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Merge pull request #5 from devfinwiz/deepsource-autofix-a9e8334b
Convert string with anomalous backslash into a raw string
2 parents 8a62914 + d4ec14f commit 482fe1f

15 files changed

+33
-33
lines changed

‎Auto generated Dataset/GarbageCollector.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -24,7 +24,7 @@ def find_csv(path_to_dir,suffix=".csv"):
2424
hold.append(name)
2525
print(hold)
2626

27-
with open("Auto generated Dataset\Tickers.csv",'r',newline='') as f:
27+
with open(r"Auto generated Dataset\Tickers.csv",'r',newline='') as f:
2828
reader=csv.reader(f)
2929
data=list(reader)
3030
#print(data)
@@ -53,7 +53,7 @@ def find_csv(path_to_dir,suffix=".csv"):
5353
#for check in hold:
5454
#os.remove(check)
5555

56-
with open("Auto generated Dataset\Tickers.csv",'w',newline='') as f:
56+
with open(r"Auto generated Dataset\Tickers.csv",'w',newline='') as f:
5757
writer=csv.writer(f)
5858
writer.writerows(lstoflst)
5959

‎Scipts/CSVGenerator.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -8,14 +8,14 @@ def dataset_generator():
88
#-------------------------------------------------------------
99
#Tickers.csv has the list of symbols of all NSE listed tickers
1010

11-
comp=csv.reader(open("Prerequisites-Outputs\Tickers.csv"))
11+
comp=csv.reader(open(r"Prerequisites-Outputs\Tickers.csv"))
1212
for c in comp:
1313

1414
symbol=c[0]
1515

1616
#Creation of individual CSVs for all listed tickers in Tickers.csv
1717

18-
history_filename="Auto generated Dataset\{}.csv".format(symbol)
18+
history_filename=r"Auto generated Dataset\{}.csv".format(symbol)
1919
f=open(history_filename,'w',newline="")
2020

2121
#---------------------------------------------------------------------------------

‎Scipts/Cufflinks Demo.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -11,7 +11,7 @@
1111

1212

1313
cf.set_config_file(theme='pearl',sharing='public',offline=True)
14-
apple_df = pd.read_csv('Auto generated Dataset\ABFRL.NS.csv', index_col=0, parse_dates=True)
14+
apple_df = pd.read_csv(r'Auto generated Dataset\ABFRL.NS.csv', index_col=0, parse_dates=True)
1515

1616
qf=cf.QuantFig(apple_df,title='ABFRL Quant Figure',legend='top',name='GS')
1717
qf.add_bollinger_bands()

‎Scipts/DiscountValuations.py

+3-3
Original file line numberDiff line numberDiff line change
@@ -14,7 +14,7 @@
1414
tickers_vas=[]
1515

1616
def discount_as_per_bv():
17-
with open("Auto generated Dataset\Valuations.csv",'r') as mf:
17+
with open(r"Auto generated Dataset\Valuations.csv",'r') as mf:
1818
data=csv.DictReader(mf)
1919

2020
for row in data:
@@ -41,7 +41,7 @@ def store(l1,l2,l3,l4,filename,aim): #aim: Valuation-Book Value or Valuation - S
4141
list_clubber=[l1,l2,l3,l4]
4242
export_data_complete=zip_longest(*list_clubber,fillvalue='')
4343

44-
with open("Auto generated Dataset\{}.csv".format(filename),'w',encoding="ISO-8859-1",newline="") as myfile:
44+
with open(r"Auto generated Dataset\{}.csv".format(filename),'w',encoding="ISO-8859-1",newline="") as myfile:
4545
wr=csv.writer(myfile)
4646
wr.writerow(("Ticker",aim,"LTP","Discount(%)"))
4747
wr.writerows(export_data_complete)
@@ -55,7 +55,7 @@ def store(l1,l2,l3,l4,filename,aim): #aim: Valuation-Book Value or Valuation - S
5555

