def test_temporary_file(self, tmpdir):
fake_csv_tmpfile = tmpdir.join('fake.csv')
with fake_csv_tmpfile.open('w') as csv:
csv.write('amy,2000-01-01\n')
csv.write('judy,1980-02-01\n')
assert calculate_age_sum(fake_csv_tmpfile.strpath) == 52
def join_segment_and_weather(segment_query):
data_out = os.path.join(os.getcwd(),'joined.csv')
wban_list = list(set([wban['WBAN'] for wban in list(leaderboard_collection.find(segment_query,{'_id':0,'WBAN':1}))])) #list of wban station ids
wban_query = {'WBAN':{'$in':wban_list}}
leaders = export_segment(segment_query)
weather = export_weather(wban_query)
concatenated = concatenate_files(leaders,weather,'concat.txt')
consoleCmds = 'python .\\analyze\\mrjob_join.py'
print consoleCmds
with open(concatenated,'r') as concat:
with open('output.txt','w') as output:
p = subprocess.Popen(consoleCmds, stdin=concat, stdout=output)
p.wait() #wait for the command to finish
with open('joined.csv','w') as csv:
with open('output.txt','r') as output:
for line in output:
try:
csv.write(ast.literal_eval(line.split('\t')[1]) + '\n')
except:
pass
os.remove('output.txt')
os.remove(concatenated)
os.remove(leaders)
os.remove(weather)
return data_out
def _batch2(model):
csv = open('lg_kdz.%s.csv' % (model), 'wb+')
csv.write('model,region,country,chip_type,prod_type,buyer_name,swversion,live_date,firmware,\n')
lg = LGMobile()
for country in lg.ftp_country_info():
ccode = country.country_code
print ccode, model
for sw in lg.tool_mode_country_check(ccode, model).itervalues():
csv.write(sw.csv() + '\n')
csv.close()
def export(self, path):
"""Exports recipe ingredients to csv
CSV is in the format "id,qty" with separate lines for each ingredient
Args:
path (pathlib.Path): Directory for the CSV file to be written to
"""
csvpath = path / (self.id + ".csv")
with csvpath.open("w") as csv:
for i in self.ingredients:
csv.write(i.id + "," + str(i.qty) + "\n")
def saveEntropyCSV(infolder,outfile):
filelist = os.listdir(infolder)
if '.DS_Store' in filelist:
filelist.remove('.DS_Store')
subprocess.call(['touch',outfile])
csv = open(outfile, 'r+')
for csvfile in filelist:
P_i = makeP_i( infolder + '/' + csvfile )[0]
S = entropy(P_i)
F = csvfile.split('_')[0] # e.g. '0.044_0.038.csv'
k = csvfile.split('_')[1][ :-4] #remove '.csv'
csv.write( F + ',' + k + ',' + str(S) + '\n')
csv.close()
def main(argv):
if len(argv) == 1:
msg = 'usage: python xlsx2vtb.py <xlsx_filename>\n'
sys.stderr.write(msg)
return 1
filename = argv[1]
workbook = WorkBook.fromfile(filename)
csvs = workbook.csvlist()
for csv in csvs:
csv.write()
vtbs = workbook.vtblist()
for vtb in vtbs:
vtb.write()
def export_csv(modeladmin, request, queryset):
response = HttpResponse(content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename=feedback.csv'
write = csv.write(response, csv.excel)
response.write(u'\ufeff'.encode('utf8'))
write.writerow([
smart_str(u"ID"),
smart_str(u"TITLE"),
smart_str(u"DATE_POSTED"),
smart_str(u"CUSTOMER"),
smart_str(u"COMPANY"),
smart_str(u"STATUS"),
])
for obj in queryset:
write.writerow([
smart_str(obj.pk),
smart_str(obj.title),
smart_str(obj.date_posted),
smart_str(obj.customer),
smart_str(obj.company),
smart_str(obj.status),
])
write.save(response)
return response
export_csv.short_description = u"Export CSV"
def generateCsvSetOfFiles(cls, top_folder):
print "\nWALKING THE TREE", top_folder+",", "SEARCHING FOR PICTURES"
csv_fullpath = DbMethods.temporaryCsvFile()
csv = open(csv_fullpath, 'w')
for dirpath, dirnames, files in os.walk(top_folder):
for name in files:
if (name.lower().endswith('bmp')
or name.lower().endswith('gif')
or name.lower().endswith('jpg')
or name.lower().endswith('png')
or name.lower().endswith('tiff')):
row = dirpath+'`'+name+'\n'
csv.write(row)
csv.close()
print "CSV FOLDER/FILE HAS BEEN GENERATED AT", csv.name
return csv_fullpath
def freqWords(string,corpus,number):
global pub,wordList
wordList=[]
stopset = set(stopwords.words('english'))
words = WordPunctTokenizer().tokenize(string)
wordsCleaned = [word.lower() for word in words if word.lower() not in stopset and len(word) > 2 ]
for i in range(len(wordsCleaned)):
wordList.append((corpus.tf_idf(wordsCleaned[i],string),wordsCleaned[i]))
wordList = list(set(wordList))
wordList = sorted(wordList,reverse=True)
final = [word[1] for word in wordList[:number]]
csv = open('db\cyttron-keywords.csv','a')
if len(final) > 1:
csv.write('"' + ','.join(final[:-1]) + ',' + final[-1] + '";')
else:
csv.write('"' + ''.join(final) + '";')
csv.close()
return final
def getData(year, month, day, csv): global first newline = "<br />" url = urlify(year, month, day) response = urllib2.urlopen(url) line = response.readline() # line = response.readline().replace(newline, "") line = response.readline().replace(newline, "") if (first == 1): date = "year,month,day," csv.write(date + line) first = 0 while (line != ""): line = response.readline().replace(newline, "") if (line == ""): break date = "%d,%d,%d," % (year, month, day) csv.write(date + line)
def siodoc(boias,dirout):
'''
Entra com o endereco de onde baixa o dado da boia
'''
data = dt.datetime.strftime(dt.datetime.now(),'%Y%m%d%H')
site = urllib2.urlopen("http://metocean.fugrogeos.com/marinha/Member/"+boiassiodoc)
print 'Baixando dado do SIODOC'
#datefile = '%02d%02d%02d' %(y,m,d)
filename = "SIODOC_"+data+".csv"
#create .csv file
csv = open(dirout+'SIODOC/'+filename,"w")
csv.write(site.read())
csv.close()
return
def findAndCopy(csv, root, indicator, nextSign):
value = None
try:
statisticsNumber = root.getElementsByTagName("statisticsNumber")[0].firstChild.nodeValue
if int(statisticsNumber) > 1:
value = 0
for i in range(int(statisticsNumber)):
value = value + int(root.getElementsByTagName(indicator)[i].firstChild.nodeValue)
elif int(statisticsNumber) <= 1:
value = root.getElementsByTagName(indicator)[0].firstChild.nodeValue
except Exception:
try:
value = root.getElementsByTagName(indicator)[0].firstChild.nodeValue
except Exception:
value = "no data avalible"
csv.write(str(value))
print (indicator + ": " + str(value))
csv.write(nextSign)
return
def merger():
f1 = csv.reader(open('aapl_historical_test.csv', 'rb'))
f2 = csv.reader(open('ibm_historical_test.csv', 'rb'))
mydict = {}
for row in f1:
mydict[row[0]] = row[1:]
for row in f2:
mydict[row[0]] = mydict[row[0]].extend(row[1:])
fout = csv.write(open('merged.csv','w'))
for k,v in mydict:
fout.write([k]+v)
def nGrams(string,corpus,number,clean=True):
global wordList
biList=[]
triList=[]
words = WordPunctTokenizer().tokenize(string)
stopset = set(stopwords.words('english'))
if clean == True:
words = [word.lower() for word in words]
if clean == False:
words = [word.lower() for word in words]
filter = lambda words: len(words) < 2 or words.isdigit()
bcf = BigramCollocationFinder.from_words(words)
bcf.apply_word_filter(filter)
biResult = bcf.nbest(BigramAssocMeasures.likelihood_ratio, number)
tcf = TrigramCollocationFinder.from_words(words)
tcf.apply_word_filter(filter)
triResult = tcf.nbest(TrigramAssocMeasures.likelihood_ratio, number)
for i in range(len(biResult)):
if len(biResult) > 0:
biPrint = " ".join(biResult[i])
biList.append(biPrint)
else:
biList=[]
csv = open('db\cyttron-keywords.csv','a')
if len(biList) > 1:
csv.write('"' + ','.join(biList[:-1]) + ',' + biList[-1] + '";')
else:
csv.write('"' + ''.join(biList) + '";')
csv.close()
for i in range(len(triResult)):
if len(triResult) > 0:
triPrint = " ".join(triResult[i])
triList.append(triPrint)
else:
triList=[]
csv = open('db\cyttron-keywords.csv','a')
if len(triList) > 1:
