def test_columns_csv_export_multiseries():
exporter = ExportCSV(MagicMock(), MagicMock())
headers = ['series', 'name', 'code', 'y'];
out = StringIO()
series = [
{
'data': [
{
'code': 'SK',
'name': 'Slovakia',
'y': 1
}
],
'name': 'series1',
'notation': None
},
{
'data': [
{
'code': 'AB',
'name': 'ABCD',
'y': 2
}
],
'name': 'series2',
'notation': None
}
]
exporter.datapoints(out, series)
out.seek(0)
csv_output = out.read().split('\r\n')
assert csv_output[2].split(',') == ['series1', 'Slovakia', 'SK', '1']
assert csv_output[3].split(',') == ['series2', 'ABCD', 'AB', '2']
def test_csv_metadata():
exporter = ExportCSV(MagicMock(), MagicMock())
out = StringIO()
metadata = {
'chart-title': 'Number of households',
'source-dataset': 'Digital-Agenda',
'chart-url': 'http://url.to/chart#table',
'filters-applied': [
['indicator', 'Internet Usage'],
['breakdown', 'by age'],
['time-period', '2012']
],
}
exporter.write_metadata(out, metadata)
out.seek(0)
output = out.read().split('\r\n')
from datetime import datetime
assert output[0] == 'Chart title:,Number of households'
assert output[1] == 'Source dataset:,Digital-Agenda'
assert output[2] == 'Extraction-Date:,' + datetime.now().strftime('%d %b %Y')
assert output[3] == 'Link to the chart/table:,http://url.to/chart#table'
assert output[4] == 'Selection of filters applied'
assert output[5] == 'indicator,Internet Usage'
assert output[6] == 'breakdown,by age'
assert output[7] == 'time-period,2012'
def test_csv_annotations():
exporter = ExportCSV(MagicMock(), MagicMock())
out = StringIO()
metadata = {
"description": "description text",
"section_title": "Definition and scopes:",
"indicators_details_url": "http://url.to/indicators",
"blocks": [
{
"definition": "dèfinitioñ ţext",
"filter_label": "Indicator",
"label": "long label text",
"source_label": "source label text",
"source_url": "http://url.to/source",
"source_definition": "source definition text",
"note": "note text"
}
],
}
exporter.write_annotations(out, metadata)
out.seek(0)
output = out.read().split('\r\n')
assert output[0] == 'Definition and scopes:'
assert output[1] == 'Indicator:,long label text'
assert output[2] == 'Definition:,dèfinitioñ ţext'
assert output[3] == 'Notes:,note text'
assert output[4] == 'Source:,source definition text'
assert output[5] == 'List of available indicators:,http://url.to/indicators'
def test_bar_profile_csv_export():
exporter = ExportCSV(MagicMock(), MagicMock())
out = StringIO()
series = [
{
'data': [
{
'attributes': {
'time-period': {
'notation': '2000'
}
},
'code': 'notation',
'name': 'long_label',
'eu': 0.5,
'original': 0.9,
'y': 2,
}
],
'name': 'Austria'
},
]
exporter.datapoints_profile(out, series)
out.seek(0)
csv_output = out.read().split('\r\n')
assert csv_output[0].split(',') == [
'period', 'name', 'eu', 'original']
assert csv_output[1].split(',') == [
'2000', 'long_label', '0.5', '0.9']
def test_table_profile_csv_export():
exporter = ExportCSV(MagicMock(), MagicMock())
out = StringIO()
series = [
{
'data': {
'latest': 2010,
'ref-area': {
'label': 'Austria'
},
'table':{
'some-key': {
'2009': 0.8,
'2010': 0.9,
'eu': 52,
'breakdown': 'All individuals',
'indicator': 'Telephoning or video calls',
'unit-measure': '% of internet users (last 3 months)',
'rank': 15,
'inner_order': 5,
'unit': 'pc_ent'
},
'some-other-key': {
'2009': 0.8,
'eu': 52,
'breakdown': 'ex breakdown',
'indicator': 'ex indicator',
'unit-measure': 'ex unit',
'rank': 15
}
}
}
}
]
exporter.datapoints_profile_table(out, series)
out.seek(0)
csv_output = out.read().split('\r\n')
assert csv_output[0].split(',') == [
'country', 'indicator', 'breakdown', 'unit', '2007', '2008', '2009', '2010', 'EU28 value 2010', 'rank']
assert csv_output[1].split(',') == [
'Austria', 'Telephoning or video calls', 'All individuals', '% of internet users (last 3 months)', '-', '-', '0.8', '0.9', '52', '15']
assert csv_output[2].split(',') == [
'Austria', 'ex indicator', 'ex breakdown', 'ex unit', '-', '-', '0.8', '-', '52', '15']
def test_columns_csv_export():
exporter = ExportCSV(MagicMock(), MagicMock())
out = StringIO()
series = [{
'data': [
{
'code': 'SK',
'name': 'Slovakia',
'y': 1
}
],
'name': 'series1',
'notation': None
}]
exporter.datapoints(out, series)
out.seek(0)
csv_output = out.read().split('\r\n')
assert csv_output[0] == 'Data extracted:';
assert csv_output[1].split(',') == ['series', 'name', 'code', 'y'];
assert csv_output[2].split(',') == ['series1', 'Slovakia', 'SK', '1']
def test_lines_csv_export():
exporter = ExportCSV(MagicMock(), MagicMock())
out = StringIO()
series = [
{
'data': [
{
'code': '2000',
'name': 'Year:2000',
'y': 1
}
],
'name': 'series1',
'notation': None
},
]
exporter.datapoints(out, series)
out.seek(0)
csv_output = out.read().split('\r\n')
assert csv_output[2].split(',') == ['series1', 'Year:2000', '2000', '1']
def test_formatter_decision():
exporter = ExportCSV(MagicMock(), MagicMock())
series = [
{
'data': [
{
'code': '2000',
'name': 'year:2000',
'y': 1
}
],
'name': 'series1',
'notation': None
},
]
exporter.datapoints = Mock()
exporter.datapoints_n = Mock()
exporter.request.form = {
'metadata': json.dumps({}),
'chart_data': json.dumps(series),
'chart_type': 'columns',
'annotations': json.dumps({})
}
exporter.export()
assert(exporter.datapoints.call_count == 1)
exporter.request.form = {
'metadata': json.dumps({}),
'chart_data': json.dumps(series),
'chart_type': 'bubbles',
'annotations': json.dumps({})
}
exporter.export()
assert(exporter.datapoints_n.call_count == 1)
exporter.request.form = {
'metadata': json.dumps({}),
'chart_data': json.dumps(series),
'chart_type': 'scatter',
'annotations': json.dumps({})
}
exporter.export()
assert(exporter.datapoints_n.call_count == 2)
def test_scatter_csv_export():
exporter = ExportCSV(MagicMock(), MagicMock())
out = StringIO()
series = [
[
{
'data': [
{
'name': 'AT',
'x': 1,
'y': 1
}
],
'name': 'Austria'
},
]
]
exporter.datapoints_n(out, series)
out.seek(0)
csv_output = out.read().split('\r\n')
assert csv_output[0].split(',') == ['series', 'name', 'x', 'y'];
assert csv_output[1].split(',') == ['Austria', 'AT', '1', '1']