def build_term(term):
term_obj = Term()
for variable, terminal in term:
if variable:
symbol_obj = Symbol(variable, True)
elif terminal:
symbol_obj = Symbol(terminal, False)
else:
print("WHY THE HELL ARE YOU HERE?! building term")
term_obj.add(symbol_obj)
return term_obj
def _get_term(data):
if 'id' in data:
term = Term.objects.get(pk=data['id'])
else:
term = Term()
term.name_en = data.get('name_en', '')
term.name_la = data.get('name_la', '')
term.name_cs = data.get('name_cs', '')
term.system = data.get('system', '')
term.bodypart = data.get('body_part', '')
term.fma_id = data.get('fma_id', -1)
term.save()
return term
def get_translations(data, text, src_lang):
# TODO fix dictionary map for all languages
dmap = {
'ru': 'english-russian',
'fr': 'english-french',
'de': 'english-german',
}
for lang, dictionary in dmap.items():
pat = '{0}/dictionary/{1}/{2}'
url = pat.format(base, dictionary, text.replace(' ', '-'))
resp = requests.get(url, headers=headers)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, 'html.parser')
for sense in soup.find_all('div', class_='sense-body'):
phrase = sense.find('div', class_='phrase-block')
if phrase: continue
trans = sense.find('span', class_='trans')
if trans:
for word in stripped_text(trans).split(','):
term = Term(text=word, lang=lang, region=None)
data['translated_as'].append(term)
return data
def get_translations(text, src_lang):
# TODO fix dictionary map for all languages
dmap = {
'ru': 'english-russian',
'fr': 'english-french',
'de': 'english-german',
}
txt = text.replace(' ', '-')
for lang, dictionary in dmap.items():
url = f'{base}/dictionary/{dictionary}/{txt}'
resp = requests.get(url, headers=headers)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, 'html.parser')
for sense in soup.find_all('div', class_='sense-body'):
phrase = sense.find('div', class_='phrase-block')
if phrase: continue
trans = sense.find('span', class_='trans')
if trans:
words = stripped_text(trans).split(',')
words = [w for w in words if not is_empty(w)]
for word in words:
term = Term(text=word, lang=lang, region=None)
yield ('translated_as', term)
def get_data(query, lang):
if lang != 'en':
return None
url = f'https://www.macmillandictionary.com/dictionary/british/{query}'
headers = {
'User-Agent': 'script',
'Accept': 'text/html',
}
resp = requests.get(url, headers=headers)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, 'html.parser')
#get transcription
transcriptions = soup.find_all(class_='PRON')
for t in transcriptions:
yield ('transcription',
Term(text=stripped_text(t).replace('/', ''),
lang=lang,
region=None))
#get tags
crop_text = stripped_text(soup.find(class_='zwsp'))
#remove bad substring
part_speech = stripped_text(soup.find(class_='PART-OF-SPEECH')).replace(
crop_text, '')
syntax_coding = stripped_text(soup.find(class_='SYNTAX-CODING'))
yield ('tag', Term(text=part_speech, lang=lang, region=None))
yield ('tag', Term(text=syntax_coding, lang=lang, region=None))
#get defenition
defenitions = soup.find_all(class_='DEFINITION')
for d in defenitions:
yield ('definition', Term(text=stripped_text(d),
lang=lang,
region=None))
#get examples
examples = soup.find_all(class_='EXAMPLES')
for e in examples:
yield ('in', Term(text=stripped_text(e), lang=lang, region=None))
examples = soup.find_all(class_='PHR-XREF')
for e in examples:
yield ('in', Term(text=stripped_text(e), lang=lang, region=None))
#get synonyms
synonyms = soup.find_all(class_='synonyms')
for allsyn in synonyms:
subsynonyms = allsyn.find_all(class_='theslink')
for syn in subsynonyms:
if (not '...' in syn.text):
yield ('synonym',
Term(text=stripped_text(syn), lang=lang, region=None))
#get audio
audio = soup.find(class_='audio_play_button')
yield ('audio', File(url=audio['data-src-mp3'], region=None))
yield ('audio', File(url=audio['data-src-ogg'], region=None))
def define_word(text, lang='en', source_idx=-1, count=1):
term_id = define_term(Term(text=text, lang=lang, region=None))
source_list = sources if source_idx < 0 else sources[
