1 | Ikoba Data Center |
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2 | **************** |
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3 | |
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4 | The Ikoba data center cares for managing CSV files and importing then. |
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5 | |
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6 | .. :doctest: |
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7 | .. :layer: waeup.ikoba.testing.IkobaUnitTestLayer |
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8 | |
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9 | Creating a data center |
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10 | ====================== |
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11 | |
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12 | A data center can be created easily: |
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13 | |
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14 | >>> from waeup.ikoba.datacenter import DataCenter |
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15 | >>> mydatacenter = DataCenter() |
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16 | >>> mydatacenter |
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17 | <waeup.ikoba.datacenter.DataCenter object at 0x...> |
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18 | |
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19 | Each data center has a location in file system where files are stored: |
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20 | |
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21 | >>> storagepath = mydatacenter.storage |
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22 | >>> storagepath |
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23 | '/tmp/tmp...' |
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24 | |
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25 | Beside other things it provides a location to put data of deleted |
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26 | items into: |
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27 | |
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28 | >>> import os |
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29 | >>> del_path = mydatacenter.deleted_path |
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30 | >>> os.path.isdir(del_path) |
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31 | True |
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32 | |
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33 | Overall it complies with the `IDataCenter` interface: |
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34 | |
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35 | >>> from zope.interface import verify |
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36 | >>> from waeup.ikoba.interfaces import IDataCenter |
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37 | >>> verify.verifyObject(IDataCenter, DataCenter() ) |
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38 | True |
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39 | |
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40 | >>> verify.verifyClass(IDataCenter, DataCenter) |
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41 | True |
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42 | |
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43 | Managing the storage path |
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44 | ------------------------- |
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45 | |
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46 | We can set another storage path: |
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47 | |
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48 | >>> import os |
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49 | >>> os.mkdir('newlocation') |
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50 | >>> newpath = os.path.abspath('newlocation') |
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51 | >>> mydatacenter.setStoragePath(newpath) |
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52 | [] |
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53 | |
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54 | The result here is a list of filenames, that could not be |
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55 | copied. Luckily, this list is empty. |
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56 | |
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57 | When we set a new storage path, we can tell to move all files in the |
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58 | old location to the new one. To see this feature in action, we first |
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59 | have to put a file into the old location: |
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60 | |
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61 | >>> open(os.path.join(newpath, 'myfile.txt'), 'wb').write('hello') |
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62 | |
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63 | Now we can set a new location and the file will be copied: |
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64 | |
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65 | >>> verynewpath = os.path.abspath('verynewlocation') |
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66 | >>> os.mkdir(verynewpath) |
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67 | |
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68 | >>> mydatacenter.setStoragePath(verynewpath, move=True) |
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69 | [] |
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70 | |
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71 | >>> storagepath = mydatacenter.storage |
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72 | >>> 'myfile.txt' in os.listdir(verynewpath) |
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73 | True |
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74 | |
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75 | We remove the created file to have a clean testing environment for |
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76 | upcoming examples: |
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77 | |
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78 | >>> os.unlink(os.path.join(storagepath, 'myfile.txt')) |
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79 | |
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80 | Uploading files |
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81 | =============== |
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82 | |
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83 | We can get a list of files stored in that location: |
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84 | |
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85 | >>> mydatacenter.getPendingFiles() |
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86 | [] |
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87 | |
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88 | Let's put some file in the storage: |
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89 | |
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90 | >>> import os |
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91 | >>> filepath = os.path.join(storagepath, 'data.csv') |
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92 | >>> open(filepath, 'wb').write('Some Content\n') |
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93 | |
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94 | Now we can find a file: |
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95 | |
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96 | >>> mydatacenter.getPendingFiles() |
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97 | [<waeup.ikoba.datacenter.DataCenterFile object at 0x...>] |
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98 | |
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99 | As we can see, the actual file is wrapped by a convenience wrapper, |
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100 | that enables us to fetch some data about the file. The data returned |
