mapnik/tests/python_tests/csv_test.py

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2011-10-29 06:57:51 +02:00
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import glob
from nose.tools import *
from utilities import execution_path
import os, mapnik2
def setup():
# All of the paths used are relative, if we run the tests
# from another directory we need to chdir()
os.chdir(execution_path('.'))
if 'csv' in mapnik2.DatasourceCache.instance().plugin_names():
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def get_csv_ds(filename):
return mapnik2.Datasource(type='csv',file=os.path.join('../data/csv/',filename),quiet=True)
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def test_broken_files(visual=False):
broken = glob.glob("../data/csv/fails/*.*")
broken.extend(glob.glob("../data/csv/warns/*.*"))
# Add a filename that doesn't exist
broken.append("../data/csv/fails/does_not_exist.csv")
for csv in broken:
throws = False
if visual:
try:
ds = mapnik2.Datasource(type='csv',file=csv,strict=True,quiet=True)
print '\x1b[33mfailed\x1b[0m',csv
except Exception:
print '\x1b[1;32m✓ \x1b[0m', csv
def test_good_files(visual=False):
good_files = glob.glob("../data/csv/*.*")
good_files.extend(glob.glob("../data/csv/warns/*.*"))
for csv in good_files:
if visual:
try:
ds = mapnik2.Datasource(type='csv',file=csv,quiet=True)
print '\x1b[1;32m✓ \x1b[0m', csv
except Exception:
print '\x1b[33mfailed\x1b[0m',csv
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def test_type_detection(**kwargs):
ds = get_csv_ds('nypd.csv')
eq_(ds.fields(),['Precinct','Phone','Address','City','geo_longitude','geo_latitude','geo_accuracy'])
eq_(ds.field_types(),['str','str','str','str','float','float','str'])
feat = ds.featureset().next()
attr = {'City': u'New York, NY', 'geo_accuracy': u'house', 'Phone': u'(212) 334-0711', 'Address': u'19 Elizabeth Street', 'Precinct': u'5th Precinct', 'geo_longitude': -70, 'geo_latitude': 40}
eq_(feat.attributes,attr)
eq_(len(ds.all_features()),2)
def test_skipping_blank_rows(**kwargs):
ds = get_csv_ds('blank_rows.csv')
eq_(ds.fields(),['x','y','name'])
eq_(ds.field_types(),['int','int','str'])
eq_(len(ds.all_features()),2)
def test_empty_rows(**kwargs):
ds = get_csv_ds('empty_rows.csv')
eq_(len(ds.fields()),10)
eq_(len(ds.field_types()),10)
eq_(ds.fields(),['x', 'y', 'text', 'date', 'integer', 'boolean', 'float', 'time', 'datetime', 'empty_column'])
eq_(ds.field_types(),['int', 'int', 'str', 'str', 'int', 'str', 'float', 'str', 'str', 'str'])
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fs = ds.featureset()
feat = fs.next()
attr = {'x': 0, 'empty_column': u'', 'text': u'a b', 'float': 1.0, 'datetime': u'1971-01-01T04:14:00', 'y': 0, 'boolean': u'True', 'time': u'04:14:00', 'date': u'1971-01-01', 'integer': 40}
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eq_(feat.attributes,attr)
while feat:
eq_(len(feat),10)
eq_(feat['empty_column'],u'')
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feat = fs.next()
def test_slashes(**kwargs):
ds = get_csv_ds('has_attributes_with_slashes.csv')
eq_(len(ds.fields()),3)
fs = ds.all_features()
eq_(fs[0].attributes,{'x':0,'y':0,'name':u'a/a'})
eq_(fs[1].attributes,{'x':1,'y':4,'name':u'b/b'})
eq_(fs[2].attributes,{'x':10,'y':2.5,'name':u'c/c'})
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def test_wkt_field(**kwargs):
ds = get_csv_ds('wkt.csv')
eq_(len(ds.fields()),2)
eq_(ds.fields(),['type','WKT'])
eq_(ds.field_types(),['str','str'])
fs = ds.all_features()
#import pdb;pdb.set_trace()
eq_(len(fs[0].geometries()),1)
eq_(fs[0].geometries()[0].type(),mapnik2.GeometryType.Point)
eq_(len(fs[1].geometries()),1)
