[12920] | 1 | Data Center |
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| 2 | *********** |
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[4169] | 3 | |
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[7819] | 4 | The Kofa data center cares for managing CSV files and importing then. |
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[4169] | 5 | |
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[5140] | 6 | .. :doctest: |
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[7819] | 7 | .. :layer: waeup.kofa.testing.KofaUnitTestLayer |
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[4169] | 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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[7811] | 14 | >>> from waeup.kofa.datacenter import DataCenter |
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[4169] | 15 | >>> mydatacenter = DataCenter() |
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| 16 | >>> mydatacenter |
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[7811] | 17 | <waeup.kofa.datacenter.DataCenter object at 0x...> |
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[4169] | 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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[7584] | 23 | '/tmp/tmp...' |
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[4169] | 24 | |
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[15416] | 25 | Beside other things it provides two locations to put data of deleted |
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[8398] | 26 | items into: |
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[4169] | 27 | |
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[8398] | 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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[15416] | 32 | >>> grad_path = mydatacenter.graduated_path |
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| 33 | >>> os.path.isdir(grad_path) |
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| 34 | True |
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[8398] | 35 | |
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| 36 | Overall it complies with the `IDataCenter` interface: |
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| 37 | |
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| 38 | >>> from zope.interface import verify |
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| 39 | >>> from waeup.kofa.interfaces import IDataCenter |
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| 40 | >>> verify.verifyObject(IDataCenter, DataCenter() ) |
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| 41 | True |
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| 42 | |
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| 43 | >>> verify.verifyClass(IDataCenter, DataCenter) |
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| 44 | True |
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| 45 | |
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[4174] | 46 | Managing the storage path |
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[12920] | 47 | ========================= |
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[4174] | 48 | |
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| 49 | We can set another storage path: |
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| 50 | |
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| 51 | >>> import os |
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| 52 | >>> os.mkdir('newlocation') |
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| 53 | >>> newpath = os.path.abspath('newlocation') |
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| 54 | >>> mydatacenter.setStoragePath(newpath) |
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[4191] | 55 | [] |
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[4174] | 56 | |
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[4191] | 57 | The result here is a list of filenames, that could not be |
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| 58 | copied. Luckily, this list is empty. |
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| 59 | |
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[4174] | 60 | When we set a new storage path, we can tell to move all files in the |
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| 61 | old location to the new one. To see this feature in action, we first |
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| 62 | have to put a file into the old location: |
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| 63 | |
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| 64 | >>> open(os.path.join(newpath, 'myfile.txt'), 'wb').write('hello') |
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| 65 | |
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| 66 | Now we can set a new location and the file will be copied: |
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| 67 | |
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| 68 | >>> verynewpath = os.path.abspath('verynewlocation') |
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| 69 | >>> os.mkdir(verynewpath) |
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| 70 | |
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| 71 | >>> mydatacenter.setStoragePath(verynewpath, move=True) |
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[4191] | 72 | [] |
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| 73 | |
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[4174] | 74 | >>> storagepath = mydatacenter.storage |
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| 75 | >>> 'myfile.txt' in os.listdir(verynewpath) |
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| 76 | True |
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| 77 | |
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| 78 | We remove the created file to have a clean testing environment for |
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| 79 | upcoming examples: |
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| 80 | |
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| 81 | >>> os.unlink(os.path.join(storagepath, 'myfile.txt')) |
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| 82 | |
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[4169] | 83 | Uploading files |
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| 84 | =============== |
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| 85 | |
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| 86 | We can get a list of files stored in that location: |
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| 87 | |
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[9023] | 88 | >>> mydatacenter.getPendingFiles() |
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[4169] | 89 | [] |
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| 90 | |
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| 91 | Let's put some file in the storage: |
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| 92 | |
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| 93 | >>> import os |
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| 94 | >>> filepath = os.path.join(storagepath, 'data.csv') |
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| 95 | >>> open(filepath, 'wb').write('Some Content\n') |
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| 96 | |
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| 97 | Now we can find a file: |
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| 98 | |
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[9023] | 99 | >>> mydatacenter.getPendingFiles() |
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[7811] | 100 | [<waeup.kofa.datacenter.DataCenterFile object at 0x...>] |
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[4169] | 101 | |
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| 102 | As we can see, the actual file is wrapped by a convenience wrapper, |
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| 103 | that enables us to fetch some data about the file. The data returned |
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| 104 | is formatted in strings, so that it can easily be put into output |
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| 105 | pages: |
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| 106 | |
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[9023] | 107 | >>> datafile = mydatacenter.getPendingFiles()[0] |
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[4169] | 108 | >>> datafile.getSize() |
