def build_db(connection, filename):
c = connection.cursor()
create_db(c)
with codecs.open(filename, 'r', encoding="utf-8") as f:
s = BMGraphDBSink(connection)
# bmgraph.logger.setLevel(logging.DEBUG)
bmgraph_file.logger.setLevel(logging.INFO)
bmgraph_file.read_file(f, s)
connection.commit()
logger.info("%i rows in the database." % node_count(c))
logger.info("%i node attributes in the database." % node_attribute_count(c))
logger.info("%i edge attributes in the database." % edge_attribute_count(c))
logger.info("%i edges in the database." % edge_count(c))
def build_db(connection, filename):
c = connection.cursor()
create_db(c)
with codecs.open(filename, 'r', encoding="utf-8") as f:
s = BMGraphDBSink(connection)
# bmgraph.logger.setLevel(logging.DEBUG)
bmgraph_file.logger.setLevel(logging.INFO)
bmgraph_file.read_file(f, s)
connection.commit()
logger.info("%i rows in the database." % node_count(c))
logger.info("%i node attributes in the database." %
node_attribute_count(c))
logger.info("%i edge attributes in the database." %
edge_attribute_count(c))
logger.info("%i edges in the database." % edge_count(c))
def simple_get(url):
"""
Attempts to get the content at `url` by making an HTTP GET request.
If the content-type of response is some kind of HTML/XML, return the
text content, otherwise return None.
"""
filename = "{0}.html".format(url.split("/").pop().lower())
filepath = abspath(join(dirname(__file__), "./cache", filename))
file_data = read_file(filepath)
if file_data != None:
return file_data
try:
print("Fetching: {0}...".format(url))
with closing(get(url, stream=True)) as resp:
if is_good_response(resp):
write_cache_file(filepath, resp.content)
return resp.content
else:
return None
except RequestException as e:
log_error('Error during requests to {0} : {1}'.format(url, str(e)))
return None
def get_station_bus_stops(self, station_name):
# get the bus stop codes
# get the interchange code (little more tricky because LTG does not provide it)
bus_stop_codes = []
slugified_station_name = station_name.replace(' ', '-').lower()
r = requests.get(
f'https://landtransportguru.net/{slugified_station_name}-station/')
if r.status_code == 200:
soup = BeautifulSoup(r.content, 'lxml')
table_cell_soup = soup.find_all('td')
for cell_soup in table_cell_soup:
# (1) Find bus stop codes. We need to go through all table cells and see if the first 5 digits are numbers
try:
# checking if the first 5 digits can be ints. If yes, they are the bus stop codes
# just for safety, we'll also check that the "–" character is present
int(cell_soup.text[0:5])
if "–" in cell_soup.text:
stop_code = cell_soup.text[0:5]
# Make sure not to add a None
# Make sure not to add if it's already there
if stop_code and stop_code not in bus_stop_codes:
bus_stop_codes.append(stop_code)
next
except:
pass
# (2) Find if interchange
a_soup = cell_soup.find('a')
if a_soup and "interchange" in a_soup.text .lower():
bus_stop_name = a_soup.text .lower() .replace("interchange", "int").replace(" bus", "").replace(
"temporary", "temp").replace("bukit", "bt") # bukit is hortened to bt in bus stop names
# print(bus_stop_name)
# go through temporary/all_stops_dict.json (or combined) and find the code matching the name
all_bus_stops_dict = read_file('temp/bus', 'all_stops_dict.json')
for bus_stop in all_bus_stops_dict.keys():
if bus_stop_name == all_bus_stops_dict[bus_stop]['name'].lower():
# match found :)
stop_code = all_bus_stops_dict[bus_stop]['code']
if stop_code not in bus_stop_codes:
bus_stop_codes.append(stop_code)
return bus_stop_codes
else:
# return empty list if error
return []
def main(target_dir, tenant):
print_gather_dir_info(target_dir)
