jupyterlab variable values change automaticaly

[RS12792]

Dear all,
i am runnig a code set under while loop but its not working as it working under pycharm
the 'symbols': '{\ added every time in previous value of symbol variable
please guide how to fixed it

code i am using
if tnow > '09:14:00' and symbol_list == 0:
print("donelist")
symbol = []
data = {"symbols":"NSE:NIFTY50-INDEX"}
response = fyersh.quotes(data=data)
#print(response)
ltp = response["d"][0].get("v").get("lp")
ltp = int(round(ltp / 50) * 50)
#symbol.clear()
pe_ce_strik_genarator(ltp, s_diff, striks) (function that generat striks)
print(symbol)
symbol = str(symbol)
symbol = symbol.replace(" ",'').replace("'",'').replace("[","").replace("]","")
#%store symbol
print(symbol)
symbol_list = 1
straddle_position = c.execute(f"SELECT value FROM variables WHERE name = 'straddle_position'").fetchone()[0]
#print(straddle_position)
straddle_tp_sl = c.execute(f"SELECT value FROM variables WHERE name = 'straddle_tp_sl'").fetchone()[0]
#print(straddle_tp_sl)
if(straddle_tp_sl == 0 and straddle_position == 0 and tnow > '09:16:00' and tnow < '23:50:00'):
#%store -r symbol
symbol = {"symbols":f"{symbol}"}
print(symbol)
response = fyersh.quotes(data=symbol)
#print(response)
response = response['d']
data = []
#data.clear()
for i in response:
sym = i['v']
op_type = sym["symbol"][-2:]
op_strik = sym["symbol"][-7:-2]
sym['type'] = op_type
sym['strik'] = op_strik
#print(op_strik)
#print(op_type)
#print(sym)
data.append(sym)
df = pd.DataFrame(data)
#print(data)
df['diff'] = df['strik'].apply(diff)
ndf = df.get(["tt", "symbol", "volume", "lp", "type", "strik", "diff"])
ndfs = ndf.sort_values(by=['diff'])
spsd = ndfs.loc[(ndf['diff'] < 20),['strik']]
fsp = int(spsd.iloc[0]['strik'])
#print(ndf)
print(ndfs)
print(fsp)
#cedf = ndf.loc[(ndf['type'] == 'CE') & (ndf['lp'] >90) & (ndf['lp'] < 110), ['strik', 'diff', 'type','lp']]
#cedf = cedf.sort_values(by=['lp'])
#sp_ce = int(cedf.iloc[0]['strik'])
#print(cedf)
#print(sp_ce)
#pedf = ndf.loc[(ndf['type'] == 'PE') & (ndf['lp'] >90) & (ndf['lp'] < 110), ['strik', 'diff', 'type', 'lp']]
#pedf = pedf.sort_values(by=['lp'])
#sp_pe = int(pedf.iloc[0]['strik'])
#print(pedf)
#print(sp_pe)
if fsp > 1 :
ce = f"{exch}:{underline}{YY}{M}{dd}{fsp}{ce}"[-21:]
pe = f"{exch}:{underline}{YY}{M}{dd}{fsp}{pe}"[-21:]
c.execute(f"update variables SET value = '{pe}' where name = 'straddle_pe_strik'")
c.execute(f"update variables SET value = '{ce}' where name = 'straddle_ce_strik'")
sql.commit()
print(ce)
print(pe)
#sell_straddle(lot=lot)
print("selling done")
time.sleep(10)
out of cell
donelist
['NSE:NIFTY2450222600CE', 'NSE:NIFTY2450222600PE', 'NSE:NIFTY2450222650CE', 'NSE:NIFTY2450222650PE', 'NSE:NIFTY2450222700CE', 'NSE:NIFTY2450222700PE', 'NSE:NIFTY2450222750CE', 'NSE:NIFTY2450222750PE', 'NSE:NIFTY2450222800CE', 'NSE:NIFTY2450222800PE', 'NSE:NIFTY2450222550CE', 'NSE:NIFTY2450222550PE', 'NSE:NIFTY2450222500CE', 'NSE:NIFTY2450222500PE', 'NSE:NIFTY2450222450CE', 'NSE:NIFTY2450222450PE', 'NSE:NIFTY2450222400CE', 'NSE:NIFTY2450222400PE', 'NSE:NIFTY2450222350CE', 'NSE:NIFTY2450222350PE']
NSE:NIFTY2450222600CE,NSE:NIFTY2450222600PE,NSE:NIFTY2450222650CE,NSE:NIFTY2450222650PE,NSE:NIFTY2450222700CE,NSE:NIFTY2450222700PE,NSE:NIFTY2450222750CE,NSE:NIFTY2450222750PE,NSE:NIFTY2450222800CE,NSE:NIFTY2450222800PE,NSE:NIFTY2450222550CE,NSE:NIFTY2450222550PE,NSE:NIFTY2450222500CE,NSE:NIFTY2450222500PE,NSE:NIFTY2450222450CE,NSE:NIFTY2450222450PE,NSE:NIFTY2450222400CE,NSE:NIFTY2450222400PE,NSE:NIFTY2450222350CE,NSE:NIFTY2450222350PE
