def main(self):
logger.initialize("./")
self.initMarkovChain()
self.loadSeenDB()
self.joinIRC()
self.save_timer = Timer(self.SAVE_TIME, self.handleSaveDatabasesTimer)
self.save_timer.start()
# Loop forever, parsing input text
while True:
try:
recv = self.irc.readlines()
except irc.ConnectionClosedException:
logging.warning(WARNING + "Connection closed: Trying to reconnect in 5 seconds...")
time.sleep(5)
self.joinIRC()
continue
for line in recv:
logging.debug(line)
# strip whitespace and split into words
words = string.rstrip(line)
words = string.split(words)
if words[0]=="PING":
self.irc.pong(words[1])
elif words[1] == 'PRIVMSG':
self.parsePrivMessage(line)
elif words[1] == "MODE":
self.parseModeMessage(words)
elif words[1] == 'PART' or words[1] == 'JOIN':
self.handlePartJoin(words)
def evaluate_experiment(_run):
log.initialize(_run)
new_cfg = _run.config
set_device(new_cfg)
experiment = new_cfg['experiment']
# quick fix for last saved model
num_models = new_cfg.get('last_x', 1)
model_paths = log.Logger.get_all_model_paths(experiment)
model_paths = model_paths[-num_models:]
cfg_path = log.Logger.get_cfg_path(experiment)
with open(cfg_path, 'r') as f:
cfg = json.load(f)
# overwrite cfg
# WARNING this means we are using a config that has not been
# filled with default values
cfg.update(new_cfg)
set_device(cfg)
# TODO
for model_path in model_paths:
score = evaluate_checkpoint_on(model_path, new_cfg['validation'], _run)
log_score(score, _run)
print(format_result(score))
return True
def setUp(self):
logger.initialize(unit_test=True, level=VERBOSE)
self.library = SeriesInfo(rtnDict=True)
self.library.args = self.library.options.parser.parse_args(
["/usr/local/bin/episode.py", "--tvdb", "--so"])
def setUp(self):
TRACE = 5
VERBOSE = 15
logger.initialize(unit_test=True, level=INFO)
self.library = FileParser()
args = self.library.options.parser.parse_args('--error')
def setUp(self):
TRACE = 5
VERBOSE = 15
logger.initialize(unit_test=True, level=INFO)
self.library = FileParser()
args = self.library.options.parser.parse_args('--error')
def setUp(self): logger.initialize(unit_test=True, level=VERBOSE) self.library = SeriesInfo(rtnDict=True) self.library.args = self.library.options.parser.parse_args(["/usr/local/bin/episode.py", "--tvdb", "--so"] )
def setUp(self):
TRACE = 5
VERBOSE = 15
logger.initialize(unit_test=True, level=INFO)
# logger.start(level=ERROR)
self.library = FileParser()
def setUp(self):
TRACE = 5
VERBOSE = 15
logger.initialize(unit_test=True, level=VERBOSE)
# logger.start(level=ERROR)
self.library = FileParser()
def evaluate_checkpoint(_run):
log.initialize(_run)
cfg = _run.config
set_device(cfg)
validation_cfg = cfg['validation']
restore_checkpoint_cfg = cfg['restore_checkpoint']
model_update_cfg = cfg.get('model', {})
scores = evaluate_checkpoint_on(restore_checkpoint_cfg, validation_cfg,
_run, model_update_cfg)
log_score(scores, _run, "val_")
return format_result(scores)
def main():
"""
Initializes the environment for a new automail bot, and schedules it to run
as specified in the settings module.