for path in list_dir(target_dir, '.js'):
original_content = read_file(path)
replaced_content, number_of_replace = replace_tenant(
original_content, tenant)
if number_of_replace > 0:
print_replace(path, number_of_replace)
write_file(path, replaced_content)
def RecognizeSpeechAndRemoveFile(AUDIO_FILENAME):
#print("Recognize and remove file", AUDIO_FILENAME)
# reading audio
audio = read_file(AUDIO_FILENAME)
delete_file(AUDIO_FILENAME)
# send to WIT.AI
recognize(audio)
def RecognizeSpeechAndRemoveFile(AUDIO_FILENAME):
# reading audio
audio = read_file(AUDIO_FILENAME)
# delete useless file because is already in "audio" variable
delete_file(AUDIO_FILENAME)
# send to WIT.AI
recognize(audio)
time.sleep(3)
def insert_stock_base():
path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
path = unicode(path, 'utf8')
json_str = read_file(path + '/stocknum.json')
stocks = json.loads(json_str)['hah']
sql = ''
startTime = datetime.datetime.now()
logging.info("拼装插入股票基础数据sql语句开始:" + str(startTime))
sql = LOCAL_SQL % ('stock', 'stockCode, stockName', '%s, %s')
values = []
for i in xrange(0, len(stocks)):
stock = stocks[i]
temp = (stock['stockCode'], stock['stockName'])
values.append(temp)
pass
endTime = datetime.datetime.now()
logging.info("拼装插入股票基础数据结束:" + str(endTime) + ", 共耗时：" + str((endTime - startTime).seconds))
insert_many(sql, tuple(values))
pass
def send_request(file_name):
# read file
file_content = file.read_file(file_name)
audio_data = encode_data(file_content)
# construct and send request
url = "http://%s:%s%s" % (host, port, path)
body = {"audio_data": audio_data}
raw_response = requests.post(url, data=json.dumps(body), headers=headers, timeout=180)
# handle response
json_response = None
try:
json_response = raw_response.json()
except Exception as e:
print("file [%s] error: " % file_name, e)
if (json_response["success"]):
return json_response["result"]
else:
print("file [%s] failed, message: %s, request_id: %s: " % (file_name, json_response["message"]["global"], json_response["request_id"]))
else:
print "Usage: python generate.py -font <font name> -l <language> -s <size> -a <input alphabet directory>"
exit()
if (sys.argv[3] == "-l"):
lang = sys.argv[4]
else:
print "Usage: python generate.py -font <font name> -l <language> -s <size> -a <input alphabet directory>"
exit()
if (sys.argv[5] == "-s"):
font_size = sys.argv[6]
else:
print "Usage: python generate.py -font <font name> -l <language> -s <size> -a <input alphabet directory>"
exit()
if (sys.argv[7] == "-a"):
alphabet_dir = sys.argv[8]
else:
print "Usage: python generate.py -font <font name> -l <language> -s <size> -a <input alphabet directory>"
exit()
font_string = font_name + " " + lang + " " + font_size
#begin training
draw(font_string, int(font_size), lang, file.read_file(
alphabet_dir)) #reads all fonts in the directory font_dir and trains
train.train(lang)
#training ends
#Comment
try:
answer = 1
while answer < 3 and answer > 0:
answer = int(input("What would you like to do? \n(1) Simple Calculator \n(2) Create / Edit / Read a File \n(3) Nothing \nAnswer: "))
if answer == 1:
print("\nYou chose '1'.")
num1 = float(input("First number: "))
num2 = float(input("Second number: "))
operator = input ("What to do with it: ")
calculator.simple_calculator(num1,num2,operator)
elif answer == 2:
print("\nYou chose '2'.")
option = input("Create, Edit, or Read a file: ")
if option.lower() == "create":
file.create_file()
elif option.lower() == "edit":
file.edit_file()
elif option.lower() == "read":
file.read_file()
else:
print("That is not an option.\n")
else:
print("\nYou chose '3' or a number that is out of range. Bye.")
except:
print("\nYou have entered an invalid answer. Bye.")