5656

5757
def discount_as_per_sales():
58-
with open("Auto generated Dataset\Valuations.csv",'r') as mf:
58+
with open(r"Auto generated Dataset\Valuations.csv",'r') as mf:
5959
data=csv.DictReader(mf)
6060

6161
for row in data:

‎Scipts/Driver.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -26,7 +26,7 @@ def __init__(self):
2626
self.geometry(f"{App.WIDTH}x{App.HEIGHT}")
2727
self.protocol("WM_DELETE_WINDOW", self.on_closing) # call .on_closing() when app gets closed
2828

29-
self.bell_image = self.load_image("Prerequisites-Outputs\LOGOn.PNG",130,70)
29+
self.bell_image = self.load_image(r"Prerequisites-Outputs\LOGOn.PNG",130,70)
3030

3131
# ============ create two frames ============
3232

‎Scipts/FinancialsExtractor.py

+4-4
Original file line numberDiff line numberDiff line change
@@ -46,7 +46,7 @@ def financials_fetcher(ticker):
4646

4747
def thread_pool_executor():
4848

49-
comp=csv.reader(open("Prerequisites-Outputs\Tickers.csv"))
49+
comp=csv.reader(open(r"Prerequisites-Outputs\Tickers.csv"))
5050

5151
for c in comp:
5252
tickers_list.extend(c)
@@ -82,22 +82,22 @@ def thread_pool_executor():
8282
list_clubber=[ticker_results,tickers_book_value,tickers_evtoebitda,tickers_priceToBook,tickers_marketcap,tickers_priceToSales,tickers_close,tickers_sharesoutstanding,tickers_total_revenue]
8383
export_data=zip_longest(*list_clubber,fillvalue='')
8484

85-
with open("Auto generated Dataset\Financials.csv",'a',encoding="ISO-8859-1",newline='') as myfile:
85+
with open(r"Auto generated Dataset\Financials.csv",'a',encoding="ISO-8859-1",newline='') as myfile:
8686
wr=csv.writer(myfile)
8787
#wr.writerow(("Ticker","Book Value"))
8888
wr.writerows(export_data)
8989
myfile.close()
9090

9191
holder=[]
9292

93-
with open("Auto generated Dataset\Financials.csv",'r') as f:
93+
with open(r"Auto generated Dataset\Financials.csv",'r') as f:
9494
csvreader=csv.reader(f)
9595
for row in csvreader:
9696
holder.append(row)
9797
if not row[1]:
9898
holder.remove(row)
9999

100-
with open("Auto generated Dataset\Financials.csv",'w',newline='') as fw:
100+
with open(r"Auto generated Dataset\Financials.csv",'w',newline='') as fw:
101101
writer=csv.writer(fw)
102102
writer.writerows(holder)
103103
print("Success")

‎Scipts/FinancialsGarbageCollector.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -8,9 +8,9 @@
88

99
def fgarbage_collector():
1010

11-
f=open("Auto generated Dataset\FinancialsBunch.csv","w",newline="")
11+
f=open(r"Auto generated Dataset\FinancialsBunch.csv","w",newline="")
1212

13-
with open('Auto generated Dataset\Financials.csv',"r+") as mf:
13+
with open(r'Auto generated Dataset\Financials.csv',"r+") as mf:
1414
data=csv.DictReader(mf)
1515
wr=csv.writer(f)
1616
wr.writerow(("Ticker","Book Value","EVToEBITDA","PToBV","MarketCap","PToSales","Close","Shares Outstanding","Revenue"))

‎Scipts/FundamentalScreener.py

+3-3
Original file line numberDiff line numberDiff line change
@@ -46,7 +46,7 @@
4646
#Filters stocks that are trading 10% discount to their book value as compared to Last Traded Price
4747

4848
def book_value_filter():
49-
with open("Auto generated Dataset\Financials.csv",'r') as mf:
49+
with open(r"Auto generated Dataset\Financials.csv",'r') as mf:
5050
data=csv.DictReader(mf)
5151