"""
logger.initialize()
logger.log("New automail bot initialized")
send_interval = settings.SEND_INTERVAL
sleep_time = settings.SLEEP_TIME
while True:
bot.routine()
current_dt = datetime.datetime.now()
logger.log("Going on standby at {}.{}.{}.{}.{}.{}".format(current_dt.year,
current_dt.month,
current_dt.day,
current_dt.hour,
current_dt.minute,
current_dt.second))
next_dt = current_dt + datetime.timedelta(hours=send_interval)
while datetime.datetime.now() < next_dt:
time.sleep(sleep_time)
def main(_run):
# initialize logger after observers are appended
log.initialize(_run)
cfg = _run.config
set_device(cfg)
train_cfg = cfg['training']
validation_cfg = cfg.get('validation')
checkpoint_frequency = train_cfg['checkpoint_frequency']
restore_checkpoint_cfg = train_cfg['restore_checkpoint']
max_epochs = train_cfg['epochs']
model_files = run_train(train_cfg['dataloader'], train_cfg['model'],
train_cfg['scheduler'], train_cfg['optimizer'],
train_cfg['losses'], validation_cfg,
checkpoint_frequency, restore_checkpoint_cfg,
max_epochs, _run)
if 'test' in cfg:
test_dataset_cfg = cfg['test']
score = evaluate_checkpoint_on(test_dataset_cfg, model_files[-1])
log_result(score, _run)
return format_result(score)
else:
return True
def __init__(self,
input_dir: str,
output_dir: str,
project_name: str,
main_file_rel_path: str,
binary_compiler_type: str = "",
binary_compiler_version: str = None,
binary_compiler_flags: list = None,
save_combinations_folders: bool = False,
is_make_file: bool = False,
makefile_commands: list = None,
makefile_exe_folder_rel_path: str = "",
makefile_output_exe_file_name: str = "",
ignored_rel_paths: list = None,
include_dirs_list: list = None,
main_file_parameters: list = None,
slurm_parameters: list = None,
extra_files: list = None,
time_limit: str = None,
slurm_partition=ComparConfig.DEFAULT_SLURM_PARTITION,
test_file_path: str = '',
mode=ComparConfig.MODES[ComparConfig.DEFAULT_MODE],
code_with_markers: bool = False,
clear_db: bool = False,
multiple_combinations: int = 1,
log_level: int = logger.DEFAULT_LOG_LEVEL):
self.db = Database(project_name, mode)
working_directory = os.path.join(output_dir,
self.db.get_project_name())
if mode == ComparMode.CONTINUE:
e.assert_original_files_folder_exists(working_directory)
else:
if os.path.exists(working_directory):
shutil.rmtree(working_directory)
os.makedirs(working_directory, exist_ok=True)
logger.initialize(log_level, working_directory)
logger.info('Starting ComPar execution')
e.assert_rel_path_starts_without_sep(makefile_exe_folder_rel_path)
e.assert_rel_path_starts_without_sep(main_file_rel_path)
if slurm_parameters and len(slurm_parameters) == 1:
slurm_parameters = str(slurm_parameters[0]).split(' ')
e.assert_folder_exist(input_dir)
e.assert_user_json_structure()
if not is_make_file:
e.assert_only_files(input_dir)
if not include_dirs_list:
include_dirs_list = []
if not makefile_commands:
makefile_commands = []
if not binary_compiler_flags:
binary_compiler_flags = []
if not main_file_parameters:
main_file_parameters = []
if not slurm_parameters:
slurm_parameters = ComparConfig.DEFAULT_SLURM_PARAMETERS
if not ignored_rel_paths:
ignored_rel_paths = []
if not test_file_path:
test_file_path = CombinationValidator.UNIT_TEST_DEFAULT_PATH
if not extra_files:
extra_files = []
self.binary_compiler = None
self.__timer = None
self.serial_run_time = {}
self.files_loop_dict = {}
self.main_file_rel_path = main_file_rel_path
self.save_combinations_folders = save_combinations_folders
self.binary_compiler_version = binary_compiler_version
self.ignored_rel_paths = ignored_rel_paths
self.include_dirs_list = include_dirs_list
self.time_limit = time_limit
self.slurm_partition = slurm_partition
self.parallel_jobs_pool_executor = JobExecutor(Compar.NUM_OF_THREADS)
self.mode = mode
self.code_with_markers = code_with_markers
self.clear_db = clear_db
self.multiple_combinations = multiple_combinations
# Unit test
self.test_file_path = test_file_path
e.assert_file_exist(self.test_file_path)
e.assert_test_file_name(os.path.basename(self.test_file_path))
e.assert_test_file_function_name(self.test_file_path)
# Initiate Compar environment
e.assert_forbidden_characters(working_directory)
self.working_directory = working_directory
self.backup_files_dir = os.path.join(working_directory,
ComparConfig.BACKUP_FOLDER_NAME)
self.original_files_dir = os.path.join(
working_directory, ComparConfig.ORIGINAL_FILES_FOLDER_NAME)
if self.mode == ComparMode.CONTINUE:
e.assert_folder_exist(self.original_files_dir)
self.__delete_combination_folder(
os.path.join(working_directory,
self.COMPAR_COMBINATION_FOLDER_NAME))
self.__delete_combination_folder(
os.path.join(working_directory,
self.FINAL_RESULTS_FOLDER_NAME))
self.combinations_dir = os.path.join(
working_directory, ComparConfig.COMBINATIONS_FOLDER_NAME)
self.__create_directories_structure(input_dir)
# Compilers variables
self.relative_c_file_list = self.make_relative_c_file_list(
self.original_files_dir)
if self.code_with_markers:
file_paths = [
file['file_full_path'] for file in
self.make_absolute_file_list(self.original_files_dir)
]
self.remove_optimal_combinations_details(file_paths)
self.binary_compiler_type = binary_compiler_type
self.parallelizers = dict()
for name, ctor in parallelizers.items():
self.parallelizers[name] = ctor(
"",
include_dirs_list=self.include_dirs_list,
extra_files=extra_files)
# Compiler flags
self.user_binary_compiler_flags = binary_compiler_flags
# Makefile
self.is_make_file = is_make_file
self.makefile_commands = makefile_commands
self.makefile_exe_folder_rel_path = makefile_exe_folder_rel_path
self.makefile_output_exe_file_name = makefile_output_exe_file_name
# Main file
self.main_file_parameters = main_file_parameters
# SLURM
self.slurm_parameters = slurm_parameters
# Initialization
if not is_make_file:
self.__initialize_binary_compiler()
self.db.create_collections()
( )
H
H
_H_
.-'-.-'-.
