singhn9 commited on
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7e4ff22
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1 Parent(s): e16db89

Update app.py

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Files changed (1) hide show
  1. app.py +235 -25
app.py CHANGED
@@ -17,40 +17,249 @@ AMCS = [
17
  "UTI MF", "Axis MF", "Aditya Birla SL MF", "Mirae MF", "DSP MF"
18
  ]
19
 
 
 
 
20
  COMPANIES = [
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- "HDFC Bank", "ICICI Bank", "Bajaj Finance", "Bajaj Finserv", "Adani Ports",
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- "Tata Motors", "Shriram Finance", "HAL", "TCS", "AU Small Finance Bank",
23
- "Pearl Global", "Hindalco", "Tata Elxsi", "Cummins India", "Vedanta"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
24
  ]
25
 
 
 
 
26
  BUY_MAP = {
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- "SBI MF": ["Bajaj Finance", "AU Small Finance Bank"],
28
- "ICICI Pru MF": ["HDFC Bank"],
29
- "HDFC MF": ["Tata Elxsi", "TCS"],
30
- "Nippon India MF": ["Hindalco"],
31
- "Kotak MF": ["Bajaj Finance"],
32
- "UTI MF": ["Adani Ports", "Shriram Finance"],
33
- "Axis MF": ["Tata Motors", "Shriram Finance"],
34
- "Aditya Birla SL MF": ["AU Small Finance Bank"],
35
- "Mirae MF": ["Bajaj Finance", "HAL"],
36
- "DSP MF": ["Tata Motors", "Bajaj Finserv"]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
37
  }
38
 
 
 
 
39
  SELL_MAP = {
40
- "SBI MF": ["Tata Motors"],
41
- "ICICI Pru MF": ["Bajaj Finance", "Adani Ports"],
42
- "HDFC MF": ["HDFC Bank"],
43
- "Nippon India MF": ["Hindalco"],
44
- "Kotak MF": ["AU Small Finance Bank"],
45
- "UTI MF": ["Hindalco", "TCS"],
46
- "Axis MF": ["TCS"],
47
- "Aditya Birla SL MF": ["Adani Ports"],
48
- "Mirae MF": ["TCS"],
49
- "DSP MF": ["HAL", "Shriram Finance"]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
50
  }
51
 
52
- COMPLETE_EXIT = {"DSP MF": ["Shriram Finance"]}
53
- FRESH_BUY = {"HDFC MF": ["Tata Elxsi"], "UTI MF": ["Adani Ports"], "Mirae MF": ["HAL"]}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
54
 
55
  def sanitize_map(m):
56
  out = {}
@@ -58,6 +267,7 @@ def sanitize_map(m):
58
  out[k] = [v for v in vals if v in COMPANIES]
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  return out
60
 
 
61
  BUY_MAP = sanitize_map(BUY_MAP)
62
  SELL_MAP = sanitize_map(SELL_MAP)
63
  COMPLETE_EXIT = sanitize_map(COMPLETE_EXIT)
 
17
  "UTI MF", "Axis MF", "Aditya Birla SL MF", "Mirae MF", "DSP MF"
18
  ]
19
 
20
+ # ---------------------------
21
+ # COMPANIES (deduplicated + screenshot items)
22
+ # ---------------------------
23
  COMPANIES = [
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+ "Bajaj Finance","Adani Power","Infosys","ICICI Bank","HDFC Bank","NTPC",
25
+ "Power Grid Corporation Of India","Trent","Colgate-Palmolive (India)","ITC",
26
+ "Dixon Technologies (India)","Bank Of Maharashtra","Affle 3i",
27
+ "L&T Finance","Kotak Mahindra Bank","AU Small Finance Bank","Titan Company",
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+ "Hindustan Unilever","Mankind Pharma","Shriram Finance","Tata Motors","Eternal",
29
+ "Mahindra & Mahindra","Glenmark Pharmaceuticals","Sundaram Finance","Tata Consultancy Services",
30
+ "Axis Bank","Dr. Reddy's Laboratories","Muthoot Finance","Avenue Supermarts",
31
+ "UNO Minda","Jindal Steel","ACC","Tata Steel","Vedanta","Godrej Industries",
32
+ "Berger Paints India","Tata Motors Passenger Vehicles","Bajaj Finserv",
33
+ "Bharti Airtel","Larsen & Toubro","Maruti Suzuki India","HDFC Asset Management Co",
34
+ "One97 Communications","Hyundai Motor India","Power Finance Corporation",
35
+ "Solar Industries India","HPCL","Fortis Healthcare",
36
+ "CEAT","NMDC","Ashok Leyland",
37
+ "Tata Elxsi","Avanti Feeds","Karur Vysya Bank","Indian Bank",
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+ "Yatharth Hospital & Trauma Care","Dalmia Bharat","IREDA","HCC",
39
+ "Premier Energies","Welspon Corp","Zydus Lifesciences",
40
+ "Travel Food Services","Sai Silks (Kalamandir)",
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+ "Sumitomo Chemical India","Adani Ports and SEZ",
42
+ "CESC",
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+ "Canara Bank","MCX","Pearl Global Industries","Aditya Birla Lifestyle Brands",
44
+ "Angel One","Thyrocare Technologies","SJS Enterprises","Shilpa Medicare",
45
+ "Hindalco Industries","Tata Communications",
46
+ "Ujjivan Small Finance Bank","Steel Authority Of India",
47
+ "Shaily Engineering Plastics","Persistent Systems",
48
+ "Hindustan Aeronautics"
49
  ]
50
 
