def main(args):
data = Data()
dataset = common.Dataset(
id=cognition.__name__,
name="COSTATOL",
description="Cognitive Structures across the Tree of Life",
publisher_name="Max Planck Institute for the Science of Human History",
publisher_place="Jena",
publisher_url="http://www.shh.mpg.de",
license="http://creativecommons.org/licenses/by/4.0/",
domain='cognition.clld.org',
jsondata={
'license_icon': 'cc-by.png',
'license_name': 'Creative Commons Attribution 4.0 International License'})
DBSession.add(dataset)
#
# TODO: add editors!
#
for rec in Database.from_file(args.data_file('sources.bib')):
data.add(common.Source, rec.id, _obj=bibtex2source(rec))
contrib = common.Contribution(id='costatol', name='COSTATOL')
for datapoint in reader(args.data_file('values.csv'), delimiter=',', dicts=True):
param = data['Parameter'].get(datapoint['cognitive capacity'])
if not param:
name = datapoint['cognitive capacity']
param = data.add(common.Parameter, name, id=slug(name), name=name)
species = data['Language'].get(datapoint['species'])
if not species:
name = datapoint['species']
species = data.add(common.Language, name, id=slug(name), name=name)
vid = '%s-%s' % (species.id, param.id)
vs = data.add(
common.ValueSet,
vid,
id=vid,
language=species,
parameter=param,
contribution=contrib)
data.add(common.Value, vid, id=vid, name=datapoint['value'], valueset=vs)
match = source_pattern.match(datapoint['source'])
if match:
DBSession.add(common.ValueSetReference(
valueset=vs,
source=data['Source'][match.group('key')],
description=match.group('pages')))
for species in reader(args.data_file('species.csv'), delimiter=',', namedtuples=True):
data['Language'][species.name].longitude = species.longitude
data['Language'][species.name].latitude = species.latitude
def main(args):
features = reader(args.data_file('grambank_features.csv'), dicts=True, )
features = [GBFeature(f) for f in features]
features = {'%s' % int(f.id[2:]): f for f in features}
errors = []
db = create_engine('postgresql://robert@/glottolog3')
for l in DBSession.query(Language):
if l.id == 'qgr':
continue
gc = l.glottocode
ma = db.execute("""
select
m.id
from
macroarea as m, languoidmacroarea as lm, language as l
where
m.pk = lm.macroarea_pk and lm.languoid_pk = l.pk and l.id = '%s';""" % gc).fetchone()[0]
if ma == 'pacific':
ma = 'papunesia'
errors.extend(export(args, l, features, gc, ma))
with UnicodeWriter(args.data_file('na_errors.tsv'), delimiter=b'\t') as writer:
writer.writerow(['Language', 'Feature', 'Value', 'Source', 'Comment'])
writer.writerows(errors)
def main(args, reload=False):
species = {}
db = args.data_file('theplantlist', 'db.json')
if reload:
for a in bs(get('/1.1/browse/-/')).find('ul', id='nametree').find_all('a'):
with iopen(args.data_file('theplantlist', a.text + '.csv'), 'w', encoding='utf8') as fp:
fp.write(get(a['href'] + a.text + '.csv'))
if db.exists():
with open(db) as fp:
species = json.load(fp)
else:
for p in args.data_file('theplantlist').files('*.csv'):
for row in reader(p, namedtuples=True, delimiter=','):
if row.Taxonomic_status_in_TPL == 'Accepted':
id_ = slug(row.Genus + row.Species)
species[id_] = row.ID
with open(db, 'w') as fp:
json.dump(species, fp)
with transaction.manager:
found = 0
for p in DBSession.query(Parameter):
id_ = slug(p.name)
if id_ in species:
found += 1
p.tpl_id = species[id_]
print(found)
def upgrade():
conn = Connection(op.get_bind())
example_map = {}
sid = 204
for example in jsonload(data_file('lingala_examples.json')):
sid += 1
kw = {
'id': '60-%s' % sid,
'language_pk': conn.pk(Language, '60'),
'name': example['Text'],
'description': example['Translation'],
'gloss': '\t'.join(example['Gloss'].split()),
'analyzed': '\t'.join(example['Text'].split()),
'type': example['Type'].strip().lower(),
'jsondata': {'sort': int(example['Order_number']), 'alt_translation': None}
}
example_map[example['Example_number']] = conn.insert(Sentence, **kw)
for ve in jsonload(data_file('lingala_value_examples.json')):
vspk = conn.pk(ValueSet, '60-%s' % ve['Features::Feature_number'])
vpk = conn.pk(Value, vspk, attr='valueset_pk')
conn.insert(
ValueSentence, value_pk=vpk, sentence_pk=example_map[ve['Example_number']])
for i, comment in enumerate(reader(data_file('lingala_valueset_comments.tab'), dicts=True)):
vspk = conn.pk(ValueSet, '60-%s' % comment['Features::Feature_number'])
comment['Comments_on_value_assignment'] = comment['Comments_on_value_assignment'].replace('\x0b', '\n')
conn.update(
ValueSet,
{
'description': comment['Comments_on_value_assignment'],
'markup_description': None,
},
pk=vspk)
def download(args):
data = dict(wikipedia={}, multitree=defaultdict(list))
for item in reader(args.data_file(DATA_FILE), namedtuples=True):
if item.Glottolog and GC_PATTERN.match(item.Glottolog.strip()):
data['wikipedia'][item.Glottolog.strip()] = item.Wiki.strip()
for code in ll_codes(item):
data['multitree'][item.Glottolog.strip()].append(code)
return data
def download(args):
data = dict(wikipedia={}, multitree=defaultdict(list))
for item in reader(args.data_file(DATA_FILE), namedtuples=True):
if item.Glottolog and GC_PATTERN.match(item.Glottolog.strip()):
data['wikipedia'][item.Glottolog.strip()] = item.Wiki.strip()
for code in ll_codes(item):
data['multitree'][item.Glottolog.strip()].append(code)
return data
def upgrade():
csv = path(phoible.__file__).dirname().joinpath("..", "data", "InventoryID-InternetArchive.csv")
ia_urls = {row[0]: row[1] for row in reader(csv) if row[1] != "NA"}
conn = Connection(op.get_bind())
for id_, url in ia_urls.items():
pk = conn.pk(Contribution, id_)
conn.update(Inventory, dict(internetarchive_url=url), pk=pk)
def get_lginfo(args, filter=None):
return [
(r.id, r) for r in
dsv.reader(
args.data_dir.joinpath('languoids', 'forkel_lginfo.tab'),
fieldnames=['id', 'longitude', 'latitude', 'macro_area', 'year'],
namedtuples=True)
if filter is None or filter(r)]
def test_reader(self):
from clld.lib.dsv import reader
lines = ['first\tline', 'sücond\tläneß']
encoded_lines = [l.encode('utf8') for l in lines]
csv_lines = [l.replace('\t', ',') for l in lines]
def check(r):
res = list(r)
assert len(res) == 2
assert res[1][1] == 'läneß'
check(reader(lines))
for lt in ['\n', '\r\n', '\r']:
check(reader(StringIO(str(lt).join(encoded_lines))))
check(reader(TESTS_DIR.joinpath('csv.txt'), delimiter=','))
res = list(reader(TESTS_DIR.joinpath('test.tab'), namedtuples=True))
assert res[0].a_name == 'b'
# Missing column values should be set to None:
assert res[2].a_name is None
r = list(reader(lines, dicts=True))
assert len(r) == 1 and r[0]['first'] == 'sücond'
r = list(reader(lines, namedtuples=True))
assert len(r) == 1 and r[0].first == 'sücond'
r = list(reader(csv_lines, namedtuples=True, delimiter=','))
assert len(r) == 1 and r[0].first == 'sücond'
def upgrade():
csv = path(phoible.__file__).dirname().joinpath(
'..', 'data', 'InventoryID-InternetArchive.csv')
ia_urls = {row[0]: row[1] for row in reader(csv) if row[1] != 'NA'}
conn = Connection(op.get_bind())
for id_, url in ia_urls.items():
pk = conn.pk(Contribution, id_)
conn.update(Inventory, dict(internetarchive_url=url), pk=pk)
def main(args):
mapping = {}
for row in reader(args.data_file('phoible-phonemes.tsv'), namedtuples=True):
if row.GlyphID not in mapping:
unicode_desc = [(c, unicodedata.name(c)) for c in row.Phoneme]
description = ' - '.join([t[1] for t in unicode_desc])
mapping[int(row.GlyphID)] = b16encode(md5(description).digest())
with open(args.data_file('segment_id_mapping.txt'), 'w') as fp:
for gid in sorted(mapping.keys()):
fp.write(' ("%s", "%s"),\n' % (gid, mapping[gid]))
def update(args):
pid, cid = 'vitality', 'unesco'
count = 0
notfound = {}
contrib = common.Contribution.get(cid, default=None)
if not contrib:
contrib = common.Contribution(
id=cid,
name='Atlas of the World’s Languages in Danger',
description='Atlas of the World’s Languages in Danger, © UNESCO, http://www.unesco.org/culture/languages-atlas')
param = common.Parameter.get(pid, default=None)
if param is None:
param = common.Parameter(
id=pid,
name='Degree of endangerment')
domain = {de.name: de for de in param.domain}
for i, spec in enumerate(VITALITY_VALUES):
name, desc = spec
if name not in domain:
number = i + 1
domain[name] = common.DomainElement(
id='%s-%s' % (pid, number),
name=name,
description=desc,
number=number,
parameter=param)
valuesets = {vs.id: vs for vs in param.valuesets}
for item in reader(args.data_file(DATA_FILE), dicts=True):
if item['ISO639-3 codes']:
for code in item['ISO639-3 codes'].split(','):
code = code.strip()
lang = Languoid.get(code, key='hid', default=None)
if lang:
count += 1
item['url'] = 'http://www.unesco.org/culture/languages-atlas/en/atlasmap/language-iso-%s.html' % code
