def convert_schwab_pos_file(infile, file=None):
'''Convert Positions export (.CSV) from Schwab to Fidelity format.'''
stamp = infile.split('_')[-1]
stamp = stamp.split('.')[0]
with open(infile) as csv:
acct_num = csv.readline().split()[4]
acct_num = acct_num.replace('XXXX', os.path.basename(infile)[:4])
outfile = 'fi' + acct_num + '_' + stamp + '.pos'
def pos(values, outfile, acct_num=acct_num, **kwargs):
symbol = values[0]
description = values[1][:40]
quantity = float(values[2])
# values[3] == price
# values[4] == price change $
# values[5] == price change %
# values[6] == market value
# values[7] == day change $
# values[8] == day change %
# values[9] == Cost Basis
# values[10] == Gain/Loss $
# values[11] == Gain/Loss %
# values[12] == Reinvest Dividends?
# values[13] == Capital Gains?
# values[14] == % Of Account
# values[15] == Security Type
#"SPY","S P D R S&P 500 ETF TR EXPIRES 01/22/2118","117","$204.50","-$0.48","-0.23%","$23,926.50","-$56.16","-0.23%","$17,508.94","$6,417.56","+36.65%","No","--","62.16%","ETFs & Closed End Funds",
#"BUFBX","BUFFALO FLEXIBLE INCOME FUND","961.733","$14.32","-$0.02","-0.14%","$13,772.02","-$19.23","-0.14%","$12,600.00","$1,172.02","+9.3%","No","No","35.78%","Mutual Fund",
#"Cash & Money Market","--","--","--","--","--","$796.11","$0.00","0%","--","--","--","--","--","2.07%","Cash and Money Market",
#"Account Total","--","--","--","--","--","$38,494.63","-$75.39","-0.2%","$30,108.94","$7,589.58","+25.21%","--","--","--","--",
sec_type = '' #values[2] and 'mf' # Mutual Funds only from TIAA-CREF
symbol = values[3].lower()
quantity = float(values[4])
amount = float(values[5])
# Other values
acct_type = 1 # Cash account
cusip = ''
trade_date_quantity = settle_date_quantity = quantity
close_price = '' # >15.05f
dts = os.path.basename(outfile)[2:8]
date_str = '20{}{}'.format(dts[-2:],
dts[:-2]) # Convert MMDDYY to YYYYMMDD
factor = face_amount = clean_price = factored = ''
option_symbol = ''
rep1 = '000' # Apparently C&D-specific values
rep2 = 'J62' # Apparently C&D-specific values
# NOTE: Verify the need for closing_price, cusip, and description
output = (
'{acct_num:14} {acct_type:1d} {cusip:9} {symbol:9} '
'{trade_date_quantity:>15.05f} {settle_date_quantity:>15.05f} '
'{close_price:15} {description:40} {date_str:8} '
'{factor:17} {face_amount:18} {clean_price:18} {factored:1} '
'{sec_type:2} {option_symbol:30} {rep1:3}{rep2:3}')
return output.format(**locals())
return convert_csv(infile, outfile, pos, file, mode='a', headers=3)
def get_headers(self,file):
'''
given a csv file, it will return the headers
(first row), as a list
'''
with open(file, 'r') as csv:
header_string = csv.readline()
return header_string.split(',')
def convert_schwab_pos_file(infile, file=None):
'''Convert Positions export (.CSV) from Schwab to Fidelity format.'''
stamp = infile.split('_')[-1]
stamp = stamp.split('.')[0]
with open(infile) as csv:
acct_num = csv.readline().split()[4]
acct_num = acct_num.replace('XXXX', os.path.basename(infile)[:4])
outfile = 'fi' + acct_num + '_' + stamp + '.pos'
def pos(values, outfile, acct_num=acct_num, **kwargs):
symbol = values[0]
description = values[1][:40]
quantity = float(values[2])