from sklearn.feature_extraction.text import TfidfTransformer
from pprint import pprint
from pymongo import MongoClient
import operator
import math
import os
import file
folder_path = os.path.dirname(os.path.realpath(__file__)) + '/pos_terms'
result = {}
raw_datas = []
datas = []
for f in os.listdir(folder_path):
path = os.path.join(folder_path, f)
if os.path.isfile(path) and '.json' in path:
raw_datas += file.read_file(path)
for raw_data in raw_datas:
concat = []
concat = ' '.join(raw_data)
datas.append(concat)
corpus = []
for data in raw_datas:
corpus.append(' '.join(data))
vectorizer = CountVectorizer()
x = vectorizer.fit_transform(corpus)
word = vectorizer.get_feature_names()
transformer = TfidfTransformer()
tfidf = transformer.fit_transform(x)
word = vectorizer.get_feature_names()
exit()
if(sys.argv[3]=="-l"):
lang=sys.argv[4]
else:
print "Usage: python generate.py -font <font name> -l <language> -s <size> -a <input alphabet directory>"
exit()
if(sys.argv[5]=="-s"):
font_size=sys.argv[6]
else:
print "Usage: python generate.py -font <font name> -l <language> -s <size> -a <input alphabet directory>"
exit()
if(sys.argv[7]=="-a"):
alphabet_dir=sys.argv[8]
else:
print "Usage: python generate.py -font <font name> -l <language> -s <size> -a <input alphabet directory>"
exit()
font_string=font_name+" "+lang+" "+font_size
#begin training
draw(font_string,int(font_size),lang,file.read_file(alphabet_dir))#reads all fonts in the directory font_dir and trains
train.train(lang)
#training ends
exit()
if(sys.argv[3]=="-l"):
lang=sys.argv[4]
else:
print "Usage: python generate.py -fd <font directory> -l <language> -a <input alphabet directory>"
exit()
if(sys.argv[5]=="-a"):
alphabet_dir=sys.argv[6]
else:
print "Usage: python generate.py -fd <font directory> -l <language> -a <input alphabet directory>"
exit()
#begin training
#font_dir="/usr/share/fonts/truetype/ttf-bengali-fonts/"
for t in os.walk(font_dir):
for f in t[2]:
if(f.split('.')[1]=="ttf"):
font_file=font_dir+f
print font_file
draw(lang,f,font_file,40,file.read_file(alphabet_dir))#reads all fonts in the directory font_dir and trains
train.train(lang)
#training ends
def all_encoding_stats(file_name):
"""output with default file_name:
Test file: cyphesis_atlas_XML_2000-03-27_no_obj.log
Msg count: 228
uncompressed gzip -9 bzip2 -9
XML 954.97 47.93 33.95
XML2_test 727.00 45.92 34.03
Packed 384.41 36.79 30.84
Bach_beta 478.61 39.11 31.35
Binary1_beta 380.54 38.58 32.26
Binary2_test 236.12 35.22 30.78
Test file: CyphesisClient_fromServerViewpoint2_no_obj.log
Msg count: 716
uncompressed gzip -9 bzip2 -9
XML 832.77 36.76 23.82
XML2_test 632.11 35.03 23.94
Packed 284.41 28.88 23.20
Bach_beta 373.68 31.91 23.28
Binary1_beta 277.63 30.53 24.04
Binary2_test 156.22 28.31 23.62
Test file: cyphesis_atlas_Packed_2001-07-13.log
Msg count: 4768
uncompressed gzip -9 bzip2 -9
XML 1250.59 27.39 14.17
XML2_test 910.63 23.97 13.20
Packed 405.12 17.34 12.67
Bach_beta 544.18 18.72 12.21
Binary1_beta 441.45 22.03 14.34
Binary2_test 260.30 19.02 13.23
"""
print()
print()
print("Test file:",file_name)
global all_msg
xml_codec = codec.get_XML()
#all_msg = xml_codec.decode(open(file_name).read())
all_msg = file.read_file(file_name)
print("Msg count:",len(all_msg))
all_stats = []
#XML size