lang.update_jsondata(unesco=item)
de = domain[item['Degree of endangerment']]
vsid = '%s-%s' % (pid, lang.id)
vs = valuesets.get(vsid)
if not vs:
vs = common.ValueSet(
id='vitality-%s' % lang.id,
parameter=param,
contribution=contrib,
language=lang)
DBSession.add(common.Value(valueset=vs, name=de.name, domainelement=de))
valuesets[vsid] = vs
else:
vs.values[0].domainelement = de
else:
notfound[code] = 1
print 'assigned', count, 'unesco urls'
print 'missing iso codes:', notfound
def import_features_collaborative_sheet(datadir, data):
for feature in reader(os.path.join(datadir, 'features_collaborative_sheet.tsv'), dicts=True):
feature = FeatureSpec(feature)
f = data.add(Feature, feature.id, id=feature.id, name=feature.name, doc=feature.doc, patron=feature.patron, std_comments=feature.std_comments, name_french=feature.name_french, jl_relevant_unit=feature.jl_relevant_unit, jl_function=feature.jl_function, jl_formal_means=feature.jl_formal_means, hard_to_deny=feature.hard_to_deny, prone_misunderstanding=feature.prone_misunderstanding, requires_extensive_data=feature.requires_extensive_data, last_edited=feature.last_edited, other_survey=feature.other_survey)
for i, (deid, desc) in enumerate(feature.domain.items()):
DomainElement(
id='%s-%s' % (f.id, deid),
parameter=f,
abbr=deid,
name='%s - %s' % (deid, desc),
number=int(deid) if deid != '?' else 999,
description=desc,
jsondata=dict(icon=ORDERED_ICONS[i].name))
def main(args):
data = Data()
# fetch language data from glottolog:
glottolog = glottocodes_by_isocode(
'postgresql://robert@/glottolog3', ['id', 'name', 'latitude', 'longitude'])
dataset = common.Dataset(
id=jcld.__name__,
name="Journal of Cross-Linguistic Databases",
domain='jcld.clld.org')
DBSession.add(dataset)
contribution = data.add(common.Contribution, '1', id='1', name='fb')
for i, row in enumerate(reader(file(args.data_file('fb_jcld.tab')), namedtuples=True, encoding='latin1')):
if row.Feature not in data['Parameter']:
parameter = data.add(common.Parameter, row.Feature, id='1', name=row.Feature)
else:
parameter = data['Parameter'][row.Feature]
if row.Value not in data['DomainElement']:
de = data.add(
common.DomainElement, row.Value,
id='%s-%s' % (parameter.id, slug(row.Value)), parameter=parameter, name=row.Value)
else:
de = data['DomainElement'][row.Value]
if row.Language not in data['Language']:
if row.Language not in glottolog:
print '--->', row.Language
continue
glottocode, name, lat, lon = glottolog[row.Language]
language = data.add(
common.Language, row.Language,
id=slug(row.Language), name=name, latitude=lat, longitude=lon)
else:
language = data['Language'][row.Language]
id_ = str(i + 1) #'%s-%s' % (parameter.id, language.id)
vs = common.ValueSet(
id=id_,
parameter=parameter,
language=language,
contribution=contribution,
description=row.Comment,
source=row.Source)
common.Value(valueset=vs, name=row.Value, domainelement=de)
def update(args):
codes = {}
for lang in reader(args.data_file(DATA_FILE), namedtuples=True):
codes[lang.LangID] = 1
count = 0
for lang in DBSession.query(Languoid)\
.filter(Languoid.hid != None)\
.filter(not_(icontains(Languoid.hid, 'nocode'))):
if lang.hid in codes:
lang.update_jsondata(ethnologue=LANGUAGE_URL + lang.hid)
else:
lang.update_jsondata(ethnologue=None)
count += 1
print count, 'iso codes have no ethnologue code'
ethnologue = args.json
leafsets = defaultdict(list)
for id_, doc in ethnologue['docs'].items():
for sid, spec in get_classification(id_, doc).items():
leafs = sorted(set([p[0] for p in spec[2]]))
if leafs:
leafsets[tuple(leafs)].append(sid)
all = 0
matched = 0
for family in DBSession.query(Languoid)\
.filter(Languoid.level == LanguoidLevel.family)\
.filter(Language.active == True):
leafs = []
all += 1
for row in DBSession.query(TreeClosureTable.child_pk, Languoid.hid)\
.filter(TreeClosureTable.parent_pk == family.pk)\
.filter(TreeClosureTable.child_pk == Languoid.pk)\
.filter(Languoid.hid != None):
if len(row[1]) == 3:
leafs.append(row[1])
leafs = tuple(sorted(set(leafs)))
for i, subgroup in enumerate(leafsets.get(leafs, [])):
if i == 0:
matched += 1
family.update_jsondata(ethnologue=SUBGROUP_URL + subgroup)
break
print matched, 'of', all, 'families have an exact counterpart in ethnologue!'
def coordinates(args, languages):
diff = lambda x, y: abs(x - y) > 0.001
for hid, lon, lat in dsv.reader(args.data_file("coordinates.tab")):
if hid not in languages:
languages[hid] = Languoid.get(hid, key="hid", default=None)
if not languages[hid]:
continue
language = languages[hid]
lat, lon = map(float, [lat, lon])
if not language.latitude or not language.longitude:
language.longitude, language.latitude = lon, lat
args.log.info("++ %s" % language.id)
elif diff(language.longitude, lon) or diff(language.latitude, lat):
language.longitude, language.latitude = lon, lat
args.log.info("~~ %s" % language.id)
def from_csv(data_file, model, data, name=None, visitor=None, filter_=None):
if filter_ is None:
filter_ = lambda r: True
kw = {'delimiter': ',', 'lineterminator': str('\r\n'), 'quotechar': '"'}
for fname in data_files(data_file, (name or model.__csv_name__) + '.csv'):
for row in list(reader(fname, **kw))[1:]:
if row and filter_(row):
try:
obj = model.from_csv(row, data)
except (KeyError, IndexError):
obj = None
print(fname)
print(row)
raise
if obj:
obj = data.add(model, row[0], _obj=obj)
if visitor:
visitor(obj, row, data)
def main(args):
sources = jsonload(args.data_file('sources.json'))
fields = ['href', 'name', 'author', 'iso', 'source', 'notes', 'wordlist']
with UnicodeWriter(args.data_file('..', 'sources.csv')) as fp:
fp.writerow(fields)
for source in sorted(sources, key=lambda i: i['name']):
fp.writerow([source.get(f, '') for f in fields])
return
ethnologue_names = {
r.ISO_639: r.Language_Name for r in reader(args.data_file(
'..', '..', 'ethnologue-17-data', 'Table_of_Languages.tab'), namedtuples=True)}
# ASJP name for language, Ethnologue's name, ISO code
rows = [['ASJP Name', 'Ethnologue name', 'ISO code']]
subquery = DBSession.query(LanguageSource.language_pk).distinct().subquery()
for i, l in enumerate(DBSession.query(Doculect).order_by(Doculect.pk).filter(not_(Doculect.pk.in_(subquery)))):
rows.append([l.id, ethnologue_names.get(l.code_iso, ''), l.code_iso or ''])
#print i
with UnicodeWriter(args.data_file('..', 'doculects_without_source.csv')) as fp:
fp.writerows(rows)
def countries(args, languages, stats):
"""update relations between languages and countries they are spoken in.
"""
cname_map = {
'Tanzania': 'Tanzania, United Republic of',
'Russia': 'Russian Federation',
'South Korea': 'Korea, Republic of',
'Iran': 'Iran, Islamic Republic of',
'Syria': 'Syrian Arab Republic',
'Laos': "Lao People's Democratic Republic",
r"C\^ote d'Ivoire": "Côte d'Ivoire",
'British Virgin Islands': 'Virgin Islands, British',
'Bolivia': 'Bolivia, Plurinational State of',
'Venezuela': 'Venezuela, Bolivarian Republic of',
'Democratic Republic of the Congo': 'Congo, The Democratic Republic of the',
'Micronesia': 'Micronesia, Federated States of',
}
countries = {}
for row in dsv.reader(
args.data_dir.joinpath('languoids', 'forkel_countries.tab'), encoding='latin1'):
hid, cnames = row[0], row[1:]
if hid not in languages:
languages[hid] = Languoid.get(hid, key='hid', default=None)
if not languages[hid]:
args.log.warn('unknown hid in countries.tab: %s' % hid)
continue
l = languages[hid]
if l.countries:
# we only add country relations to new languages or languages which have none.
continue
for cname in set(cnames):
if cname not in countries:
q = cname if '(' not in cname else cname.split('(')[0].strip()
countries[cname] = Country.get(cname_map.get(q, q), key='name', default=None)
if not countries[cname]:
args.log.warn('unknown country name in countries.tab: %s' % cname)
continue
c = countries[cname]
if c.id not in [_c.id for _c in l.countries]:
l.countries.append(c)
stats.update(['countries'])
def main(args): # pragma: no cover
# we merge information about extinct languages from unesco and Harald.
extinct = dict(list(dsv.reader(args.data_file('extinct.tab'))))
with transaction.manager:
query = language_query().options(
joinedload_all(Language.valuesets, ValueSet.values))
# loop over active, established languages with geo-coords
for l in page_query(query, n=100, verbose=True):
# let's collect the relevant sources in a way that allows computation of med.
# Note: we limit refs to the ones without computerized assignments.
sources = DBSession.query(Ref).join(LanguageSource)\
.filter(LanguageSource.language_pk == l.pk) \
.filter(Ref.ca_doctype_trigger == None)\
.filter(Ref.ca_language_trigger == None)\
.options(joinedload(Ref.doctypes))
sources = sorted(map(Source, sources))