source_idx:source_idx + count]
for source in source_list:
data = get_data_safe(source, text, lang)
if data is None:
sys.exit(-1)
push_data(term_id, data)
def parse_phrase_row(row, lang, trans_lang, tags):
def parse_td(td):
# if 'class' not in td.attrs:
# return None
# k = td.attrs['class']
# if k not in ['phraselist1', 'phraselist2']:
# return None
a = td.find('a')
return stripped_text(a)
result = [parse_td(t) for t in row.find_all('td')]
if len(result) != 2:
return []
if any(t is None for t in result):
return []
term = Term(text=result[0], lang=lang, region=None)
trans = Term(text=result[1], lang=trans_lang, region=None)
return [TermWithData(term, {'tag': tags, 'translated_as': [trans]})]
def achievements(request):
current_term = Term.current_term_key()
active = Participant.objects.filter(is_active=True)
with_awards = active.filter(grant__term_id=current_term
).annotate(num_grants=Count('grant'), time=Max('grant__granted')
).order_by('-num_grants', '-time')
without_awards = active.exclude(grant__term_id=current_term)
hide_nominate_link = request.REQUEST.get('hide_nominate_links', False)
return render_to_response('achievements.html',
{'participants': itertools.chain(with_awards, without_awards),
'show_nominate_link': not hide_nominate_link},
context_instance=RequestContext(request))
def parse_thesaurus(lang, page):
soup = BeautifulSoup(page, 'html.parser')
dlist = soup.find_all('span', class_='syn-list')
for d in dlist:
synonyms = d.find_all('a')
for s in synonyms:
yield ('synonym',
Term(text=stripped_text(s), lang=lang, region=None))
dlist = soup.find_all('span', class_='rel-list')
for d in dlist:
related = d.find_all('a')
for r in related:
yield ('related',
Term(text=stripped_text(r), lang=lang, region=None))
dlist = soup.find_all('span', class_='ant-list')
for d in dlist:
antonyms = d.find_all('a')
for r in antonyms:
yield ('antonym',
Term(text=stripped_text(r), lang=lang, region=None))
def achievements(request):
current_term = Term.current_term_key()
active = Participant.objects.filter(is_active=True)
with_awards = active.filter(grant__term_id=current_term).annotate(
num_grants=Count('grant'),
time=Max('grant__granted')).order_by('-num_grants', '-time')
without_awards = active.exclude(grant__term_id=current_term)
hide_nominate_link = request.REQUEST.get('hide_nominate_links', False)
return render_to_response(
'achievements.html', {
'participants': itertools.chain(with_awards, without_awards),
'show_nominate_link': not hide_nominate_link
},
context_instance=RequestContext(request))
def __init__(self, *args, **kwargs):
super(NominatePersonForm, self).__init__(*args, **kwargs)
this_term = Term.current_term_key()
term_grants = Grant.objects.filter(\
participant = self.instance.participant,\
term = this_term)
term_user_nominations = Nomination.objects.filter(\
nominator = self.instance.nominator,
participant = self.instance.participant,
term = this_term)
self.fields['achievement'] = forms.ModelChoiceField(\
queryset = Achievement.objects.filter(\
can_nominate=True).exclude(\
grant__in = term_grants).exclude(\
nomination__in = term_user_nominations))
def __init__(self, *args, **kwargs):
super(NominatePersonForm, self).__init__(*args, **kwargs)
this_term = Term.current_term_key()
term_grants = Grant.objects.filter(\
participant = self.instance.participant,\
term = this_term)
term_user_nominations = Nomination.objects.filter(\
nominator = self.instance.nominator,
participant = self.instance.participant,
term = this_term)
self.fields['achievement'] = forms.ModelChoiceField(\
queryset = Achievement.objects.filter(\
can_nominate=True).exclude(\
grant__in = term_grants).exclude(\
nomination__in = term_user_nominations))
def get_data(query, lang):
if lang != 'en':
return None
data = {
'audio': [],
#'visual': [],
'tag': [],
'transcription': [],
'definition': [],
'in': [],
'synonym': [],
'antonym': [],
'related': []
}
pat = 'https://www.merriam-webster.com/dictionary/{0}'
url = pat.format(query)
headers = {