csv.write('"' + ','.join(triList[:-1]) + ',' + triList[-1] + '"\n')
else:
csv.write('"' + ''.join(triList) + '"\n')
csv.close()
print biList
print triList
def getcontent(self, filename):
contentfile = file('1.csv', 'wb')
writer = csv.write(contentfile)
writer.writerow(['作者', '内容'])
for url in geturls:
req = urllib2.Request(url, heads=self.heads)
res = urllib2.urlopen(req)
html = res.read().decode('utf-8')
soup = BeautifulSoup(html)
blockcontents = soup.find_all(
'div', class_="article block untagged mb15")
for blockcontent in blockcontents:
auther = blockcontent.find('div', class_="auther")
content = blockcontent.find('div', class_="content")
writer.writerow([auther, contern])
contentfile.close()
def run( self ):
dealer_rule = self.dealer_rule_map[self.dealer_rule]()
split_rule = self.split_rule_map[self.split_rule]()
try:
payout = ast.literal_eval( slef.payout )
assert len(payout) == 2
except Exception as e:
raise Exception('Invalid payout {0}'.format(self.payout))
table = Table( decks=self.decks, limit=self.limit,
dealer=dealer_rule, split=split_rule, payout=payout)
player_rule = self.player_rule_map[self.player_rule]()
betting_rule = self.betting_rule_map[self.betting_rule]()
player = Player( play=player_rule, betting=betting_rule,
rounds=self.rounds, stake=self.stake)
simulate = Simulate(table, player, self.samples)
with open( self.outputfile, 'w', newline='' ) as target:
wtr = csv.write(target)
wtr.writerows(simulate)
req = urllib.request.Request(url)
res = urllib.request.urlopen(req)
html = res.read()
return html
narou_root_url = 'http://ncode.syosetu.com/'
work_id = 'n9735cv'
url = narou_root_url + work_id
html = url_html(url)
soup = BeautifulSoup(html, 'html.parser')
csv_fname = 'narou_docs/narou.' + work_id + '.csv'
csv = open(csv_fname, 'w')
csv.write('name, since, user_note, text, url, when, access, card_note\n')
pretext_id = 0
who = soup.select('.novel_writername')[0].a.text
access = 'public'
note = 'corpus narou dev oz'
for sub in soup.select('.novel_sublist2'):
url = 'http://ncode.syosetu.com' + sub.a.get('href')
date = sub.select('.long_update')[0]\
.get_text().split('\n')[1].split(' ')
when = ''.join(date[0].split('/')) + 'T' + ''.join(
date[1].split(':')) + '00+0900'
work_fname = 'narou_docs/narou.' + '.'.join(
url.split('/')[3:5]) + '.doc.txt'
lines = open(work_fname).readlines()
for line in lines:
items = i.find_all('tbody')
rows = i.find_all('tr')
for row in rows:
cols = row.find_all('td')
cols = [ele.text.strip() for ele in cols]
data.append([ele for ele in cols if ele])
student_name = soup.find('td', attrs={'style': 'padding-left:15px'})
student_name = student_name.text.strip()
print("Extracting results for: " + str(area_code) +
str(college_code).upper() + str(year) + branch.upper() + usn)
usn = "University Seat Number: " + "," + str(area_code) + str(
college_code).upper() + str(year) + branch.upper() + usn + "\n"
student = "Student name: " + "," + student_name[2:] + "\n"
csv.write(usn)
csv.write(student)
thead = table.find('thead')
trow = thead.find('tr')
h = thead.find_all('th', attrs={'style': 'text-align:center;'})
hvar = []
for i in h:
i = i.text.strip()
hvar.append(i)
hh = hvar[0] + "," + hvar[1] + "," + hvar[2] + "," + hvar[
3] + "," + hvar[4] + "," + hvar[
5] + "," + "Grades" + "," + "Grade Point" + "\n"
csv.write(hh)
def CAM_Writer(name, path, cam_times, gaps, indexes, base, header, Attitudes,
Altitudes, Camera_Labels, if_reative, base_alt,
if_gimbal): #Esta function va a escribir el archivo
download_dir = os.path.join(
path, name + '.log'
) #path+'\\'+name+'.log' #where you want the file to be downloaded to
csv = open(download_dir, "w")
location_constructor = [
] # Lo que va a escribir ese jugoso location csv file que Agisoft le encanta, con atitudes y todo (delay incluido)
# Para el log de mission planner, se necesita un header
for a_row in header:
for every_string in a_row:
if every_string != a_row[-1]:
csv.write(every_string + ',')
else:
csv.write(every_string)
csv.write('\n')
# Aca comienza lo bacano
i = 0
for an_index in indexes:
gap = m.fabs(cam_times[i] - int(base[an_index][1]))
if m.fabs(gap - gaps[i]) < 0.001:
if base[an_index][0] == 'GPS' or base[an_index][0] == ' GPS':
base[an_index][0] = 'CAM'
del base[an_index][2]
del base[an_index][4]
del base[an_index][4]
base[an_index][7] = base[an_index][6]
base[an_index].append(
'55'
) # Adiciona otra dimension a la fila GPS, debido a que esta se queda corta una
if if_reative == 1: # Si se tiene la altura del sitio de depsegue, esta se usa + la del barometro para generar una altura muy buena
use_altitude = Altitudes[i] + base_alt
base[an_index][6] = str(
use_altitude
) # Escribo al CAM a TODAS las altitudes la altitud calculada
base[an_index][7] = str(use_altitude)
base[an_index][8] = str(use_altitude)
else: #Si no, pues se usa la altitud GPS (la cual estaba en la columna 7 de la fila GPS
base[an_index][7] = base[an_index][6]
base[an_index][8] = base[an_index][6]
if if_gimbal == 1:
location_constructor.append([
Camera_Labels[i], base[an_index][4], base[an_index][5],
base[an_index][6],
str(Attitudes[i][2]), '0.0', '0'
])
else:
location_constructor.append([
Camera_Labels[i], base[an_index][4], base[an_index][5],
base[an_index][6],
str(Attitudes[i][2]),
str(Attitudes[i][1]),
str(Attitudes[i][0])
])
if if_gimbal == 1:
base[an_index][9] = '0'
base[an_index][10] = '0.0'
base[an_index][11] = str(Attitudes[i][2])
else:
base[an_index][9] = str(Attitudes[i][0])
base[an_index][10] = str(Attitudes[i][1])
base[an_index][11] = str(Attitudes[i][2])
for every_string in base[an_index]:
if every_string != base[an_index][-1]:
csv.write(every_string + ',')
else:
csv.write(every_string)
csv.write('\n')
else:
print('Error on index' + str(an_index))
i = i + 1
download_dir = os.path.join(
path, name + '_location.csv'
) #path+'\\'+name+'.log' #where you want the file to be downloaded to
csv = open(download_dir, "w")
for a_line in location_constructor:
for every_string in a_line:
if every_string != a_line[-1]:
csv.write(every_string + ',')
else:
csv.write(every_string)
csv.write('\n')
import json
import csv
#Read a json file
with open('employee.json', 'r') as f:
datastore = json.load(f)
print (datastore)
empployee_data = datastore['employee_details']
#open a file for writing csv
write_file = open('parm.csv','w')
# create the csv write object
csvconverter = csv.write(write_file)
count = 0
for emp in empployee_data:
if count == 0:
header = emp.keys()
csvwriter.writerow(header)
count += 1
csvconverter.writerow(emp.values())
empployee_data.close()
def CSV (liste) :
nom_fichier = 'donnees.csv'
csv = open(nom_fichier, "w")
csv.write('"mot";'+'"effectif";'+'"rang";'+'"rang*effectif";'+'"longueur";'+"\n")
counteur = 1
for tupple in liste :
csv.write('"'+tupple[0].encode("utf-8")+'"'+";")
csv.write('"'+str(tupple[1]).encode("utf-8")+'"'+";")
csv.write('"'+str(counteur)+'"'+";")
csv.write('"'+str(counteur*tupple[1])+'"'+";")
csv.write('"'+str(len(tupple[0]))+'"'+";"+"\n")
counteur+=1
print " Pierre Beland, 06-2013"
print " Statistics of history of contribution by user and team"
print "date range and bbox as input"
print "Objects (ie. nodes, ways, relations) created, modified and deleted"
print "Original script (Seb's stats script v0.4 ) written by Sebastien Pierrel produced only statistics for objects created"
print "========================================================================="
print "Input variables "
print "list of users by team : vectors users [1] to [6]"
print "date_from=" + str(date_from)
