1 | JAMB registration numbers |
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2 | ************************* |
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3 | |
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4 | .. :doctest: |
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5 | |
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6 | JAMB data is stored in a JAMBDataTable. |
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7 | |
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8 | Creating JAMB Tables |
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9 | ==================== |
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10 | |
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11 | We can import JAMB registration data from a regular CSV file: |
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12 | |
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13 | >>> datafile = 'jambsample.csv' |
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14 | >>> open(datafile, 'wb').write( |
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15 | ... '''reg_no,fst_sit_fname,lastname,firstname,middlenames,sex,date_of_birth,jamb_state,jamb_lga,course1,screening_date,screening_venue,entry_session,screening_type |
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16 | ... 91100546DD,ISUOSUO MOSES ODOMERO,ISUOSUO,MOSES,ODOMERO,M,25/5/1982,DEL,ISO-S,BSCPOL,2009/09/25 09:00:00 GMT+1,REPRINT SLIP AS FROM WED 23/09/2009,9,pde |
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17 | ... 91111834CC,DURUIHEOMA AUGUSTINA ADANNA,DURUIHEOMA,AUGUSTINA,ADANNA,F,15/4/1986,IMO,MBAIT,BSCPOL,2009/09/25 09:00:00 GMT+1,REPRINT SLIP AS FROM WED 23/09/2009,9,pde |
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18 | ... 91109351AC,ARISERE EBIKEBUNA COMFORT,ARISERE,EBIKEBUNA,COMFORT,F,6/1/1984,EDO,OV-SW,BSCPOL,2009/09/25 09:00:00 GMT+1,REPRINT SLIP AS FROM WED 23/09/2009,9,pde |
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19 | ... ''') |
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20 | |
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21 | JAMB CSV tables have to provide the following header fields in the |
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22 | first line: |
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23 | |
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24 | >>> from pprint import pprint |
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25 | >>> from waeup.sirp.jambtables.jambtables import JAMB_DATA_HEADERS |
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26 | >>> JAMB_DATA_HEADERS |
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27 | ['firstname', 'lastname', 'middlenames', 'screening_type', |
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28 | 'screening_venue', 'reg_no', 'sex', 'course1', 'jamb_state', |
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29 | 'screening_date', 'jamb_lga', 'fst_sit_fname', 'date_of_birth'] |
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30 | |
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31 | Now we create a JAMBDataTable and import the data: |
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32 | |
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33 | >>> from waeup.sirp.jambtables import JAMBDataTable |
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34 | >>> table = JAMBDataTable() |
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35 | >>> len(list(table)) |
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36 | 0 |
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37 | |
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38 | >>> table.importFromCSV(datafile) |
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39 | >>> len(list(table)) |
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40 | 3 |
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41 | |
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42 | Accessing JAMB Data |
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43 | =================== |
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44 | |
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45 | Getting Entries |
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46 | --------------- |
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47 | |
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48 | We can get the entries from the table as an iterator: |
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49 | |
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50 | >>> from pprint import pprint |
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51 | >>> entries = [x for x in table] |
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52 | >>> pprint(entries) |
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53 | [{'course1': u'BSCPOL', |
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54 | 'date_of_birth': datetime.date(1982, 5, 25), |
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55 | 'entry_session': '9', |
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56 | 'firstname': u'MOSES', |
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57 | 'fst_sit_fname': u'ISUOSUO MOSES ODOMERO', |
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58 | 'jamb_lga': u'ISO-S', |
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59 | 'jamb_state': u'DEL', |
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60 | 'lastname': u'ISUOSUO', |
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61 | 'middlenames': u'ODOMERO', |
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62 | 'reg_no': u'91100546DD', |
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63 | 'screening_date': u'2009/09/25 09:00:00 GMT+1', |
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64 | 'screening_type': u'pde', |
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65 | 'screening_venue': u'REPRINT SLIP AS FROM WED 23/09/2009', |
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66 | 'sex': u'M'}, |
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67 | {...}, |
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68 | {...}] |
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69 | |
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70 | Also a :meth:`keys` and :meth:`items` method are available. They both |
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71 | return an iterator. |
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72 | |
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73 | The :meth:`keys` method in action: |
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74 | |
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75 | >>> pprint(list(table.keys())) |
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76 | [u'91100546DD', u'91111834CC', u'91109351AC'] |
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77 | |
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78 | The :meth:`items` method in action: |
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79 | |
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80 | >>> pprint(list(table.items())) |
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81 | [(u'91100546DD', |
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82 | {'course1': u'BSCPOL', |
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83 | 'date_of_birth': datetime.date(1982, 5, 25), |
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84 | 'entry_session': '9', |
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85 | 'firstname': u'MOSES', |
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86 | 'fst_sit_fname': u'ISUOSUO MOSES ODOMERO', |
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87 | 'jamb_lga': u'ISO-S', |
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88 | 'jamb_state': u'DEL', |
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89 | 'lastname': u'ISUOSUO', |
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90 | 'middlenames': u'ODOMERO', |
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91 | 'reg_no': u'91100546DD', |
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92 | 'screening_date': u'2009/09/25 09:00:00 GMT+1', |
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93 | 'screening_type': u'pde', |
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94 | 'screening_venue': u'REPRINT SLIP AS FROM WED 23/09/2009', |
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95 | 'sex': u'M'}), |
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96 | (u'91111834CC', |
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97 | {...}), |
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98 | (u'91109351AC', |
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99 | {...})] |
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100 | |
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101 | A ``values()``-like behaviour cen be archieved by simply using the |
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102 | iterator. |
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103 | |
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104 | Getting JAMB Table Meta Data |
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105 | ---------------------------- |
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106 | |
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107 | We can also get a datetime stamp, that tells, when the table was |
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108 | imported. This could help with maintaining old tables: |
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109 | |
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110 | >>> table.import_datetime |
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111 | datetime.datetime(..., ..., ..., ..., ..., ..., ...) |
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112 | |
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113 | |
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114 | We can delete the table: |
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115 | |
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116 | >>> del JAMBDataTable |
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117 | |
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118 | Clean up: |
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119 | |
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120 | >>> import os |
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121 | >>> os.unlink(datafile) |
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