# keep the overall med
# note: this source may not be included in the potential meds computed below,
# e.g. because it may not have a year.
med = sources[0].__json__() if sources else None
# now we have to compute meds respecting a cut-off year.
# to do so, we collect eligible sources per year and then
# take the med of this collection.
potential_meds = []
# we only have to loop over publication years within all sources, because
# only in these years something better might have come along.
for year in set(s.year for s in sources if s.year):
# let's see if something better was published!
eligible = [s for s in sources if s.year and s.year <= year]
if eligible:
potential_meds.append(sorted(eligible)[0])
# we store the precomputed sources information as jsondata:
l.update_jsondata(
endangerment='Extinct' if l.hid in extinct else l.endangerment,
med=med,
sources=[s.__json__() for s in
sorted(set(potential_meds), key=lambda s: -s.year)])
def main(args): # pragma: no cover
# we merge information about extinct languages from unesco and Harald.
extinct = dict(list(dsv.reader(args.data_file('extinct.tab'))))
with transaction.manager:
query = language_query().options(
joinedload_all(Language.valuesets, ValueSet.values))
# loop over active, established languages with geo-coords
for l in page_query(query, n=100, verbose=True):
# let's collect the relevant sources in a way that allows computation of med.
# Note: we limit refs to the ones without computerized assignments.
sources = DBSession.query(Ref).join(LanguageSource)\
.filter(LanguageSource.language_pk == l.pk) \
.filter(Ref.ca_doctype_trigger == None)\
.filter(Ref.ca_language_trigger == None)\
.options(joinedload(Ref.doctypes))
sources = sorted(map(Source, sources))
# keep the overall med
# note: this source may not be included in the potential meds computed below,
# e.g. because it may not have a year.
med = sources[0].__json__() if sources else None
# now we have to compute meds respecting a cut-off year.
# to do so, we collect eligible sources per year and then
# take the med of this collection.
potential_meds = []
# we only have to loop over publication years within all sources, because
# only in these years something better might have come along.
for year in set(s.year for s in sources if s.year):
# let's see if something better was published!
eligible = [s for s in sources if s.year and s.year <= year]
if eligible:
potential_meds.append(sorted(eligible)[0])
# we store the precomputed sources information as jsondata:
l.update_jsondata(
endangerment='Extinct' if l.hid in extinct else l.endangerment,
med=med,
sources=[s.__json__() for s in
sorted(set(potential_meds), key=lambda s: -s.year)])
def countries(args, languages):
count = 0
countries = {}
for row in dsv.reader(args.data_file("countries.tab"), encoding="latin1"):
hid, cnames = row[0], row[1:]
if hid not in languages:
languages[hid] = Languoid.get(hid, key="hid", default=None)
if not languages[hid]:
continue
l = languages[hid]
if l.countries:
continue
for cname in set(cnames):
if cname not in countries:
countries[cname] = Country.get(cname, key="name", default=None)
if not countries[cname]:
continue
c = countries[cname]
if c.id not in [_c.id for _c in l.countries]:
l.countries.append(c)
count += 1
print "countries:", count, "relations added"
def macroareas(args, languages):
ma_map = get_map(Macroarea)
# we store references to languages to make computation of cumulated macroareas for
# families easier
lang_map = {}
for hid, macroarea in dsv.reader(args.data_file("macroareas.tab")):
if hid not in languages:
languages[hid] = Languoid.get(hid, key="hid", default=None)
if not languages[hid]:
continue
lang_map[languages[hid].pk] = languages[hid]
update_relationship(languages[hid].macroareas, [ma_map[macroarea]], log=args.log)
for family in (
DBSession.query(Languoid).filter(Languoid.level == LanguoidLevel.family).filter(Language.active == True)
):
mas = []
for lang in DBSession.query(TreeClosureTable.child_pk).filter(TreeClosureTable.parent_pk == family.pk):
if lang[0] in lang_map:
mas.extend(lang_map[lang[0]].macroareas)
update_relationship(family.macroareas, mas, log=args.log)
print "macroareas done"
def main(args):
# determine if we run on a machine where other databases are available for lookup
# locally:
data = Data()
genera = get_genera(data) if astroman else {}
glottocodes, lnames, geocoords = {}, {}, {}
if astroman:
for k, v in glottocodes_by_isocode(
'postgresql://robert@/glottolog3',
cols=['id', 'name', 'latitude', 'longitude']).items():
glottocodes[k] = v[0]
lnames[k] = v[1]
geocoords[k] = (v[2], v[3])
refs = defaultdict(list)
for row in get_rows(args, 'BibtexKey'):
if row[1] == 'NO SOURCE GIVEN':
refs[row[0]] = []
else:
refs[row[0]].append(row[1])
add_sources(args, data)
dataset = data.add(
common.Dataset,
'phoible',
id='phoible',
name='PHOIBLE Online',
description='PHOIBLE Online',
publisher_name="Max Planck Institute for Evolutionary Anthropology",
publisher_place="Leipzig",
publisher_url="http://www.eva.mpg.de",
domain='phoible.org',
license='http://creativecommons.org/licenses/by-sa/3.0/',
contact='*****@*****.**',
jsondata={
'license_icon':
'http://i.creativecommons.org/l/by-sa/3.0/88x31.png',
'license_name':
'Creative Commons Attribution-ShareAlike 3.0 Unported License'
})
for i, spec in enumerate([
('moran', "Steven Moran"),
('mccloy', "Daniel McCloy"),
('wright', "Richard Wright"),
]):
DBSession.add(
common.Editor(dataset=dataset,
ord=i + 1,
contributor=common.Contributor(id=spec[0],
name=spec[1])))
squibs = defaultdict(list)
for row in get_rows(args, 'Squib'):
squibs[row[0]].append(row[1])
source_urls = dict(get_rows(args, 'URL'))
ia_urls = dict(get_rows(args, 'InternetArchive'))
aggregated = list(
reader(args.data_file('phoible-aggregated.tsv'), namedtuples=True))
inventory_names = {}
for key, items in groupby(sorted(aggregated,
key=lambda t: (t.LanguageCode, t.Source)),
key=lambda t: (t.LanguageCode, t.Source)):
items = list(items)
lname = lnames.get(key[0])
if not lname:
lname = items[0].LanguageName
lnames[key[0]] = lname
if len(items) == 1:
inventory_names[items[0].InventoryID] = '%s (%s)' % (lname, key[1])
else:
for i, item in enumerate(items):
inventory_names[item.InventoryID] = '%s %s (%s)' % (lname, i +
1, key[1])
family_map = {
("Arawakan", "arwk"): "Arawakan",
("Trans-New Guinea", "trng"): "Trans-New Guinea",
("Moklen", "anes"): "Austronesian",
("Oko", "ncon"): "Niger-Congo",
("Muniche", "saso"): "Muniche",
("Tinigua", "saso"): "Tinigua",
("Vilela", "luvi"): "Vilela",
("Ofayé", "macg"): "Kamakanan",
("Purian", "macg"): "PurianPrint",
("Mixed language", "saml"): "Mixed language",
("Tupian", "tupi"): "Tupian",
("Yuwana", "saun"): "YuwanaPrint",
}
family_code_map = {k[1]: v for k, v in family_map.items()}
for row in aggregated:
lang = data['Variety'].get(row.LanguageCode)
if not lang:
if row.LanguageFamilyGenus == 'UNCLASSIFIED':
genus = None
else:
genus_id = slug(strip_quotes(row.LanguageFamilyGenus))
genus = genera.get(genus_id)
if not genus:
genus = genera.get(row.LanguageCode)
if not genus:
#print(row.LanguageFamilyGenus, row.LanguageFamilyRoot)
family = family_map.get(
(row.LanguageFamilyGenus, row.LanguageFamilyRoot))
genus = genera[genus_id] = data.add(
models.Genus,
genus_id,
id=genus_id,
name=row.LanguageFamilyGenus,
description=family or row.LanguageFamilyRoot,
active=False,
root=row.LanguageFamilyRoot)
if not genus.root:
genus.root = row.LanguageFamilyRoot
if genus.description in family_code_map:
genus.description = family_code_map[genus.description]
if row.LanguageCode in geocoords:
coords = geocoords[row.LanguageCode]
elif row.Latitude != 'NULL' and row.Longitude != 'NULL':
coords = (float(row.Latitude), float(row.Longitude))
lang = data.add(models.Variety,
row.LanguageCode,
id=row.LanguageCode,
name=lnames[row.LanguageCode],
genus=genus,
country=strip_quotes(row.Country),
area=strip_quotes(row.Area),
latitude=coords[0],
longitude=coords[1],
jsondata=dict(inventory_id=row.InventoryID))
add_language_codes(data,
lang,
row.LanguageCode,
glottocodes=glottocodes)
contributor = data['Contributor'].get(row.Source)
if not contributor:
contributor = data.add(common.Contributor,
row.Source,
id=row.Source,
name=SOURCES[row.Source][0],
description=SOURCES[row.Source][2])
for ref in SOURCES[row.Source][1]:
DBSession.add(
models.ContributorReference(source=data['Source'][ref],
contributor=contributor))
contrib = data.add(models.Inventory,
row.InventoryID,
id=row.InventoryID,
language=lang,
source=row.Source,
source_url=source_urls.get(row.InventoryID),
internetarchive_url=ia_urls.get(row.InventoryID),
name=inventory_names[row.InventoryID],
description=row.LanguageName)
DBSession.add(
common.ContributionContributor(contribution=contrib,
contributor=contributor))
for j, squib in enumerate(squibs.get(row.InventoryID, [])):
f = common.Contribution_files(object=contrib,
id='squib-%s-%s.pdf' %
(contrib.id, j + 1),
name='Phonological squib',
description=squib,
mime_type='application/pdf')
assert f
# f.create(files_dir, file(args.data_file('phonological_squibs', src)).read())
DBSession.flush()
unknown_refs = {}
for row in reader(args.data_file('phoible-phonemes.tsv'),
namedtuples=True):
inventory = data['Inventory'][row.InventoryID]
segment = data['Segment'].get(row.Phoneme)
if not segment:
unicode_desc = [(c, unicodedata.name(c)) for c in row.Phoneme]
description = ' - '.join([t[1] for t in unicode_desc])
segment = data.add(
models.Segment,
row.Phoneme,
id=b16encode(md5(description).digest()),
name=row.Phoneme,
description=description,
equivalence_class=''.join([
t[0] for t in unicode_desc
if t[1].split()[0] not in ['COMBINING', 'MODIFIER']
]),
segment_class=row.Class,
combined_class=row.CombinedClass)
DBSession.flush()
vs = common.ValueSet(id=row.PhonemeID,
contribution=inventory,
