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SuperCowPowers/workbench | workbench/server/data_store.py | DataStore.all_sample_md5s | def all_sample_md5s(self, type_tag=None):
"""Return a list of all md5 matching the type_tag ('exe','pdf', etc).
Args:
type_tag: the type of sample.
Returns:
a list of matching samples.
"""
if type_tag:
cursor = self.database[self.sample_coll... | python | def all_sample_md5s(self, type_tag=None):
"""Return a list of all md5 matching the type_tag ('exe','pdf', etc).
Args:
type_tag: the type of sample.
Returns:
a list of matching samples.
"""
if type_tag:
cursor = self.database[self.sample_coll... | [
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SuperCowPowers/workbench | workbench/server/data_store.py | DataStore.clear_worker_output | def clear_worker_output(self):
"""Drops all of the worker output collections"""
print 'Dropping all of the worker output collections... Whee!'
# Get all the collections in the workbench database
all_c = self.database.collection_names()
# Remove collections that we don't... | python | def clear_worker_output(self):
"""Drops all of the worker output collections"""
print 'Dropping all of the worker output collections... Whee!'
# Get all the collections in the workbench database
all_c = self.database.collection_names()
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SuperCowPowers/workbench | workbench/server/data_store.py | DataStore.periodic_ops | def periodic_ops(self):
"""Run periodic operations on the the data store.
Operations like making sure collections are capped and indexes are set up.
"""
# Only run every 30 seconds
if (time.time() - self.last_ops_run) < 30:
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... | python | def periodic_ops(self):
"""Run periodic operations on the the data store.
Operations like making sure collections are capped and indexes are set up.
"""
# Only run every 30 seconds
if (time.time() - self.last_ops_run) < 30:
return
try:
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SuperCowPowers/workbench | workbench/server/data_store.py | DataStore.to_unicode | def to_unicode(self, s):
"""Convert an elementary datatype to unicode.
Args:
s: the datatype to be unicoded.
Returns:
Unicoded data.
"""
# Fixme: This is total horseshit
if isinstance(s, unicode):
return s
if isinstance(s, st... | python | def to_unicode(self, s):
"""Convert an elementary datatype to unicode.
Args:
s: the datatype to be unicoded.
Returns:
Unicoded data.
"""
# Fixme: This is total horseshit
if isinstance(s, unicode):
return s
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SuperCowPowers/workbench | workbench/server/data_store.py | DataStore.data_to_unicode | def data_to_unicode(self, data):
"""Recursively convert a list or dictionary to unicode.
Args:
data: The data to be unicoded.
Returns:
Unicoded data.
"""
if isinstance(data, dict):
return {self.to_unicode(k): self.to_unicode(v) for k, v in da... | python | def data_to_unicode(self, data):
"""Recursively convert a list or dictionary to unicode.
Args:
data: The data to be unicoded.
Returns:
Unicoded data.
"""
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SuperCowPowers/workbench | workbench/workers/timeout_corner/swf_meta.py | SWFMeta.execute | def execute(self, input_data):
# Spin up SWF class
swf = SWF()
# Get the raw_bytes
raw_bytes = input_data['sample']['raw_bytes']
# Parse it
swf.parse(StringIO(raw_bytes))
# Header info
head = swf.header
output = {'versio... | python | def execute(self, input_data):
# Spin up SWF class
swf = SWF()
# Get the raw_bytes
raw_bytes = input_data['sample']['raw_bytes']
# Parse it
swf.parse(StringIO(raw_bytes))
# Header info
head = swf.header
output = {'versio... | [
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tag_map = {tag.name:index for tag,index in enumerate(swf.tags)}
# FileAttribute Info
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SuperCowPowers/workbench | workbench/clients/client_helper.py | grab_server_args | def grab_server_args():
"""Grab server info from configuration file"""
workbench_conf = ConfigParser.ConfigParser()
config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'config.ini')
workbench_conf.read(config_path)
server = workbench_conf.get('workbench', 'server_uri')
p... | python | def grab_server_args():
"""Grab server info from configuration file"""
workbench_conf = ConfigParser.ConfigParser()
config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'config.ini')
workbench_conf.read(config_path)
server = workbench_conf.get('workbench', 'server_uri')
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kidig/django-mailjet | django_mailjet/backends.py | MailjetBackend._make_attachment | def _make_attachment(self, attachment, str_encoding=None):
"""Returns EmailMessage.attachments item formatted for sending with Mailjet
Returns mailjet_dict, is_inline_image
"""
is_inline_image = False
if isinstance(attachment, MIMEBase):
name = attachment.get_filenam... | python | def _make_attachment(self, attachment, str_encoding=None):
"""Returns EmailMessage.attachments item formatted for sending with Mailjet
Returns mailjet_dict, is_inline_image
"""
is_inline_image = False
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SuperCowPowers/workbench | workbench/server/els_indexer.py | ELSIndexer.index_data | def index_data(self, data, index_name, doc_type):
"""Take an arbitrary dictionary of data and index it with ELS.