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| 109 | '13 bytes' |
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| 110 | |
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| 111 | >>> datafile.getDate() # Nearly current datetime... |
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| 112 | '...' |
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| 113 | |
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| 114 | Clean up: |
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| 115 | |
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[4174] | 116 | >>> import shutil |
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| 117 | >>> shutil.rmtree(newpath) |
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| 118 | >>> shutil.rmtree(verynewpath) |
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[4169] | 119 | |
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| 120 | |
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[4897] | 121 | Distributing processed files |
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| 122 | ============================ |
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| 123 | |
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| 124 | When files were processed by a batch processor, we can put the |
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| 125 | resulting files into desired destinations. |
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| 126 | |
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| 127 | We recreate the datacenter root in case it is missing: |
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| 128 | |
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| 129 | >>> import os |
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| 130 | >>> dc_root = mydatacenter.storage |
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| 131 | >>> fin_dir = os.path.join(dc_root, 'finished') |
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| 132 | >>> unfin_dir = os.path.join(dc_root, 'unfinished') |
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| 133 | |
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| 134 | >>> def recreate_dc_storage(): |
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| 135 | ... if os.path.exists(dc_root): |
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| 136 | ... shutil.rmtree(dc_root) |
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| 137 | ... os.mkdir(dc_root) |
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| 138 | ... mydatacenter.setStoragePath(mydatacenter.storage) |
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| 139 | >>> recreate_dc_storage() |
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| 140 | |
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| 141 | We define a function that creates a set of faked result files: |
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| 142 | |
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| 143 | >>> import os |
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| 144 | >>> import tempfile |
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| 145 | >>> def create_fake_results(source_basename, create_pending=True): |
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| 146 | ... tmp_dir = tempfile.mkdtemp() |
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| 147 | ... src = os.path.join(dc_root, source_basename) |
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| 148 | ... pending_src = None |
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| 149 | ... if create_pending: |
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| 150 | ... pending_src = os.path.join(tmp_dir, 'mypendingsource.csv') |
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| 151 | ... finished_src = os.path.join(tmp_dir, 'myfinishedsource.csv') |
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| 152 | ... for path in (src, pending_src, finished_src): |
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| 153 | ... if path is not None: |
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| 154 | ... open(path, 'wb').write('blah') |
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| 155 | ... return tmp_dir, src, finished_src, pending_src |
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| 156 | |
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| 157 | Now we can create the set of result files, that typically come after a |
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| 158 | successful processing of a regular source: |
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| 159 | |
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| 160 | Now we can try to distribute those files. Let's start with a source |
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| 161 | file, that was processed successfully: |
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| 162 | |
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| 163 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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| 164 | ... 'mysource.csv', create_pending=False) |
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| 165 | >>> mydatacenter.distProcessedFiles(True, src, finished_src, |
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[4999] | 166 | ... pending_src, mode='create') |
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[4897] | 167 | >>> sorted(os.listdir(dc_root)) |
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[15416] | 168 | ['deleted', 'finished', 'graduated', 'logs', 'unfinished'] |
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[4897] | 169 | |
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| 170 | >>> sorted(os.listdir(fin_dir)) |
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[4999] | 171 | ['mysource.create.finished.csv', 'mysource.csv'] |
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[4897] | 172 | |
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| 173 | >>> sorted(os.listdir(unfin_dir)) |
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| 174 | [] |
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| 175 | |
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[4907] | 176 | The created dir will be removed for us by the datacenter. This way we |
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| 177 | can assured, that less temporary dirs are left hanging around: |
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[4897] | 178 | |
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[4907] | 179 | >>> os.path.exists(tmp_dir) |
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| 180 | False |
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| 181 | |
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[4897] | 182 | The root dir is empty, while the original file and the file containing |
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| 183 | all processed data were moved to'finished/'. |
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| 184 | |
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| 185 | Now we restart, but this time we fake an erranous action: |
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| 186 | |
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| 187 | >>> recreate_dc_storage() |
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| 188 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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| 189 | ... 'mysource.csv') |
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| 190 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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[4999] | 191 | ... pending_src, mode='create') |
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[4897] | 192 | >>> sorted(os.listdir(dc_root)) |
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[15416] | 193 | ['deleted', 'finished', 'graduated', 'logs', 'mysource.create.pending.csv', 'unfinished'] |
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[4897] | 194 | |
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| 195 | >>> sorted(os.listdir(fin_dir)) |
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[4999] | 196 | ['mysource.create.finished.csv'] |
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[4897] | 197 | |
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| 198 | >>> sorted(os.listdir(unfin_dir)) |
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| 199 | ['mysource.csv'] |
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| 200 | |
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| 201 | While the original source was moved to the 'unfinished' dir, the |
