def month_detail(request, year, month):
year_month = '%s%s' % (year, month)
month_name = MONTH_NAMES[int(month) - 1]
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n - 1]] = capitolwords.top_phrases(
entity_type='month', entity_value=year_month, n=n, per_page=30)
ngrams = ngrams.iteritems()
dates = capitolwords._dates_in_month(year=year, month=month)
def date_str_to_date(date_str):
year, month, day = map(int, date_str.split('-'))
return datetime.date(year, month, day)
dates_by_week = [
(weeknum, list(dates)) for weeknum, dates in itertools.groupby(
dates, lambda x: date_str_to_date(x['date']).strftime('%U'))
]
return render_to_response('cwod/month_detail.html', {
'month_name': month_name,
'year': year,
'ngrams': ngrams,
'dates_by_week': dates_by_week,
},
context_instance=RequestContext(request))
def month_detail(request, year, month):
year_month = '%s%s' % (year, month)
month_name = MONTH_NAMES[int(month)-1]
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n-1]] = capitolwords.top_phrases(
entity_type='month',
entity_value=year_month,
n=n,
per_page=30
)
ngrams = ngrams.iteritems()
dates = capitolwords._dates_in_month(year=year, month=month)
def date_str_to_date(date_str):
year, month, day = map(int, date_str.split('-'))
return datetime.date(year, month, day)
dates_by_week = [(weeknum, list(dates)) for weeknum, dates in itertools.groupby(dates, lambda x: date_str_to_date(x['date']).strftime('%U'))]
return render_to_response('cwod/month_detail.html',
{'month_name': month_name,
'year': year,
'ngrams': ngrams,
'dates_by_week': dates_by_week,
},
context_instance=RequestContext(request))
def date_detail(request, year, month, day):
kwargs = {}
if request.GET.get('bioguide_id'):
kwargs['bioguide_id'] = request.GET['bioguide_id']
date = datetime.date(year=int(year), month=int(month), day=int(day))
entries = entries_for_date(date, **kwargs)
print entries
if not entries:
raise Http404
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n - 1]] = capitolwords.top_phrases(
entity_type='date',
entity_value=date,
n=n,
per_page=30,
)
ngrams = ngrams.iteritems()
by_chamber = {
'House': [],
'Senate': [],
'Extensions of Remarks': [],
}
similar_dates = get_similar_entities('date', date)
return render_to_response('cwod/date_detail.html', {
'date': date,
'ngrams': ngrams,
'entries': entries,
'similar_dates': similar_dates,
},
context_instance=RequestContext(request))
def date_detail(request, year, month, day):
kwargs = {}
if request.GET.get('bioguide_id'):
kwargs['bioguide_id'] = request.GET['bioguide_id']
date = datetime.date(year=int(year), month=int(month), day=int(day))
entries = entries_for_date(date, **kwargs)
print entries
if not entries:
raise Http404
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n-1]] = capitolwords.top_phrases(
entity_type='date',
entity_value=date,
n=n,
per_page=30,
)
ngrams = ngrams.iteritems()
by_chamber = {'House': [], 'Senate': [], 'Extensions of Remarks': [], }
similar_dates = get_similar_entities('date', date)
return render_to_response('cwod/date_detail.html',
{'date': date,
'ngrams': ngrams,
'entries': entries,
'similar_dates': similar_dates,
}, context_instance=RequestContext(request))
def legislator_detail(request, bioguide_id, slug=None):
legislator = legislator_lookup(bioguide_id)
if not legislator:
raise Http404
if legislator['slug'] != slug:
return HttpResponsePermanentRedirect(reverse('cwod_legislator_detail', kwargs={'bioguide_id':bioguide_id, 'slug':legislator['slug']}))
similar_legislators = []
for i in get_similar_entities('bioguide', bioguide_id)[:10]:
i['legislator'] = legislator_lookup(i['bioguide'])
similar_legislators.append(i)
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n-1]] = capitolwords.top_phrases(
entity_type='legislator',
entity_value=bioguide_id,
n=n,
per_page=30
)
ngrams = ngrams.iteritems()
entries = capitolwords.text(bioguide_id=bioguide_id, sort='date desc', per_page=5)
return render_to_response('cwod/legislator_detail.html',
{'legislator': legislator,
'current_congress': get_current_congress(),
'similar_legislators': similar_legislators,
'entries': entries,
'ngrams': ngrams,
}, context_instance=RequestContext(request))
def state_detail(request, state):
state_name = dict(STATE_CHOICES + TERRITORY_CHOICES).get(state)
if not state_name:
raise Http404
entries = capitolwords.text(state='"%s"' % state,
sort='date desc,score desc',
