{"action":"created","comment":{"url":"https://api.github.com/repos/hydroshare/hydroshare/pulls/comments/78444404","id":78444404,"diff_hunk":"@@ -607,8 +670,25 @@ def test_metadata_is_dirty_flag(self):\n             )\n         utils.resource_post_create_actions(resource=self.resTimeSeries, user=self.user, metadata=[])\n \n-        # at this point the is_dirty be set to false\n-        self.assertEqual(self.resTimeSeries.metadata.is_dirty, False)\n+        # updating the core metadata element title should also set the metadata is_dirty to True\n+        title = self.resTimeSeries.metadata.title\n+        self.resTimeSeries.metadata.update_element('title', title.id, value=\"New Resource Title\")\n+        # at this point the is_dirty be set to true\n+        self.assertEqual(self.resTimeSeries.metadata.is_dirty, True)\n+        # rest metadata is_dirty to false\n+        TimeSeriesMetaData.objects.filter(id=self.resTimeSeries.metadata.id).update(is_dirty=False)\n+\n+        # updating the core metadata element Description (Abstract) should also set the\n+        # metadata is_dirty to True\n+        description = self.resTimeSeries.metadata.description\n+        self.resTimeSeries.metadata.update_element('description', description.id,\n+                                                   value=\"New abstract\")\n+        # at this point the is_dirty be set to trye\n+        self.assertEqual(self.resTimeSeries.metadata.is_dirty, True)\n+        # rest metadata is_dirty to false","path":"hs_app_timeseries/tests/test_timeseries_metadata.py","position":185,"original_position":185,"commit_id":"ef073f502a0da530ec5ac65fbe1241083ca4c09b","original_commit_id":"ef073f502a0da530ec5ac65fbe1241083ca4c09b","user":{"login":"hyi","id":476302,"avatar_url":"https://avatars.githubusercontent.com/u/476302?v=3","gravatar_id":"","url":"https://api.github.com/users/hyi","html_url":"https://github.com/hyi","followers_url":"https://api.github.com/users/hyi/followers","following_url":"https://api.github.com/users/hyi/following{/other_user}","gists_url":"https://api.github.com/users/hyi/gists{/gist_id}","starred_url":"https://api.github.com/users/hyi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hyi/subscriptions","organizations_url":"https://api.github.com/users/hyi/orgs","repos_url":"https://api.github.com/users/hyi/repos","events_url":"https://api.github.com/users/hyi/events{/privacy}","received_events_url":"https://api.github.com/users/hyi/received_events","type":"User","site_admin":false},"body":"change rest to reset in comment","created_at":"2016-09-12T20:05:47Z","updated_at":"2016-09-12T20:05:47Z","html_url":"https://github.com/hydroshare/hydroshare/pull/1422#discussion_r78444404","pull_request_url":"https://api.github.com/repos/hydroshare/hydroshare/pulls/1422","_links":{"self":{"href":"https://api.github.com/repos/hydroshare/hydroshare/pulls/comments/78444404"},"html":{"href":"https://github.com/hydroshare/hydroshare/pull/1422#discussion_r78444404"},"pull_request":{"href":"https://api.github.com/repos/hydroshare/hydroshare/pulls/1422"}}},"pull_request":{"url":"https://api.github.com/repos/hydroshare/hydroshare/pulls/1422","id":83186044,"html_url":"https://github.com/hydroshare/hydroshare/pull/1422","diff_url":"https://github.com/hydroshare/hydroshare/pull/1422.diff","patch_url":"https://github.com/hydroshare/hydroshare/pull/1422.patch","issue_url":"https://api.github.com/repos/hydroshare/hydroshare/issues/1422","number":1422,"state":"open","locked":false,"title":"Timeseries  phase-2 (csv upload)","user":{"login":"pkdash","id":2523434,"avatar_url":"https://avatars.githubusercontent.com/u/2523434?v=3","gravatar_id":"","url":"https://api.github.com/users/pkdash","html_url":"https://github.com/pkdash","followers_url":"https://api.github.com/users/pkdash/followers","following_url":"https://api.github.com/users/pkdash/following{/other_user}","gists_url":"https://api.github.com/users/pkdash/gists{/gist_id}","starred_url":"https://api.github.com/users/pkdash/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pkdash/subscriptions","organizations_url":"https://api.github.com/users/pkdash/orgs","repos_url":"https://api.github.com/users/pkdash/repos","events_url":"https://api.github.com/users/pkdash/events{/privacy}","received_events_url":"https://api.github.com/users/pkdash/received_events","type":"User","site_admin":false},"body":"Phase 2 of time series functionality involves creating a time series resource from a CSV file. The CSV format would have one DateTime column and one or more DataValue columns. Each DataValue column would represent a different variable. Metadata would all be created via the Resource metadata editing form in the web user interface.