all_stats.append(calculate_stats(all_msg,xml_codec))
#XML2 size
all_stats.append(calculate_stats(all_msg,codec.get_XML2_test()))
#Packed size
all_stats.append(calculate_stats(all_msg,codec.get_Packed()))
#Bach size
all_stats.append(calculate_stats(all_msg,codec.get_Bach_beta()))
#Binary1_beta size
all_stats.append(calculate_stats(all_msg,codec.get_Binary1_beta()))
#Binary2_test size
all_stats.append(calculate_stats(all_msg,codec.get_Binary2_test()))
## for name in binary2.attribute_type_dict.keys():
## print name
## binary2.discard_name = name
## all_stats.append(calculate_stats(all_msg,codec.get_Binary2_test()))
## all_stats[-1][0] = list(all_stats[-1][0])
## all_stats[-1][0][0] = name
## all_stats.sort(lambda e1,e2:cmp(e1[2][2],e2[2][2]))
print()
filter_types = ("uncompressed", "gzip -9", "bzip2 -9")
print(" %10s %10s %10s" % filter_types)
for stat in all_stats:
print("%-13s %10.2f %10.2f %10.2f" % (
stat[0][0], stat[0][2], stat[1][2], stat[2][2]))
def cam_setup(camidx=0,
roi=None,
flatf=None,
darkf=None,
maskshape='all',
procd=32,
usecam=True,
outdir='./',
verb=0):
"""
Setup IEEE1394 camera using Python's binding for OpenCV. Setup will be
stored in global CAM_CFG dictionary for use by cam_getimage().
@param camidx Camera index
@param roi Region of Interest to use, as (x, y, width, height)
@param flatf Flatfield image to use [file]
@param darkf Darkfield image to use [file]
@param maskshape Shape for processing mask, 'circ' or 'all'
@param procd Bitdepth to process images at (32 or 64)
@param outdir Directory to store stuff to
@param verb Verbosity
"""
global CAM_CFG
if (verb & VERB_M > L_INFO): print "Setting up camera..."
if (procd == 64):
npdtype = np.float64
cvdtype = cv.IPL_DEPTH_64F
else:
npdtype = np.float32
cvdtype = cv.IPL_DEPTH_32F
if (darkf and os.path.isfile(darkf)):
if (verb & VERB_M > L_DEBG): print "Processing dark frames..."
# Hard-link to used files for new cache
newdarkf = pjoin(outdir, CAM_DARKFIELD)
if (os.path.exists(newdarkf)):
os.unlink(newdarkf)
os.link(darkf, newdarkf)
darkim = file.read_file(darkf).astype(npdtype)
CAM_CFG['dark'] = cv.fromarray(darkim)
if (flatf and os.path.isfile(flatf)):
if (verb & VERB_M > L_DEBG): print "Processing flat frame(s)..."
newflatf = pjoin(outdir, CAM_FLATFIELD)
if (os.path.exists(newflatf)):
os.unlink(newflatf)
os.link(flatf, newflatf)
flatim = file.read_file(flatf).astype(npdtype)
CAM_CFG['flat'] = cv.fromarray(flatim)
if (CAM_CFG.has_key('dark')):
cv.Sub(CAM_CFG['flat'], CAM_CFG['dark'], CAM_CFG['flat'])
if (verb & VERB_M > L_XNFO): print "Configuring camera..."
if (not CAM_CFG.has_key('window')):
CAM_CFG['window'] = 'cam_live'
cv.NamedWindow(CAM_CFG['window'], cv.CV_WINDOW_AUTOSIZE)
cv.NamedWindow("cam_histogram", cv.CV_WINDOW_AUTOSIZE)
CAM_CFG['idx'] = camidx
CAM_CFG['roi'] = roi
if (usecam):
CAM_CFG['handle'] = cv.CaptureFromCAM(camidx)
#cv.GetCaptureProperty(CAM_CFG['handle'], cv.CV_CAP_PROP_FPS)
cv.SetCaptureProperty(CAM_CFG['handle'], cv.CV_CAP_PROP_FPS, 60)
else:
CAM_CFG['handle'] = None
if (roi):
CAM_CFG['dshape'] = (roi[2], roi[3])
elif (usecam):
# GetSize returns (width, h), NumPy arrays expect (height, w)
rawframe = cv.QueryFrame(CAM_CFG['handle'])
CAM_CFG['dshape'] = cv.GetSize(rawframe)[::-1]
else:
raise ValueError("Need ROI or camera to determine data shape.")