Args:
data: data to be Indexed. Should be a dictionary.
index_name: Name of the index.
doc_type: The type of the document.
Raises:
Ru... | python | def index_data(self, data, index_name, doc_type):
"""Take an arbitrary dictionary of data and index it with ELS.
Args:
data: data to be Indexed. Should be a dictionary.
index_name: Name of the index.
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SuperCowPowers/workbench | workbench/server/els_indexer.py | ELSIndexer.search | def search(self, index_name, query):
"""Search the given index_name with the given ELS query.
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index_name: Name of the Index
query: The string to be searched.
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List of results.
Raises:
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"""Search the given index_name with the given ELS query.
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index_name: Name of the Index
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SuperCowPowers/workbench | workbench/server/els_indexer.py | ELSStubIndexer.index_data | def index_data(self, data, index_name, doc_type):
"""Index data in Stub Indexer."""
print 'ELS Stub Indexer getting called...'
print '%s %s %s %s' % (self, data, index_name, doc_type) | python | def index_data(self, data, index_name, doc_type):
"""Index data in Stub Indexer."""
print 'ELS Stub Indexer getting called...'
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SuperCowPowers/workbench | workbench/workers/pe_deep_sim.py | PEDeepSim.execute | def execute(self, input_data):
''' Execute method '''
my_ssdeep = input_data['meta_deep']['ssdeep']
my_md5 = input_data['meta_deep']['md5']
# For every PE sample in the database compute my ssdeep fuzzy match
sample_set = self.workbench.generate_sample_set('exe')
results ... | python | def execute(self, input_data):
''' Execute method '''
my_ssdeep = input_data['meta_deep']['ssdeep']
my_md5 = input_data['meta_deep']['md5']
# For every PE sample in the database compute my ssdeep fuzzy match
sample_set = self.workbench.generate_sample_set('exe')
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SuperCowPowers/workbench | workbench/workers/help_formatter.py | HelpFormatter.execute | def execute(self, input_data):
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input_data = input_data['help_base']
type_tag = input_data['type_tag']
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input_data = input_data['help_base']
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SuperCowPowers/workbench | workbench/server/workbench_server.py | run | def run():
""" Run the workbench server """
# Load the configuration file relative to this script location
config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'config.ini')
workbench_conf = ConfigParser.ConfigParser()
config_ini = workbench_conf.read(config_path)
if not conf... | python | def run():
""" Run the workbench server """
# Load the configuration file relative to this script location
config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'config.ini')
workbench_conf = ConfigParser.ConfigParser()
config_ini = workbench_conf.read(config_path)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.store_sample | def store_sample(self, input_bytes, filename, type_tag):
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Args:
input_bytes: the actual bytes of the sample e.g. f.read()
filename: name of the file (used purely as meta data not for lookup)
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input_bytes: the actual bytes of the sample e.g. f.read()
filename: name of the file (used purely as meta data not for lookup)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.get_sample | def get_sample(self, md5):
""" Get a sample from the DataStore.
Args:
md5: the md5 of the sample
Returns:
A dictionary of meta data about the sample which includes
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Raises:
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""" Get a sample from the DataStore.
Args:
md5: the md5 of the sample
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A dictionary of meta data about the sample which includes
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md5: the md5 of the sample
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.is_sample_set | def is_sample_set(self, md5):
""" Does the md5 represent a sample_set?