51
+ # ---------------------------
52
+ # BUY_MAP (from screenshot)
53
+ # ---------------------------
54
  BUY_MAP = {
55
+ "SBI MF": [
56
+ "Bajaj Finance",
57
+ "Adani Power",
58
+ "Infosys"
59
+ ],
60
+ "ICICI Pru MF": [
61
+ "ICICI Bank",
62
+ "HDFC Bank",
63
+ "NTPC"
64
+ ],
65
+ "HDFC MF": [
66
+ "HDFC Bank",
67
+ "ICICI Bank",
68
+ "Power Grid Corporation Of India",
69
+ "Trent"
70
+ ],
71
+ "Nippon India MF": [
72
+ "Trent",
73
+ "HDFC Bank",
74
+ "Colgate-Palmolive (India)",
75
+ "ITC"
76
+ ],
77
+ "Kotak MF": [
78
+ "ITC",
79
+ "HDFC Bank",
80
+ "L&T Finance"
81
+ ],
82
+ "UTI MF": [
83
+ "Dixon Technologies (India)",
84
+ "Bank Of Maharashtra",
85
+ "Affle 3i"
86
+ ],
87
+ "Axis MF": [
88
+ "Kotak Mahindra Bank",
89
+ "AU Small Finance Bank",
90
+ "Titan Company"
91
+ ],
92
+ "Aditya Birla SL MF": [
93
+ "Hindustan Unilever",
94
+ "Thyrocare Technologies",
95
+ "Mankind Pharma"
96
+ ],
97
+ "Mirae MF": [
98
+ "ICICI Bank",
99
+ "Shriram Finance"
100
+ ],
101
+ "DSP MF": [
102
+ "Tata Consultancy Services",
103
+ "Axis Bank"
104
+ ]
105
  }
106
 