print "date_to=" + str(date_to)
print "bbox : min_lon=" + str(min_lon) + ", max_lon=" + str(max_lon) + ", min_lat=" + str(min_lat) + ", max_lat=" + str(max_lat)
print "Checking changesets for "
osmApi = OsmApi.OsmApi(app = "api.openstreetmap.fr",debug=True)
csv = open(nom_csv, 'wb')
csv.write("ekip, user, changeset, node_c,way_c,relation_c, node_m,way_m,relation_m, node_d,way_d,relation_d \n")
csv.flush()
nom_csv_team=nom_csv+'_team'
csv_team = open(nom_csv_team, 'wb')
csv_team.write("ekip, user, changeset, node_c,way_c,relation_c, node_m,way_m,relation_m, node_d,way_d,relation_d \n")
csv_team.flush()
print "trainee number of changesets"
for ekip in range(1,8):
stats_team= {"changeset":0,"node_c":0, "way_c":0, "relation_c":0,"node_m":0, "way_m":0, "relation_m":0,"node_d":0, "way_d":0, "relation_d":0}
print "\n ekip " + str(ekip)
for user in users[ekip]:
stats = {"changeset":0,"node_c":0, "way_c":0, "relation_c":0,"node_m":0, "way_m":0, "relation_m":0,"node_d":0, "way_d":0, "relation_d":0}
changesets = getChangesets(username=user)
nb_changesets=len(changesets)
# print string.rjust(`x`, 2), string.rjust(`x*x`, 3),
#print str(user) +"\t\t" + str(nb_changesets)
if verbose == True:
print("Length of corrected DATA dictionary=", len(DATA))
print("Length of corrected INT dictionary=", len(INT))
print("Corrected time array:\n", corrected_time)
# <codecell>
### Saves the Time Profile Data to .csv in the run directory ###
if savedata == True: # When saving is active:
save = Base + Dye + "\\" + Concentration + "\\" + Run + "\\" + "timeprofiledata.csv" # Path and name of file
csv = open(save, "w") # Opens the file to write
for each, value in enumerate(INT): # For the length of INT:
x = corrected_time[each] # First column is times (x_axis)
y = INT[each] / max(
INT) # Second column is relative integral values (y_axis)
row = str(x) + "," + str(y) + "\n" # Sets up each row with delimiter
csv.write(row) # Writes each row to file
if verbose == True:
print("File saved as:", save)
csv.close()
# <codecell>
### Plots spectroscope data ###
peak = max(datacut[Cut]["Intensity"]) # Determines the maxima of the spectrum
for i in range(len(DATA)): # For each file:
#for i in np.arange(0,9): # For a small test sample:
textstr = "{}\nConcentration={}\nIntegration Time={}\nLaser Power={}\nFilter={} nm\n{}".format(
Long_Dye, Long_Concentration, Integration_Time, Laser_Power, Filter,
clocks[i])
yfrac = 1 - ((peak - DATA[i]["Intensity"]) / peak)
except ValueError:
print('您輸入了非數值之字元，請重新輸入數字代碼！')
end_date = dt.datetime.today().date()
start_date = end_date - dt.timedelta(days=dt_num - 1)
#####################################
## 瀏覽器開啟、爬蟲開始
print('即將取得近 %d 天的貼文，欲取得的粉專共有 %d 個' % (dt_num, len(page_list)))
print('\n>> 請注意，程式執行完畢後會自動關閉 Chrome 瀏覽器，請勿手動關閉以免程式錯誤。\n若出現防火牆訊息，可點選關閉或接受。')
input('---請按下 Enter 鍵以開始爬蟲---')
csv = open('Facebook 粉專爬文_%s.csv' % end_date.strftime('%m%d'),
'w',
encoding='utf8')
csv.write('粉專名稱,編號,日期時間,內文,文章連結,按讚數,留言+分享數,\n')
print('>> 正在開啟瀏覽器...')
driver = webdriver.Chrome('./chromedriver.exe')
print('>> 開啟網頁中...')
driver.get('https://www.facebook.com')
print('>> 登入中...')
driver.find_element_by_id('email').send_keys(username)
driver.find_element_by_id('pass').send_keys(password)
driver.find_element_by_id('loginbutton').click()
brand = ''
brand_index = 0
for index in page_list:
brand = index.split('/')[3]
print('正在開啟網頁...')
def video():
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-o",
"--output",
type=str,
default="barcodes.csv",
help="path to output CSV file containing barcodes")
# ap.add_argument("-o1", "--output2", type=str, default=files_name,
# help="path to output CSV file containing barcodes")
args = vars(ap.parse_args())
# initialize time and date and make filename friendly
time_header = str(datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S'))
# initialize the video stream and allow the camera sensor to warm up
print("[ALERT] starting video stream...")
print("Press 'Q' to exit")
vs = VideoStream(src=0).start()
# this is for a mobile solution
#vs = VideoStream(usePiCamera=True).start()
time.sleep(5.0)
# open the output CSV file for writing and initialize the set of
# barcodes found thus far
csv = open(args["output"], "w")
# time track variables. These are used to keep track of QR codes as they enter the screen
found = []
found_time = []
found_status = []
ctxAuth = AuthenticationContext(url=settings['url'])
# loop over the frames from the video stream
while True:
# grab the frame from the threaded video stream and resize it to
# have a maximum width of 400 pixels
frame = vs.read()
frame = imutils.resize(frame, width=400)
# find the barcodes in the frame and decode each of the barcodes
barcodes = pyzbar.decode(frame)
timestr = strftime("%m/%d/%Y %H:%M")
# loop over the detected barcodes
for barcode in barcodes:
# extract the bounding box location of the barcode and draw
# the bounding box surrounding the barcode on the image
(x, y, w, h) = barcode.rect
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
# the barcode data is a bytes object so if we want to draw it
# on our output image we need to convert it to a string first
barcodeData = barcode.data.decode("utf-8")
barcodeType = barcode.type
# draw the barcode data and barcode type on the image
text = "{} ({})".format(barcodeData, barcodeType)
cv2.putText(frame, text, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX,
0.5, (0, 0, 255), 2)
# if the barcode text is currently not in our CSV file, write
# the timestamp + barcode to disk and update the set
# if barcode data has never been seen, check the user in and record id, date, and time information
if barcodeData not in found:
csv.write("{},{},{},{}\n".format(system_id,
datetime.datetime.now(),
barcodeData, "IN"))
csv.flush()
contentstr = "{},{},{},{}\n".format(system_id, timestr,
barcodeData, "IN")
create_list_item(ctx, contentstr)
fname = "QRT" + "-" + system_id + "_" + time_header + ".csv"
upload_file(ctx, contentstr, fname, bkcsvfolder)
found.append(barcodeData)
found_time.append(datetime.datetime.now())
found_status.append("IN")
sys.stdout.write('\a')
sys.stdout.flush()
print(barcodeData + " checking IN at " +
str(datetime.datetime.now()) + " at location: " +
system_id)
# if barcode information is found...
elif barcodeData in found:
time_check = datetime.datetime.now() - found_time[found.index(
barcodeData)]
status_check = found_status[found.index(barcodeData)]
# if time exceeds wait period and user is checked in then check them out
if time_check > t_value and status_check == "IN":
index_loc = found.index(barcodeData)
found_status[index_loc] = "OUT"
found_time[index_loc] = datetime.datetime.now()
csv.write("{},{},{},{},{}\n".format(
system_id, datetime.datetime.now(), barcodeData, "OUT",
time_check))
csv.flush()
contentstr = "{},{},{},{},{}\n".format(
system_id, timestr, barcodeData, "OUT", time_check)
create_list_item(ctx, contentstr)
fname = "QRT" + "-" + system_id + "_" + time_header + ".csv"
upload_file(ctx, contentstr, fname, bkcsvfolder)
sys.stdout.write('\a')
sys.stdout.flush()
print(barcodeData + " checking OUT at " +
str(datetime.datetime.now()) + " at location: " +
system_id + " for duration of " + str(time_check))
# if found and check-in time is less than the specified wait time then wait
elif time_check < t_value and status_check == "OUT":
pass
# if found and time check exceeds specified wait time and user is checked out, delete ID and affiliated data from the list. This resets everything for said user and allows the user to check back in at a later time.