# values[3] == price
# values[4] == price change $
# values[5] == price change %
# values[6] == market value
# values[7] == day change $
# values[8] == day change %
# values[9] == Cost Basis
# values[10] == Gain/Loss $
# values[11] == Gain/Loss %
# values[12] == Reinvest Dividends?
# values[13] == Capital Gains?
# values[14] == % Of Account
# values[15] == Security Type
#"SPY","S P D R S&P 500 ETF TR EXPIRES 01/22/2118","117","$204.50","-$0.48","-0.23%","$23,926.50","-$56.16","-0.23%","$17,508.94","$6,417.56","+36.65%","No","--","62.16%","ETFs & Closed End Funds",
#"BUFBX","BUFFALO FLEXIBLE INCOME FUND","961.733","$14.32","-$0.02","-0.14%","$13,772.02","-$19.23","-0.14%","$12,600.00","$1,172.02","+9.3%","No","No","35.78%","Mutual Fund",
#"Cash & Money Market","--","--","--","--","--","$796.11","$0.00","0%","--","--","--","--","--","2.07%","Cash and Money Market",
#"Account Total","--","--","--","--","--","$38,494.63","-$75.39","-0.2%","$30,108.94","$7,589.58","+25.21%","--","--","--","--",
sec_type = '' #values[2] and 'mf' # Mutual Funds only from TIAA-CREF
symbol = values[3].lower()
quantity = float(values[4])
amount = float(values[5])
# Other values
acct_type = 1 # Cash account
cusip = ''
trade_date_quantity = settle_date_quantity = quantity
close_price = '' # >15.05f
dts = os.path.basename(outfile)[2:8]
date_str = '20{}{}'.format(dts[-2:], dts[:-2]) # Convert MMDDYY to YYYYMMDD
factor = face_amount = clean_price = factored = ''
option_symbol = ''
rep1 = '000' # Apparently C&D-specific values
rep2 = 'J62' # Apparently C&D-specific values
# NOTE: Verify the need for closing_price, cusip, and description
output = ('{acct_num:14} {acct_type:1d} {cusip:9} {symbol:9} '
'{trade_date_quantity:>15.05f} {settle_date_quantity:>15.05f} '
'{close_price:15} {description:40} {date_str:8} '
'{factor:17} {face_amount:18} {clean_price:18} {factored:1} '
'{sec_type:2} {option_symbol:30} {rep1:3}{rep2:3}')
return output.format(**locals())
return convert_csv(infile, outfile, pos, file, mode='a', headers=3)
def load_csv(filepath):
"""Read and convert a CSV file in the prettytable format."""
csv = open(filepath, 'r')
for i in range(2):
csv.readline() # skip the first two lines
lin = csv.readline()
f, p_0, p_1 = [], [], []
while lin != "":
if lin.count('+') == 5:
pass
else:
dat = lin.split('|')
f_i = float(dat[1].strip())
p0_i = float(dat[2].strip())
p1_i = float(dat[3].strip())
f.append(f_i)
p_0.append(p0_i)
p_1.append(p1_i)
lin = csv.readline()
csv.close()
return f, p_0, p_1
def getOffsetsAndSensitivity(boardNo):
i=1
fileName=boardNo+'.csv'
csv=open(fileName, 'r')
hdr = csv.readline()
hdr = hdr.strip().split(',')
d = defaultdict(list)
for line in csv:
row = line.strip().split(',')
for i in range(len(hdr)):
key = str(hdr[i])
value = str(row[i])
d[key].append(value)
csv.close()
return d
def _get_row_by_line_num(self, line_num):
csv = codecs.open(self.file.name, self.file.mode, self.file.encoding)
count = 0
while True:
line = csv.readline()
count += 1
if count == line_num + 1:
break
delimiter = '%s%s%s' % (self.dialect.quotechar, self.dialect.delimiter, self.dialect.quotechar)
line = line.lstrip(self.dialect.quotechar).rstrip(self.dialect.quotechar)
line = line.split(delimiter)
line_dict = {}
for field in self.data.fieldnames:
index = self.data.fieldnames.index(field)
line_dict[field] = line[index]
return line_dict
def getOffsetsAndSensitivity(self):
# i=1
fileName = self.O3boardNo + '.csv'
csv = open(fileName, 'r')
hdr = csv.readline()
hdr = hdr.strip().split(',')
self.gasOffsetsAndSensitivity = defaultdict(list)
lines = csv.readlines()
for line in lines:
row = line.strip().split(',')
for i in range(1, len(hdr)):
key = str(hdr[i])
value = str(row[i])
self.gasOffsetsAndSensitivity[key].append(value)
csv.close()
return self.gasOffsetsAndSensitivity
def read_csv2(path):
csv = open(path, 'r')
data = []
keys = []
# collect keys from 1st line and init data
for i in csv.readline().rstrip().split(','):
keys.append(i)
# fill data with values
for i in csv.readlines():
obj = {}
for key, val in zip(keys, i.rstrip().split(',')):
if re.match(r'\d*\.?\d+', val):
obj[key] = float(val)
else:
obj[key] = val
data.append(obj)
return data
ax.imshow(img)
for (x1,y1,x2,y2) in orig_coords:
rect = Rectangle((x1,y1),x2-x1, y2-y1, edgecolor='r', fill=False)
ax.add_patch(rect)
plt.show()
def test_crop_results(img, orig_coords, region, percent):
print(orig_coords)
cropped_img, cropped_coords = crop(img, orig_coords, region, percent)
print(cropped_coords)
show_img_with_fractions(img, orig_coords, cropped_img=cropped_img, cropped_coords=cropped_coords)
from PIL import Image
csv = open(CSV_SAVE_PATH + '\\new_validation_' + extension[1:] + '.csv', 'r')
img_path, x1, y1, x2, y2, _ = csv.readline().split(',')
orig_coords = np.array([[int(x1), int(y1), int(x2), int(y2)]])
while True:
new_img_path, x1, y1, x2, y2, _ = csv.readline().split(',')
if new_img_path != img_path:
break
orig_coords = np.append(orig_coords, [[int(x1), int(y1), int(x2), int(y2)]], axis=0)
if __name__ == '__main__':
TL = 1
ML = 2
BR = 3
TM = 4
MM = 5
BM = 6
TR = 7
import os import csv import fileinput dirs = os.listdir(os.getcwd()+'/csv') for f in dirs: csv=open(f,'r') print csv.readline()
def readdata(fname):
print(f"readdata: reading from File: {fname}")
csv = open(fname, mode="r")
csv.readline()
return csv