107
+ # ---------------------------
108
+ # SELL_MAP (from screenshot)
109
+ # ---------------------------
110
  SELL_MAP = {
111
+ "SBI MF": [
112
+ "HDFC Bank",
113
+ "ICICI Bank",
114
+ "Adani Ports and SEZ"
115
+ ],
116
+ "ICICI Pru MF": [
117
+ "Bharti Airtel",
118
+ "Axis Bank",
119
+ "Larsen & Toubro",
120
+ "Maruti Suzuki India"
121
+ ],
122
+ "HDFC MF": [
123
+ "NTPC",
124
+ "Tata Consultancy Services"
125
+ ],
126
+ "Nippon India MF": [
127
+ "HDFC Asset Management Co",
128
+ "One97 Communications",
129
+ "Hyundai Motor India"
130
+ ],
131
+ "Kotak MF": [
132
+ "Power Finance Corporation",
133
+ "Solar Industries India",
134
+ "HPCL"
135
+ ],
136
+ "UTI MF": [
137
+ "Dr. Reddy's Laboratories",
138
+ "Bajaj Finance",
139
+ "Muthoot Finance",
140
+ "Avenue Supermarts"
141
+ ],
142
+ "Axis MF": [
143
+ "Bajaj Finance",
144
+ "UNO Minda",
145
+ "Jindal Steel"
146
+ ],
147
+ "Aditya Birla SL MF": [
148
+ "Fortis Healthcare",
149
+ "Mahindra & Mahindra",
150
+ "Suzlon Energy",
151
+ "Tata Steel",
152
+ "Vedanta",
153
+ "Ashok Leyland"
154
+ ],
155
+ "Mirae MF": [
156
+ "Berger Paints India",
157
+ "Godrej Industries"
158
+ ],
159
+ "DSP MF": [
160
+ "Bajaj Finance",
161
+ "Tata Motors Passenger Vehicles",
162
+ "Bajaj Finserv"
163
+ ]
164
+ }
165
+
166
+ # ---------------------------
167
+ # COMPLETE_EXIT (from screenshot)
168
+ # ---------------------------
169
+ COMPLETE_EXIT = {
170
+ "ICICI Pru MF": [
171
+ "Tata Elxsi",
172
+ "Avanti Feeds"
173
+ ],
174
+ "HDFC MF": [
175
+ "IREDA",
176
+ "HCC"
177
+ ],
178
+ "Nippon India MF": [
179
+ "Premier Energies",
180
+ "Welspon Corp",
181
+ "Zydus Lifesciences"
182
+ ],
183
+ "Kotak MF": [
184
+ "Travel Food Services",
185
+ "Colgate-Palmolive (India)"
186
+ ],
187
+ "UTI MF": [
188
+ "Bajaj Finserv",
189
+ "Sai Silks (Kalamandir)"
190
+ ],
191
+ "Axis MF": [
192
+ "Sumitomo Chemical India",
193
+ "Adani Ports and SEZ",
194
+ "CEAT",
195
+ "ACC"
196
+ ],
197
+ "Aditya Birla SL MF": [
198
+ # screenshot shows no complete-exit items under ABSL; keep empty list to be explicit
199
+ ],
200
+ "Mirae MF": [
201
+ "NMDC"
202
+ ],
203
+ "DSP MF": [
204
+ "Praj Industries"
205
+ ]
206
  }
207
 
208
+ # Ensure empty list for Aditya Birla SL if the language of the file requires it:
209
+ COMPLETE_EXIT["Aditya Birla SL MF"] = COMPLETE_EXIT.get("Aditya Birla SL MF", [])
210
+
211
+ # ---------------------------
212
+ # FRESH_BUY (from screenshot)
213
+ # ---------------------------
214
+ FRESH_BUY = {
215
+ "SBI MF": [
216
+ "Canara Bank",
217
+ "MCX"
218
+ ],
219
+ "ICICI Pru MF": [
220
+ "Pearl Global Industries",
221
+ "Aditya Birla Lifestyle Brands",
222
+ "Angel One"
223
+ ],
224
+ "HDFC MF": [
225
+ "Shriram Finance",
226
+ "Thyrocare Technologies",
227
+ "SJS Enterprises",
228
+ "Shilpa Medicare"
229
+ ],
230
+ "Nippon India MF": [
231
+ "UNO Minda",
232
+ "Hindalco Industries"
233
+ ],
234
+ "Kotak MF": [
235
+ "Pearl Global Industries"
236
+ ],
237
+ "UTI MF": [
238
+ "Tata Communications",
239
+ "Ujjivan Small Finance Bank",
240
+ "CESC"
241
+ ],
242
+ "Axis MF": [
243
+ "Adani Power",
244
+ "Steel Authority Of India",
245
+ "Shaily Engineering Plastics",
246
+ "Persistent Systems",
247
+ "Hindustan Aeronautics"
248
+ ],
249
+ "Aditya Birla SL MF": [
250
+ "Eternal",
251
+ "Hindustan Aeronautics",
252
+ "Ujjivan Small Finance Bank"
253
+ ],
254
+ "Mirae MF": [
255
+ # empty in screenshot
256
+ ],
257
+ "DSP MF": [
258
+ "Eternal",
259
+ "Hindustan Aeronautics",
260
+ "Ujjivan Small Finance Bank"
261
+ ]
262
+ }
263
 
264
  def sanitize_map(m):
265
  out = {}
 
267
  out[k] = [v for v in vals if v in COMPANIES]
268
  return out
269
 
270
+ # sanitize_map call will keep only items present in COMPANIES
271
  BUY_MAP = sanitize_map(BUY_MAP)
272
  SELL_MAP = sanitize_map(SELL_MAP)
273
  COMPLETE_EXIT = sanitize_map(COMPLETE_EXIT)