472 lines
18 KiB
Python
472 lines
18 KiB
Python
#!/usr/bin/env python
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"""
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Client library to communicate with a Refine server.
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"""
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# Copyright (c) 2011 Paul Makepeace, Real Programmers. All rights reserved.
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import csv
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import json
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import gzip
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import os
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import re
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import StringIO
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import urllib
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import urllib2_file
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import urllib2
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import urlparse
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from google.refine import facet
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from google.refine import history
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REFINE_HOST = os.environ.get('GOOGLE_REFINE_HOST', '127.0.0.1')
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REFINE_PORT = os.environ.get('GOOGLE_REFINE_PORT', '3333')
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class RefineServer(object):
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"""Communicate with a Refine server."""
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def __init__(self, server='http://%s:%s' % (REFINE_HOST, REFINE_PORT)):
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self.server = server[:-1] if server.endswith('/') else server
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def urlopen(self, command, data=None, project_id=None):
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"""Open a Refine URL and optionally POST data."""
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url = self.server + '/command/core/' + command
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if data is None:
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data = {}
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if project_id:
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# XXX haven't figured out pattern on qs v body
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if 'delete' in command:
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data['project'] = project_id
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else:
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url += '?project=' + project_id
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req = urllib2.Request(url)
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if data:
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req.add_data(data) # data = urllib.urlencode(data)
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#req.add_header('Accept-Encoding', 'gzip')
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try:
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response = urllib2.urlopen(req)
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except urllib2.URLError as (url_error,):
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if 'Connection refused' in url_error:
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raise urllib2.URLError(
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'%s for %s. No Refine server reachable/running; ENV set?' %
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(url_error, self.server))
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else:
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raise
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if response.info().get('Content-Encoding', None) == 'gzip':
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# Need a seekable filestream for gzip
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gzip_fp = gzip.GzipFile(fileobj=StringIO.StringIO(response.read()))
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# XXX Monkey patch response's filehandle. Better way?
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urllib.addbase.__init__(response, gzip_fp)
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return response
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def urlopen_json(self, *args, **kwargs):
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"""Open a Refine URL, optionally POST data, and return parsed JSON."""
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response = json.loads(self.urlopen(*args, **kwargs).read())
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if 'code' in response and response['code'] != 'ok':
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raise Exception(
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response['code'] + ': ' +
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response.get('message', response.get('stack', response)))
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return response
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class Refine:
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"""Class representing a connection to a Refine server."""
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def __init__(self, server, **kwargs):
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if isinstance(server, RefineServer):
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self.server = server
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else:
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self.server = RefineServer(server)
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def get_version(self):
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"""Return version data.
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{"revision":"r1836","full_version":"2.0 [r1836]",
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"full_name":"Google Refine 2.0 [r1836]","version":"2.0"}"""
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return self.server.urlopen_json('get-version')
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def list_projects(self):
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"""Return a dict of projects indexed by id.
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{u'1877818633188': {
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'id': u'1877818633188', u'name': u'akg',
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u'modified': u'2011-04-07T12:30:07Z',
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u'created': u'2011-04-07T12:30:07Z'
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},
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"""
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# It's tempting to add in an index by name but there can be
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# projects with the same name.
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return self.server.urlopen_json('get-all-project-metadata')['projects']
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def get_project_name(self, project_id):
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"""Returns project name given project_id."""
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projects = self.list_projects()
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return projects[project_id]['name']
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def open_project(self, project_id):
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"""Open a Refine project."""
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return RefineProject(self.server, project_id)
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def new_project(self, project_file=None, project_url=None,
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project_name=None,
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split_into_columns=True,
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separator='',
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ignore_initial_non_blank_lines=0,
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header_lines=1, # use 0 if your data has no header
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skip_initial_data_rows=0,
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limit=None, # no more than this number of rows
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guess_value_type=True, # numbers, dates, etc.