/ \\ #### #### ##### # # ##### #### # #
| | # # # # # # # # # # # #
| .-------'._ #### #### ### # # # ### #### # #
| / / '.' '. \\ # # # # # # # # # # # #
| \\ \\ @ @ / / #### # # ##### # # ##### # # #
| '---------'
| _______| = 2014 =
| .'-+-+-+|
| '.-+-+-+|
| """""" |
'-.__ __.-'
"""''')
import eventloop
import logger
import leds
logger.initialize(args)
loop = eventloop.EventLoop(args.statemachine, args.webserver_port, not args.disable_interbot)
leds.initialize(loop)
loop.start()
logger.close()
sys.exit(loop.exit_value)
.-'-.-'-.
/ \\ #### #### ##### # # ##### #### # #
| | # # # # # # # # # # # #
| .-------'._ #### #### ### # # # ### #### # #
| / / '.' '. \\ # # # # # # # # # # # #
| \\ \\ @ @ / / #### # # ##### # # ##### # # #
| '---------'
| _______| = 2015 =
| .'-+-+-+|
| '.-+-+-+|
| """""" |
'-.__ __.-'
"""''')
import eventloop
import logger
import leds
logger.initialize(args)
loop = eventloop.EventLoop(args.statemachine, args.webserver_port,
not args.disable_interbot)
leds.initialize(loop)
loop.start()
logger.close()
if args.pydev_debug:
pydevd.stoptrace()
sys.exit(loop.exit_value)
def setUp(self):
logger.initialize(unit_test=True, level=INFO)
self.library = FileInfo()
self.kv = {}
def setUp(self):
logger.initialize(unit_test=True, level=INFO)
self.library = FileInfo()
self.kv = {}
def main():
# Initialization
start_date = date()
logger.initialize('.')
bank = DocumentBank(document_class=Movie)
# Fetching stopwords
logging.info('Fetching stop words')
stop_words = utils.stop_words(config.LANGUAGE_STOP_WORDS_PATH)
stop_words.extend(utils.stop_words(config.PROJECT_STOP_WORDS_PATH))
logging.info('Fetched %i stop words' % len(stop_words))
n_movies = config.maxsize if config.READ_ALL_THEN_SHUFFLE else config.MOVIES_TO_CLASSIFY + config.MOVIES_TO_ANALYZE
# Read reviews from disk
n_reviews, movies_reviews = AmazonReviewsParser.from_json(config.AMAZON_REVIEWS_FILE,
meta=config.METADATA_FILE,
max_movies=n_movies)
movies = [Movie(movie_id, movie['title'], [{
'userID': review['reviewer_id'],
'rating': review['score'],
'review': review['review']
} for review in movie['reviews']])
for movie_id, movie in movies_reviews.items()]
# Shuffle the array, so that the movies to classify at the end aren't biased
shuffle(movies)
# Separate movies to add to the bank (and add them to it), and movies to classify afterwards
movies_to_analyze = [movie for movie in movies[:config.MOVIES_TO_ANALYZE]]
movies_to_classify = [movie for movie in movies[-config.MOVIES_TO_CLASSIFY:]]
logging.info('Analyzing %i movies' % len(movies_to_analyze))
bank.add_documents([movie.serialize() for movie in movies_to_analyze])
# First vectorize the dataset
bank.vectorize(stop_words=stop_words, max_features=config.MAX_FEATURES)
# Then extract topics and assign them to movies in the dataset
training_counter = bank.topic_extraction({'rank': config.N_TOPICS, 'beta': config.BETA}, n_words=config.N_TOP_WORDS)
# Train the classifiers with the assigned topics
bank.train_classifiers_fullset(n_jobs=config.N_JOBS,
min_amount_relevant=int(config.MIN_RELEVANCE * len(movies_to_analyze)))
# Retrieving results
topics = bank.shelf['topics']
classification_counter = dict((i, []) for i in range(-1, config.N_TOPICS))
for movie in movies_to_classify:
movie_topics = [topics[topic_id] for topic_id in
bank.classify_document(movie.full_text())]
for topic in movie_topics:
classification_counter[topic.id].append({
'id': movie.id,
'title': movie.title
})
if len(movie_topics):
logging.info('Topics for document: %s: %s' % (movie.title, str(movie_topics)))
else:
classification_counter[-1].append(movie.title)