Args:
md5: the md5 of the sample_set
Returns:
True/False
"""
try:
self.get_sample_set(md5)
return True
except WorkBench.DataNotFound:
... | python | def is_sample_set(self, md5):
""" Does the md5 represent a sample_set?
Args:
md5: the md5 of the sample_set
Returns:
True/False
"""
try:
self.get_sample_set(md5)
return True
except WorkBench.DataNotFound:
... | [
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.get_sample_window | def get_sample_window(self, type_tag, size):
""" Get a sample from the DataStore.
Args:
type_tag: the type of samples ('pcap','exe','pdf')
size: the size of the window in MegaBytes (10 = 10MB)
Returns:
A sample_set handle which represents t... | python | def get_sample_window(self, type_tag, size):
""" Get a sample from the DataStore.
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type_tag: the type of samples ('pcap','exe','pdf')
size: the size of the window in MegaBytes (10 = 10MB)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.combine_samples | def combine_samples(self, md5_list, filename, type_tag):
"""Combine samples together. This may have various use cases the most significant
involving a bunch of sample 'chunks' got uploaded and now we combine them together
Args:
md5_list: The list of md5s to combine, orde... | python | def combine_samples(self, md5_list, filename, type_tag):
"""Combine samples together. This may have various use cases the most significant
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md5_list: The list of md5s to combine, orde... | [
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.stream_sample | def stream_sample(self, md5, kwargs=None):
""" Stream the sample by giving back a generator, typically used on 'logs'.
Args:
md5: the md5 of the sample
kwargs: a way of specifying subsets of samples (None for all)
max_rows: the maximum number of ro... | python | def stream_sample(self, md5, kwargs=None):
""" Stream the sample by giving back a generator, typically used on 'logs'.
Args:
md5: the md5 of the sample
kwargs: a way of specifying subsets of samples (None for all)
max_rows: the maximum number of ro... | [
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.get_dataframe | def get_dataframe(self, md5, compress='lz4'):
"""Return a dataframe from the DataStore. This is just a convenience method
that uses get_sample internally.
Args:
md5: the md5 of the dataframe
compress: compression to use: (defaults to 'lz4' but can be set t... | python | def get_dataframe(self, md5, compress='lz4'):
"""Return a dataframe from the DataStore. This is just a convenience method
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Args:
md5: the md5 of the dataframe
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.guess_type_tag | def guess_type_tag(self, input_bytes, filename):
""" Try to guess the type_tag for this sample """
mime_to_type = {'application/jar': 'jar',
'application/java-archive': 'jar',
'application/octet-stream': 'data',
'application/pdf': '... | python | def guess_type_tag(self, input_bytes, filename):
""" Try to guess the type_tag for this sample """
mime_to_type = {'application/jar': 'jar',
'application/java-archive': 'jar',
'application/octet-stream': 'data',
'application/pdf': '... | [
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.add_tags | def add_tags(self, md5, tags):
"""Add tags to this sample"""
if not tags: return
tag_set = set(self.get_tags(md5)) if self.get_tags(md5) else set()
if isinstance(tags, str):
tags = [tags]
for tag in tags:
tag_set.add(tag)
self.data_store.store_work... | python | def add_tags(self, md5, tags):
"""Add tags to this sample"""
if not tags: return
tag_set = set(self.get_tags(md5)) if self.get_tags(md5) else set()
if isinstance(tags, str):
tags = [tags]
for tag in tags:
tag_set.add(tag)
self.data_store.store_work... | [
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.set_tags | def set_tags(self, md5, tags):
"""Set the tags for this sample"""
if isinstance(tags, str):
tags = [tags]
tag_set = set(tags)
self.data_store.store_work_results({'tags': list(tag_set)}, 'tags', md5) | python | def set_tags(self, md5, tags):
"""Set the tags for this sample"""
if isinstance(tags, str):
tags = [tags]
tag_set = set(tags)
self.data_store.store_work_results({'tags': list(tag_set)}, 'tags', md5) | [
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.get_tags | def get_tags(self, md5):
"""Get tags for this sample"""
tag_data = self.data_store.get_work_results('tags', md5)
return tag_data['tags'] if tag_data else None | python | def get_tags(self, md5):
"""Get tags for this sample"""
tag_data = self.data_store.get_work_results('tags', md5)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.index_sample | def index_sample(self, md5, index_name):
""" Index a stored sample with the Indexer.