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ignore_quotes=False):
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if ((project_file and project_url) or
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(not project_file and not project_url)):
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raise ValueError('One (only) of project_file and project_url must be set')
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def s(opt):
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if isinstance(opt, bool):
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return 'on' if opt else ''
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if opt is None:
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return ''
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return str(opt)
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options = {
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'split-into-columns': s(split_into_columns),
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'separator': s(separator),
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'ignore': s(ignore_initial_non_blank_lines),
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'header-lines': s(header_lines),
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'skip': s(skip_initial_data_rows), 'limit': s(limit),
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'guess-value-type': s(guess_value_type),
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'ignore-quotes': s(ignore_quotes),
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}
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if project_url is not None:
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options['url'] = project_url
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elif project_file is not None:
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options['project-file'] = {
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'fd': open(project_file),
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'filename': project_file,
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}
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if project_name is None:
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# make a name for itself by stripping extension and directories
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project_name = (project_file or 'New project').rsplit('.', 1)[0]
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project_name = os.path.basename(project_name)
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options['project-name'] = project_name
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response = self.server.urlopen('create-project-from-upload', options)
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# expecting a redirect to the new project containing the id in the url
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url_params = urlparse.parse_qs(
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urlparse.urlparse(response.geturl()).query)
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if 'project' in url_params:
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project_id = url_params['project'][0]
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return RefineProject(self.server, project_id)
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else:
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raise Exception('Project not created')
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def RowsResponseFactory(column_index):
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"""Factory for the parsing the output from get_rows().
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Uses the project's model's row cell index so that a row can be used
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as a dict by column name."""
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class RowsResponse(object):
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class RefineRows(object):
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class RefineRow(object):
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def __init__(self, row_response):
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self.flagged = row_response['flagged']
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self.starred = row_response['starred']
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self.index = row_response['i']
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self.row = [c['v'] if c else None
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for c in row_response['cells']]
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def __getitem__(self, column):
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# Trailing nulls seem to be stripped from row data
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try:
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return self.row[column_index[column]]
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except IndexError:
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return None
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def __init__(self, rows_response):
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self.rows_response = rows_response
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def __iter__(self):
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for row_response in self.rows_response:
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yield self.RefineRow(row_response)
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def __getitem__(self, index):
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return self.RefineRow(self.rows_response[index])
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def __len__(self):
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return len(self.rows_response)
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def __init__(self, response):
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self.mode = response['mode']
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self.filtered = response['filtered']
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self.start = response['start']
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self.limit = response['limit']
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self.total = response['total']
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# 'pool': {"reconCandidates": {},"recons": {}}
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self.pool = response['pool']
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self.rows = self.RefineRows(response['rows'])
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return RowsResponse
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class RefineProject:
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"""A Google Refine project."""
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def __init__(self, server, project_id=None):
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if not isinstance(server, RefineServer):
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if '/project?project=' in server:
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server, project_id = server.split('/project?project=')
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server = RefineServer(server)
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self.server = server
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if not project_id:
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raise Exception('Missing Refine project ID')
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self.project_id = project_id
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self.engine = facet.Engine()
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self.sorting = facet.Sorting()
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self.history_entry = None
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# following filled in by get_models()
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self.has_records = False
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self.columns = None
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self.column_order = {} # map of column names to order in UI
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self.rows_response_factory = None # for parsing get_rows()
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self.get_models()
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def project_name(self):
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return Refine(self.server).get_project_name(project_id)
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def do_raw(self, command, data):
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"""Issue a command to the server & return a response object."""
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return self.server.urlopen(command, self.project_id, data)
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def do_json(self, command, data=None, include_engine=True):
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"""Issue a command to the server, parse & return decoded JSON."""