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| 202 | pending file went to the root and the set of already processed items |
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| 203 | are stored in finished/. |
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| 204 | |
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| 205 | We fake processing the pending file and assume that everything went |
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| 206 | well this time: |
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| 207 | |
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| 208 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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[4999] | 209 | ... 'mysource.create.pending.csv', create_pending=False) |
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[4897] | 210 | >>> mydatacenter.distProcessedFiles(True, src, finished_src, |
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[4999] | 211 | ... pending_src, mode='create') |
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[4897] | 212 | |
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| 213 | >>> sorted(os.listdir(dc_root)) |
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[15416] | 214 | ['deleted', 'finished', 'graduated', 'logs', 'unfinished'] |
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[4897] | 215 | |
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| 216 | >>> sorted(os.listdir(fin_dir)) |
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[4999] | 217 | ['mysource.create.finished.csv', 'mysource.csv'] |
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[4897] | 218 | |
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| 219 | >>> sorted(os.listdir(unfin_dir)) |
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| 220 | [] |
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| 221 | |
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| 222 | The result is the same as in the first case shown above. |
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| 223 | |
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| 224 | We restart again, but this time we fake several non-working imports in |
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| 225 | a row. |
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| 226 | |
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| 227 | We start with a faulty start-import: |
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| 228 | |
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| 229 | >>> recreate_dc_storage() |
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| 230 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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| 231 | ... 'mysource.csv') |
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| 232 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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[4999] | 233 | ... pending_src, mode='create') |
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[4897] | 234 | |
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| 235 | We try to process the pending file, which fails again: |
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| 236 | |
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| 237 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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[4999] | 238 | ... 'mysource.create.pending.csv') |
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[4897] | 239 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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[4999] | 240 | ... pending_src, mode='create') |
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[4897] | 241 | |
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| 242 | We try to process the new pending file: |
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| 243 | |
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| 244 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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[4999] | 245 | ... 'mysource.create.pending.csv') |
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[4897] | 246 | >>> mydatacenter.distProcessedFiles(False, src, finished_src, |
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[4999] | 247 | ... pending_src, mode='create') |
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[4897] | 248 | |
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| 249 | >>> sorted(os.listdir(dc_root)) |
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[15416] | 250 | ['deleted', 'finished', 'graduated', 'logs', 'mysource.create.pending.csv', 'unfinished'] |
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[4897] | 251 | |
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| 252 | >>> sorted(os.listdir(fin_dir)) |
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[4999] | 253 | ['mysource.create.finished.csv'] |
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[4897] | 254 | |
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| 255 | >>> sorted(os.listdir(unfin_dir)) |
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| 256 | ['mysource.csv'] |
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| 257 | |
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| 258 | Finally, we process the pending file and everything works: |
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| 259 | |
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| 260 | >>> tmp_dir, src, finished_src, pending_src = create_fake_results( |
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[4999] | 261 | ... 'mysource.create.pending.csv', create_pending=False) |
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[4897] | 262 | >>> mydatacenter.distProcessedFiles(True, src, finished_src, |
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[4999] | 263 | ... pending_src, mode='create') |
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[4897] | 264 | |
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| 265 | >>> sorted(os.listdir(dc_root)) |
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[15416] | 266 | ['deleted', 'finished', 'graduated', 'logs', 'unfinished'] |
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[4897] | 267 | |
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| 268 | >>> sorted(os.listdir(fin_dir)) |
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[4999] | 269 | ['mysource.create.finished.csv', 'mysource.csv'] |
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[4897] | 270 | |
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| 271 | >>> sorted(os.listdir(unfin_dir)) |
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| 272 | [] |
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| 273 | |
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| 274 | The root dir is empty (contains no input files) and only the files in |
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| 275 | finished-subdirectory remain. |
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| 276 | |
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[9023] | 277 | |
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| 278 | We can get a list of imported files stored in the finished subfolder: |
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| 279 | |
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| 280 | >>> mydatacenter.getFinishedFiles() |
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[9589] | 281 | [<waeup.kofa.datacenter.DataCenterFile object at ...>] |
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[9023] | 282 | |
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| 283 | >>> datafile = mydatacenter.getFinishedFiles()[0] |
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| 284 | >>> datafile.getSize() |
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| 285 | '2 bytes' |
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| 286 | |
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| 287 | >>> datafile.getDate() # Nearly current datetime... |
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| 288 | '...' |
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| 289 | |
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| 290 | |
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[4897] | 291 | Clean up: |
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| 292 | |
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| 293 | >>> shutil.rmtree(verynewpath) |
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