Args:
md5: the md5 of the sample
index_name: the name of the index
Returns:
Nothing
"""
generator = self.stream_sample(md5)
for row... | python | def index_sample(self, md5, index_name):
""" Index a stored sample with the Indexer.
Args:
md5: the md5 of the sample
index_name: the name of the index
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.index_worker_output | def index_worker_output(self, worker_name, md5, index_name, subfield):
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worker_name: 'strings', 'pe_features', whatever
md5: the md5 of the sample
index_name: the name of the index
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.add_node | def add_node(self, node_id, name, labels):
""" Add a node to the graph with name and labels.
Args:
node_id: the unique node_id e.g. 'www.evil4u.com'
name: the display name of the node e.g. 'evil4u'
labels: a list of labels e.g. ['domain','evil']
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.add_rel | def add_rel(self, source_id, target_id, rel):
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source_id: the unique node_id of the source
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.clear_db | def clear_db(self):
""" Clear the Main Database of all samples and worker output.
Args:
None
Returns:
Nothing
"""
self.data_store.clear_db()
# Have the plugin manager reload all the plugins
self.plugin_manager.load_all_plug... | python | def clear_db(self):
""" Clear the Main Database of all samples and worker output.
Args:
None
Returns:
Nothing
"""
self.data_store.clear_db()
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.clear_worker_output | def clear_worker_output(self):
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Args:
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Returns:
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"""
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# Have the plugin manager reload all the plugins
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.work_request | def work_request(self, worker_name, md5, subkeys=None):
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Args:
worker_name: 'strings', 'pe_features', whatever
md5: the md5 of the sample (or sample_set!)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.set_work_request | def set_work_request(self, worker_name, sample_set, subkeys=None):
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worker_name: 'strings', 'pe_features', whatever
sample_set: the md5 of a sample_set in the Workbench data store
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""" Make a work request for an existing stored sample (or sample_set).
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worker_name: 'strings', 'pe_features', whatever
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.store_sample_set | def store_sample_set(self, md5_list):
""" Store a sample set (which is just a list of md5s).
Note: All md5s must already be in the data store.
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md5_list: a list of the md5s in this set (all must exist in data store)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.generate_sample_set | def generate_sample_set(self, tags=None):
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The sample_set of those samples matching the tags... | python | def generate_sample_set(self, tags=None):
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.help | def help(self, topic=None):
""" Returns the formatted, colored help """
if not topic:
topic = 'workbench'
# It's possible to ask for help on something that doesn't exist
# so we'll catch the exception and push back an object that
# indicates we didn't find what they ... | python | def help(self, topic=None):
""" Returns the formatted, colored help """
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._help_workbench | def _help_workbench(self):
""" Help on Workbench """
help = '%sWelcome to Workbench Help:%s' % (color.Yellow, color.Normal)
help += '\n\t%s- workbench.help(\'basic\') %s for getting started help' % (color.Green, color.LightBlue)
help += '\n\t%s- workbench.help(\'workers\') %s for help on... | python | def _help_workbench(self):
""" Help on Workbench """
help = '%sWelcome to Workbench Help:%s' % (color.Yellow, color.Normal)
help += '\n\t%s- workbench.help(\'basic\') %s for getting started help' % (color.Green, color.LightBlue)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._help_basic | def _help_basic(self):
""" Help for Workbench Basics """
help = '%sWorkbench: Getting started...' % (color.Yellow)
help += '\n%sStore a sample into Workbench:' % (color.Green)
help += '\n\t%s$ workbench.store_sample(raw_bytes, filename, type_tag)' % (color.LightBlue)
help += '\... | python | def _help_basic(self):
""" Help for Workbench Basics """
help = '%sWorkbench: Getting started...' % (color.Yellow)
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._help_commands | def _help_commands(self):
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... | python | def _help_commands(self):
""" Help on all the available commands """
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._help_workers | def _help_workers(self):
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench.list_all_commands | def list_all_commands(self):
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._store_information | def _store_information(self):
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._new_plugin | def _new_plugin(self, plugin):
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._store_work_results | def _store_work_results(self, results, collection, md5):
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._get_work_results | def _get_work_results(self, collection, md5):
""" Internal: Method for fetching work results."""