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if include_engine:
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if data is None:
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data = {}
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data['engine'] = self.engine.as_json()
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response = self.server.urlopen_json(command,
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project_id=self.project_id,
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data=data)
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if 'historyEntry' in response:
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# **response['historyEntry'] won't work as keys are unicode :-/
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he = response['historyEntry']
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self.history_entry = history.HistoryEntry(he['id'], he['time'],
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he['description'])
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return response
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def get_models(self):
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"""Fill out column metadata.
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column structure is sent in a list of columns in their order.
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The cellIndex is used to find that column's data when returned from
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get_rows()."""
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response = self.do_json('get-models', include_engine=False)
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column_model = response['columnModel']
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column_index = {}
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self.columns = [column['name'] for column in column_model['columns']]
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for i, column in enumerate(column_model['columns']):
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name = column['name']
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self.column_order[name] = i
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column_index[name] = column['cellIndex']
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self.key_column = column_model['keyColumnName']
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self.has_records = response['recordModel'].get('hasRecords', False)
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self.rows_response_factory = RowsResponseFactory(column_index)
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# TODO: implement rest
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return response
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def wait_until_idle(self, polling_delay=0.5):
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while True:
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response = self.do('get-processes')
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if 'processes' in response and len(response['processes']) > 0:
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time.sleep(polling_delay)
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else:
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return
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def apply_operations(self, file_path, wait=True):
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json = open(file_path).read()
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response_json = self.do('apply-operations', {'operations': json})
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if response_json['code'] == 'pending' and wait:
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self.wait_until_idle()
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return 'ok'
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return response_json['code'] # can be 'ok' or 'pending'
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def export(self, export_format='tsv'):
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"""Return a fileobject of a project's data."""
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url = ('export-rows/' + urllib.quote(self.project_name()) + '.' +
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export_format)
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return self.do_raw(url, {'format': export_format})
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def export_rows(self, **kwargs):
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"""Return an iterable of parsed rows of a project's data."""
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return csv.reader(self.export(**kwargs), dialect='excel-tab')
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def delete(self):
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response_json = self.do_json('delete-project', include_engine=False)
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return 'code' in response_json and response_json['code'] == 'ok'
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def compute_facets(self, facets=None):
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"""Compute facets as per the project's engine.
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The response object has two attributes, mode & facets. mode is one of
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'row-based' or 'record-based'. facets is a magic list of facets in the
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same order as they were specified in the Engine. Magic allows the
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original Engine's facet as index into the response, e.g.,
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name_facet = TextFacet('name')
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response = project.compute_facets(name_facet)
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response.facets[name_facet] # same as response.facets[0]
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"""
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if facets:
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self.engine.set_facets(facets)
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response = self.do_json('compute-facets')
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return self.engine.facets_response(response)
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def get_rows(self, facets=None, sort_by=None, start=0, limit=10):
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if facets:
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self.engine.set_facets(facets)
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if sort_by is not None:
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self.sorting = facet.Sorting(sort_by)
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response = self.do_json('get-rows', {'sorting': self.sorting.as_json(),
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'start': start, 'limit': limit})
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return self.rows_response_factory(response)
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def reorder_rows(self, sort_by=None):
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if sort_by is not None:
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self.sorting = facet.Sorting(sort_by)
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response = self.do_json('reorder-rows',
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{'sorting': self.sorting.as_json()})
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# clear sorting
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self.sorting = facet.Sorting()
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return response
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def remove_rows(self, facets=None):
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if facets:
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self.engine.set_facets(facets)
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return self.do_json('remove-rows')
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def text_transform(self, column, expression, on_error='set-to-blank',
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repeat=False, repeat_count=10):
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response = self.do_json('text-transform', {
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'columnName': column, 'expression': expression,
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'onError': on_error, 'repeat': repeat,
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'repeatCount': repeat_count})
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return response
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def edit(self, column, edit_from, edit_to):
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edits = [{'from': [edit_from], 'to': edit_to}]
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return self.mass_edit(column, edits)
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def mass_edit(self, column, edits, expression='value'):
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"""edits is [{'from': ['foo'], 'to': 'bar'}, {...}]"""
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edits = json.dumps(edits)
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response = self.do_json('mass-edit', {
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'columnName': column, 'expression': expression, 'edits': edits})
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return response
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clusterer_defaults = {
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'binning': {
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'type': 'binning',
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'function': 'fingerprint',
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'params': {},
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},
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'knn': {
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'type': 'knn',
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'function': 'levenshtein',
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'params': {
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'radius': 1,
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'blocking-ngram-size': 6,
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},
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},
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}
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def compute_clusters(self, column, clusterer_type='binning',
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function=None, params=None):
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"""Returns a list of clusters of {'value': ..., 'count': ...}."""