elif time_check > t_value and status_check == "OUT":
del found_status[index_loc]
del found_time[index_loc]
del found[index_loc]
else:
print("Something happened... error")
# show the output frame
cv2.imshow("QR Toolbox", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
# close the output CSV file do a bit of cleanup
print("[ALERT] cleaning up... \n")
csv.close()
cv2.destroyAllWindows()
vs.stop()
with open('adr_tst.csv') as cs:
rdr = csv.DictReader(cs)
for row in rdr:
st = row['street']
hs = row['house']
sear = {
'macroRegionId': 107000000000,
'regionId': 107401000000,
'street': st,
'house': hs
}
r = requests.get('http://rosreestr.ru/api/online/address/fir_objects',
params=sear)
output = open("result.txt", "a")
output.write(r.text)
output.close()
rw = rw + 1
print('Seek for ' + st, hs)
print(r.text)
js_pars = json.loads(r.text)
rjs = js_pars['objectId']
js_out = open('js_out.csv', 'w')
csvwriter = csv.write(js_out)
for jsd in rjs:
if count == 0:
header = jsd.keys()
csvwriter.writerow(header)
count += 1
csvwriter.writerow(jsd.values())
js_out.close()
print(rw)
def write_vendor_usage(csv, filename, tryBool):
if (tryBool):
csv.write("%s,%s,%s,%s,%s,%s,%s,%s\n" %
(usage__buildingCode, usage__issuerAbbriviation,
usage__accountNumber, usage__charge, usage__meterNumber,
usage__date, usage__usageAmount, usage__usageType))
with open('test5.csv') as csvfile:
readC = csv.reader(csvfile, delimiter=',')
totalsum = 0
for avgclc in readC:
totalsum = totalsum + int(avgclc[0])
totalavg = totalsum / 60000
with open('test5.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')
j = 0
i = 0
sum = 0
avg = 0
for row in readCSV:
if j < 250:
sum = sum + int(row[0])
j = j + 1
elif j == 250:
j = 0
avg = sum / 250
if (avg > totalavg):
print("Yes")
binary.append("Yes")
else:
print("No")
binary.append("No")
sum = 0
i = i + 1
csv = open("output5.csv", "w")
for bit in binary:
csv.write(bit + "\n")
com_li=[]
#text_file=open("company_names.txt","w")
#text_file.write("start:\n")
for each in com_tags:
names=cop_for.match(each)
if names!=None:
#print str(names.group(1))
com_li.append(str(names.group(1)))
print com_li
today=datetime.date.today()
starting=today-datetime.timedelta(days=30)
sdate=str(int(starting.strftime('%d')))
smonth=str(int(starting.strftime('%m'))-1)
syear=str(int(starting.strftime('%Y')))
edate=str(int(today.strftime('%d')))
emonth=str(int(today.strftime('%m'))-1)
eyear=str(int(today.strftime('%Y')))
date_url="&a="+smonth+"&b="+sdate+"&c="+syear+"&d="+emonth+"&e="+edate+"&f="+eyear+"&g=d&ignore=.csv"
print date_url
for each in com_li:
main_url=company_url+"s="+each+date_url
u = urllib2.urlopen(main_url)
with open('Companies\\'+each+'.csv',"w") as csv:
csv.write(u.read())
csv.close()
osmApi = OsmApi.OsmApi()
csv = open("stats.csv", "wb")
for user in users:
stats = {"node": 0, "way": 0, "relation": 0}
# print "Checking changesets for " + str(user)
str("Checking changesets for " + str(user))
changesets = getChangesets(username=user)
for id in changesets:
csstat = getChangesetStats(id)
stats["node"] += csstat["node"]
stats["way"] += csstat["way"]
stats["relation"] += csstat["relation"]
# stats = updateStat(stats, getChangesetStats(id))
# print user + ", " + str(len(changesets)) + ", " + str(stats["node"]) + ", " + str(stats["way"]) + ", " + str(stats["relation"])
csv.write(
str(user)
+ ", "
+ str(len(changesets))
+ ", "
+ str(stats["node"])
+ ", "
+ str(stats["way"])
+ ", "
+ str(stats["relation"])
+ "\n"
)
csv.flush()
csv.close()
# print "Done."
"Done."
def create_file():
try:
accesslog = open('/opt/wow/WOWHoneypot/log/access_log')
lines = accesslog.readlines()
accesslog.close
logcount = 0
rawdata = "■アクセスlogのrawdataは以下となってます。\n\n"
for line in lines:
if line.find(yestarday.strftime("%Y-%m-%d")) >= 0 and line.find(
ExclusionIP) < 0:
logcount += 1
rawdata += "-=-=" + str(logcount) + "件目のlog=-=-\n\n"
rawdata += line[:-1]
bunkatsu = line.rsplit(" ", 1)
decdata = (base64.decodestring(
bunkatsu[-1].encode("ascii")).decode("utf8"))
rawdata += ("\n\n" + str(decdata) + "\n\n")
ac_log = str()
for line in lines:
if line.find(yestarday.strftime("%Y-%m-%d")) >= 0 and line.find(
ExclusionIP) < 0:
bunkatsu2 = line.rsplit(" ", 1)
decdata2 = (base64.decodestring(
bunkatsu2[-1].encode("ascii")).decode("utf8"))
ac_log += line.rsplit(" ", 1)[0] + decdata2
all_iplist = []
for line in lines:
if line.find(yestarday.strftime("%Y-%m-%d")) >= 0 and line.find(
ExclusionIP) < 0:
all_ips = re.search(
"(([1-9]?[0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])\.){3}(([1-9]?[0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])\s)",
line)
all_iplist.append(all_ips.group())
unique_iplist = list(dict.fromkeys(all_iplist))
if os.path.exists("/opt/wow/WOWHoneypot/log/hunting.log"):
with open('/opt/wow/WOWHoneypot/log/hunting.log',
"r") as huntinglog:
lines2 = huntinglog.readlines()
huntinglog.close
huntingdata = "■huntinglogのrawdataは以下となってます。\n\n"
for line in lines2:
if line.find(yestarday.strftime(
"%Y-%m-%d")) >= 0 and line.find(ExclusionIP) < 0:
huntingdata += line[:-1]
huntingdata += "\n\n"
else:
huntingdata = ("■hunting.logは生成されていません。\n\n")
body = "■" + yestarday.strftime("%Y-%m-%d") + "のアクセス数は" + str(logcount) + "件でした。\n\n"+ "■送信元IPアドレスの数は\n"\
+ str(len(unique_iplist)) + "件です。\n\n"
if not os.path.exists("./log/"):
os.mkdir("./log/")
csv = open("./log/access_" + yestarday.strftime("%Y-%m-%d") + ".log",
"w")
csv.write(ac_log)
csv.close
f = open("./log/honeypot_" + yestarday.strftime("%Y-%m-%d") + ".log",
"w")
f.write(huntingdata + rawdata)
f.close
return body
except Exception as e:
body = str(e)
print = str(e)
return body
for line in fileinput.input(file_name, inplace=False):
line = re.sub('(\\|)+(\d)+(\\|)+.+', "", line.rstrip())
line = re.sub('\\||{|}|fb|style=\".*\"', "", line.rstrip())
line = re.sub('\\[|\\]', "", line.rstrip())
line = re.sub('FIFA World Cup(\d){4}(#\d\\*)*', "", line.rstrip())
line = re.sub('#\d\\^', "", line.rstrip())
line = re.sub('(^style=.+)|-|<sup>...</sup>|\\(|\\)', "", line.rstrip())
line = re.sub(' , ', " ", line.rstrip())
lines.append(line)
num_lines = len(lines)
i = 0
outputFile = open("output.csv", 'wb')
wr = csv.write(outputFile);
while(not re.match('[A-Z]{3}', lines[i])):
i += 1
csv = []
csv.append(["country", "year", "placing"])
while(i < num_lines and re.match('[A-Z]{3}', lines[i])):
country = lines[i].rstrip()
x = [1,2,3,4]
for placing in x:
l2 = lines[i+placing]
if(not re.match('align=centersort dash', l2)):
for year in l2.split(" "):
if len(year) > 1:
try:
r = 1
reader = csv.reader(f)
for row in reader:
if r == 1:
header = row
if r == 2:
subheader = row
r = r + 1
if (r > 2):
break
# print header
csv = open(TransposeFile, "w")
csv.write('id, header, subheader, value\n')
for row in reader:
r = 0
for column in row:
if (r > 1):
transrow = id + ',' + header[r] + ',' + subheader[r] + ',' + column + '\n'
csv.write(transrow)
print('%s,%s,%s,%s' % (id, header[r], subheader[r], column))
elif r == 0:
id = column
r = r + 1
finally:
f.close()
# = [ (-63.3, 'manual_0.pdb), (...)]
all_cst_scores = [(float(row[0]),row[2]) for row in cr]
all_cst_scores.sort()
lowest_energy_filename = all_cst_scores[0][1]
rmsd_ref_pose = Pose()
pose_from_pdb( rmsd_ref_pose, os.path.basename(lowest_energy_filename) )
# why does cr empty itself upon first call?
cr = csv.reader(open('energies.sc','rb'))
for row in cr:
cen_score_with_cst = row[0]
cen_score_without_cst = row[1]
filename = row[2]
this_pdb = os.path.join( this_directory, filename )
pose = Pose()
pose_from_pdb( pose, os.path.basename(filename) )
# RMSD
rmsd = CA_rmsd( rmsd_ref_pose, pose )
with open('rmsds_energies.sc', 'a') as csv:
linetowrite = str(rmsd)+','+cen_score_with_cst+','+cen_score_without_cst+','+filename
csv.write( linetowrite + '\n' )
import csv
def xor(val1, val2):
if (len(val1) != len(val2)):
print("Failure to xor due to unequal lengths in input.")