results = self.data_store.get_work_results(collection, md5)
if not results:
raise WorkBench.DataNotFound(md5 + ': Data/Sample not found...')
return {collection: results} | python | def _get_work_results(self, collection, md5):
""" Internal: Method for fetching work results."""
results = self.data_store.get_work_results(collection, md5)
if not results:
raise WorkBench.DataNotFound(md5 + ': Data/Sample not found...')
return {collection: results} | [
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._work_chain_mod_time | def _work_chain_mod_time(self, worker_name):
""" Internal: We compute a modification time of a work chain.
Returns:
The newest modification time of any worker in the work chain.
"""
# Bottom out on sample, info or tags
if worker_name=='sample' or worker_name... | python | def _work_chain_mod_time(self, worker_name):
""" Internal: We compute a modification time of a work chain.
Returns:
The newest modification time of any worker in the work chain.
"""
# Bottom out on sample, info or tags
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SuperCowPowers/workbench | workbench/server/workbench_server.py | WorkBench._recursive_work_resolver | def _recursive_work_resolver(self, worker_name, md5):
""" Internal: Input dependencies are recursively backtracked, invoked and then
passed down the pipeline until getting to the requested worker. """
# Looking for the sample?
if worker_name == 'sample':
return self.g... | python | def _recursive_work_resolver(self, worker_name, md5):
""" Internal: Input dependencies are recursively backtracked, invoked and then
passed down the pipeline until getting to the requested worker. """
# Looking for the sample?
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.load_sample | def load_sample(self, file_path, tags=None):
"""Load a sample (or samples) into workbench
Args:
file_path: path to a file or directory
tags (optional): a list of tags for the sample/samples ['bad','aptz13']
Returns:
The list of md5s for all... | python | def load_sample(self, file_path, tags=None):
"""Load a sample (or samples) into workbench
Args:
file_path: path to a file or directory
tags (optional): a list of tags for the sample/samples ['bad','aptz13']
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.pivot | def pivot(self, md5, tag=''):
"""Pivot on an md5 (md5 can be a single sample or a sample_set)
Args:
md5: The md5 can be a single sample or a sample_set
tags (optional): a tag for the sample (for the prompt)
Returns:
Nothing but it's sets th... | python | def pivot(self, md5, tag=''):
"""Pivot on an md5 (md5 can be a single sample or a sample_set)
Args:
md5: The md5 can be a single sample or a sample_set
tags (optional): a tag for the sample (for the prompt)
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.tags | def tags(self):
'''Display tag information for all samples in database'''
tags = self.workbench.get_all_tags()
if not tags:
return
tag_df = pd.DataFrame(tags)
tag_df = self.vectorize(tag_df, 'tags')
print '\n%sSamples in Database%s' % (color.LightPurple, color... | python | def tags(self):
'''Display tag information for all samples in database'''
tags = self.workbench.get_all_tags()
if not tags:
return
tag_df = pd.DataFrame(tags)
tag_df = self.vectorize(tag_df, 'tags')
print '\n%sSamples in Database%s' % (color.LightPurple, color... | [
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.pull_df | def pull_df(self, md5):
"""Wrapper for the Workbench get_dataframe method
Args:
md5: pull the dataframe identified by this md5
Returns:
The uncompressed/unserialized dataframe
"""
try:
_packed_df = self.workbench.get_dataframe(m... | python | def pull_df(self, md5):
"""Wrapper for the Workbench get_dataframe method
Args:
md5: pull the dataframe identified by this md5
Returns:
The uncompressed/unserialized dataframe
"""
try:
_packed_df = self.workbench.get_dataframe(m... | [
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.vectorize | def vectorize(self, df, column_name):
"""Vectorize a column in the dataframe"""
vec_df = df[column_name].str.join(sep='-').str.get_dummies(sep='-')
return vec_df | python | def vectorize(self, df, column_name):
"""Vectorize a column in the dataframe"""
vec_df = df[column_name].str.join(sep='-').str.get_dummies(sep='-')
return vec_df | [
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.flatten | def flatten(self, df, column_name):
"""Flatten a column in the dataframe that contains lists"""
_exp_list = [[md5, x] for md5, value_list in zip(df['md5'], df[column_name]) for x in value_list]
return pd.DataFrame(_exp_list, columns=['md5',column_name]) | python | def flatten(self, df, column_name):
"""Flatten a column in the dataframe that contains lists"""
_exp_list = [[md5, x] for md5, value_list in zip(df['md5'], df[column_name]) for x in value_list]
return pd.DataFrame(_exp_list, columns=['md5',column_name]) | [
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.top_corr | def top_corr(self, df):
"""Give aggregation counts and correlations"""
tag_freq = df.sum()
tag_freq.sort(ascending=False)
corr = df.corr().fillna(1)
corr_dict = corr.to_dict()
for tag, count in tag_freq.iteritems():
print ' %s%s: %s%s%s (' % (color.Green, t... | python | def top_corr(self, df):
"""Give aggregation counts and correlations"""
tag_freq = df.sum()
tag_freq.sort(ascending=False)