for topic in classification_counter.keys():
logging.info('Topic #%i: %i movies assigned' % (topic, len(classification_counter[topic])))
logging.info('Managed to classify %i%% of the documents.' %
int((len(movies_to_classify) - len(classification_counter[-1])) / len(movies_to_classify) * 100))
# Writing results to JSON
report_filename = date()
write_report(report_filename, {
'start_date': start_date,
'end_date': date(),
'params': {
'max_reviews': config.MAX_REVIEWS,
'max_features': config.MAX_FEATURES,
'min_relevance': config.MIN_RELEVANCE,
'n_topics': config.N_TOPICS,
'n_reviews': n_reviews,
'n_movies': len(movies),
'n_movies_training': len(movies_to_analyze),
'n_movies_classify': len(movies_to_classify),
'beta': config.BETA,
},
'results': [{
'topic': topics[topic_id].top_words,
'training_movies_in_topic': training_counter[topic_id],
'classification_movies_in_topic': classification_counter[topic_id]
} for topic_id in topics]
})
bank.close()
copyfile('./all.log', './reports/%s.log' % report_filename)
import logger
import reddit
import re
import checklog
from datetime import datetime
### Script arguments ###
parser = argparse.ArgumentParser()
parser.add_argument("subname", help="Name of subreddit")
args = parser.parse_args()
### Config ini vars ###
config = configparser.ConfigParser()
config.read('config.ini')
debug_mode = config['DEFAULT'].getboolean('DebugMode')
logger.initialize(args.subname)
logmsg = logging.getLogger("Rotating_Log")
### Handles main segment ###
def main():
if not re.match(r'^[A-Za-z0-9_]+$', args.subname):
sys.exit("Invalid subreddit name, aborting.")
s = reddit.reddit.subreddit(args.subname)
common.debug_msg('Mod Permission: ' + str(s.user_is_moderator))
if not s.user_is_moderator:
logmsg.critical("[ERROR] Bot check as mod failed, aborting.")
sys.exit("Shutting down due to bot permission issue.")
checklog.check_for_admins(s)
checklog.health_check(s)
if not common.bool_sidebar_queued(s):
_formats_found[_ext] = True
_file_names.append(_file)
for _entry in _formats_found:
if _entry == 'ifo' or _entry == 'bup':
continue
_number_of_formats += 1
if _number_of_formats > 1:
log.info('Possible Dups Found: {}'.format(_root))
for _file in _file_names:
log.info(' FileName: {}'.format(_file))
if __name__ == '__main__':
logger.initialize()
Library.args = Library.cmdoptions.ParseArgs(sys.argv[1:])
if not Library.args.filespec:
Library.args.filespec = [Library.settings.MoviesDir]
if type(Library.args.filespec) != list:
Library.args.filespec = [Library.args.filespec]
library = CheckMovies()
for _lib_path in Library.args.filespec:
if os.path.exists(_lib_path):
library.check_movies(_lib_path)
else:
log.error('Library Not Found: {}'.format(_lib_path))
def logs():
import logger
logger.initialize()
pass
try:
log.verbose('Deleting File as Requested: {}'.format(pathname))
os.remove(pathname)
except:
log.warn('Delete File: Unable to Delete requested file: %s' % (sys.exc_info()[1]))
class _get_out_of_loop(Exception):
pass
if __name__ == "__main__":
logger.initialize()
library = RenameSeries()
Library.args = library.options.parser.parse_args(sys.argv[1:])
log.debug("Parsed command line: {!s}".format(library.args))
log_level = logging.getLevelName(library.args.loglevel.upper())
if library.args.logfile == 'daddyvision.log':
log_file = '{}.log'.format(__pgmname__)
else:
log_file = os.path.expanduser(library.args.logfile)
# If an absolute path is not specified, use the default directory.
if not os.path.isabs(log_file):
def main():
"""
Initialize the environment before the launch of a new automail bot.
"""
logger.initialize()
compose.set_previous(0)