language=inventory.language,
parameter=segment)
for ref in refs.get(row.InventoryID, []):
if ref not in data['Source']:
if ref not in unknown_refs:
print('-------', ref)
unknown_refs[ref] = 1
continue
DBSession.add(
common.ValueSetReference(source=data['Source'][ref],
valueset=vs))
DBSession.add(
common.Value(
id=row.PhonemeID,
name='%s %s' %
(row.Phoneme, data['Inventory'][row.InventoryID].name),
valueset=vs))
DBSession.flush()
for inventory_id in refs:
for ref in refs[inventory_id]:
if ref not in data['Source']:
continue
data.add(common.ContributionReference,
'%s-%s' % (inventory_id, ref),
source=data['Source'][ref],
contribution=data['Inventory'][inventory_id])
for i, row in enumerate(
reader(args.data_file('phoible-segments-features.tsv'))):
if i == 0:
features = list(map(feature_name, row))
continue
if row[0] not in data['Segment']:
# print('skipping feature vector:', row)
continue
for j, value in enumerate(row):
if j and value != '0':
DBSession.add(
common.Parameter_data(
key=features[j],
value=value,
ord=j,
object_pk=data['Segment'][row[0]].pk))
DBSession.flush()
def import_dataset(path, data, icons):
# look for metadata
# look for sources
# then loop over values
dirpath, fname = os.path.split(path)
basename, ext = os.path.splitext(fname)
glottolog = Glottolog()
contrib = Contribution(id=basename, name=basename)
md = {}
mdpath = path + '-metadata.json'
if os.path.exists(mdpath):
md = jsonload(mdpath)
contributor_name = HumanName(md.get('contributed_datapoint', 'Team NTS'))
contributor_id = slug(contributor_name.last + contributor_name.first)
contributor = data['Contributor'].get(contributor_id)
if not contributor:
contributor = data.add(
Contributor,
contributor_id,
id=contributor_id,
name='%s' % contributor_name)
DBSession.add(ContributionContributor(contribution=contrib, contributor=contributor))
bibpath = os.path.join(dirpath, basename + '.bib')
if os.path.exists(bibpath):
for rec in Database.from_file(bibpath):
if rec['key'] not in data['Source']:
data.add(Source, rec['key'], _obj=bibtex2source(rec))
languages = {f['properties']['glottocode']: f for f in md.get('features', [])}
for i, row in enumerate(reader(path, dicts=True, quoting=csv.QUOTE_NONE, delimiter=',' if 'c' in ext else '\t')):
if not row['Value'] or not row['Feature_ID']:
continue
vsid = '%s-%s-%s' % (basename, row['Language_ID'], row['Feature_ID'])
vid = row.get('ID', '%s-%s' % (basename, i + 1))
parameter = data['Feature'].get(row['Feature_ID'])
if parameter is None:
print('skip value for invalid feature %s' % row['Feature_ID'])
continue
#parameter = data.add(
# Feature, row['Feature_ID'], id=row['Feature_ID'], name=row.get('Feature', row['Feature_ID']))
language = data['GrambankLanguage'].get(row['Language_ID'])
if language is None:
# query glottolog!
languoid = glottolog.languoid(row['Language_ID'])
gl_md = {
'name': languoid.name,
'longitude': languoid.longitude,
'latitude': languoid.latitude}
lmd = languages.get(row['Language_ID'])
if lmd:
if lmd.get('properties', {}).get('name'):
gl_md['name'] = lmd['properties']['name']
if lmd.get('geometry', {}).get('coordinates'):
gl_md['longitude'], gl_md['latitude'] = lmd['geometry']['coordinates']
language = data.add(
GrambankLanguage, row['Language_ID'],
id=row['Language_ID'],
name=gl_md['name'],
latitude=gl_md.get('latitude'),
longitude=gl_md.get('longitude'))
vs = data['ValueSet'].get(vsid)
if vs is None:
vs = data.add(
ValueSet, vsid,
id=vsid,
parameter=parameter,
language=language,
contribution=contrib,
source=row['Source'])
domain = {de.abbr: de for de in parameter.domain}
name = row['Value']
if name in domain:
name = domain[name].name
Value(
id=vid,
valueset=vs,
name=name,
description=row['Comment'],
domainelement=domain.get(row['Value']))
for key, src in data['Source'].items():
if key in vs.source:
ValueSetReference(valueset=vs, source=src, key=key)
def main(args):
data = Data()
editors = OrderedDict()
editors['Susanne Maria Michaelis'] = None
editors['Philippe Maurer'] = None
editors['Martin Haspelmath'] = None
editors['Magnus Huber'] = None
for row in read(args, 'People'):
name = row['First name'] + ' ' if row['First name'] else ''
name += row['Last name']
kw = dict(
name=name,
id=slug('%(Last name)s%(First name)s' % row),
url=row['Contact Website'].split()[0]
if row['Contact Website'] else None,
address=row['Comments on database'],
)
contrib = data.add(common.Contributor, row['Author ID'], **kw)
if kw['name'] in editors:
editors[kw['name']] = contrib
DBSession.flush()
dataset = common.Dataset(
id='apics',
name='APiCS Online',
description='Atlas of Pidgin and Creole Language Structures Online',
domain='apics-online.info',
published=date(2013, 11, 4),
license='http://creativecommons.org/licenses/by/3.0/',
contact='*****@*****.**',
jsondata={
'license_icon': 'cc-by.png',
'license_name': 'Creative Commons Attribution 3.0 Unported License'
})
DBSession.add(dataset)
for i, editor in enumerate(editors.values()):
common.Editor(dataset=dataset, contributor=editor, ord=i + 1)
colors = dict(
(row['ID'], row['RGB_code']) for row in read(args, 'Colours'))
abbrs = {}
for id_, name in LGR_ABBRS.items():
DBSession.add(common.GlossAbbreviation(id=id_, name=name))
abbrs[id_] = 1
for id_, name in {
'C**T': 'clitic',
'IMPF': 'imperfect',
'INTERM': 'intermediate',
'NCOMPL': 'noncompletive',
'NONFUT': 'nonfuture',
'NPROX': 'nonproximal',
'NSG': 'nonsingular',
'PP': 'past participle',
'PROP': 'proprietive',
'TMA': 'tense-mood-aspect',
}.items():
DBSession.add(common.GlossAbbreviation(id=id_, name=name))
abbrs[id_] = 1
for row in reader(args.data_file('non-lgr-gloss-abbrs.csv'),
delimiter=',',
namedtuples=True):
for match in GLOSS_ABBR_PATTERN.finditer(row.standard):
if match.group('abbr') not in abbrs:
abbrs[match.group('abbr')] = 1
DBSession.add(
common.GlossAbbreviation(id=match.group('abbr'),
name=row.meaning))
non_bibs = {}
for row in read(args, 'References', 'Reference_ID'):
if row['Reference_type'] == 'Non-bib':
non_bibs[row['Reference_ID']] = row['Reference_name']
continue
if isinstance(row['Year'], int):
year_int = row['Year']
year = str(row['Year'])
elif row['Year']:
year_int = None
for m in re.finditer('(?P<year>(1|2)[0-9]{3})', row['Year']):
year_int = int(m.group('year'))
break
year = row['Year']
else:
year, year_int = None, None
title = row['Article_title'] or row['Book_title']
attrs = {}
jsondata = {}
for attr, field in {
'Additional_information': 'note',
'Article_title': 'title',
'Book_title': 'booktitle',
'City': 'address',
'Editors': 'editor',
'Full_reference': None,
'Issue': None,
'Journal': 'journal',
'Language_codes': None,
'LaTeX_cite_key': None,
'Pages': 'pages',
'Publisher': 'publisher',
'Reference_type': 'type',
'School': 'school',
'Series_title': 'series',
'URL': 'url',
'Volume': 'volume',
}.items():
value = row.get(attr)
if not isinstance(value, int):
value = (value or '').strip()
if attr == 'Issue' and value:
try:
value = str(int(value))
except ValueError:
pass
if value:
if field:
attrs[field] = value
else:
jsondata[attr] = value
p = data.add(common.Source,
row['Reference_ID'],
id=str(row['Reference_ID']),
name=row['Reference_name'],
description=title,
author=row['Authors'],
year=year,
year_int=year_int,
bibtex_type=getattr(EntryType, row['BibTeX_type']
or 'misc'),
jsondata=jsondata,
**attrs)
if p.bibtex_type.value == 'misc' and not p.description:
p.description = p.note
DBSession.flush()
DBSession.flush()
infobox = jsonload(args.data_file('infobox.json'))
glottocodes = jsonload(args.data_file('glottocodes.json'))
for row in read(args, 'Languages', 'Order_number'):
lon, lat = [
float(c.strip()) for c in row['map_coordinates'].split(',')
]
kw = dict(
name=row['Language_name'],
id=str(row['Order_number']),
latitude=lat,
longitude=lon,
region=row['Category_region'],
)
lect = data.add(models.Lect, row['Language_ID'], **kw)
DBSession.flush()
for i, item in enumerate(infobox[lect.id]):
DBSession.add(
common.Language_data(object_pk=lect.pk,
ord=i,
key=item[0],
value=item[1]))
if row["Languages_contribution_documentation::Lect_description_checked_status"] \
!= "Checked":
print 'unchecked! ---', row['Language_name']
desc = row.get(
'Languages_contribution_documentation::Lect description', '')
markup_desc = normalize_markup(row[
'Languages_contribution_documentation::z_calc_GetAsCSS_Lect_description']
)
c = data.add(
models.ApicsContribution,
row['Language_ID'],
id=str(row['Order_number']),
name=row['Language_name'],
description=desc,
markup_description=markup_desc,
survey_reference=data['Source'][row['Survey_reference_ID']],
language=lect)
for ext, label, mtype in [
('pdf', 'Glossed text', 'application/pdf'),
('mp3', 'Glossed text audio', 'audio/mpeg'),
]:
fid = '%s-gt.%s' % (c.id, ext)
if args.data_file('files', 'contribution', c.id, fid).exists():
common.Contribution_files(object=c,
id=fid,
name=label,
mime_type=mtype)
else:
print label, 'missing for:', row['Language_name']
#
# TODO: for michif, 75, add link http://www.youtube.com/watch?v=f0C4cODsSyE
#
iso = None
if row['ISO_code'] and len(row['ISO_code']) == 3:
iso = row['ISO_code'].lower()
if 'iso:%s' % row['ISO_code'] not in data['Identifier']:
data.add(common.Identifier,
'iso:%s' % row['ISO_code'],
id=row['ISO_code'].lower(),
name=row['ISO_code'].lower(),
type=common.IdentifierType.iso.value)
DBSession.add(
common.LanguageIdentifier(
language=data['Lect'][row['Language_ID']],
identifier=data['Identifier']['iso:%s' % row['ISO_code']]))
if lect.id in glottocodes:
identifier = data.add(common.Identifier,
'gc:%s' % glottocodes[lect.id],
id=glottocodes[lect.id],
name=glottocodes[lect.id],
type=common.IdentifierType.glottolog.value)
DBSession.add(
common.LanguageIdentifier(
language=data['Lect'][row['Language_ID']],
identifier=identifier))
if row['Language_name_ethnologue']:
if row['Language_name_ethnologue'] not in data['Identifier']:
data.add(common.Identifier,
row['Language_name_ethnologue'],
id=iso
or 'ethnologue:%s' % row['Language_name_ethnologue'],
name=row['Language_name_ethnologue'],
type='ethnologue')
DBSession.add(
common.LanguageIdentifier(
language=data['Lect'][row['Language_ID']],
identifier=data['Identifier'][
row['Language_name_ethnologue']]))
example_count = {}
for row in read(args, 'Examples', 'Order_number'):
assert row['Language_ID']
lang = data['Lect'][row['Language_ID']]
id_ = '%(Language_ID)s-%(Example_number)s' % row
atext, gloss = igt(row)
example_count[row['Language_ID']] = max(
[example_count.get(row['Language_ID'], 1), row['Example_number']])
p = add_sentence(
args,
data,
id_,
id='%s-%s' % (lang.id, row['Example_number']),
name=row['Text'] or row['Analyzed_text'],
description=row['Translation'],
type=row['Type'].strip().lower() if row['Type'] else None,
comment=row['Comments'],
gloss=gloss,
analyzed=atext,
markup_text=normalize_markup(row['z_calc_Text_CSS']),
markup_gloss=normalize_markup(row['z_calc_Gloss_CSS']),
markup_comment=normalize_markup(row['z_calc_Comments_CSS']),
markup_analyzed=normalize_markup(row['z_calc_Analyzed_text_CSS']),
original_script=row['Original_script'],
jsondata={
'sort': row['Order_number'],
'alt_translation': (row['Translation_other'] or '').strip()
or None
},
language=lang)
if row['Reference_ID']:
if row['Reference_ID'] in data['Source']:
source = data['Source'][row['Reference_ID']]
DBSession.add(
common.SentenceReference(
sentence=p,
source=source,
key=source.id,
description=row['Reference_pages']))
else:
p.source = non_bibs[row['Reference_ID']]
DBSession.flush()
for row in read(args, 'Language_references'):
if row['Reference_ID'] not in data['Source']:
assert row['Reference_ID'] in non_bibs
continue
assert row['Language_ID'] in data['ApicsContribution']
source = data['Source'][row['Reference_ID']]
DBSession.add(
common.ContributionReference(
contribution=data['ApicsContribution'][row['Language_ID']],
source=source,
description=row['Pages'],
key=source.id))
#
# global counter for features - across feature types
#
feature_count = 0
for row in read(args, 'Features', 'Feature_number'):
id_ = str(row['Feature_number'])
if int(id_) > feature_count:
feature_count = int(id_)
wals_id = None
desc = row['Feature_annotation_publication']
if row['WALS_match'] == 'Total':
if isinstance(row['WALS_No.'], int):
wals_id = row['WALS_No.']
else:
wals_id = int(row['WALS_No.'].split('.')[0].strip())
p = data.add(models.Feature,
row['Feature_code'],
name=row['Feature_name'],
id=id_,
description=desc,
markup_description=normalize_markup(
row['z_calc_Feature_annotation_publication_CSS']),
feature_type='primary',
multivalued=row['Value_relation_type'] != 'Single',
area=row['Feature_area'],
wals_id=wals_id)
names = {}
for i in range(1, 10):
if not row['Value%s_publication' % i] \
or not row['Value%s_publication' % i].strip():
continue
name = row['Value%s_publication' % i].strip()
if name in names:
name += ' (%s)' % i
names[name] = 1
de = data.add(
common.DomainElement,
'%s-%s' % (row['Feature_code'], i),
id='%s-%s' % (id_, i),
name=name,
parameter=p,
abbr=row['Value%s_for_book_maps' % i] if p.id != '0' else name,
number=int(row['Value%s_value_number_for_publication' % i]),
jsondata={'color': colors[row['Value_%s_colour_ID' % i]]},
)
assert de
if row['Authors_FeatureArticles']:
authors, _ = row['Authors_FeatureArticles'].split('and the APiCS')
authors = authors.strip()
if authors.endswith(','):
authors = authors[:-1].strip()
for i, name in enumerate(authors.split(',')):
assert name.strip() in editors
p._authors.append(
models.FeatureAuthor(ord=i + 1,
contributor=editors[name.strip()]))
DBSession.flush()
primary_to_segment = {123: 63, 126: 35, 128: 45, 130: 41}
segment_to_primary = dict(
zip(primary_to_segment.values(), primary_to_segment.keys()))
number_map = {}
names = {}
for row in read(args, 'Segment_features', 'Order_number'):
symbol = row['Segment_symbol']
if row['Segment_name'] == 'voiceless dental/alveolar sibilant affricate':
symbol = 't\u0361s'
truth = lambda s: s and s.strip().lower() == 'yes'
name = '%s - %s' % (symbol, row['Segment_name'])
if name in names:
number_map[row['Segment_feature_number']] = names[name]
continue
number_map[
row['Segment_feature_number']] = row['Segment_feature_number']
names[name] = row['Segment_feature_number']
feature_count += 1
if row['Segment_feature_number'] in segment_to_primary:
primary_to_segment[segment_to_primary[row['Segment_feature_number']]]\
= str(feature_count)
p = data.add(models.Feature,
row['Segment_feature_number'],
name=name,
id=str(feature_count),
feature_type='segment',
area='Vowels' if truth(row['Vowel']) else
('Obstruent consonants'
if truth(row['Obstruent']) else 'Sonorant consonants'),
jsondata=dict(
number=int(row['Segment_feature_number']),
vowel=truth(row['Vowel']),
consonant=truth(row['Consonant']),
obstruent=truth(row['Obstruent']),
core_list=truth(row['Core_list_segment']),
symbol=symbol,
))
for i, spec in SEGMENT_VALUES.items():
data.add(common.DomainElement,
'%s-%s' % (row['Segment_feature_number'], spec[0]),
id='%s-%s' % (p.id, i),
name=spec[0],
parameter=p,
jsondata={'color': spec[1]},
number=i)
print '--> remapped:', primary_to_segment
DBSession.flush()
for row in read(args, 'Sociolinguistic_features',
'Sociolinguistic_feature_number'):
feature_count += 1
p = data.add(models.Feature,
row['Sociolinguistic_feature_code'],
name=row['Sociolinguistic_feature_name'],
id='%s' % feature_count,
description=row['Sociolinguistic_feature_annotation'],
area='Sociolinguistic',
feature_type='sociolinguistic')
names = {}
for i in range(1, 10):
id_ = '%s-%s' % (row['Sociolinguistic_feature_code'], i)
if row.get('Value%s' % i) and row['Value%s' % i].strip():
name = row['Value%s' % i].strip()
if name in names:
name += ' (%s)' % i
names[name] = 1
else:
continue
kw = dict(id='%s-%s' % (p.id, i), name=name, parameter=p, number=i)
data.add(common.DomainElement,
id_,
id='%s-%s' % (p.id, i),
name=name,
parameter=p,
number=i,
jsondata={
'color':
colors.get(row['Value%s_colour_ID' % i],
colors.values()[i])
})
sd = {}
for row in read(args, 'Segment_data'):
if row['Segment_feature_number'] not in number_map:
continue
number = number_map[row['Segment_feature_number']]
if not row['Presence_in_the_language']:
continue
lang = data['Lect'][row['Language_ID']]
param = data['Feature'][number]
id_ = '%s-%s' % (lang.id, param.id)
if id_ in sd:
assert row['c_Record_is_a_duplicate'] == 'Yes'
continue
sd[id_] = 1
valueset = data.add(
common.ValueSet,
id_,
id=id_,
parameter=param,
language=lang,
contribution=data['ApicsContribution'][row['Language_ID']],
description=row['Comments'],
markup_description=normalize_markup(row['z_calc_Comments_CSS']),
)
v = data.add(
common.Value,
id_,
id=id_,
frequency=float(100),
valueset=valueset,
domainelement=data['DomainElement'][
'%s-%s' % (number, row['Presence_in_the_language'])],
)
if row['Example_word'] and row['Example_word_gloss']:
example_count[row['Language_ID']] += 1
p = add_sentence(args,
data,
'%s-p%s' % (lang.id, data['Feature'][number].id),
id='%s-%s' %
(lang.id, example_count[row['Language_ID']]),
name=row['Example_word'],
description=row['Example_word_gloss'],
language=lang)
DBSession.add(common.ValueSentence(value=v, sentence=p))
source = data['Source'].get(row['Refers_to_references_Reference_ID'])
if source:
DBSession.add(
common.ValueSetReference(valueset=valueset,
source=source,
key=source.id))
elif row['Refers_to_references_Reference_ID'] in non_bibs:
valueset.source = non_bibs[
row['Refers_to_references_Reference_ID']]
lects = defaultdict(lambda: 1)
lect_map = {}
records = {}
false_values = {}
no_values = {}
wals_value_number = {}
for row in read(args, 'wals'):
if row['z_calc_WALS_value_number']:
wals_value_number[
row['Data_record_id']] = row['z_calc_WALS_value_number']
def prefix(attr, _prefix):
if _prefix:
return '%s_%s' % (_prefix, attr)
return attr.capitalize()
for _prefix, abbr in [('', ''), ('Sociolinguistic', 'sl')]:
num_values = 10
for row in read(args, prefix('data', _prefix)):
if not row[prefix('feature_code', _prefix)]:
print('no associated feature for', prefix('data', _prefix),
row[prefix('data_record_id', _prefix)])
continue
lid = row['Language_ID']
lect_attr = row.get('Lect_attribute', 'my default lect').lower()
if lect_attr != 'my default lect':
if (row['Language_ID'], row['Lect_attribute']) in lect_map:
lid = lect_map[(row['Language_ID'], row['Lect_attribute'])]
else:
lang = data['Lect'][row['Language_ID']]
c = lects[row['Language_ID']]
lid = '%s-%s' % (row['Language_ID'], c)
kw = dict(
name='%s (%s)' % (lang.name, row['Lect_attribute']),
id='%s' % (1000 + 10 * int(lang.id) + c),
latitude=lang.latitude,
longitude=lang.longitude,
description=row['Lect_attribute'],
language=lang,
)
data.add(models.Lect, lid, **kw)
lects[row['Language_ID']] += 1
lect_map[(row['Language_ID'], row['Lect_attribute'])] = lid
id_ = abbr + str(row[prefix('data_record_id', _prefix)])
assert id_ not in records
records[id_] = 1
assert row[prefix('feature_code', _prefix)] in data['Feature']
language = data['Lect'][lid]
parameter = data['Feature'][row[prefix('feature_code', _prefix)]]
valueset = common.ValueSet(
id='%s-%s' % (language.id, parameter.id),
description=row['Comments_on_value_assignment'],
markup_description=normalize_markup(
row.get('z_calc_Comments_on_value_assignment_CSS')),
)
values_found = {}
for i in range(1, num_values):
if not row['Value%s_true_false' % i]:
continue
if row['Value%s_true_false' % i].strip().lower() != 'true':
assert row['Value%s_true_false' %
i].strip().lower() == 'false'
false_values[row[prefix('data_record_id', _prefix)]] = 1
continue
iid = '%s-%s' % (row[prefix('feature_code', _prefix)], i)
if iid not in data['DomainElement']:
print(iid, row[prefix('data_record_id',
_prefix)], '--> no domainelement!')
