def upload_contacts_file(request):
"""
Uploads a file to a server
Responds with:
- Mapping contactinfo types
- List of n rows specified by a request param "rows"
- Filename in the system
"""
n_rows = request.GET.get('rows', 1)
uploaded_file = request.FILES['myfile']
filename = str(uuid4()).replace('-', '')
save_path = os.path.join(CONTACTS_FILES_DIR, filename)
with open(save_path, 'wb+') as saved_file:
for chunk in uploaded_file.chunks():
saved_file.write(chunk)
decoded_file = uploaded_file.read().decode('utf-8').splitlines()
reader = csv.Reader(decoded_file)
returned_rows = [row for row in reader[0: n_rows]]
return JsonResponse({
'filename': filename,
'returned_rows': returned_rows,
'mapped_contact_types': CONTACT_INFO_TYPES,
})
def readCsvToList(filename):
file = open(filename, encoding="utf-8")
dataset = []
reader = csv.Reader(file)
for i in reader:
dataset.append(i) # reading to dict
return dataset
def import_grades(self,
name,
gfile,
points_possible=None,
matching=False,
weight=1.0):
"""import grades from file.
Parameters
----------
name : str
Name of the assignment which is being added
gfile : str
Full path to .csv file containing grades
points_possible : float, int, or None
Number of points possible (Default value = None)
matching : bool
Matches grades to students in roster if an exact match doesn't exist (Default value = False)
weight : float
Weight to apply to assignment (Default value = 1.0)
Returns
-------
"""
self.grades['Entries'].append(name)
self.grades['Points Possible'].append(points_possible)
self.grades['Weights'].append(weight)
tmp_grades = {}
with open(gfile, "r") as f:
reader = csv.Reader(f)
for row in reader:
try:
lastname = self.roster[row[0]][row[1]]['Last Name']
firstname = self.roster[row[0]][row[1]]['First Name']
except KeyError:
if matching:
lastname, firstname = self.roster.match(row[0], row[1])
if (lastname, firstname) in tmp_grades.keys():
continue
else:
continue
tmp_grades[lastname, firstname] = float(row[2])
for student in self.roster.studentlist:
lastname = student['Last Name']
firstname = student['First Name']
score = 0
try:
score = tmp_grades[lastname, firstname]
except KeyError:
pass
self.grades["Students"][lastname,
firstname]["Scores"].append(score)
self.grades["Students"][lastname, firstname][name] = score
self.grades["Students"][lastname, firstname]["Total"] += score
def Berkeley_Arts_Magnet():
with open('BUILD_SiteTimes2.csv') as g:
site_times = csv.Reader(g)
BAM_avail = {}
for site from site_times
start_time = []
start_time = list.site['Mond']
BAM_avail = dict.fromkeys(days)
def handle(self, *args, **options):
file_path = options['squirrel_file']
try:
with open(file_path) as f:
reader = csv.Reader(f)
for item in reader:
#item
pass
msg = f'You are importing from {file_path}'
self.stdout.write(self.style.SUCCESS(msg))
except:
raise CommandError('Import file failed')
def verifyLogin(self):
#This is a routine which returns a bool value of true or false for the user's login
#If true is returned, this means taht user will be able to login and will be greeted with an appropriate welcome screen.
#Otherwise the user will be told their login information is wrong and will be sent back to the login screen to try again.
file = open("usernames.txt","r")
fr = csv.Reader(file)
users = []
for row in fr:
for item in row:
users.append(item)
un = input("please enter your username")
pw = input("please enter your password")
for item in range(len(users[::3])):
if users[item] == un and users[item+1] == hashlib.sha256(b(pw)).hexdigest():
self.__name=un
self.__ID=users[item+2]
self.sessionToken=Token.Token(self.__ID)
return True
else:
return False
def fetch_tsv_header(file_path):
with open(file_path) as fin:
reader = csv.Reader(fin, delimiter='\t')
return next(reader)
# Budget Calendar
# To calculate how much money is available to spend daily to meet savings goals
# Variables:
# Overall goal
# Daily goal
# Days until End
# Balance
# Daily Income
# Deductions
# Spending Limit
# Deductions Class
# Bills
# Money spent
# Process: Balance = Balance + Daily income - Deductions
# Daily goal = Overall goal / Days until End
# Spending Limit = Balance - Daily goal
# Get inputs from file (???)
import csv
with open() as csvDataFile:
csvReader = csv.Reader(csvDataFile)
for column in csvReader:
print(column)
def reset(self):
self.file.close()
self.file = open(self.filename, 'r')
self.file.readline() #get rid of headers
self.reader = csv.Reader(self.file)
import csv
import json
import networkx as nx #Libreria de las redes
import matplotlib.pyplot as plt #Libreria para la representacion de redes
jsonfile = open('file.json', 'w')
data = {}
csvfile = open('PDVR.csv', 'r')
reader = csv.Reader(csvfile)
mylist.append(reader)
for user in mylist.values():
data[user] = []
path = 'userdata/' + user + '.csv'
fcsv = open(path, 'r')
readerr = csv.Reader(csvfile)
mylistt = list(readerr)
for usefollower in mylistt.values():
data[user].append(follower)
with open('data.txt', 'w') as outfile:
json.dump(data, outfile)
# with open() as edge_list:
# data = json.load(edge_list)
# G = nx.Graph()
# for user in data['users']:
# for follower in user['follower']
import numpy as np
import csv
from numpy import array, random
from scipy.cluster.vq import vq, kmeans, whiten
fl = open('SentiWordNet.csv', 'r');
csvReader = csv.Reader(fl, delimiter = ',');
features = np.asarray(list(csvReader));
features_n = [];
for feature in features:
fea = [float(feature[0]), float(feature[1])]
features_n.append(fea)
features = np.asarray(list(features_n));
whitened = whiten(features)
book = array((whitened[0],whitened[2]))
kmeans(whitened,book)
random.seed((1000,2000))
codes = 5
kmeans(whitened,codes)