sys.exit()
xored = []
for i in range(len(val1)):
bit1 = int(val1[i])
bit2 = int(val2[i])
xorBit = int(bool(bit1) ^ bool(bit2))
xored.append(xorBit)
return ''.join(map(str, xored))
with open('output1.csv', 'r') as csv_file:
csv_reader = csv.reader(csv_file)
for row in csv_reader:
count = 0
row = str(row).split('\\t')
r1 = row[0].replace("['", "")
r2 = row[2].replace("']", "")
xored = xor(r1, r2)
for c in xored:
if (c == '1'):
count += 1
with open('outputxor.csv', 'a') as csv:
csv.write(r1 + '\t' + r2 + '\t' + xored + '\t' + str(count) + '\n')
cnt2 = 0
with open('/home/pfb16181/NetBeansProjects/birch/data/datasets/clef171819.csv',
'r') as read_obj:
csv_reader = reader(read_obj)
for idx, row in enumerate(csv_reader):
try:
line = row[0]
docid = line.split('\t')[-3].split('_')[0]
qid = line.split('\t')[-2]
# if docid in unique_flat_LIST_OF_LISTs_OF_PMIDS_FOR_EACH_TOPIC and qid in CLEF_TOPIC_LIST:
if qid in CLEF_TOPIC_LIST:
modified_line = row[0]
temp = modified_line.split('\t')
temp[-1] = str(cnt2)
list_lines_saved_for_1718TestCLEF.append(temp)
cnt2 += 1
except Exception:
cnt += 1
print(
'created list_lines_saved_for_1718TestCLEF.. with {} exceptions and size = {}. length of csv reader {}'
.format(cnt, len(list_lines_saved_for_1718TestCLEF), idx))
# write results to output.
sep = "\t"
with open('/home/pfb16181/NetBeansProjects/birch/data/datasets/clef1718.csv',
'w') as csv:
for row in list_lines_saved_for_1718TestCLEF:
csv.write(sep.join(row))
csv.write("\n")
def write_training_test_results(df_time, methods):
download_dir = "/Users/raghav/Documents/Uni/oc-nn/trainTest_Time/usps_trainTest.csv" # where you want the file to be downloaded to
print "Writing file to ", download_dir
csv = open(download_dir, "a")
for method in methods:
if (method == "OC-NN-Linear"):
row = method + "," + str(df_time["tf_OneClass_NN-Linear-Train"]) + "," + str(
df_time["tf_OneClass_NN-Linear-Test"]) + "\n"
csv.write(row)
if (method == "OC-NN-Sigmoid"):
row = method + "," + str(df_time["tf_OneClass_NN-Sigmoid-Train"]) + "," + str(
df_time["tf_OneClass_NN-Sigmoid-Test"]) + "\n"
csv.write(row)
if (method == "CAE-OCSVM-Linear"):
row = method + "," + str(df_time["cae_ocsvm-linear-Train"]) + "," + str(
df_time["cae_ocsvm-linear-Test"]) + "\n"
csv.write(row)
if (method == "CAE-OCSVM-RBF"):
row = method + "," + str(df_time["cae_ocsvm-rbf-Train"]) + "," + str(df_time["cae_ocsvm-rbf-Test"]) + "\n"
csv.write(row)
if (method == "AE2-SVDD-Linear"):
row = method + "," + str(df_time["ae_svdd-linear-Train"]) + "," + str(df_time["ae_svdd-linear-Test"]) + "\n"
csv.write(row)
if (method == "AE2-SVDD-RBF"):
row = method + "," + str(df_time["ae_svdd-rbf-Train"]) + "," + str(df_time["ae_svdd-rbf-Test"]) + "\n"
csv.write(row)
if (method == "OCSVM-Linear"):
row = method + "," + str(df_time["sklearn-OCSVM-Linear-Train"]) + "," + str(
df_time["sklearn-OCSVM-Linear-Test"]) + "\n"
csv.write(row)
if (method == "OCSVM-RBF"):
row = method + "," + str(df_time["sklearn-OCSVM-RBF-Train"]) + "," + str(
df_time["sklearn-OCSVM-RBF-Test"]) + "\n"
csv.write(row)
if (method == "RPCA_OCSVM"):
row = method + "," + str(df_time["rpca_ocsvm-Train"]) + "," + str(df_time["rpca_ocsvm-Test"]) + "\n"
csv.write(row)
if (method == "Isolation_Forest"):
row = method + "," + str(df_time["isolation-forest-Train"]) + "," + str(
df_time["isolation-forest-Test"]) + "\n"
csv.write(row)
return
def write_pseg_from_lines(invoice, csv, buildingCode, invoiceNumber, date,
invAmount, accountNumber, issuerCode, filename,
failedInvoices):
successfullyWroteCsv = False
electricAndOthersFlag = False
# Go through the Billing Summary table and pick out every charge in a less regexy way
dstSum = 0 #count if these lines add up if not, just write a line that that describes this
if (hasattr(invoice, 'lines')):
for line in invoice.lines:
#print(line['charge_description'], " " ,line['charge_amount'])
if (('charges' in line['charge_description']) |
('Charges' in line['charge_description'])):
# print(line)
if ('Electric' in line['charge_description']):
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
elif (('gas' in line['charge_description']) |
('Gas' in line['charge_description'])):
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
elif (('unmetered' in line['charge_description']) |
('Unmetered' in line['charge_description'])):
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
elif ('month' in line['charge_description']):
print('expected total')
else:
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
if (invAmount == invoice.amount_total_electric +
round(float(dstAmount.replace(',', '')), 2)):
electricAndOthersFlag = True
# print("Electric adds up")
if ((dstSum != invAmount) & (round(dstSum, 2) != invAmount)):
## print("Printing in sum doesn't add up in Line by line for loop")
failedInvoices.append(filename)
else:
csv.write("%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s\n" %
('INVH', invoiceNumber, date, round(
invAmount, 2), accountNumber, "U", issuerCode, date,
date, "1", "YES", filename))
dstSum = 0
for line in invoice.lines:
#print(line['charge_description'], " " ,line['charge_amount'])
if (('charges' in line['charge_description']) |
('Charges' in line['charge_description'])):
# print(line['charge_amount'].replace('$',''))
if ('Electric' in line['charge_description']):
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
pseg_error_dst(invoice, csv, buildingCode, '5500-5000',
date, dstAmount)
elif (('gas' in line['charge_description']) |
('Gas' in line['charge_description'])):
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
pseg_error_dst(invoice, csv, buildingCode, '5500-6000',
date, dstAmount)
elif (('unmetered' in line['charge_description']) |
('Unmetered' in line['charge_description'])):
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
pseg_error_dst(invoice, csv, buildingCode, '5500-6000',
date, dstAmount)
elif ('month' in line['charge_description']):
print('expected total')
else:
dstAmount = line['charge_amount'].replace('$', '')
if (line['charge_description'].endswith('-')):
dstAmount = '-' + dstAmount
dstSum += float(dstAmount.replace(',', ''))
print("FOUNDD THE NEGATIVE CHARGE " + dstAmount)
pseg_error_dst(invoice, csv, buildingCode, '5500-5000',
date, dstAmount)
add_to_total_expense(round(float(str(dstSum).replace(',', '')), 2))
rename(invoice, filename, accountNumber, buildingCode,
invoice.issuer, invAmount, date)
successfullyWroteCsv = True
else:
failedInvoices.append(filename)
return successfullyWroteCsv
def GetSnap():
global total_snap_size;
global total_old_snap_size;
csv = open(snap_fileout, "w");
columnTitleRow = "SnapshotId, StartTime, Base VolumeId, VolumeSize(GB), Tags\n";
csv.write(columnTitleRow);
print "Retrieving Snapshot info [Started]";
snap_c = 0;
for snapshot in ec2client.describe_snapshots(DryRun=dry_run,OwnerIds=[ownerid])['Snapshots']:
row =[];
if debug_run: print snapshot['SnapshotId'];
if debug_run: print snapshot['StartTime'];
if debug_run: print snapshot['VolumeId'];
if debug_run: print snapshot['VolumeSize'];
row.append(snapshot['SnapshotId']);
row.append(snapshot['StartTime']);
row.append(snapshot['VolumeId']);
row.append(snapshot['VolumeSize']);
total_snap_size += snapshot['VolumeSize'];
timestamp = '{:%Y-%m-%d}'.format(snapshot['StartTime']);
if re.match(timestampY, timestamp) is None:
if debug_run: print "snap is old";
total_old_snap_size += snapshot['VolumeSize'];
if 'Tags' in snapshot.keys():
Tag=snapshot['Tags'];
if debug_run: print "Tags:- ",;
for j in sorted(Tag):
if debug_run: print j['Key'] + " : "+ j['Value'],;
row.append(j['Key'] + " : "+ j['Value']);
if debug_run: print " ";
else:
if debug_run: print "[This snapshot doesn't have tags]";
row.append("[This snapshot doesn't have tags]");
row.append("\n");
csv.write(','.join(map(str, row)));
snap_c +=1;
print "Retrieving Snapshot info [Completed]";
total_snap ="Total "+str(snap_c)+" Snapshots and total Snapshots size on " + region +" is "+ str(total_snap_size)+" GB";
total_old_snap ="Total Old Snapshots (Created a year before) size on " + region +" is "+ str(total_old_snap_size)+" GB";
print "---------------------------------------------------------------------------------------"
print total_snap;
print total_old_snap;
print "---------------------------------------------------------------------------------------"
print "Please refer '"+snap_fileout+"' for more details\n";
csv.write("-----------------------------------------------------------------------------------------------\n");
csv.write(total_snap+"\n");
csv.write(total_old_snap+"\n");
csv.write("-----------------------------------------------------------------------------------------------\n");
csv.write("*Amazon EBS snapshots are stored incrementally: only the blocks that have changed after your last snapshot are saved,\n");
csv.write("and you are billed only for the changed blocks\n");
csv.write("*When an EBS snapshot is copied new EBS snapshot volume ID shows as vol-ffffffff\n");
csv.close();
return;
def getSeasons(self, FirstDay, FirstSeason, LastDay,LastSeason, league):
"""
crawling data from Website and saving
- hometeam,
- awayteam,
- homegoals,
- awaygoals,
- date
into a csv file.