CAM_CFG['frame'] = cv.CreateImage(CAM_CFG['dshape'][::-1], cvdtype, 1)
if (maskshape == 'circ'):
CAM_CFG['mask'] = im.mk_rad_mask(*CAM_CFG['dshape']) < 1
else:
CAM_CFG['mask'] = np.ones(CAM_CFG['dshape']).astype(np.bool)
CAM_CFG['imask'] = (CAM_CFG['mask'] == False)
file.store_file(pjoin(outdir, CAM_APTMASK),
CAM_CFG['mask'].astype(np.uint8),
clobber=True)
if (verb & VERB_M > L_INFO): print "Camera setup complete..."
cam_getimage(show=True)
from post_details import post_details
browser = webdriver.Chrome('chromedriver.exe')
file = 'main.txt'
username = '******'
password = '******'
url_page = 'https://www.instagram.com/tarbiate_jensi1/'
#login(browser,username,password)
go_to_page(browser, url_page)
print("go_to_page")
if post_of_page(browser, file):
list_of_post = read_file('main.txt')
lenght_of_list = int(len(list_of_post) / 3)
for i in range(lenght_of_list):
print("i= ", i)
counter = 3 * i
load_comments(browser, list_of_post[counter + 1])
post_details(browser, list_of_post[counter], list_of_post[counter + 1],
list_of_post[counter + 2])
print("done")
else:
print("post of page is not find!")
tkn = tag[1].replace('[','').replace(']','').split('\',')
if len(tkn) > 3:
continue
ltype = set()
for t in tkn:
# type-to-tag
typ = t.replace('\'','').strip()
ltag = type2tag.setdefault(typ, set())
ltag.add(ptag)
type2tag[typ] = ltag
# tag-to-type
ltype.add (typ)
tag2type[ptag] = ltype
# tag - group
sgroup = ufile.read_file ('app/resources/semantic-groups.txt')
if sgroup is None:
log.error ('impossible to load the semantic categories - interrupting')
sys.exit()
group2tag = {}
group2type = {}
tag2group = {}
for sg in sgroup:
tkn = sg.strip().split('|')
grp = tkn[0].strip()
typ = tkn[2].strip().lower()
if typ not in type2tag:
continue
# group-to-tag
if typ in type2tag:
ltag = group2tag.setdefault (grp, set())
def cam_setup(camidx=0, roi=None, flatf=None, darkf=None, maskshape='all', procd=32, usecam=True, outdir='./', verb=0):
"""
Setup IEEE1394 camera using Python's binding for OpenCV. Setup will be
stored in global CAM_CFG dictionary for use by cam_getimage().
@param camidx Camera index
@param roi Region of Interest to use, as (x, y, width, height)
@param flatf Flatfield image to use [file]
@param darkf Darkfield image to use [file]
@param maskshape Shape for processing mask, 'circ' or 'all'
@param procd Bitdepth to process images at (32 or 64)
@param outdir Directory to store stuff to
@param verb Verbosity
"""
global CAM_CFG
if (verb&VERB_M > L_INFO): print "Setting up camera..."
if (procd == 64):
npdtype = np.float64
cvdtype = cv.IPL_DEPTH_64F
else:
npdtype = np.float32
cvdtype = cv.IPL_DEPTH_32F
if (darkf and os.path.isfile(darkf)):
if (verb&VERB_M > L_DEBG): print "Processing dark frames..."