continue
values_found['%s-%s' % (id_, i)] = dict(
id='%s-%s' % (valueset.id, i),
domainelement=data['DomainElement']['%s-%s' % (row[prefix(
'feature_code', _prefix)], i)],
confidence=row['Value%s_confidence' % i],
frequency=float(row['c_V%s_frequency_normalised' %
i]) if _prefix == '' else 100)
if values_found:
if row[prefix('data_record_id', _prefix)] in wals_value_number:
valueset.jsondata = {
'wals_value_number':
wals_value_number.pop(row[prefix(
'data_record_id', _prefix)])
}
valueset.parameter = parameter
valueset.language = language
valueset.contribution = data['ApicsContribution'][
row['Language_ID']]
valueset = data.add(common.ValueSet, id_, _obj=valueset)
for i, item in enumerate(values_found.items()):
if i > 0 and not parameter.multivalued:
print 'multiple values for single-valued parameter: %s' % id_
break
id_, kw = item
kw['valueset'] = valueset
value = data.add(common.Value, id_, **kw)
#
# store references to additional data for segments which should be reused
# for corresponding primary features!
#
if int(parameter.id) in primary_to_segment:
assert len(values_found) == 1
seg_id = '%s-%s' % (language.id, primary_to_segment[int(
parameter.id)])
seg_valueset = data['ValueSet'][seg_id]
seg_value = data['Value'][seg_id]
if not valueset.description and seg_valueset.description:
valueset.description = seg_valueset.description
for s in seg_value.sentence_assocs:
DBSession.add(
common.ValueSentence(value=value,
sentence=s.sentence))
for r in seg_valueset.references:
DBSession.add(
common.ValueSetReference(valueset=valueset,
source=r.source,
key=r.key))
if not valueset.source and seg_valueset.source:
valueset.source = seg_valueset.source
DBSession.flush()
else:
no_values[id_] = 1
DBSession.flush()
for prefix, abbr, num_values in [
('D', '', 10),
('Sociolinguistic_d', 'sl', 7),
]:
for row in read(args, prefix + 'ata_references'):
assert row['Reference_ID'] in data['Source'] \
or row['Reference_ID'] in non_bibs
try:
vs = data['ValueSet'][abbr +
str(row[prefix + 'ata_record_id'])]
if row['Reference_ID'] in data['Source']:
source = data['Source'][row['Reference_ID']]
DBSession.add(
common.ValueSetReference(
valueset=vs,
source=source,
key=source.id,
description=row['Pages'],
))
else:
if vs.source:
vs.source += '; ' + non_bibs[row['Reference_ID']]
else:
vs.source = non_bibs[row['Reference_ID']]
except KeyError:
continue
DBSession.flush()
missing = 0
for row in read(args, 'Value_examples'):
try:
DBSession.add(
common.ValueSentence(
value=data['Value']['%(Data_record_id)s-%(Value_number)s' %
row],
sentence=data['Sentence'][
'%(Language_ID)s-%(Example_number)s' % row],
description=row['Notes'],
))
except KeyError:
missing += 1
print('%s Value_examples are missing data' % missing)
print('%s data sets with false values' % len(false_values))
print('%s data sets without values' % len(no_values))
for k, v in wals_value_number.items():
print 'unclaimed wals value number:', k, v
for i, row in enumerate(read(args, 'Contributors')):
kw = dict(contribution=data['ApicsContribution'][row['Language ID']],
contributor=data['Contributor'][row['Author ID']])
if row['Order_of_appearance']:
kw['ord'] = int(float(row['Order_of_appearance']))
data.add(common.ContributionContributor, i, **kw)
DBSession.flush()
def get_rows(args, name):
for i, row in enumerate(reader(args.data_file('InventoryID-%s.csv' %
name))):
if i and row[1] != 'NA':
yield row
def justifications(args, languages):
"""
- text goes into ValueSet.description
- refs go into ValueSetReference objects
"""
def normalized_pages(s):
if PAGES_PATTERN.match(s or ""):
return s or ""
#
# create mappings to look up glottolog languoids matching names in justification files
#
langs_by_hid = languages
langs_by_hname = {}
langs_by_name = {}
for l in DBSession.query(Languoid).filter(Languoid.active == False):
langs_by_hname[l.jsondatadict.get("hname")] = l
langs_by_hid[l.hid] = l
langs_by_name[l.name] = l
for l in DBSession.query(Languoid).filter(Languoid.active == True):
langs_by_hname[l.jsondatadict.get("hname")] = l
langs_by_hid[l.hid] = l
langs_by_name[l.name] = l
for id_, type_ in [("fc", "family"), ("sc", "subclassification")]:
for i, row in enumerate(dsv.reader(args.data_file("%s_justifications.tab" % type_))):
name = row[0]
name = name.replace("_", " ") if not name.startswith("NOCODE") else name
l = langs_by_hname.get(name, langs_by_hid.get(name, langs_by_name.get(name)))
if not l:
args.log.warn("ignoring %s" % name)
continue
_r = 3 if type_ == "family" else 2
comment = (row[_r].strip() or None) if len(row) > _r else None
if comment and not WORD_PATTERN.search(comment):
comment = None
#
# TODO: look for [NOCODE_ppp] patterns as well!?
#
refs = [(int(m.group("id")), normalized_pages(m.group("comment"))) for m in REF_PATTERN.finditer(row[2])]
vs = None
for _vs in l.valuesets:
if _vs.parameter.id == id_:
vs = _vs
break
if not vs:
args.log.info("%s %s ++" % (l.id, type_))
vs = ValueSet(
id="%s%s" % (type_, l.id),
description=comment,
language=l,
parameter=Parameter.get(id_),
contribution=Contribution.first(),
)
DBSession.add(Value(id="%s%s" % (type_, l.id), name="%s - %s" % (l.level, l.status), valueset=vs))
DBSession.flush()
else:
if vs.description != comment:
args.log.info("%s %s ~~ description" % (l.id, type_))
vs.description = comment
for r in vs.references:
DBSession.delete(r)
for r, pages in refs:
vs.references.append(ValueSetReference(source=Source.get(str(r)), description=pages))
args.log.info("%s %s" % (i, type_))
def get_vs2008(args): # pragma: no cover
vs2008 = {}
for row in reader(args.data_file('datapoints_2008.csv'), delimiter=','):
vs2008[(row[0], '%sA' % row[1])] = int(row[2])
return vs2008
def prime_cache(args):
"""
we use a versioned session to insert the changes in value assignment
"""
#
# compute the changes from 2008 to 2011:
#
vs2008 = get_vs2008(args)
for row in DB.execute("select * from datapoint"):
key = (row['language_id'], row['feature_id'])
old_value = vs2008.get(key)
new_value = row['value_numeric']
if old_value and old_value != new_value:
valueset = VersionedDBSession.query(common.ValueSet)\
.join(common.Language)\
.join(common.Parameter)\
.filter(common.Parameter.id == row['feature_id'])\
.filter(common.Language.id == row['language_id'])\
.one()
value = valueset.values[0]
assert value.domainelement.number == old_value
for de in valueset.parameter.domain:
if de.number == new_value:
value.domainelement = de
break
assert value.domainelement.number == new_value
valueset.updated = E2011
value.updated = E2011
VersionedDBSession.flush()
for row in reader(args.data_file('corrections_2013.tab'), namedtuples=True, newline='\r'):
valueset = VersionedDBSession.query(common.ValueSet)\
.join(common.Language)\
.join(common.Parameter)\
.filter(common.Parameter.id == row.feature)\
.filter(common.Language.id == row.wals_code)\
.one()
value = valueset.values[0]
if value.domainelement.number == int(row.new):
print '**** old news', valueset.language.id, valueset.parameter.id
continue
if value.domainelement.number != int(row.old):
print '--->', valueset.language.id, valueset.parameter.id, value.domainelement.number
for de in valueset.parameter.domain:
if de.number == int(row.new):
value.domainelement = de
break
assert value.domainelement.number == int(row.new)
valueset.updated = E2013
value.updated = E2013
VersionedDBSession.flush()
print 'corrections 2013 done'
for issue in ['0', '9', '10', '11', '13', '14', '15', '16', '17', '19', '20', '24', '26', '27', '28']:
issue = getattr(issues, 'issue' + issue)
issue(VersionedDBSession, E2013)
VersionedDBSession.flush()
transaction.commit()
transaction.begin()