{'symbols': 'NSE:NIFTY2450222600CE,NSE:NIFTY2450222600PE,NSE:NIFTY2450222650CE,NSE:NIFTY2450222650PE,NSE:NIFTY2450222700CE,NSE:NIFTY2450222700PE,NSE:NIFTY2450222750CE,NSE:NIFTY2450222750PE,NSE:NIFTY2450222800CE,NSE:NIFTY2450222800PE,NSE:NIFTY2450222550CE,NSE:NIFTY2450222550PE,NSE:NIFTY2450222500CE,NSE:NIFTY2450222500PE,NSE:NIFTY2450222450CE,NSE:NIFTY2450222450PE,NSE:NIFTY2450222400CE,NSE:NIFTY2450222400PE,NSE:NIFTY2450222350CE,NSE:NIFTY2450222350PE'}
tt symbol volume lp type strik diff
2 1714521600 NSE:NIFTY2450222650CE 54390475 74.40 CE 22650 3.60
3 1714521600 NSE:NIFTY2450222650PE 72032975 78.00 PE 22650 3.60
0 1714521600 NSE:NIFTY2450222600CE 53069325 105.00 CE 22600 44.85
1 1714521600 NSE:NIFTY2450222600PE 105136725 60.15 PE 22600 44.85
4 1714521600 NSE:NIFTY2450222700CE 168286825 47.40 CE 22700 54.60
5 1714521600 NSE:NIFTY2450222700PE 156388550 102.00 PE 22700 54.60
10 1714521600 NSE:NIFTY2450222550CE 9891675 140.95 CE 22550 94.95
11 1714521600 NSE:NIFTY2450222550PE 46309350 46.00 PE 22550 94.95
6 1714521600 NSE:NIFTY2450222750CE 140323100 28.00 CE 22750 106.35
7 1714521600 NSE:NIFTY2450222750PE 92238300 134.35 PE 22750 106.35
13 1714521600 NSE:NIFTY2450222500PE 89741425 35.00 PE 22500 140.80
12 1714521600 NSE:NIFTY2450222500CE 17044375 175.80 CE 22500 140.80
9 1714521600 NSE:NIFTY2450222800PE 76818450 170.65 PE 22800 154.65
8 1714521600 NSE:NIFTY2450222800CE 173021475 16.00 CE 22800 154.65
14 1714521600 NSE:NIFTY2450222450CE 1938725 217.95 CE 22450 191.55
15 1714521600 NSE:NIFTY2450222450PE 41362150 26.40 PE 22450 191.55
16 1714521600 NSE:NIFTY2450222400CE 3200325 260.15 CE 22400 240.75
17 1714521600 NSE:NIFTY2450222400PE 58798475 19.40 PE 22400 240.75
18 1714521600 NSE:NIFTY2450222350CE 363075 305.20 CE 22350 291.85
19 1714521600 NSE:NIFTY2450222350PE 33641900 13.35 PE 22350 291.85
22650
NSE:NIFTY2450222650CE
NSE:NIFTY2450222650PE
selling done
{'symbols': "{'symbols': 'NSE:NIFTY2450222600CE,NSE:NIFTY2450222600PE,NSE:NIFTY2450222650CE,NSE:NIFTY2450222650PE,NSE:NIFTY2450222700CE,NSE:NIFTY2450222700PE,NSE:NIFTY2450222750CE,NSE:NIFTY2450222750PE,NSE:NIFTY2450222800CE,NSE:NIFTY2450222800PE,NSE:NIFTY2450222550CE,NSE:NIFTY2450222550PE,NSE:NIFTY2450222500CE,NSE:NIFTY2450222500PE,NSE:NIFTY2450222450CE,NSE:NIFTY2450222450PE,NSE:NIFTY2450222400CE,NSE:NIFTY2450222400PE,NSE:NIFTY2450222350CE,NSE:NIFTY2450222350PE'}"}
'symbol'
{'symbols': '{'symbols': "{'symbols': 'NSE:NIFTY2450222600CE,NSE:NIFTY2450222600PE,NSE:NIFTY2450222650CE,NSE:NIFTY2450222650PE,NSE:NIFTY2450222700CE,NSE:NIFTY2450222700PE,NSE:NIFTY2450222750CE,NSE:NIFTY2450222750PE,NSE:NIFTY2450222800CE,NSE:NIFTY2450222800PE,NSE:NIFTY2450222550CE,NSE:NIFTY2450222550PE,NSE:NIFTY2450222500CE,NSE:NIFTY2450222500PE,NSE:NIFTY2450222450CE,NSE:NIFTY2450222450PE,NSE:NIFTY2450222400CE,NSE:NIFTY2450222400PE,NSE:NIFTY2450222350CE,NSE:NIFTY2450222350PE'}"}'}
'symbol'
{'symbols': '{'symbols': '{\'symbols\': "{\'symbols\': \'NSE:NIFTY2450222600CE,NSE:NIFTY2450222600PE,NSE:NIFTY2450222650CE,NSE:NIFTY2450222650PE,NSE:NIFTY2450222700CE,NSE:NIFTY2450222700PE,NSE:NIFTY2450222750CE,NSE:NIFTY2450222750PE,NSE:NIFTY2450222800CE,NSE:NIFTY2450222800PE,NSE:NIFTY2450222550CE,NSE:NIFTY2450222550PE,NSE:NIFTY2450222500CE,NSE:NIFTY2450222500PE,NSE:NIFTY2450222450CE,NSE:NIFTY2450222450PE,NSE:NIFTY2450222400CE,NSE:NIFTY2450222400PE,NSE:NIFTY2450222350CE,NSE:NIFTY2450222350PE\'}"}'}'}