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101 | is formatted in strings, so that it can easily be put into output |
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102 | pages: |
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103 | |
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104 | >>> datafile = mydatacenter.getPendingFiles()[0] |
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105 | >>> datafile.getSize() |
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106 | '13 bytes' |
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107 | |
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108 | >>> datafile.getDate() # Nearly current datetime... |
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109 | '...' |
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110 | |
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111 | Clean up: |
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112 | |
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113 | >>> import shutil |
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114 | >>> shutil.rmtree(newpath) |
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115 | >>> shutil.rmtree(verynewpath) |
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116 | |
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117 | |
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118 | Distributing processed files |
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119 | ============================ |
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120 | |
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121 | When files were processed by a batch processor, we can put the |
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122 | resulting files into desired destinations. |
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123 | |
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124 | We recreate the datacenter root in case it is missing: |
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125 | |
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126 | >>> import os |
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127 | >>> dc_root = mydatacenter.storage |
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128 | >>> fin_dir = os.path.join(dc_root, 'finished') |
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129 | >>> unfin_dir = os.path.join(dc_root, 'unfinished') |
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130 | |
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131 | >>> def recreate_dc_storage(): |
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132 | ... if os.path.exists(dc_root): |
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133 | ... shutil.rmtree(dc_root) |
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134 | ... os.mkdir(dc_root) |
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135 | ... mydatacenter.setStoragePath(mydatacenter.storage) |
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136 | >>> recreate_dc_storage() |
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137 | |
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138 | We define a function that creates a set of faked result files: |
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139 | |
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140 | >>> import os |
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141 | >>> import tempfile |
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142 | >>> def create_fake_results(source_basename, create_pending=True): |
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143 | ... tmp_dir = tempfile.mkdtemp() |
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144 | ... src = os.path.join(dc_root, source_basename) |
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145 | ... pending_src = None |
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146 | ... if create_pending: |
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147 | ... pending_src = os.path.join(tmp_dir, 'mypendingsource.csv') |
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148 | ... finished_src = os.path.join(tmp_dir, 'myfinishedsource.csv') |
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149 | ... for path in (src, pending_src, finished_src): |
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150 | ... if path is not None: |
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151 | ... open(path, 'wb').write('blah') |
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152 | ... return tmp_dir, src, finished_src, pending_src |
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153 | |
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154 | Now we can create the set of result files, that typically come after a |
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155 | successful processing of a regular source: |
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156 | |
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157 | Now we can try to distribute those files. Let's start with a source |
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158 | file, that was processed successfully: |
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159 | |
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160 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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161 | ... 'mysource.csv', create_pending=False) |
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162 | >>> mydatacenter.distProcessedFiles(True, src, finished_src, |
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163 | ... pending_src, mode='create') |
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164 | >>> sorted(os.listdir(dc_root)) |
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165 | ['deleted', 'finished', 'logs', 'unfinished'] |
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166 | |
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167 | >>> sorted(os.listdir(fin_dir)) |
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168 | ['mysource.create.finished.csv', 'mysource.csv'] |
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169 | |
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170 | >>> sorted(os.listdir(unfin_dir)) |
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171 | [] |
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172 | |
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173 | The created dir will be removed for us by the datacenter. This way we |
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174 | can assured, that less temporary dirs are left hanging around: |
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175 | |
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176 | >>> os.path.exists(tmp_dir) |
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177 | False |
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178 | |
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179 | The root dir is empty, while the original file and the file containing |
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180 | all processed data were moved to'finished/'. |
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181 | |
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182 | Now we restart, but this time we fake an erranous action: |
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183 | |
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184 | >>> recreate_dc_storage() |
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185 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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186 | ... 'mysource.csv') |
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187 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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188 | ... pending_src, mode='create') |
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189 | >>> sorted(os.listdir(dc_root)) |
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190 | ['deleted', 'finished', 'logs', 'mysource.create.pending.csv', 'unfinished'] |
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191 | |
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192 | >>> sorted(os.listdir(fin_dir)) |
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193 | ['mysource.create.finished.csv'] |
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194 | |