#
# TODO: these must be recomputed as well, after migrations!
#
# cache number of languages for a parameter:
for parameter, valuesets in groupby(
DBSession.query(common.ValueSet).order_by(common.ValueSet.parameter_pk),
lambda vs: vs.parameter):
parameter.representation = str(len(set(v.language_pk for v in valuesets)))
print 'recomputation of representation done'
transaction.commit()
transaction.begin()
# cache iso codes for languages:
for language in DBSession.query(common.Language).options(joinedload_all(
common.Language.languageidentifier, common.LanguageIdentifier.identifier
)):
iso_codes = []
for identifier in language.identifiers:
if identifier.type == common.IdentifierType.iso.value:
iso_codes.append(identifier.name)
language.iso_codes = ', '.join(sorted(set(iso_codes)))
print 'recomputation of iso codes done'
transaction.commit()
transaction.begin()
compute_language_sources()
transaction.commit()
transaction.begin()
gbs_func('update', args)
def get_vs2008(args):
vs2008 = {}
for row in reader(args.data_file('datapoints_2008.csv'), delimiter=','):
vs2008[(row[0], '%sA' % row[1])] = int(row[2])
return vs2008
def main(args):
# determine if we run on a machine where other databases are available for lookup
# locally:
data = Data()
genera = get_genera(data) if astroman else {}
glottocodes, lnames, geocoords = {}, {}, {}
if astroman:
for k, v in glottocodes_by_isocode(
'postgresql://robert@/glottolog3',
cols=['id', 'name', 'latitude', 'longitude']).items():
glottocodes[k] = v[0]
lnames[k] = v[1]
geocoords[k] = (v[2], v[3])
refs = defaultdict(list)
for row in get_rows(args, 'BibtexKey'):
if row[1] == 'NO SOURCE GIVEN':
refs[row[0]] = []
else:
refs[row[0]].append(row[1])
add_sources(args, data)
dataset = data.add(
common.Dataset, 'phoible',
id='phoible',
name='PHOIBLE Online',
description='PHOIBLE Online',
publisher_name="Max Planck Institute for Evolutionary Anthropology",
publisher_place="Leipzig",
publisher_url="http://www.eva.mpg.de",
domain='phoible.org',
license='http://creativecommons.org/licenses/by-sa/3.0/',
contact='*****@*****.**',
jsondata={
'license_icon': 'http://i.creativecommons.org/l/by-sa/3.0/88x31.png',
'license_name':
'Creative Commons Attribution-ShareAlike 3.0 Unported License'})
for i, spec in enumerate([
('moran', "Steven Moran"),
('mccloy', "Daniel McCloy"),
('wright', "Richard Wright"),
]):
DBSession.add(common.Editor(
dataset=dataset,
ord=i + 1,
contributor=common.Contributor(id=spec[0], name=spec[1])))
squibs = defaultdict(list)
for row in get_rows(args, 'Squib'):
squibs[row[0]].append(row[1])
source_urls = dict(get_rows(args, 'URL'))
ia_urls = dict(get_rows(args, 'InternetArchive'))
aggregated = list(reader(args.data_file('phoible-aggregated.tsv'), namedtuples=True))
inventory_names = {}
for key, items in groupby(
sorted(aggregated, key=lambda t: (t.LanguageCode, t.Source)),
key=lambda t: (t.LanguageCode, t.Source)):
items = list(items)
lname = lnames.get(key[0])
if not lname:
lname = items[0].LanguageName
lnames[key[0]] = lname
if len(items) == 1:
inventory_names[items[0].InventoryID] = '%s (%s)' % (lname, key[1])
else:
for i, item in enumerate(items):
inventory_names[item.InventoryID] = '%s %s (%s)' % (lname, i + 1, key[1])
family_map = {
("Arawakan", "arwk"): "Arawakan",
("Trans-New Guinea", "trng"): "Trans-New Guinea",
("Moklen", "anes"): "Austronesian",
("Oko", "ncon"): "Niger-Congo",
("Muniche", "saso"): "Muniche",
("Tinigua", "saso"): "Tinigua",
("Vilela", "luvi"): "Vilela",
("Ofayé", "macg"): "Kamakanan",
("Purian", "macg"): "PurianPrint",
("Mixed language", "saml"): "Mixed language",
("Tupian", "tupi"): "Tupian",
("Yuwana", "saun"): "YuwanaPrint",
}
family_code_map = {k[1]: v for k, v in family_map.items()}
for row in aggregated:
lang = data['Variety'].get(row.LanguageCode)
if not lang:
if row.LanguageFamilyGenus == 'UNCLASSIFIED':
genus = None
else:
genus_id = slug(strip_quotes(row.LanguageFamilyGenus))
genus = genera.get(genus_id)
if not genus:
genus = genera.get(row.LanguageCode)
if not genus:
#print(row.LanguageFamilyGenus, row.LanguageFamilyRoot)
family = family_map.get(
(row.LanguageFamilyGenus, row.LanguageFamilyRoot))
genus = genera[genus_id] = data.add(
models.Genus, genus_id,
id=genus_id,
name=row.LanguageFamilyGenus,
description=family or row.LanguageFamilyRoot,
active=False,
root=row.LanguageFamilyRoot)
if not genus.root:
genus.root = row.LanguageFamilyRoot
if genus.description in family_code_map:
genus.description = family_code_map[genus.description]
if row.LanguageCode in geocoords:
coords = geocoords[row.LanguageCode]
elif row.Latitude != 'NULL' and row.Longitude != 'NULL':
coords = (float(row.Latitude), float(row.Longitude))
lang = data.add(
models.Variety, row.LanguageCode,
id=row.LanguageCode,
name=lnames[row.LanguageCode],
genus=genus,
country=strip_quotes(row.Country),
area=strip_quotes(row.Area),
latitude=coords[0],
longitude=coords[1],
jsondata=dict(inventory_id=row.InventoryID))
add_language_codes(data, lang, row.LanguageCode, glottocodes=glottocodes)
contributor = data['Contributor'].get(row.Source)
if not contributor:
contributor = data.add(
common.Contributor, row.Source,
id=row.Source,
name=SOURCES[row.Source][0],
description=SOURCES[row.Source][2])
for ref in SOURCES[row.Source][1]:
DBSession.add(models.ContributorReference(
source=data['Source'][ref], contributor=contributor))
contrib = data.add(
models.Inventory, row.InventoryID,
id=row.InventoryID,
language=lang,
source=row.Source,
source_url=source_urls.get(row.InventoryID),
internetarchive_url=ia_urls.get(row.InventoryID),
name=inventory_names[row.InventoryID],
description=row.LanguageName)
DBSession.add(common.ContributionContributor(
contribution=contrib, contributor=contributor))
for j, squib in enumerate(squibs.get(row.InventoryID, [])):
f = common.Contribution_files(
object=contrib,
id='squib-%s-%s.pdf' % (contrib.id, j + 1),
name='Phonological squib',
description=squib,
mime_type='application/pdf')
assert f
# f.create(files_dir, file(args.data_file('phonological_squibs', src)).read())
DBSession.flush()
unknown_refs = {}
for row in reader(args.data_file('phoible-phonemes.tsv'), namedtuples=True):
inventory = data['Inventory'][row.InventoryID]
segment = data['Segment'].get(row.Phoneme)
if not segment:
unicode_desc = [(c, unicodedata.name(c)) for c in row.Phoneme]
description = ' - '.join([t[1] for t in unicode_desc])
segment = data.add(
models.Segment, row.Phoneme,
id=b16encode(md5(description).digest()),
name=row.Phoneme,
description=description,
equivalence_class=''.join(
[t[0] for t in unicode_desc
if t[1].split()[0] not in ['COMBINING', 'MODIFIER']]),
segment_class=row.Class,
combined_class=row.CombinedClass)
DBSession.flush()
vs = common.ValueSet(
id=row.PhonemeID,
contribution=inventory,
language=inventory.language,
parameter=segment)
for ref in refs.get(row.InventoryID, []):
if ref not in data['Source']:
if ref not in unknown_refs:
print('-------', ref)
unknown_refs[ref] = 1
continue
DBSession.add(common.ValueSetReference(
source=data['Source'][ref],
valueset=vs))
DBSession.add(common.Value(
id=row.PhonemeID,
name='%s %s' % (row.Phoneme, data['Inventory'][row.InventoryID].name),
valueset=vs))
DBSession.flush()
for inventory_id in refs:
for ref in refs[inventory_id]:
if ref not in data['Source']:
continue
data.add(
common.ContributionReference, '%s-%s' % (inventory_id, ref),
source=data['Source'][ref],
contribution=data['Inventory'][inventory_id])
for i, row in enumerate(reader(args.data_file('phoible-segments-features.tsv'))):
if i == 0:
features = list(map(feature_name, row))
continue
if row[0] not in data['Segment']:
# print('skipping feature vector:', row)
continue
for j, value in enumerate(row):
if j and value != '0':
DBSession.add(common.Parameter_data(
key=features[j],
value=value,
ord=j,
object_pk=data['Segment'][row[0]].pk))
DBSession.flush()
def prime_cache(args): # pragma: no cover
"""
we use a versioned session to insert the changes in value assignment
"""
#
# compute the changes from 2008 to 2011:
#
vs2008 = get_vs2008(args)
for row in DB.execute("select * from datapoint"):
key = (row['language_id'], row['feature_id'])
old_value = vs2008.get(key)
new_value = row['value_numeric']
if old_value and old_value != new_value:
valueset = VersionedDBSession.query(common.ValueSet)\
.join(common.Language)\
.join(common.Parameter)\
.filter(common.Parameter.id == row['feature_id'])\
.filter(common.Language.id == row['language_id'])\
.one()
value = valueset.values[0]
assert value.domainelement.number == old_value
for de in valueset.parameter.domain:
if de.number == new_value:
value.domainelement = de
break
assert value.domainelement.number == new_value
valueset.updated = E2011
value.updated = E2011
VersionedDBSession.flush()
for row in reader(args.data_file('corrections_2013.tab'),
namedtuples=True,
newline='\r'):
valueset = VersionedDBSession.query(common.ValueSet)\
.join(common.Language)\
.join(common.Parameter)\
.filter(common.Parameter.id == row.feature)\
.filter(common.Language.id == row.wals_code)\
.one()
value = valueset.values[0]
if value.domainelement.number == int(row.new):
print('**** old news', valueset.language.id, valueset.parameter.id)
continue
if value.domainelement.number != int(row.old):
print('--->', valueset.language.id, valueset.parameter.id,
value.domainelement.number)
for de in valueset.parameter.domain:
if de.number == int(row.new):
value.domainelement = de
break
assert value.domainelement.number == int(row.new)
valueset.updated = E2013
value.updated = E2013
VersionedDBSession.flush()
print('corrections 2013 done')
for issue in [
'0', '9', '10', '11', '13', '14', '15', '16', '17', '19', '20',
'24', '26', '27', '28'
]:
issue = getattr(issues, 'issue' + issue)
issue(VersionedDBSession, E2013)
VersionedDBSession.flush()
transaction.commit()
transaction.begin()
