) + \
len(analyzer_work)*len(filtered_nodes) + \
len(filtered_nodes)*2
current_progress = 0
progress(current_progress, total_progress)
# perform comparision for each node
for i,n in enumerate(filtered_nodes):
if n!="0" and c.remap:
# build remap for s1 and s2
r1 = Remap(n, "%s/0/%s/node-%s" % (tmp, s1._id, n))
current_progress+=1
r2 = Remap(n, "%s/1/%s/node-%s" % (tmp, s2._id, n))
current_progress+=1
else:
# create disabled remap objects
r1 = Remap(n)
r2 = Remap(n)
current_progress+=2
progress(current_progress, total_progress)
work = []
# build out classwork
for classname in class_work:
o = managed_objects[classname]
cn = "node-%s/%s.json" % (n, classname)
f1 = "%s/0/%s/%s" % (tmp, s1._id, cn)
f2 = "%s/1/%s/%s" % (tmp, s2._id, cn)
work.append(("class", c, o, f1, f2, r1, r2))
# build out analyzer work
f1 = "%s/0/%s/node-%s/" % (tmp, s1._id, n)
f2 = "%s/1/%s/node-%s/" % (tmp, s2._id, n)
for analyzer in analyzer_work:
work.append(("custom", analyzer, c, f1, f2, r1, r2 ))
# start the work using multiprocessing or serialize
if c.serialize:
for w in work:
generic_compare(w)
current_progress+=1
progress(current_progress, total_progress)
else:
pool.map(generic_compare, work)
current_progress+= len(work)
progress(current_progress, total_progress)
# cleanup tmp extracted files
tmp_cleanup()
# create totals by summing over current compareResults
counters = ["created", "modified", "deleted", "equal"]
base = {"created":0, "modified":0, "deleted":0, "equal":0}
total = copy.deepcopy(base)
per_class = {} # indexed per classname
per_node = {} # indexed per node_id
results = CompareResults.read(compare_id=c._id)
for o in results["objects"]:
if o["classname"] not in per_class:
per_class[o["classname"]] = copy.deepcopy(base)
per_class[o["classname"]]["classname"] = o["classname"]
per_class[o["classname"]]["name"] = o["name"]
if o["node_id"] not in per_node:
per_node[o["node_id"]] = copy.deepcopy(base)
per_node[o["node_id"]]["node_id"] = o["node_id"]
for counter in counters:
per_class[o["classname"]][counter]+= o["total"][counter]
per_node[o["node_id"]][counter]+= o["total"][counter]
total[counter]+= o["total"][counter]
# save totals
c.total = total
c.total_per_class = [per_class[k] for k in sorted(per_class.keys())]
c.total_per_node = [per_node[k] for k in sorted(per_node.keys())]
# after everything is complete, update progress to 100% and complete
c.progress = 1.0
c.status = "complete"
c.total_time = abs(time.time() - ts)
if not c.save(): logger.warn("failed to save compare status")
logger.debug("compare complete: %s " % c._id)
except Exception as e:
logger.debug(traceback.format_exc())
fail("unexpected error occurred: %s" % e)
