def species_from_csv(filename, section):
curdata = load_species_refval()
with open(filename, 'rb') as f:
reader = UnicodeDictReader(f)
for row in reader:
key = row['code'] + '-' + row['region']
for k, v in curdata[key][section].iteritems():
if k in row:
curdata[key][section][k] = row[k]
save_species_refval(curdata)
def species_from_csv(filename, section):
curdata = load_species_refval()
with open(filename, 'rb') as f:
reader = UnicodeDictReader(f)
for row in reader:
key = row['code'] + '-' + row['region']
for k, v in curdata[key][section].iteritems():
if k in row:
curdata[key][section][k] = row[k]
save_species_refval(curdata)
def species_methods_from_csv(filename):
curdata = load_species_refval()
with open(filename, 'rb') as f:
reader = UnicodeDictReader(f)
for row in reader:
code = row.pop('code')
for region in REGIONS:
key = code + '-' + region
if not key in curdata:
continue
for k, v in row.iteritems():
section, field = k.split('-')
curdata[key][section][field] = v
save_species_refval(curdata)
def species_methods_from_csv(filename):
curdata = load_species_refval()
with open(filename, 'rb') as f:
reader = UnicodeDictReader(f)
for row in reader:
code = row.pop('code')
for region in REGIONS:
key = code + '-' + region
if not key in curdata:
continue
for k, v in row.iteritems():
section, field = k.split('-')
curdata[key][section][field] = v
save_species_refval(curdata)
def species_from_dataset(dataset_id=1):
"""
Import the reference values from a previous dataset - not reference,
but actual values.
range:
'Areal favorabil referinta' - r.range_surface_area
habitat:
u'Suprafața adecvata' - r.habitat_surface_area
population_range:
'Populatia favorabila de referinta' - population_alt_minimum_size
"""
from art17.scripts.export_refval import generic_species_exporter
def format_row(sp, sr):
key = '{}-{}'.format(sp.code, sr.region)
population_size = (sr.population_minimum_size
or sr.population_alt_minimum_size
or sr.population_alt_maximum_size)
data = {
'range': {
'Areal favorabil referinta':
unicode(sr.range_surface_area)
if sr.range_surface_area else None,
},
'habitat': {
u'Suprafața adecvata':
unicode(sr.habitat_surface_area)
if sr.habitat_surface_area else None,
},
'population_range': {
'Populatia favorabila de referinta':
unicode(population_size) if population_size else None
}
}
print key, data
return (key, data)
newdata = dict(generic_species_exporter(format_row, dataset_id=dataset_id))
curdata = load_species_refval()
data = smart_update(curdata, newdata)
save_species_refval(data)
print "Done."
def species_from_dataset(dataset_id=1):
"""
Import the reference values from a previous dataset - not reference,
but actual values.
range:
'Areal favorabil referinta' - r.range_surface_area
habitat:
u'Suprafața adecvata' - r.habitat_surface_area
population_range:
'Populatia favorabila de referinta' - population_alt_minimum_size
"""
from art17.scripts.export_refval import generic_species_exporter
def format_row(sp, sr):
key = '{}-{}'.format(sp.code, sr.region)
population_size = (sr.population_minimum_size or
sr.population_alt_minimum_size or
sr.population_alt_maximum_size)
data = {
'range': {
'Areal favorabil referinta': unicode(
sr.range_surface_area) if sr.range_surface_area else None,
},
'habitat': {
u'Suprafața adecvata': unicode(sr.habitat_surface_area)
if sr.habitat_surface_area else None,
},
'population_range': {
'Populatia favorabila de referinta': unicode(population_size)
if population_size else None
}
}
print key, data
return (key, data)
newdata = dict(generic_species_exporter(format_row, dataset_id=dataset_id))
curdata = load_species_refval()
data = smart_update(curdata, newdata)
save_species_refval(data)
print "Done."
def post(self, **kwargs):
context = self.get_context(**kwargs)
form = context['form']
subject = context['subject']
if form.validate():
required_struct = get_struct(get_refvals(context['subject']))
wb = load_workbook(form.excel_doc.data)
struct = {sheet: [r.value for r in wb[sheet].rows[0] if r.value]
for sheet in wb.get_sheet_names()}
if required_struct == struct:
d = process_xls(wb, struct)
if subject == 'species':
save_species_refval(d)
elif subject == 'habitat':
save_habitat_refval(d)
else:
raise NotImplementedError
flash(u'Noile valori de referință au fost salvate.', 'success')
else:
flash(u'Documentul Excel nu este în formatul acceptat.',
'danger')
return render_template(self.template_name, **context)
def refactor_species_refval():
data = refactor_refval('species.json', 'species')
save_species_refval(data)
def refactor_species_refval():
data = refactor_refval('species.json', 'species')
save_species_refval(data)