5252
for row in data:
@@ -67,11 +67,11 @@ def book_value_filter():
6767
list_clubber_final_50=[tickers_gre_50,tickers_gre_50_bookval,tickers_gre_50_close]
6868
export_data_complete_50=zip_longest(*list_clubber_final_50,fillvalue='')
6969

70-
with open("Auto generated Dataset\Filtered_50_percent.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
70+
with open(r"Auto generated Dataset\Filtered_50_percent.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
7171
wr=csv.writer(myfile)
7272
wr.writerow(("Ticker","Book Value","LTP"))
7373
wr.writerows(export_data_complete_50)
7474

75-
with open("Auto generated Dataset\Filtered_50_percent.csv",'r') as f,open('Filtered_50_percentt.csv','w') as out_file:
75+
with open(r"Auto generated Dataset\Filtered_50_percent.csv",'r') as f,open('Filtered_50_percentt.csv','w') as out_file:
7676
out_file.writelines(unique_everseen(f))
7777

‎Scipts/Fundamental_Screener3.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -16,7 +16,7 @@
1616
#Filters stocks with attractive P/S of below 1.25 value
1717

1818
def pts_filter():
19-
with open("Auto generated Dataset\FinancialsBunch.csv",'r') as mf:
19+
with open(r"Auto generated Dataset\FinancialsBunch.csv",'r') as mf:
2020
data=csv.DictReader(mf)
2121

2222
for row in data:
@@ -41,7 +41,7 @@ def pts_filter():
4141
list_clubber=[tickers_name,tickers_MCap,tickers_PTS,tickers_close,tickers_bookval]
4242
export_data_complete=zip_longest(*list_clubber,fillvalue='')
4343

44-
with open("Auto generated Dataset\MCapPTS.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
44+
with open(r"Auto generated Dataset\MCapPTS.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
4545
wr=csv.writer(myfile)
4646
wr.writerow(("Ticker","Market Cap","P/S","LTP","Book Value"))
4747
wr.writerows(export_data_complete)

‎Scipts/GarbageCollector.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -35,7 +35,7 @@ def garbage_collector():
3535
if(len(csv_dict)<2):
3636
hold.append(name)
3737

38-
with open("Prerequisites-Outputs\Tickers.csv",'r',newline='') as f:
38+
with open(r"Prerequisites-Outputs\Tickers.csv",'r',newline='') as f:
3939
reader=csv.reader(f)
4040
data=list(reader)
4141
#print(data)
@@ -66,6 +66,6 @@ def garbage_collector():
6666
#for check in hold:
6767
#os.remove(check)
6868

69-
with open("Prerequisites-Outputs\Tickers.csv",'w',newline='') as f:
69+
with open(r"Prerequisites-Outputs\Tickers.csv",'w',newline='') as f:
7070
writer=csv.writer(f)
7171
writer.writerows(lstoflst)

‎Scipts/Mailer.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -17,7 +17,7 @@
1717
def mailer(emailto,fileToSend,username,password):
1818
emailfrom = '"DEV_FINWIZ"'
1919
emailto = "receiver's email"
20-
fileToSend = "Auto generated Dataset\Discount_Sales.csv"
20+
fileToSend = r"Auto generated Dataset\Discount_Sales.csv"
2121
username = "sender's email id"
2222
password = "sender's password here"
2323

‎Scipts/PatternRecognition.py

+5-5
Original file line numberDiff line numberDiff line change
@@ -68,7 +68,7 @@ def pattern_recognition_initializer(candles,index):
6868

6969

7070
def pattern_recognition():
71-
symbols_file=open("Prerequisites-Outputs\Tickers.csv")
71+
symbols_file=open(r"Prerequisites-Outputs\Tickers.csv")
7272
tickers=csv.reader(symbols_file)
7373

7474

@@ -77,7 +77,7 @@ def pattern_recognition():
7777

7878
ticker=company[0]
7979
try:
80-
history_file=open("Auto generated Dataset\{}.csv".format(ticker))
80+
history_file=open(r"Auto generated Dataset\{}.csv".format(ticker))
8181
except:
8282
continue
8383