-----------
Parameters:
-----------
FirstDay : int
start day of the first season
FirstSeason : int
from this season on the data get crawled
LastDay : int
last day of the last season
LastSeason : int
till this season the data get crawled
league : string
selection of the league:
input can only be "1. Bundesliga" , "2. Bundesliga", "3. Bundesliga", "1. Handball Bundesliga"
-------
Return:
-------
saving data into csv file
"""
self.clear()
csv = open("teamproject/BundesligaData.csv", "w")
csv.write(
"HomeTeam" +
"," +
"AwayTeam" +
"," +
"HomeGoals" +
"," +
"AwayGoals" +
"," +
"Date" +
"," +
"win"+
"\n")
if league == "1. Bundesliga" or league == "2. Bundesliga" or league == "3. Bundesliga" or league == "1. Handball Bundesliga":
for i in range(FirstSeason, (LastSeason + 1)):
counter = 0
startday_counter = 0
Game = {}
Date = {}
GameDay = {}
HomeTeam = {}
AwayTeam = {}
GoalsHome = {}
GoalsAway = {}
win_team = {}
if FirstSeason == LastSeason:
start_season_day = FirstDay
end_season_day = LastDay
elif i == FirstSeason and FirstDay != 1:
start_season_day = FirstDay
end_season_day = 34
elif i == LastSeason and LastDay != 34:
start_season_day = 1
end_season_day = LastDay
else:
start_season_day = 1
end_season_day = 34
if league == "1. Bundesliga":
game_data = json.loads(requests.get(f'http://www.openligadb.de/api/getmatchdata/bl1/{i}').text)
elif league == "2. Bundesliga":
game_data = json.loads(requests.get(f'http://www.openligadb.de/api/getmatchdata/bl2/{i}').text)
elif league == "3. Bundesliga":
game_data = json.loads(requests.get(f'http://www.openligadb.de/api/getmatchdata/bl3/{i}').text)
elif league == "1. Handball Bundesliga":
game_data = json.loads(requests.get(f'http://www.openligadb.de/api/getmatchdata/hbl/{i}').text)
for game in game_data:
startday_counter += 1
if (startday_counter / 9) + 1 > start_season_day and (startday_counter / 9) <= end_season_day:
Date[counter] = game['MatchDateTime']
Team1 = game['Team1']
HomeTeam[counter] = Team1['TeamName']
Team2 = game['Team2']
AwayTeam[counter] = Team2['TeamName']
Matchresults = game['MatchResults']
Result_half = Matchresults[0]
TeamA_half = Result_half['PointsTeam1']
TeamB_half = Result_half['PointsTeam2']
if not len(Matchresults) == 1:
Result = Matchresults[1]
TeamA = Result['PointsTeam1']
TeamB = Result['PointsTeam2']
else:
TeamA = -1
TeamB = -1
if TeamA_half + TeamB_half > TeamA + TeamB:
GoalsHome[counter] = TeamA_half
GoalsAway[counter] = TeamB_half
if TeamA_half > TeamB_half:
win_team[counter] = "h"
elif TeamA_half < TeamB_half:
win_team[counter] = "a"
elif TeamA_half == TeamB_half:
win_team[counter] = "d"
else:
GoalsHome[counter] = TeamA
GoalsAway[counter] = TeamB
if TeamA_half > TeamB_half:
win_team[counter] = "h"
elif TeamA_half < TeamB_half:
win_team[counter] = "a"
elif TeamA_half == TeamB_half:
win_team[counter] = "d"
match = HomeTeam[counter] + "," + AwayTeam[counter] + "," + str(GoalsHome[counter]) + "," + str(GoalsAway[counter]) + "," + Date[counter] + "," + win_team[counter] + "\n"
csv.write(match)
counter += 1
else:
print('Wrong string for crawling a certain league')
def GetAmi():
global total_amivol_size;
csv = open(ami_fileout, "w");
columnTitleRow = "ImageId, CreationDate, State, BlockDeviceMappings 01:, BlockDeviceMappings 02, BlockDeviceMappings 03, Tags\n";
csv.write(columnTitleRow);
print "Retrieving AMI info [Started]";
ami_c = 0;
for ami in ec2client.describe_images(DryRun=dry_run,Owners=['self'])['Images']:
#filter"ImageIds=['ami-7ae6541a']
row =[];
#print(volume)
if debug_run: print "AMI: " +ami['ImageId'] + " Creation date: "+ str(ami['CreationDate']),;
row.append(ami['ImageId']);
row.append(ami['CreationDate']);
row.append(ami['State']);
if 'BlockDeviceMappings' in ami.keys():
EBS=ami['BlockDeviceMappings'];
if debug_run: print "EBSs:- ",;
for j in EBS:
#if debug_run: print j;
if "Ebs" in j:
Ebs_d = j['Ebs'];
Ebs_dn = j['DeviceName'];
#print Ebs_d;
if 'SnapshotId' in Ebs_d.keys():
if debug_run: print Ebs_d['SnapshotId']+" : "+str(Ebs_d['VolumeSize']),;
row.append(j['DeviceName']+":"+Ebs_d['SnapshotId'] + " :"+ str(Ebs_d['VolumeSize'])+"GB");
total_amivol_size += Ebs_d['VolumeSize'];
else:
if debug_run: print "No Snapshot info available";
row.append("No Snapshot info available");
else:
if debug_run: print "This is ephemeral not a EBS"
row.append(j['DeviceName']+" : Ephemeral");
if debug_run: print " ";
else:
if debug_run: print "[This AMI doesn't have BlockDeviceMappings]";
row.append("No EBS");
if 'Tags' in ami.keys():
Tag=ami['Tags'];
if debug_run: print "Tags:- ",;
for j in sorted(Tag):
if debug_run: print j['Key'] + " : "+ j['Value'],;
row.append(j['Key'] + " : "+ j['Value']);
if debug_run: print " ";
else:
if debug_run: print "[This AMI doesn't have tags]";
row.append("[This AMI doesn't have tags]");
if debug_run: print "Array out----------------------------------"
row.append("\n");
csv.write(','.join(map(str, row)));
ami_c +=1;
print "Retrieving AMI info [Completed]";
total_amivol ="Total "+str(ami_c)+" AMIs and total Volumes size attached to AMIs on " + region +" is "+ str(total_amivol_size)+" GB";
print "---------------------------------------------------------------------------------------"
print total_amivol;
print "---------------------------------------------------------------------------------------"
print "Please refer '"+ami_fileout+"' for more details\n";
csv.write("-----------------------------------------------------------------------------------------------\n");
csv.write(total_amivol+"\n");
csv.write("-----------------------------------------------------------------------------------------------\n");
csv.close();
return;
def awsCall(barcodeData, idR, c, URL, URLV):
#Send AWS
z = datetime.strftime("%A")
arrival_time = str(time.strftime("%H:%M"))
Day = z.lower()
qr = str(barcode)
# defining a params dict for the parameters to be sent to the API
PARAMS = {
'qrCode': barcodeData,
'arrival_time': arrival_time,
'Day': Day,
'residential_id': idR,
'cpu_serial': c
}
print(PARAMS)
# sending get request and saving the response as response object
conexion = False
try:
with eventlet.Timeout(10):
r = requests.get(url=URL, params=PARAMS)
except:
logging.info('Error al verificar el codigo')
time.sleep(4)
return
# extracting data in json format
try:
message = r.json()
print(message)
QRstatus = message['result']
logging.info('%s', QRstatus)
tipolector = configLec.get('garitappiot', 'tipo')
funcionlector = configLec.get('garitappiot', 'funcion')
if funcionlector == 'Entrada' and tipolector == 'CONRF':
if QRstatus == "Valido": fotofile = message['photo']
if QRstatus == "Invalido": fotofile = "no valido"
fotofile = message['photo']
cortesia = "Bienvenido"
print(QRstatus, fotofile)
if funcionlector == 'Salida' and tipolector == 'CONRF':
if QRstatus == "Valido": fotofile = message['photo']
if QRstatus == "Invalido": fotofile = "no valido"
cortesia = "Buen viaje"
print(QRstatus, fotofile)
if funcionlector == 'Entrada' and tipolector == 'NORF':
fotofile = "norfacial"
cortesia = "Bienvenido"
if funcionlector == 'Salida' and tipolector == 'NORF':
fotofile = "norfacial"
cortesia = "Buen viaje"
print(QRstatus, cortesia, fotofile)
if QRstatus == "Invalido":
led.on()
time.sleep(2)
led.off()
time.sleep(3)
if QRstatus == "Valido" and tipolector == 'CONRF':
for x in range(3):
logging.info('Comenzando reconocimiento facial')
os.system(
'sudo wget http://' + IP +
':9000/?action=snapshot -O /home/pi/Documents/QRscan/cara.jpg'
)
img = Image.open("/home/pi/Documents/QRscan/cara.jpg")
img.save("/home/pi/Documents/QRscan/patron.jpg",
dpi=(640, 480))
targetFile = '/home/pi/Documents/QRscan/patron.jpg'
sourceFile = fotofile
coincidence = 0
client = boto3.client('rekognition')
imageTarget = open(targetFile, 'rb')
try:
response = client.compare_faces(
SimilarityThreshold=70,
SourceImage={
'S3Object': {
'Bucket': 'garitapp.guest.id.pictures',
'Name': sourceFile
}
},
TargetImage={'Bytes': imageTarget.read()})
for faceMatch in response['FaceMatches']:
similarity = str(faceMatch['Similarity'])
coincidence = float(similarity)
print(coincidence)
logging.info('Similitud de un %s', similarity)
imageTarget.close()
if coincidence >= 85:
GPIO.setup(pluma, GPIO.OUT)
GPIO.output(pluma, GPIO.LOW)
time.sleep(1)
GPIO.output(pluma, GPIO.HIGH)
GPIO.setup(pluma, GPIO.IN)
logging.info('Acceso concedido')
csv.write("{},{},{},{}\n".format(
datetime, barcodeData, "Valido", coincidence))
csv.flush()
#validate if it is simple invitation
if barcodeData.split("_")[0] == "001":
# defining a params dict for the parameters to be sent to the API
PARAMS = {
'qrCode': barcodeData,
'arrival_time': arrival_time,
'Day': Day,
'residential_id': idR,
'cpu_serial': c
}
# sending get request and saving the response as response object
while True:
try:
with eventlet.Timeout(10):
r = requests.get(url=URLV,
params=PARAMS)
break
except:
pass
else:
logging.info('Acceso denegado')
csv.write("{},{},{}\n".format(datetime, barcodeData,
"Invalido"))
csv.flush()
time.sleep(3)
break
except:
logging.info('Usuario no detectado')
csv.write("{},{},{}\n".format(datetime, barcodeData,
"Invalido"))
csv.flush()
time.sleep(5)
if QRstatus == "Valido" and tipolector == 'NORF':
GPIO.setup(pluma, GPIO.OUT)
GPIO.output(pluma, GPIO.LOW)
time.sleep(1)
GPIO.output(pluma, GPIO.HIGH)
GPIO.setup(pluma, GPIO.IN)
logging.info('Acceso concedido')
csv.write("{},{},{}\n".format(datetime, barcodeData, "Valido"))
csv.flush()
except:
logging.info('Error leyedo datos')
time.sleep(5)
pass
def GetVolumes():
global total_unattached;
csv = open(vol_fileout, "w");
columnTitleRow = "VolumeId, Size(GB), VolumeType, State, Attached Instnace, Device, Tags\n";
csv.write(columnTitleRow);
print "Retrieving Volume info [Started]";
vol_c = 0;
for volume in ec2client.describe_volumes(DryRun=dry_run)['Volumes']:
row =[];
#print(volume)
if debug_run: print "Vol: " +volume['VolumeId'] + " Size: "+ str(volume['Size']) + "GB",;
row.append(volume['VolumeId']);
row.append(volume['Size']);
row.append(volume['VolumeType']);
if volume['Attachments']:
Attachment=volume['Attachments'];
for i in Attachment:
if debug_run: print i['State'] + " to "+ i['InstanceId'] +" as "+ i['Device'],;
row.append(i['State']);
row.append(i['InstanceId']);
row.append(i['Device']);
else:
if debug_run: print "[This volume not attached to any instance]",;
row.append("[This volume not attached to any instance]");
total_unattached += volume['Size'];
if 'Tags' in volume.keys():
Tag=volume['Tags'];
if debug_run: print "Tags:- ",;
for j in sorted(Tag):
if debug_run: print j['Key'] + " : "+ j['Value'],;
row.append(j['Key'] + " : "+ j['Value']);
if debug_run: print " ";
else:
if debug_run: print "[This volume doesn't have tags]";
row.append("[This volume doesn't have tags]");
if debug_run: print "Array out----------------------------------"
row.append("\n");
csv.write(','.join(map(str, row)));
vol_c +=1;
print "Retrieving Volume info [Completed]";
total_vol ="Total "+str(vol_c)+" Volumes and total unattached Volumes size on " + region +" is "+ str(total_unattached)+" GB";
print "---------------------------------------------------------------------------------------"
print total_vol;
print "---------------------------------------------------------------------------------------"
print "Please refer '"+vol_fileout+"' for more details\n";
csv.write("-----------------------------------------------------------------------------------------------\n");
csv.write(total_vol+"\n");
csv.write("-----------------------------------------------------------------------------------------------\n");
csv.close();
return;
def write_file(file, filename):
with open("csv_upload_directory/%s.csv" % filename, 'w') as csv:
for d in file:
csv.write(d)
csv.write('\n')
csv.close()
# Ob times are always CDT
ts1 = mx.DateTime.strptime(d['TIMESTAMP'], '%Y-%m-%d %H:%M:%S')
gts1 = ts1 + mx.DateTime.RelativeDateTime(hours=5)
iem = access.Ob( 'RSAI4', "OT")
iem.setObTimeGMT( gts1 )
drct = d['WindDir']
iem.data['drct'] = drct
sknt = float(d['WS_mph_S_WVT']) / 1.15
iem.data['sknt'] = sknt
gust = float(d['WS_mph_Max']) / 1.15
iem.data['gust'] = gust
iem.updateDatabase( cursor=icursor )
csv.write("%s,%s,%s,%.1f,%.1f\n" % ('RSAI4',
gts1.strftime("%Y/%m/%d %H:%M:%S"),
drct, sknt, gust) )
# Red Rock
try:
req = urllib2.Request("ftp://%s:%[email protected]/Red Rock_Table3Min_current.dat" % (secret.CTRE_FTPUSER,
secret.CTRE_FTPPASS))
data = urllib2.urlopen(req, timeout=30).readlines()
except:
if now.minute % 15 == 0:
print 'Download CTRE Bridge Data Failed!!!'