# Hard-link to used files for new cache
newdarkf = pjoin(outdir, CAM_DARKFIELD)
if (os.path.exists(newdarkf)):
os.unlink(newdarkf)
os.link(darkf, newdarkf)
darkim = file.read_file(darkf).astype(npdtype)
CAM_CFG['dark'] = cv.fromarray(darkim)
if (flatf and os.path.isfile(flatf)):
if (verb&VERB_M > L_DEBG): print "Processing flat frame(s)..."
newflatf = pjoin(outdir, CAM_FLATFIELD)
if (os.path.exists(newflatf)):
os.unlink(newflatf)
os.link(flatf, newflatf)
flatim = file.read_file(flatf).astype(npdtype)
CAM_CFG['flat'] = cv.fromarray(flatim)
if (CAM_CFG.has_key('dark')):
cv.Sub(CAM_CFG['flat'], CAM_CFG['dark'], CAM_CFG['flat'])
if (verb&VERB_M > L_XNFO): print "Configuring camera..."
if (not CAM_CFG.has_key('window')):
CAM_CFG['window'] = 'cam_live'
cv.NamedWindow(CAM_CFG['window'], cv.CV_WINDOW_AUTOSIZE)
cv.NamedWindow("cam_histogram", cv.CV_WINDOW_AUTOSIZE)
CAM_CFG['idx'] = camidx
CAM_CFG['roi'] = roi
if (usecam):
CAM_CFG['handle'] = cv.CaptureFromCAM(camidx)
#cv.GetCaptureProperty(CAM_CFG['handle'], cv.CV_CAP_PROP_FPS)
cv.SetCaptureProperty(CAM_CFG['handle'], cv.CV_CAP_PROP_FPS, 60)
else:
CAM_CFG['handle'] = None
if (roi):
CAM_CFG['dshape'] = (roi[2], roi[3])
elif (usecam):
# GetSize returns (width, h), NumPy arrays expect (height, w)
rawframe = cv.QueryFrame(CAM_CFG['handle'])
CAM_CFG['dshape'] = cv.GetSize(rawframe)[::-1]
else:
raise ValueError("Need ROI or camera to determine data shape.")
CAM_CFG['frame'] = cv.CreateImage(CAM_CFG['dshape'][::-1], cvdtype, 1)
if (maskshape == 'circ'):
CAM_CFG['mask'] = im.mk_rad_mask(*CAM_CFG['dshape']) < 1
else:
CAM_CFG['mask'] = np.ones(CAM_CFG['dshape']).astype(np.bool)
CAM_CFG['imask'] = (CAM_CFG['mask'] == False)
file.store_file(pjoin(outdir, CAM_APTMASK), CAM_CFG['mask'].astype(np.uint8), clobber=True)
if (verb&VERB_M > L_INFO): print "Camera setup complete..."
cam_getimage(show=True)
#!/bin/python
import sys
from OutWritter import OutWritter
from file import read_file
from PySide2.QtWidgets import QApplication
from PySide2.QtQuick import QQuickView
from PySide2.QtCore import QUrl, QTimer
app = QApplication([])
writter = OutWritter()
view = QQuickView()
url = QUrl("components/list_view.qml")
view.setResizeMode(QQuickView.SizeRootObjectToView)
view.setSource(url)
timer = QTimer()
timer.timeout.connect(lambda: None)
timer.start(100)
list = view.rootObject()
list.setProperty('entries', read_file("./config/bookmarks"))
context = view.rootContext()
context.setContextProperty("out", writter)
view.show()
sys.exit(app.exec_())
def all_encoding_stats(file_name):
"""output with default file_name:
Test file: cyphesis_atlas_XML_2000-03-27_no_obj.log
Msg count: 228
uncompressed gzip -9 bzip2 -9
XML 954.97 47.93 33.95
XML2_test 727.00 45.92 34.03
Packed 384.41 36.79 30.84
Bach_beta 478.61 39.11 31.35
Binary1_beta 380.54 38.58 32.26
Binary2_test 236.12 35.22 30.78
Test file: CyphesisClient_fromServerViewpoint2_no_obj.log
Msg count: 716
uncompressed gzip -9 bzip2 -9
XML 832.77 36.76 23.82
