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)