\r\n\r\nWhat's a valid time series CSV file?\r\n1. Must have a column heading row (column headings need to be unique)\r\n2. Must have at least one data row\r\n3. There has to be at least 2 columns (one date/time and one or more data value columns)\r\n4. First column must contain date/time value rest of the columns must have a numerical value\r\n5. A data row must have a value for each of the columns\r\n\r\n**Summary of CSV upload functionalities:** \r\n\r\n1. Time Series resource can be created now by uploading a csv file.\r\n2. If the csv file fails validation, the resource will be created, but the csv file will not be added to the resource. If the validation succeeds, system will add a blank SQLite file (ODM2.sqlite) to the resource.\r\n3. A csv file can be added to an existing time series resource if the resource does not contain any file.\r\n\t\r\n   -  If the csv file fails validation at the time of adding to a resource, then it won't be added to the resource.\r\n\t\r\n  -  If the validation succeeds any existing metadata will be deleted and a blank SQLite file (ODM2.sqlite) will be added to the resource by the system.\r\n4. The number of data columns in csv file is the number of time series for which metadata can be added. Data column headings are initially used for selecting a time series for metadata viewing or editing.\r\n5. For editing metadata, user first needs to select a time series from a dropdown list. If metadata exists for the selected series, it will be displayed, otherwise blank forms\r\nwill be displayed for each of the resource specific metadata elements.\r\n  - User will be able to copy data for an element (this option is not available if the user has uploaded a sqlite file), if data exists for the same type element for other serieses. A dropdown list appears if data for same type element exists for other series. Use this dropdown list to select the specific data that you want to copy for the currently selected series. You won't be able to edit the copied data\tprior to saving it for the current element (form elements for the copied data are grayed out). However, after selecting data to copy, if you decide not to copy rather enter new data for the element then select the option '----' from the copy data dropdown list. The copy data option is available for all resource specific elements except 'Time Series Result' element.\r\n  - When you save data for an element, you will not be able to edit again that element until page reload (which can be done by selecting a different series).\r\n - The resource coverage metadata spatial values are automatically calculated based on the lat/lon values of each of the 'Site' metadata elements. User won't be able to edit the resource coverage data.\r\n- Resource temporal coverage element is created automatically at the time of CSV upload.\t\r\n- Updates to core metadata elements (title, abstract, creators/contributors) are also written to the sqlite file when the user triggers the sync operation (see below)\r\n\t\r\n\r\n7. After the resource has all the required metadata, user will see an option to sync metadata changes\r\nin django database to the blank sqlite file (ODM2.sqlite). First time when data is written to the blank sqlite file, data values will be read from the csv file to populate the ResultDataValues table in the sqlite file. All other relevant tables in sqlite file is populated using metadata stored in django db. Therefore, initial writing of data to the blank sqlite file takes longer compared to subsequent updates of the sqlite file on metadata updates.\r\n\r\n8. After the initial the writing of data to the blank sqlite file, the options to select a series will no longer use csv data column headings. Metadata attributes are used for creating series labels for\r\nselecting a series.\r\n\r\n9. After the initial writing data to the blank sqlite file, any time user edits resource specific metadata or one of these core metadata (title, abstract, creator/contributor), the option to sync sqlite file will appear immediately.\r\n10. If the SQLite file is out of sync due to metadata edits, a message will appear on page load (both view and edit mode).\r\n11. If the user has not synced the metadata changes to the SQLite file before downloading the bag, the bag will have the SQLite file that's out of 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