eq_(fs[1].geometries()[0].type(),mapnik2.GeometryType.LineString)
eq_(len(fs[2].geometries()),1)
eq_(fs[2].geometries()[0].type(),mapnik2.GeometryType.Polygon)
eq_(len(fs[3].geometries()),1) # one geometry, two parts
eq_(fs[3].geometries()[0].type(),mapnik2.GeometryType.Polygon)
# tests assuming we want to flatten geometries
# ideally we should not have to:
# https://github.com/mapnik/mapnik/issues?labels=multigeom+robustness&sort=created&direction=desc&state=open&page=1
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eq_(len(fs[4].geometries()),4)
eq_(fs[4].geometries()[0].type(),mapnik2.GeometryType.Point)
eq_(len(fs[5].geometries()),2)
eq_(fs[5].geometries()[0].type(),mapnik2.GeometryType.LineString)
eq_(len(fs[6].geometries()),2)
eq_(fs[6].geometries()[0].type(),mapnik2.GeometryType.Polygon)
eq_(len(fs[7].geometries()),2)
eq_(fs[7].geometries()[0].type(),mapnik2.GeometryType.Polygon)
def test_handling_of_missing_header(**kwargs):
ds = get_csv_ds('missing_header.csv')
eq_(len(ds.fields()),6)
eq_(ds.fields(),['one','two','x','y','_4','aftermissing'])
fs = ds.featureset()
feat = fs.next()
eq_(feat['_4'],'missing')
def test_handling_of_headers_that_are_numbers(**kwargs):
ds = get_csv_ds('numbers_for_headers.csv')
eq_(len(ds.fields()),5)
eq_(ds.fields(),['x','y','1990','1991','1992'])
fs = ds.featureset()
feat = fs.next()
eq_(feat['x'],0)
eq_(feat['y'],0)
eq_(feat['1990'],1)
eq_(feat['1991'],2)
eq_(feat['1992'],3)
eq_(mapnik2.Expression("[1991]=2").evaluate(feat),True)
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def test_quoted_numbers(**kwargs):
ds = get_csv_ds('points.csv')
eq_(len(ds.fields()),3)
eq_(ds.fields(),['x','y','label'])
fs = ds.all_features()
eq_(fs[0]['label'],"0,0")
eq_(fs[1]['label'],"5,5")
eq_(fs[2]['label'],"0,5")
eq_(fs[3]['label'],"5,0")
eq_(fs[4]['label'],"2.5,2.5")
def test_windows_newlines(**kwargs):
ds = get_csv_ds('windows_newlines.csv')
eq_(len(ds.fields()),3)
feats = ds.all_features()
eq_(len(feats),1)
fs = ds.featureset()
feat = fs.next()
eq_(feat['x'],1)
eq_(feat['y'],10)
eq_(feat['z'],9999.9999)
def test_mac_newlines(**kwargs):
ds = get_csv_ds('windows_newlines.csv')
eq_(len(ds.fields()),3)
feats = ds.all_features()
eq_(len(feats),1)
fs = ds.featureset()
feat = fs.next()
eq_(feat['x'],1)
eq_(feat['y'],10)
eq_(feat['z'],9999.9999)
def test_tabs(**kwargs):
ds = get_csv_ds('tabs_in_csv.csv')
eq_(len(ds.fields()),3)
eq_(ds.fields(),['x','y','z'])
fs = ds.featureset()
feat = fs.next()
eq_(feat['x'],-122)
eq_(feat['y'],48)
eq_(feat['z'],0)
def test_separator_pipes(**kwargs):
ds = get_csv_ds('pipe_delimiters.csv')
eq_(len(ds.fields()),3)
eq_(ds.fields(),['x','y','z'])
fs = ds.featureset()
feat = fs.next()
eq_(feat['x'],0)
eq_(feat['y'],0)
eq_(feat['z'],'hello')
def test_separator_semicolon(**kwargs):
ds = get_csv_ds('semicolon_delimiters.csv')
eq_(len(ds.fields()),3)
eq_(ds.fields(),['x','y','z'])
fs = ds.featureset()
feat = fs.next()
eq_(feat['x'],0)
eq_(feat['y'],0)
eq_(feat['z'],'hello')
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def test_that_null_and_bool_keywords_are_empty_strings(**kwargs):
ds = get_csv_ds('nulls_and_booleans_as_strings.csv')
eq_(len(ds.fields()),4)
eq_(ds.fields(),['x','y','null','boolean'])
eq_(ds.field_types(),['int','int','str','str'])
fs = ds.featureset()
feat = fs.next()
eq_(feat['x'],0)
eq_(feat['y'],0)
eq_(feat['null'],'null')
eq_(feat['boolean'],'true')
feat = fs.next()
eq_(feat['x'],0)
eq_(feat['y'],0)
eq_(feat['null'],'')
eq_(feat['boolean'],'false')
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if __name__ == "__main__":
setup()
[eval(run)(visual=True) for run in dir() if 'test_' in run]