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clusterer = self.clusterer_defaults[clusterer_type]
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if params is not None:
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clusterer['params'] = params
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if function is not None:
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clusterer['function'] = function
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clusterer['column'] = column
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response = self.do_json('compute-clusters', {
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'clusterer': json.dumps(clusterer)})
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return [[{'value': x['v'], 'count': x['c']} for x in cluster]
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for cluster in response]
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def annotate_one_row(self, row, annotation, state=True):
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if annotation not in ('starred', 'flagged'):
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raise ValueError('annotation must be one of starred or flagged')
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state = 'true' if state == True else 'false'
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return self.do_json('annotate-one-row', {'row': row.index,
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annotation: state})
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def flag_row(self, row, flagged=True):
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return self.annotate_one_row(row, 'flagged', flagged)
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def star_row(self, row, starred=True):
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return self.annotate_one_row(row, 'starred', starred)
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def add_column(self, column, new_column, expression='value',
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column_insert_index=None, on_error='set-to-blank'):
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if column_insert_index is None:
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column_insert_index = self.column_order[column] + 1
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response = self.do_json('add-column', {'baseColumnName': column,
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'newColumnName': new_column, 'expression': expression,
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'columnInsertIndex': column_insert_index, 'onError': on_error})
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self.get_models()
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return response
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def split_column(self, column, separator=',', mode='separator',
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regex=False, guess_cell_type=True,
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remove_original_column=True):
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response = self.do_json('split-column', {'columnName': column,
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'separator': separator, 'mode': mode, 'regex': regex,
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'guessCellType': guess_cell_type,
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'removeOriginalColumn': remove_original_column})
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self.get_models()
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return response
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def rename_column(self, column, new_column):
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response = self.do_json('rename-column', {'oldColumnName': column,
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'newColumnName': new_column})
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self.get_models()
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return response
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def reorder_columns(self, new_column_order):
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"""Takes an array of column names in the new order."""
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response = self.do_json('reorder-columns', {
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'columnNames': new_column_order})
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self.get_models()
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return response
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def move_column(self, column, index):
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"""Move column to a new position."""
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if index == 'end':
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index = len(self.columns) - 1
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response = self.do_json('move-column', {'columnName': column,
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'index': index})
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self.get_models()
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return response
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def blank_down(self, column):
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response = self.do_json('blank-down', {'columnName': column})
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self.get_models()
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return response
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def fill_down(self, column):
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response = self.do_json('fill-down', {'columnName': column})
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self.get_models()
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return response
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def transpose_columns_into_rows(self, start_column, column_count,
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combined_column_name, separator=':', prepend_column_name=True,
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ignore_blank_cells=True):
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response = self.do_json('transpose-columns-into-rows', {
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'startColumnName': start_column, 'columnCount': column_count,
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'combinedColumnName': combined_column_name,
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'prependColumnName': prepend_column_name,
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'separator': separator, 'ignoreBlankCells': ignore_blank_cells})
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self.get_models()
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return response
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def transpose_rows_into_columns(self, column, row_count):
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response = self.do_json('transpose-rows-into-columns', {
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'columnName': column, 'rowCount': row_count})
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self.get_models()
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return response
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