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195 | >>> sorted(os.listdir(unfin_dir)) |
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196 | ['mysource.csv'] |
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197 | |
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198 | While the original source was moved to the 'unfinished' dir, the |
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199 | pending file went to the root and the set of already processed items |
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200 | are stored in finished/. |
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201 | |
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202 | We fake processing the pending file and assume that everything went |
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203 | well this time: |
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204 | |
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205 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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206 | ... 'mysource.create.pending.csv', create_pending=False) |
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207 | >>> mydatacenter.distProcessedFiles(True, src, finished_src, |
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208 | ... pending_src, mode='create') |
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209 | |
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210 | >>> sorted(os.listdir(dc_root)) |
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211 | ['deleted', 'finished', 'logs', 'unfinished'] |
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212 | |
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213 | >>> sorted(os.listdir(fin_dir)) |
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214 | ['mysource.create.finished.csv', 'mysource.csv'] |
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215 | |
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216 | >>> sorted(os.listdir(unfin_dir)) |
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217 | [] |
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218 | |
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219 | The result is the same as in the first case shown above. |
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220 | |
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221 | We restart again, but this time we fake several non-working imports in |
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222 | a row. |
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223 | |
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224 | We start with a faulty start-import: |
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225 | |
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226 | >>> recreate_dc_storage() |
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227 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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228 | ... 'mysource.csv') |
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229 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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230 | ... pending_src, mode='create') |
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231 | |
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232 | We try to process the pending file, which fails again: |
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233 | |
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234 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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235 | ... 'mysource.create.pending.csv') |
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236 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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237 | ... pending_src, mode='create') |
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238 | |
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239 | We try to process the new pending file: |
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240 | |
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241 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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242 | ... 'mysource.create.pending.csv') |
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243 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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244 | ... pending_src, mode='create') |
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245 | |
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246 | >>> sorted(os.listdir(dc_root)) |
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247 | ['deleted', 'finished', 'logs', 'mysource.create.pending.csv', 'unfinished'] |
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248 | |
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249 | >>> sorted(os.listdir(fin_dir)) |
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250 | ['mysource.create.finished.csv'] |
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251 | |
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252 | >>> sorted(os.listdir(unfin_dir)) |
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253 | ['mysource.csv'] |
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254 | |
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255 | Finally, we process the pending file and everything works: |
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256 | |
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257 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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258 | ... 'mysource.create.pending.csv', create_pending=False) |
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259 | >>> mydatacenter.distProcessedFiles(True, src, finished_src, |
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260 | ... pending_src, mode='create') |
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261 | |
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262 | >>> sorted(os.listdir(dc_root)) |
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263 | ['deleted', 'finished', 'logs', 'unfinished'] |
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264 | |
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265 | >>> sorted(os.listdir(fin_dir)) |
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266 | ['mysource.create.finished.csv', 'mysource.csv'] |
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267 | |
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268 | >>> sorted(os.listdir(unfin_dir)) |
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269 | [] |
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270 | |
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271 | The root dir is empty (contains no input files) and only the files in |
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272 | finished-subdirectory remain. |
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273 | |
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274 | |
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275 | We can get a list of imported files stored in the finished subfolder: |
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276 | |
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277 | >>> mydatacenter.getFinishedFiles() |
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278 | [<waeup.ikoba.datacenter.DataCenterFile object at ...>] |
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279 | |
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280 | >>> datafile = mydatacenter.getFinishedFiles()[0] |
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281 | >>> datafile.getSize() |
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282 | '2 bytes' |
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283 | |
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284 | >>> datafile.getDate() # Nearly current datetime... |
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285 | '...' |
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286 | |
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287 | |
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288 | Clean up: |
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289 | |
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290 | >>> shutil.rmtree(verynewpath) |
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