corr = df.corr().fillna(1)
corr_dict = corr.to_dict()
for tag, count in tag_freq.iteritems():
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.search | def search(self, tags=None):
"""Wrapper for the Workbench search method
Args:
tags: a single tag 'pcap' or a list of tags to search for ['bad','aptz13']
Returns:
A sample_set that contains the md5s for all matching samples
"""
if isinstance... | python | def search(self, tags=None):
"""Wrapper for the Workbench search method
Args:
tags: a single tag 'pcap' or a list of tags to search for ['bad','aptz13']
Returns:
A sample_set that contains the md5s for all matching samples
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.versions | def versions(self):
"""Announce Versions of CLI and Server
Args: None
Returns:
The running versions of both the CLI and the Workbench Server
"""
print '%s<<< Workbench CLI Version %s >>>%s' % (color.LightBlue, self.version, color.Normal)
print self... | python | def versions(self):
"""Announce Versions of CLI and Server
Args: None
Returns:
The running versions of both the CLI and the Workbench Server
"""
print '%s<<< Workbench CLI Version %s >>>%s' % (color.LightBlue, self.version, color.Normal)
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell.run | def run(self):
''' Running the workbench CLI '''
# Announce versions
self.versions()
# Sample/Tag info and Help
self.tags()
print '\n%s' % self.workbench.help('cli')
# Now that we have the Workbench connection spun up, we register some stuff
# with the ... | python | def run(self):
''' Running the workbench CLI '''
# Announce versions
self.versions()
# Sample/Tag info and Help
self.tags()
print '\n%s' % self.workbench.help('cli')
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell._connect | def _connect(self, server_info):
"""Connect to the workbench server"""
# First we do a temp connect with a short heartbeat
_tmp_connect = zerorpc.Client(timeout=300, heartbeat=2)
_tmp_connect.connect('tcp://'+server_info['server']+':'+server_info['port'])
try:
_tmp_c... | python | def _connect(self, server_info):
"""Connect to the workbench server"""
# First we do a temp connect with a short heartbeat
_tmp_connect = zerorpc.Client(timeout=300, heartbeat=2)
_tmp_connect.connect('tcp://'+server_info['server']+':'+server_info['port'])
try:
_tmp_c... | [
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SuperCowPowers/workbench | workbench_apps/workbench_cli/workbench_shell.py | WorkbenchShell._progress_print | def _progress_print(self, sent, total):
"""Progress print show the progress of the current upload with a neat progress bar
Credits: http://redino.net/blog/2013/07/display-a-progress-bar-in-console-using-python/
"""
percent = min(int(sent*100.0/total), 100)
sys.stdout.write('\r... | python | def _progress_print(self, sent, total):
"""Progress print show the progress of the current upload with a neat progress bar
Credits: http://redino.net/blog/2013/07/display-a-progress-bar-in-console-using-python/
"""
percent = min(int(sent*100.0/total), 100)
sys.stdout.write('\r... | [
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaConfig.store | def store(self, name, value, atype, new_name=None, multiplier=None, allowed_values=None):
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return int(_val) | python | def multi_session(self):
''' convert the multi_session param a number '''
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager._fetch_transfer_spec | def _fetch_transfer_spec(self, node_action, token, bucket_name, paths):
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager.upload_directory | def upload_directory(self, directory, bucket, key, transfer_config=None, subscribers=None):
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check_io_access(directory, os.R_OK)
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager.download_directory | def download_directory(self, bucket, key, directory, transfer_config=None, subscribers=None):
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager.upload | def upload(self, fileobj, bucket, key, transfer_config=None, subscribers=None):
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager.download | def download(self, bucket, key, fileobj, transfer_config=None, subscribers=None):
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager.set_log_details | def set_log_details(aspera_log_path=None,
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set the internal aspera sdk activity - for debug purposes '''
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''' set the aspera log path - used by th Ascp process
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager._validate_args | def _validate_args(self, args):
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assert(args.bucket)
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''' validate the user arguments '''
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager._queue_task | def _queue_task(self, bucket, file_pair_list, transfer_config, subscribers, direction):
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config = transfer_config if transfer_config else self._transfer_config
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferManager._shutdown | def _shutdown(self, cancel, cancel_msg, exc_type=CancelledError):
''' Internal shutdown used by 'shutdown' method above '''
if cancel:
# Cancel all in-flight transfers if requested, before waiting
# for them to complete.
self._coordinator_controller.cancel(cancel_msg... | python | def _shutdown(self, cancel, cancel_msg, exc_type=CancelledError):
''' Internal shutdown used by 'shutdown' method above '''
if cancel:
# Cancel all in-flight transfers if requested, before waiting
# for them to complete.
self._coordinator_controller.cancel(cancel_msg... | [
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferCoordinatorController.cleanup | def cleanup(self):
''' Stop backgroud thread and cleanup resources '''
self._processing_stop = True
self._wakeup_processing_thread()
self._processing_stopped_event.wait(3) | python | def cleanup(self):
''' Stop backgroud thread and cleanup resources '''
self._processing_stop = True
self._wakeup_processing_thread()
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferCoordinatorController.tracked_coordinator_count | def tracked_coordinator_count(self, count_ascps=False):
''' count the number of cooridnators currently being processed
or count the number of ascps currently being used '''
with self._lock:
_count = 0
if count_ascps:
for _coordinator in self._tracked_trans... | python | def tracked_coordinator_count(self, count_ascps=False):
''' count the number of cooridnators currently being processed
or count the number of ascps currently being used '''
with self._lock:
_count = 0
if count_ascps:
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferCoordinatorController._queue_task | def _queue_task(self, args):
''' add transfer to waiting queue if possible
then notify the background thread to process it '''
if self._cancel_called:
raise AsperaTransferQueueError("Cancel already called")
elif self._wait_called:
raise AsperaTransferQueueErro... | python | def _queue_task(self, args):
''' add transfer to waiting queue if possible
then notify the background thread to process it '''
if self._cancel_called:
raise AsperaTransferQueueError("Cancel already called")
elif self._wait_called:
raise AsperaTransferQueueErro... | [
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferCoordinatorController.remove_aspera_coordinator | def remove_aspera_coordinator(self, transfer_coordinator):
''' remove entry from the waiting waiting
or remove item from processig queue and add to processed quque
notify background thread as it may be able to process watiign requests
'''
# usually called on processing co... | python | def remove_aspera_coordinator(self, transfer_coordinator):
''' remove entry from the waiting waiting
or remove item from processig queue and add to processed quque
notify background thread as it may be able to process watiign requests
'''
# usually called on processing co... | [
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IBM/ibm-cos-sdk-python-s3transfer | ibm_s3transfer/aspera/manager.py | AsperaTransferCoordinatorController.append_waiting_queue | def append_waiting_queue(self, transfer_coordinator):
''' append item to waiting queue '''
logger.debug("Add to waiting queue count=%d" % self.waiting_coordinator_count())
with self._lockw:
self._waiting_transfer_coordinators.append(transfer_coordinator) | python | def append_waiting_queue(self, transfer_coordinator):
''' append item to waiting queue '''
logger.debug("Add to waiting queue count=%d" % self.waiting_coordinator_count())
with self._lockw:
self._waiting_transfer_coordinators.append(transfer_coordinator) | [
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