@@ -110,23 +110,23 @@ def pattern_recognition():
110110
list_clubber=[bullishengulf,datee]
111111
export_data_complete=zip_longest(*list_clubber,fillvalue='')
112112

113-
with open("Prerequisites-Outputs\BullishEngulfing.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
113+
with open(r"Prerequisites-Outputs\BullishEngulfing.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
114114
wr=csv.writer(myfile)
115115
wr.writerow(("Ticker","Date Of Formation"))
116116
wr.writerows(export_data_complete)
117117

118118
list_clubberr=[bearishengulf,dateee]
119119
export_data_completee=zip_longest(*list_clubberr,fillvalue='')
120120

121-
with open("Prerequisites-Outputs\BearishEngulfing.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
121+
with open(r"Prerequisites-Outputs\BearishEngulfing.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
122122
wr=csv.writer(myfile)
123123
wr.writerow(("Ticker","Date Of Formation"))
124124
wr.writerows(export_data_completee)
125125

126126
list_clubberrr=[gravestone,dateeee]
127127
export_data_completeee=zip_longest(*list_clubberrr,fillvalue='')
128128

129-
with open("Prerequisites-Outputs\Gravestone.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
129+
with open(r"Prerequisites-Outputs\Gravestone.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
130130
wr=csv.writer(myfile)
131131
wr.writerow(("Ticker","Date Of Formation"))
132132
wr.writerows(export_data_completeee)

‎Scipts/Valuation.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -15,7 +15,7 @@
1515
#Computes fair value for all tickers as per their book value and as per their annual sales
1616

1717
def valuation_computer():
18-
with open("Auto generated Dataset\FinancialsBunch.csv",'r') as mf:
18+
with open(r"Auto generated Dataset\FinancialsBunch.csv",'r') as mf:
1919
data=csv.DictReader(mf)
2020

2121
for row in data:
@@ -50,7 +50,7 @@ def valuation_computer():
5050
list_clubber=[tickers,val_as_per_bv,val_as_per_pts,latest_close]
5151
export_data_complete=zip_longest(*list_clubber,fillvalue='')
5252

53-
with open("Auto generated Dataset\Valuations.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
53+
with open(r"Auto generated Dataset\Valuations.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
5454
wr=csv.writer(myfile)
5555
wr.writerow(("Ticker","Valuation As Per Book Value","Valuation As Per Sales","LTP"))
5656
wr.writerows(export_data_complete)

‎Scipts/evebitda_screening.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -16,7 +16,7 @@
1616
#Filters stocks with EV/EBITDA ratio in range 0-10, stores the resultant dataset in EVToEbitda_Output.csv
1717

1818
def ev_ebitda_filter():
19-
with open("Auto generated Dataset\FinancialsBunch.csv",'r') as mf:
19+
with open(r"Auto generated Dataset\FinancialsBunch.csv",'r') as mf:
2020
data=csv.DictReader(mf)
2121

2222
for row in data:
@@ -41,7 +41,7 @@ def ev_ebitda_filter():
4141
list_clubber=[tickers_name,tickers_EV,tickers_PTS,tickers_close,tickers_bookval]
4242
export_data_complete=zip_longest(*list_clubber,fillvalue='')
4343

44-
with open("Prerequisites-Outputs\EVToEbitda_Output.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
44+
with open(r"Prerequisites-Outputs\EVToEbitda_Output.csv",'w',encoding="ISO-8859-1",newline="") as myfile:
4545
wr=csv.writer(myfile)
4646
wr.writerow(("Ticker","EVToEBITDA","P/S","LTP","Book Value"))
4747
wr.writerows(export_data_complete)

‎Scipts/talibtest.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -4,7 +4,7 @@
44
import numpy
55
import csv
66

7-
symbols_file=open("Auto generated Dataset\Tickers.csv",'r')
7+
symbols_file=open(r"Auto generated Dataset\Tickers.csv",'r')
88
tickers=csv.reader(symbols_file)
99

1010
def can_strat(openn,high,low,close):

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