sys.exit(0)
if len(data) < 2:
sys.exit(0)
def lemur2csv(lemurfile, csvfile): lemur=loadlemur(lemurfile) csv=open(csvfile,'w') for e,g in lemur.items(): csv.write(e+"\t"+g) csv.close()
def write_to_csv(invoice, csv, filename, usageCSV, failedInvoices,
creditInvoices):
# print(filename)
wroteInvBool = False
try:
print(invoice.issuer, hasattr(invoice, 'issuer'))
if ((invoice.issuer == 'null')):
failedInvoices.append(filename)
return
#cross invoice object
fullDate = invoice.date
date = str(fullDate.month) + '/' + str(fullDate.day) + '/' + str(
fullDate.year)
buildingCode = building_code(
invoice) #grab building code - Takes invoice as input
invoiceNumber = invoice.invoice_number
invAmount = invoice.amount
accountNumber = get_account_number(invoice)
issuerCode = get_issuer_code(invoice)
# print(issuerCode)
chargeCode = get_charge_code(invoice)
meterReading = get_meter_amount(invoice, "")
#set globals
usage__charge = invAmount # this will be reset for PSEG gas or electric in PSEG section
usage__meterNumber = '0'
usage__usageAmount = '0'
usage__date = date
usage__glCode = chargeCode
usage__issuerAbbriviation = issuerCode
usage__accountNumber = accountNumber
usage__buildingCode = buildingCode
if (hasattr(invoice, "credit_bool")):
newName = str(buildingCode) + " " + invoice.issuer + " " + str(
accountNumber) + " " + "$" + str(
invAmount) + " " + date.replace('/', "-") + ".pdf"
creditInvoices.append([newName, filename])
rename(invoice, filename, accountNumber, buildingCode,
invoice.issuer, "(" + str(invAmount) + ")", date)
return
if (invoice.issuer == "Comcast"):
invoiceNumber = date.replace("/", '') + accountNumber[12:]
if (invoice.issuer != "PSE&G"):
# print("Are we here")
csv.write("%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s\n" %
('INVH', invoiceNumber, date, round(
invAmount, 2), accountNumber, "U", issuerCode, date,
date, "1", "YES", filename))
#DST Line
csv.write("%s,%s,%s,%s,%s\n" % ("DIST", buildingCode, chargeCode,
meterReading, round(invAmount, 2)))
add_to_total_expense(invAmount)
wroteInvBool = True
rename(invoice, filename, accountNumber, buildingCode,
invoice.issuer, invAmount, date)
if (invoice.issuer == 'American Water'):
if (hasattr(invoice, 'total_gallons')):
usage__usageAmount = invoice.total_gallons
else:
## THIS IS JUST FOR PSEG ####
psegInfo = check_pseg_info(invoice)
if (psegInfo == -1):
csv.write(
"%s,%s,%s\n" %
("Could not parse pdf", filename, ', , , , , , , , Error'))
gas = electric = electricSupply = gasSupply = other = unmetered = 0
psegCharges = [
'gas_charge', 'amount_total_electric', 'other_charges'
]
addsUp = 0
for charge in psegCharges:
if (hasattr(invoice, charge)):
addsUp = addsUp + float(invoice.__getattribute__(charge))
if (addsUp != invAmount):
wroteProperly = write_pseg_from_lines(
invoice, csv, buildingCode, invoiceNumber, date, invAmount,
accountNumber, issuerCode, filename, failedInvoices)
if (wroteProperly):
wroteInvBool = True
else:
######### if DIST lines add up to invoice lines #############
csv.write(
"%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s\n" %
('INVH', invoiceNumber, date, invAmount, accountNumber,
"U", issuerCode, date, date, "1", "YES", filename))
for charge in psegCharges:
# print(charge)
if (hasattr(invoice, charge)):
# print('has attribute')
#DST Line
chargeCode = get_charge_code(
str(charge)) #returns the GL CODE
meterAmount = get_meter_amount(invoice, charge)
chargeAmount = get_charge_amount(invoice, charge)
csv.write("%s,%s,%s,%s,%s\n" %
("DIST", buildingCode, chargeCode,
meterAmount, chargeAmount))
add_to_total_expense(round(invAmount, 2))
rename(invoice, filename, accountNumber, buildingCode,
invoice.issuer, invAmount, date)
wroteInvBool = True
## Running Total for header BTCH Lines ##
# write_vendor_usage(invoice, filename, True)
except Exception as error:
print(error)
wroteInvBool = False
failedInvoices.append(filename)
# write_vendor_usage(invoice, filename, False)
pass
return wroteInvBool
articles.update(pickle.load(inputfile))
break
print len(articles)
for article in articles:
date = articles[article][0]
date = date[:date.rfind("/")] + date[date.find("/")+1:]
if len(date) < 3:
continue
date = int(date)
if date < 198000:
print date
continue
if date not in dates:
dates[date] = 1
else:
dates[date] += 1
print len(dates)
with open("dates.csv", "w") as csv:
for x in dates:
w = "%s,%s\n"%(x,dates[x])
csv.write(w)
# plt.bar(dates.keys(), dates.values())
# plt.show()
def lemur2csv(lemurfile, csvfile):
lemur = loadlemur(lemurfile)
csv = open(csvfile, 'w')
for e, g in lemur.items():
csv.write(e + "\t" + g)
csv.close()
def _generate_blank(self):
csv = open(self.csv, "w")
csv.write("TYPE,START POINT,END POINT,TURN COMMENTS,TURN CUE,"
"ROAD,ROAD COMMENTS,LANES,SHOULDER,SPEED,TRAFFIC\n")
csv.close()
import csv
import sys
import re
filename = sys.argv[1]
results = []
with open(filename) as csvfile:
reader = csv.reader(csvfile) # change contents to floats
# print(reader)
for row in reader: # each row is a list
if len(row) > 0:
results.append(row)
results = "module.exports = " + str(results)
results = re.sub('\', ', '\',', results)
results = re.sub(', ', ',', results)
csv = open('data/' + filename, "w")
csv.write(results)
print(results)
#!/usr/bin/env python3
import csv
# Simplest example of reading a CSV file
with open('some.csv', newline='') as f:
reader = csv.reader(f)
for row in reader:
print(row)
# Reading a file with an alternate format:
with open('passwd', newline='') as f:
reader = csv.reader(f, delimiter=':', quoting=csv.QUOTE_NONE)
for row in reader:
print(row)
# Simplest writing example
with open('some.csv', mode='w', newline='') as f:
writer = csv.writer(f)
writer.writerows(someiterable)
# Better interface?
with open('some.csv') as f:
for line in f:
print(csv.read(line))
with open('some.csv', mode='w') as f:
csv.write(line for line in f)
import csv
dic = {"John": "*****@*****.**", "Mary": "*****@*****.**"} #dictionary
download_dir = "exampleCsv.csv" #where you want the file to be downloaded to
csv = open(download_dir, "w")
#"w" indicates that you're writing strings to the file
columnTitleRow = "name, email\n"
csv.write(columnTitleRow)
for key in dic.keys():
name = key
email = dic[key]
row = name + "," + email + "\n"
csv.write(row)
def createCSV(fname, nodes):
csv = open(fname,'wb')
for node in nodes.values():
for k,v in node.links.items():
csv_item = node.links[k].__str__()
csv.write(csv_item+'\n')
import os,csv,json
with open('people.json') as f:
jsonfile = json.load(f)
with open('student-dev-ports.csv','w') as csvfile:
streamwriter = csv.write(csvfile,delimiter=' ',quotechar='|', quoting=csv.QUOTE_MINIMAL)
streamwriter.writerow(['Student Name','Dev Port'])
for r in jsonfile:
streamwriter.writerow([r['name'],r['dev']])
if '.xls' in args.input_path:
dframe = pd.read_excel(args.input_path)
elif '.csv' in args.input_path:
dframe = pd.read_csv(args.input_path)
else:
print("Unknown input file type")
sys.exit(1)
docLst = text_preprocess(dframe, args)
else:
docLst = load_text_pre(args)
# 加载/生成count vector词频统计
tf, tf_vectorizer = get_count_vector(docLst, args)
# 训练LDA模型
lda_model = train_lda(tf, args)
# 保存并输出topic_word矩阵
print("#########Topic-Word Distribution#########")
tf_vectorizer._validate_vocabulary()
tf_feature_names = tf_vectorizer.get_feature_names()
print_top_words(lda_model, tf_feature_names, args.n_top_words)
# 保存doc_topic_distr
doc_topic_dist = lda_model.transform(tf)
with open(args.doc_topic_path, 'w') as f:
writer = csv.write(f)
f.writerow(['Index', 'TopicDistribution'])
for idx, dist in enumerate(doc_topic_dist):
# 注意：由于sklearn LDA函数限制，此函数中输出的topic_word矩阵未normalize
f.writerow([idx + 1] + dist)
import csv
## 2. Abrimos nuestro XML
archivo = open('59CHRTMZ01R-Alignment.xml','r')
texto = archivo.read()
archivo.close()
#print(texto)
## 3. Interpretamos el XML con BeautifulSoup
soup = BeautifulSoup(texto)
## 4. Aplicamos los métodos que ya conocemos: .findAll(), find(), .string
hits = soup.findAll('hit')
output = csv.write(open('BLAST.csv','w'))
output.writerows(['Hit','Evalue'])
for x in hits:
hsps = x.findAll('hit_hsps')
for y in hsps:
print(y.findAll('hsp_num'))
hit_id = x.find('hit_id').string
evalue = float(x.find('hsp_evalue').string)
seq = x.find('hsp_hseq').string
defi = x.find('hit_def').string
print(hit_id,defi,evalue,seq)
output.writerows([hit_id,evalue])
# collecting final group list and group-wise list of assigned clusters
return finalGroupList, groupWiseMatchList
# checking group overlap in cluster matching across courses
# defining global variables
for n in range(7, 40):
courseCount = 3
groupCount = n
groupList = list(range(1, groupCount + 1))
fileName = './Group Overlap Data/avgdiff_data_' + str(n) + '.csv'
csv = open(fileName, 'w')
for k in range(100000):
finalList, groupWiseMatchList = finalgrouplist(
courseCount, groupList, clusterstructure(courseCount, groupCount))
diffLenSum = 0
for i in range(groupCount):
j = i + 1
flatList = [
x for sublist in groupWiseMatchList[i] for x in sublist
]
listLen = len(flatList)
diffLen = listLen - len(set(flatList)) - 2
diffLenSum += diffLen
avgDiff = diffLenSum / groupCount
csv.write(str(avgDiff) + '\n')
print('Script done for: ', n)
count += 1
filtercol = ''
for i in range(0, L):
filtercol = filtercol + str(m[i]) + ','
fftcol = ''
for i in range(0, lfft):
fftcol = fftcol + str(Y[i]) + ','
filtercol = filtercol + str(classify) + "\n"
an = ''
for i in range(0, count):
if i == (count - 1):
an = an + str(data_test[i])
else:
an = an + str(data_test[i]) + ','
fftcol = fftcol + str(classify) + "," + an + "\n"
#write filter data
file = open('filter_data.csv', "a")
file.write(filtercol)
file.close()
#write fft data
file = open('fft_data.csv', "a")
file.write(fftcol)
file.close()
print('Writing complete !!')