#
# TODO: these must be recomputed as well, after migrations!
#
# cache number of languages for a parameter:
for parameter, valuesets in groupby(
DBSession.query(common.ValueSet).order_by(
common.ValueSet.parameter_pk), lambda vs: vs.parameter):
parameter.representation = str(
len(set(v.language_pk for v in valuesets)))
print('recomputation of representation done')
transaction.commit()
transaction.begin()
# cache iso codes for languages:
for language in DBSession.query(common.Language).options(
joinedload_all(common.Language.languageidentifier,
common.LanguageIdentifier.identifier)):
iso_codes = []
for identifier in language.identifiers:
if identifier.type == common.IdentifierType.iso.value:
iso_codes.append(identifier.name)
language.iso_codes = ', '.join(sorted(set(iso_codes)))
print('ecomputation of iso codes done')
transaction.commit()
transaction.begin()
compute_language_sources()
transaction.commit()
transaction.begin()
gbs_func('update', args)
def justifications(args, languages, stats):
"""
- text goes into ValueSet.description
- refs go into ValueSetReference objects
"""
hh_bibkey_to_glottolog_id = {}
for rec in get_bib(args):
for provider, bibkeys in get_bibkeys(rec).items():
if provider == 'hh':
for bibkey in bibkeys:
hh_bibkey_to_glottolog_id[bibkey] = rec['glottolog_ref_id']
break
def substitute_hh_bibkeys(m):
return '**%s**' % hh_bibkey_to_glottolog_id[m.group('bibkey')]
#
# create mappings to look up glottolog languoids matching names in justification files
#
langs_by_hid = languages
langs_by_hname = {}
langs_by_name = {}
# order by active to make sure, we active languoid overwrite the data of obsolete ones.
for l in DBSession.query(Languoid).order_by(Languoid.active):
langs_by_hname[l.jsondata.get('hname')] = l
langs_by_hid[l.hid] = l
langs_by_name[l.name] = l
def normalize_pages(s):
return (s or '').strip().rstrip(',') or None
for id_, type_ in [('fc', 'family'), ('sc', 'subclassification')]:
for i, row in enumerate(dsv.reader(
args.data_dir.joinpath('languoids', 'forkel_%s_justifications-utf8.tab' % type_))):
name = row[0]
name = name.replace('_', ' ') if not name.startswith('NOCODE') else name
l = langs_by_hname.get(name, langs_by_hid.get(name, langs_by_name.get(name)))
if not l:
args.log.warn('ignoring %s' % name)
continue
_r = 3 if type_ == 'family' else 2
comment = (row[_r].strip() or None) if len(row) > _r else None
if comment and not WORD_PATTERN.search(comment):
comment = None
if comment:
comment = re.sub('\*\*(?P<bibkey>[^\*]+)\*\*', substitute_hh_bibkeys, comment)
#
# TODO: look for [NOCODE_ppp] patterns as well!?
#
refs = [(int(m.group('id')), normalize_pages(m.group('pages')))
for m in REF_PATTERN.finditer(
re.sub('\*\*(?P<bibkey>[^\*]+)\*\*', substitute_hh_bibkeys, row[2]))]
vs = None
for _vs in l.valuesets:
if _vs.parameter.id == id_:
vs = _vs
break
if not vs:
args.log.info('%s %s ++' % (l.id, type_))
vs = ValueSet(
id='%s%s' % (id_, l.pk),
description=comment,
language=l,
parameter=Parameter.get(id_),
contribution=Contribution.first())
DBSession.add(Value(
id='%s%s' % (id_, l.pk),
name='%s - %s' % (l.level, l.status),
valueset=vs))
DBSession.flush()
else:
if vs.description != comment:
args.log.info('%s %s ~~ description: %s ---> %s' % (l.id, type_, vs.description, comment))
vs.description = comment
stats.update(['justifications-%s' % type_])
for r in vs.references:
DBSession.delete(r)
for r, pages in refs:
# FIXME: we must make sure not to link sources which will subsequently be
# replaced!
vs.references.append(ValueSetReference(
source=Source.get(str(r)),
description=pages))
args.log.info('%s %s' % (i, type_))
def get_vs2008(args): # pragma: no cover
vs2008 = {}
for row in reader(args.data_file("datapoints_2008.csv"), delimiter=","):
vs2008[(row[0], "%sA" % row[1])] = int(row[2])
return vs2008
def read(table):
return list(dsv.reader(
args.data_file(table + '.csv'), delimiter=',', namedtuples=True))
def get_rows(args, name):
for i, row in enumerate(reader(args.data_file('InventoryID-%s.csv' % name))):
if i and row[1] != 'NA':
yield row
def prime_cache(args): # pragma: no cover
"""
we use a versioned session to insert the changes in value assignment
"""
#
# compute the changes from 2008 to 2011:
#
vs2008 = get_vs2008(args)
for row in DB.execute("select * from datapoint"):
key = (row["language_id"], row["feature_id"])
old_value = vs2008.get(key)
new_value = row["value_numeric"]
if old_value and old_value != new_value:
valueset = (
VersionedDBSession.query(common.ValueSet)
.join(common.Language)
.join(common.Parameter)
.filter(common.Parameter.id == row["feature_id"])
.filter(common.Language.id == row["language_id"])
.one()
)
value = valueset.values[0]
assert value.domainelement.number == old_value
for de in valueset.parameter.domain:
if de.number == new_value:
value.domainelement = de
break
assert value.domainelement.number == new_value
valueset.updated = E2011
value.updated = E2011
VersionedDBSession.flush()
for row in reader(args.data_file("corrections_2013.tab"), namedtuples=True, newline="\r"):
valueset = (
VersionedDBSession.query(common.ValueSet)
.join(common.Language)
.join(common.Parameter)
.filter(common.Parameter.id == row.feature)
.filter(common.Language.id == row.wals_code)
.one()
)
value = valueset.values[0]
if value.domainelement.number == int(row.new):
print("**** old news", valueset.language.id, valueset.parameter.id)
continue
if value.domainelement.number != int(row.old):
print("--->", valueset.language.id, valueset.parameter.id, value.domainelement.number)
for de in valueset.parameter.domain:
if de.number == int(row.new):
value.domainelement = de
break
assert value.domainelement.number == int(row.new)
valueset.updated = E2013
value.updated = E2013
VersionedDBSession.flush()
print("corrections 2013 done")
for issue in ["0", "9", "10", "11", "13", "14", "15", "16", "17", "19", "20", "24", "26", "27", "28"]:
issue = getattr(issues, "issue" + issue)
issue(VersionedDBSession, E2013)
VersionedDBSession.flush()
transaction.commit()
transaction.begin()
#
# TODO: these must be recomputed as well, after migrations!
#
# cache number of languages for a parameter:
for parameter, valuesets in groupby(
DBSession.query(common.ValueSet).order_by(common.ValueSet.parameter_pk), lambda vs: vs.parameter
):
parameter.representation = str(len(set(v.language_pk for v in valuesets)))
print("recomputation of representation done")
transaction.commit()
transaction.begin()
# cache iso codes for languages:
for language in DBSession.query(common.Language).options(
joinedload_all(common.Language.languageidentifier, common.LanguageIdentifier.identifier)
):
iso_codes = []
for identifier in language.identifiers:
if identifier.type == common.IdentifierType.iso.value:
iso_codes.append(identifier.name)
language.iso_codes = ", ".join(sorted(set(iso_codes)))
print("ecomputation of iso codes done")
transaction.commit()
transaction.begin()
compute_language_sources()
transaction.commit()
transaction.begin()
gbs_func("update", args)
def get_tab(name):
"""generator for entries in a tab file specified by name.
"""
return dsv.reader(get(get_taburls()[name]).split('\n'), namedtuples=True)