'User-Agent': 'script',
'Accept': 'text/html',
}
resp = requests.get(url, headers=headers)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, 'html.parser')
#find transcription and audio
prs = soup.find('span', class_='prs')
transcription = prs.find('span', class_='pr')
transcription = stripped_text(transcription)
data['transcription'].append(transcription)
btns = prs.find_all('a', class_='play-pron')
urls = [parse_btn(b) for b in btns]
urls = [u for u in urls if utils.url_exists(u)]
for url in urls:
data['audio'].append(File(url=url, region=None))
#find definitions and 'in'
vg = soup.find_all('div', class_='vg')
for v in vg:
definitions = v.find_all(class_='dt')
for d in definitions:
text = stripped_text(d)
#all defenitions start with ':' with class mw_t_bc
if (d.find(class_='mw_t_bc') is not None):
text = text.lstrip(':').strip()
#with defenitions we can take examples of text with class ex-sent, we need drop it
if (d.find(class_='ex-sent') is not None):
text = text.split('\n')[0].strip()
data['definition'].append(
Term(text=text, lang=lang, region=None))
#parse examples
data_in = soup.find_all(class_='ex-sent')
for d in data_in:
if ('t' in d['class']):
data['in'].append(
Term(text=stripped_text(d), lang=lang, region=None))
#parse related
ure = soup.find_all(class_='ure')
for d in ure:
data['related'].append(
Term(text=stripped_text(d), lang=lang, region=None))
#parse tags
tag = soup.find_all('span', class_='fl')
for d in tag:
data['tag'].append(Term(text=stripped_text(d), lang=lang, region=None))
#add tag with name 'word', becouse our name is word
data['tag'].append(Term(text='word', lang=lang, region=None))
#move to second page, in teasaurus
pat_t = 'https://www.merriam-webster.com/thesaurus/{0}'
url_t = pat_t.format(query)
resp = requests.get(url_t, headers=headers)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, 'html.parser')
dlist = soup.find_all('span', class_='syn-list')
for d in dlist:
synonyms = d.find_all('a')
for s in synonyms:
data['synonym'].append(
Term(text=stripped_text(s), lang=lang, region=None))
dlist = soup.find_all('span', class_='rel-list')
for d in dlist:
related = d.find_all('a')
for r in related:
data['related'].append(
Term(text=stripped_text(r), lang=lang, region=None))
dlist = soup.find_all('span', class_='ant-list')
for d in dlist:
antonyms = d.find_all('a')
for r in antonyms:
data['antonym'].append(
Term(text=stripped_text(r), lang=lang, region=None))
return data
def define_word(text, lang='en', source_idx=-1):
term_id = define_term(Term(text=text, lang=lang, region=None))
source_list = sources if source_idx < 0 else [sources[source_idx]]
for source in source_list:
data = source.get_data(text, lang)
push_data(term_id, data)
def get_data(query, lang):
if lang != 'en':
return
url = f'https://www.merriam-webster.com/dictionary/{query}'
headers = {
'User-Agent': 'script',
'Accept': 'text/html',
}
resp = requests.get(url, headers=headers)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, 'html.parser')
#find transcription and audio
prs = soup.find('span', class_='prs')
if prs is not None:
transcription = prs.find('span', class_='pr')
transcription = stripped_text(transcription)
yield ('transcription',
Term(text=transcription, lang='ipa', region=None))
btns = prs.find_all('a', class_='play-pron')
urls = [parse_btn(b) for b in btns]
urls = [u for u in urls if utils.url_exists(u)]
for url in urls:
yield ('audio', File(url=url, region=None))
#find definitions and 'in'
vg = soup.find_all('div', class_='vg')
for v in vg:
definitions = v.find_all(class_='dt')
for d in definitions:
text = stripped_text(d)
#all defenitions start with ':' with class mw_t_bc
if (d.find(class_='mw_t_bc') is not None):
text = text.lstrip(':').strip()
#with defenitions we can take examples of text with class ex-sent, we need drop it
if (d.find(class_='ex-sent') is not None):
text = text.split('\n')[0].strip()
yield ('definition', Term(text=text, lang=lang, region=None))
#parse examples
data_in = soup.find_all(class_='ex-sent')
for d in data_in:
if ('t' in d['class']):
yield ('in', Term(text=stripped_text(d), lang=lang, region=None))
#parse related
ure = soup.find_all(class_='ure')
for d in ure:
yield ('related', Term(text=stripped_text(d), lang=lang, region=None))
#parse tags
tag = soup.find_all('span', class_='fl')
for d in tag:
yield ('tag', Term(text=stripped_text(d), lang=lang, region=None))
#add tag with name 'word', becouse our name is word
yield ('tag', Term(text='word', lang=lang, region=None))
#move to second page, in teasaurus
url_t = f'https://www.merriam-webster.com/thesaurus/{query}'
resp = requests.get(url_t, headers=headers)
if resp.ok:
for t in parse_thesaurus(lang, resp.text):
yield t
import sys
import utils
import requests
import json
from bs4 import BeautifulSoup
from models import Term, TermWithData
headers = {
'User-Agent': utils.CHROME_USER_AGENT,
'Accept': 'text/html',
}
# TODO consider collecting automatically https://www.multitran.com/m.exe?s=place&l1=2&l2=1&fl=1
categories = [{
'tag': [
Term(text='idiom', lang='en', region=None),
Term(text='идиома', lang='ru', region=None),
],
'id':
895,
}, {
'tag': [
Term(text='proverb', lang='en', region=None),
Term(text='пословица', lang='ru', region=None),
],
'id':
310,
}, {
'tag': [
Term(text='americanism', lang='en', region=None),
Term(text='американизм', lang='ru', region=None),
def query(term_id):
query = (Term.select(Term.title).where(Term.id == term_id).dicts())
return query
def get_data(text, lang):
if lang != 'en':
return
txt = text.replace(' ', '-')
url = f'{base}/dictionary/english/{txt}'
resp = requests.get(url, headers=headers)
resp.raise_for_status()
codes = {
'C': 'countable',
'U': 'uncountable',
'S': 'singular',
}
posgram_found = False
gram_found = False
if utils.is_word(text):
yield ('tag', Term(text='word', lang=lang, region=None))
soup = BeautifulSoup(resp.text, 'html.parser')
page = soup.find('div', class_='page')
for dictionary in page.find_all('div', class_='dictionary'):
header = dictionary.find('div', class_='pos-header')
body = dictionary.find('div', class_='pos-body')
posgram = header.find('div', class_='posgram')
if posgram and not posgram_found:
pos = find_strip(posgram, 'span', class_='pos')
term = Term(text=pos, lang=lang, region=None)
yield ('tag', term)
posgram_found = True
if not gram_found:
for gram in body.find_all('span', class_='gram'):
for gc in gram.find_all('span', class_='gc'):
code = stripped_text(gc)
if code in codes and not gram_found:
term = Term(text=codes[code], lang=lang, region=None)
yield ('tag', term)
gram_found = True
# parse pronunciations
for dpron in header.find_all('span', class_='dpron-i'):
region = find_strip(dpron, 'span', 'region')
amp = header.find('amp-audio')
for source in amp.find_all('source'):
file = File(url=base + source.attrs['src'], region=region)
yield ('audio', file)
ipa = find_strip(dpron, 'span', class_='ipa')
if not is_empty(ipa):
yield ('transcription', Term(text=ipa,
lang=lang,
region=region))
for dblock in body.find_all('div', class_='def-block'):
def_text = stripped_text(dblock.find('div', class_='def'))
if not is_empty(def_text):
yield ('definition', Term(text=def_text,
lang=lang,
region=None))
img = dblock.find('amp-img')
if img is not None:
file = File(url=base + img.attrs['src'], region=None)
yield ('visual', file)
for eg in dblock.find_all('span', 'eg'):
term = Term(text=stripped_text(eg), lang=lang, region=None)
yield ('in', term)
for dataset in page.find_all('div', class_='dataset'):
for eg in dataset.find_all('span', class_='deg'):
term = Term(text=stripped_text(eg), lang=lang, region=None)
yield ('in', term)
cpegs = dataset.find('div', class_='cpegs')
if cpegs:
for lbb in cpegs.find_all('div', class_='lbb'):
for a in lbb.find_all('a', class_='hdib'):
term = Term(text=stripped_text(a), lang=lang, region=None)
yield ('collocation', term)
for t in get_translations(text, lang):
yield t
def get_all_terms(self):
query = (Term.select(Term.title, Term.id).dicts())
return query