per_page=5)
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n - 1]] = capitolwords.top_phrases(
entity_type='state', entity_value=state, n=n, per_page=30)
ngrams = ngrams.iteritems()
similar_states = get_similar_entities('state', state)
# legislators = LegislatorRole.objects.filter(state=state, end_date__gte=datetime.date.today())
legislators = capitolwords.legislators(state=state,
congress=get_current_congress())
def sort_districts(x, y):
try:
x_district = int(x['district'])
except ValueError:
x_district = 0
try:
y_district = int(y['district'])
except ValueError:
y_district = 0
return cmp(x_district, y_district)
legislators = sorted(legislators, sort_districts)
bodies = {
'House': [],
'Senate': [],
}
for legislator in legislators:
if legislator['chamber'] == 'Senate':
bodies['Senate'].append(legislator)
else:
bodies['House'].append(legislator)
bodies = sorted(bodies.items(), key=itemgetter(0), reverse=True)
return render_to_response(
'cwod/state_detail.html',
{
'state': state,
'state_name': state_name,
'entries': entries,
'ngrams': ngrams,
#'other_states': other_states,
'similar_states': similar_states,
'bodies': bodies,
},
context_instance=RequestContext(request))
def state_detail(request, state):
state_name = dict(STATE_CHOICES + TERRITORY_CHOICES).get(state)
if not state_name:
raise Http404
entries = capitolwords.text(state='"%s"' % state, sort='date desc,score desc', per_page=5)
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n-1]] = capitolwords.top_phrases(
entity_type='state',
entity_value=state,
n=n,
per_page=30
)
ngrams = ngrams.iteritems()
similar_states = get_similar_entities('state', state)
# legislators = LegislatorRole.objects.filter(state=state, end_date__gte=datetime.date.today())
legislators = capitolwords.legislators(state=state, congress=get_current_congress())
def sort_districts(x, y):
try:
x_district = int(x['district'])
except ValueError:
x_district = 0
try:
y_district = int(y['district'])
except ValueError:
y_district = 0
return cmp(x_district, y_district)
legislators = sorted(legislators, sort_districts)
bodies = {'House': [], 'Senate': [], }
for legislator in legislators:
if legislator['chamber'] == 'Senate':
bodies['Senate'].append(legislator)
else:
bodies['House'].append(legislator)
bodies = sorted(bodies.items(), key=itemgetter(0), reverse=True)
return render_to_response('cwod/state_detail.html',
{'state': state,
'state_name': state_name,
'entries': entries,
'ngrams': ngrams,
#'other_states': other_states,
'similar_states': similar_states,
'bodies': bodies,
}, context_instance=RequestContext(request))
def state_list(request):
states = []
for abbrev, statename in (US_STATES + US_TERRITORIES):
states.append((abbrev, statename,
capitolwords.top_phrases(entity_type='state',
entity_value=abbrev,
n=1,
per_page=5)))
state_chunks = chunks(states, (len(states) + 1) / 3)
return render_to_response('cwod/state_list.html', {
'state_chunks': state_chunks,
},
context_instance=RequestContext(request))
def state_list(request):
states = []
for abbrev, statename in (US_STATES + US_TERRITORIES):
states.append((abbrev, statename, capitolwords.top_phrases(
entity_type='state',
entity_value=abbrev,
n=1,
per_page=5)
))
state_chunks = chunks(states, (len(states)+1)/3)
return render_to_response('cwod/state_list.html',
{'state_chunks': state_chunks,
}, context_instance=RequestContext(request))
def legislator_detail(request, bioguide_id, slug=None):
legislator = legislator_lookup(bioguide_id)
if not legislator:
raise Http404
if legislator['slug'] != slug:
return HttpResponsePermanentRedirect(
reverse('cwod_legislator_detail',
kwargs={
'bioguide_id': bioguide_id,
'slug': legislator['slug']
}))
similar_legislators = []
for i in get_similar_entities('bioguide', bioguide_id)[:10]:
i['legislator'] = legislator_lookup(i['bioguide'])
similar_legislators.append(i)
ngrams = {}
for n in range(1, 6):
ngrams[GRAM_NAMES[n - 1]] = capitolwords.top_phrases(
entity_type='legislator',
entity_value=bioguide_id,
n=n,
per_page=30)
ngrams = ngrams.iteritems()
entries = capitolwords.text(bioguide_id=bioguide_id,
sort='date desc',
per_page=5)
return render_to_response('cwod/legislator_detail.html', {
'legislator': legislator,
'current_congress': get_current_congress(),
'similar_legislators': similar_legislators,
'entries': entries,
'ngrams': ngrams,
},
context_instance=RequestContext(request))
