dQQcHqn3

1import h5py
2import numpy as np
3import pandas as pd
4
5from datetime import datetime
6from os import listdir
7from pandas import HDFStore
8
9
10def maintainLedger(mode, tick, lastBuyy = 0, lastSell = 0, quan = 0, prof = 0):
11    """THIS FUNCTION WRITES AND READS TRANSACTION DETAILS.
12       mode = 0 - IF FILE EXITS, READ FILE
13       mode = 1 - IF FILE EXITS, APPEND TO FILE"""
14
15    # CHECK IF LEDGER FILE EXISTS, IF NOT CREATE A LEDGER FILE FOR THE FIRST TIME
16    path = r'ledger'
17    suff = r'h5'
18    flie = listdir(path)
19    flie = [item for item in flie if item.endswith(suff)]
20
21    if len(flie) == 0:
22        HDF5Data = HDFStore('ledger/ledger.h5')
23
24        # GENERATE NEW VALUES OF DATE/TIME
25        mi = int(datetime.now().minute)
26        ho = int(datetime.now().hour)
27        da = int(datetime.now().day)
28        we = int(datetime.now().isocalendar()[1])
29        mo = int(datetime.now().month)
30        ye = int(datetime.now().year)
31
32        newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
33        newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
34        HDF5Data.put('data', newwData, format = 'table', data_columns = True)
35        HDF5Data.close()
36
37    elif len(flie) == 1:
38        if mode == 0:
39            # READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME
40            readData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
41
42            # DO SOMETHING...
43
44        elif mode == 1:
45            # GENERATE NEW VALUES OF DATE/TIME
46            mi = int(datetime.now().minute)
47            ho = int(datetime.now().hour)
48            da = int(datetime.now().day)
49            we = int(datetime.now().isocalendar()[1])
50            mo = int(datetime.now().month)
51            ye = int(datetime.now().year)
52
53            # GATHER NEW DATA INTO NUMPY ARRAY AND CONVERT TO PANDAS DATAFRAME
54            newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
55            newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
56
57            # READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME AND APPEND NEW DATA
58            readData = pd.read_hdf('ledger/ledger.h5', mode = 'a')
59            readData.append('data', newwData)
60
61            tempData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
62            print(tempData)
63
64        else:
65            print('Please check input data for errors!')
66
67
68
69if __name__ == '__main__':
70    maintainLedger(1, "AAPL")
71	
72TypeError: cannot concatenate object of type "<class 'str'>"; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid
73	
74import h5py
75import numpy as np
76import pandas as pd
77
78from datetime import datetime
79from os import listdir
80from pandas import HDFStore
81
82
83def maintainLedger(mode, tick = 'QUERY', lastBuyy = 0, lastSell = 0, quan = 0, prof = 0):
84    """THIS FUNCTION WRITES AND READS TRANSACTION DETAILS.
85       mode = 0 - IF FILE EXITS, READ FILE
86       mode = 1 - IF FILE EXITS, APPEND TO FILE"""
87
88    # CHECK IF LEDGER FILE EXISTS, IF NOT CREATE A LEDGER FILE FOR THE FIRST TIME
89    path = r'ledger'
90    suff = r'h5'
91    flie = listdir(path)
92    flie = [item for item in flie if item.endswith(suff)]
93
94    if len(flie) == 0:
95        # GENERATE NEW VALUES OF DATE/TIME
96        mi = int(datetime.now().minute)
97        ho = int(datetime.now().hour)
98        da = int(datetime.now().day)
99        we = int(datetime.now().isocalendar()[1])
100        mo = int(datetime.now().month)
101        ye = int(datetime.now().year)
102
103        # GATHER NEW DATA INTO NUMPY ARRAY AND CONVERT TO PANDAS DATAFRAME
104        newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
105        newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
106
107        # SAVE ALL DATA INTO .H5 FORMAT
108        HDF5Data = HDFStore('ledger/ledger.h5')
109        HDF5Data.put('data', newwData, format = 'table', data_columns = True)
110        HDF5Data.close()
111
112    elif len(flie) == 1:
113        if mode == 0:
114            """THIS OPTION ENABLES CODE TO READ DATA."""
115
116            # READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME
117            readData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
118
119            # DO SOMETHING...
120            print(readData)
121
122        elif mode == 1:
123            """THIS OPTION ENABLES CODE TO APPEND DATA."""
124
125            # GENERATE NEW VALUES OF DATE/TIME
126            mi = int(datetime.now().minute)
127            ho = int(datetime.now().hour)
128            da = int(datetime.now().day)
129            we = int(datetime.now().isocalendar()[1])
130            mo = int(datetime.now().month)
131            ye = int(datetime.now().year)
132
133            # GATHER NEW DATA INTO NUMPY ARRAY AND CONVERT TO PANDAS DATAFRAME
134            newwData = np.array([mode, mi, ho, da, we, mo, ye, tick, lastBuyy, lastSell, quan, prof]).reshape(1, 12)
135            newwData = pd.DataFrame(newwData, columns = ['mode', 'mi', 'ho', 'da', 'we', 'mo', 'ye', 'tick', 'laBu', 'laSe', 'quan', 'prof'])
136
137            # READ PREVIOUSLY SAVED DATA AS PANDAS DATAFRAME AND APPEND NEW DATA
138            readData = pd.read_hdf('ledger/ledger.h5', mode = 'r')
139            readData = readData.append(newwData)
140
141            # SAVE ALL DATA INTO .H5 FORMAT
142            HDF5Data = HDFStore('ledger/ledger.h5')
143            HDF5Data.put('data', readData, format = 'table', data_columns = True)
144            HDF5Data.close()
145
146        else:
147            print('Please check input data for errors!')
148
149
150
151if __name__ == '__main__':
152    maintainLedger(1, 'MSFT')