XML2_test 632.11 35.03 23.94
Packed 284.41 28.88 23.20
Bach_beta 373.68 31.91 23.28
Binary1_beta 277.63 30.53 24.04
Binary2_test 156.22 28.31 23.62
Test file: cyphesis_atlas_Packed_2001-07-13.log
Msg count: 4768
uncompressed gzip -9 bzip2 -9
XML 1250.59 27.39 14.17
XML2_test 910.63 23.97 13.20
Packed 405.12 17.34 12.67
Bach_beta 544.18 18.72 12.21
Binary1_beta 441.45 22.03 14.34
Binary2_test 260.30 19.02 13.23
"""
print
print
print "Test file:",file_name
global all_msg
xml_codec = codec.get_XML()
#all_msg = xml_codec.decode(open(file_name).read())
all_msg = file.read_file(file_name)
print "Msg count:",len(all_msg)
all_stats = []
#XML size
all_stats.append(calculate_stats(all_msg,xml_codec))
#XML2 size
all_stats.append(calculate_stats(all_msg,codec.get_XML2_test()))
#Packed size
all_stats.append(calculate_stats(all_msg,codec.get_Packed()))
#Bach size
all_stats.append(calculate_stats(all_msg,codec.get_Bach_beta()))
#Binary1_beta size
all_stats.append(calculate_stats(all_msg,codec.get_Binary1_beta()))
#Binary2_test size
all_stats.append(calculate_stats(all_msg,codec.get_Binary2_test()))
## for name in binary2.attribute_type_dict.keys():
## print name
## binary2.discard_name = name
## all_stats.append(calculate_stats(all_msg,codec.get_Binary2_test()))
## all_stats[-1][0] = list(all_stats[-1][0])
## all_stats[-1][0][0] = name
## all_stats.sort(lambda e1,e2:cmp(e1[2][2],e2[2][2]))
print
filter_types = ("uncompressed", "gzip -9", "bzip2 -9")
print " %10s %10s %10s" % filter_types
for stat in all_stats:
print "%-13s %10.2f %10.2f %10.2f" % (
stat[0][0], stat[0][2], stat[1][2], stat[2][2])
tkn = tag[1].replace('[', '').replace(']', '').split('\',')
if len(tkn) > 3:
continue
ltype = set()
for t in tkn:
# type-to-tag
typ = t.replace('\'', '').strip()
ltag = type2tag.setdefault(typ, set())
ltag.add(ptag)
type2tag[typ] = ltag
# tag-to-type
ltype.add(typ)
tag2type[ptag] = ltype
# tag - group
sgroup = ufile.read_file('app/resources/semantic-groups.txt')
if sgroup is None:
log.error('impossible to load the semantic categories - interrupting')
sys.exit()
group2tag = {}
group2type = {}
tag2group = {}
for sg in sgroup:
tkn = sg.strip().split('|')
grp = tkn[0].strip()
typ = tkn[2].strip().lower()
if typ not in type2tag:
continue
# group-to-tag
if typ in type2tag:
ltag = group2tag.setdefault(grp, set())
def test_read_file(self):
self.assertEqual('Hogehoge\nFoobar\n',
file.read_file("../file/read_file.txt"))
import file import json a = file.read_file() b = file.add_json(a, 'test')
for v in votes:
votesPerc.append(v / X)
votesMissing = []
sumDif = 0
for vp in votesPerc:
dif = votesPerc[indMax] - vp
votesMissing.append(dif)
sumDif += dif
return maxEle, sumDif, votesMissing
if __name__ == '__main__':
lines = file.read_file('A-large.in')
i = 0
write = []
for line in lines:
if i != 0:
line = line.split(" ")
N = line[0]
votes1 = line[1:]
votes = []
for j in votes1:
votes.append(float(j))
X = sum(votes)
maxEle, sumDif, votesMissing = greaterThan1(votes, X)
if sumDif <= 1:
