id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
|---|---|---|---|---|---|---|---|---|---|---|---|
18,000 | caktus/django-timepiece | timepiece/reports/views.py | BillableHours.get_hours_data | def get_hours_data(self, entries, date_headers):
"""Sum billable and non-billable hours across all users."""
project_totals = get_project_totals(
entries, date_headers, total_column=False) if entries else []
data_map = {}
for rows, totals in project_totals:
for u... | python | def get_hours_data(self, entries, date_headers):
"""Sum billable and non-billable hours across all users."""
project_totals = get_project_totals(
entries, date_headers, total_column=False) if entries else []
data_map = {}
for rows, totals in project_totals:
for u... | [
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18,001 | caktus/django-timepiece | timepiece/templatetags/timepiece_tags.py | add_parameters | def add_parameters(url, parameters):
"""
Appends URL-encoded parameters to the base URL. It appends after '&' if
'?' is found in the URL; otherwise it appends using '?'. Keep in mind that
this tag does not take into account the value of existing params; it is
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"""
Appends URL-encoded parameters to the base URL. It appends after '&' if
'?' is found in the URL; otherwise it appends using '?'. Keep in mind that
this tag does not take into account the value of existing params; it is
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18,002 | caktus/django-timepiece | timepiece/templatetags/timepiece_tags.py | get_max_hours | def get_max_hours(context):
"""Return the largest number of hours worked or assigned on any project."""
progress = context['project_progress']
return max([0] + [max(p['worked'], p['assigned']) for p in progress]) | python | def get_max_hours(context):
"""Return the largest number of hours worked or assigned on any project."""
progress = context['project_progress']
return max([0] + [max(p['worked'], p['assigned']) for p in progress]) | [
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18,003 | caktus/django-timepiece | timepiece/templatetags/timepiece_tags.py | get_uninvoiced_hours | def get_uninvoiced_hours(entries, billable=None):
"""Given an iterable of entries, return the total hours that have
not been invoiced. If billable is passed as 'billable' or 'nonbillable',
limit to the corresponding entries.
"""
statuses = ('invoiced', 'not-invoiced')
if billable is not None:
... | python | def get_uninvoiced_hours(entries, billable=None):
"""Given an iterable of entries, return the total hours that have
not been invoiced. If billable is passed as 'billable' or 'nonbillable',
limit to the corresponding entries.
"""
statuses = ('invoiced', 'not-invoiced')
if billable is not None:
... | [
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18,004 | caktus/django-timepiece | timepiece/templatetags/timepiece_tags.py | humanize_hours | def humanize_hours(total_hours, frmt='{hours:02d}:{minutes:02d}:{seconds:02d}',
negative_frmt=None):
"""Given time in hours, return a string representing the time."""
seconds = int(float(total_hours) * 3600)
return humanize_seconds(seconds, frmt, negative_frmt) | python | def humanize_hours(total_hours, frmt='{hours:02d}:{minutes:02d}:{seconds:02d}',
negative_frmt=None):
"""Given time in hours, return a string representing the time."""
seconds = int(float(total_hours) * 3600)
return humanize_seconds(seconds, frmt, negative_frmt) | [
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18,005 | caktus/django-timepiece | timepiece/templatetags/timepiece_tags.py | _timesheet_url | def _timesheet_url(url_name, pk, date=None):
"""Utility to create a time sheet URL with optional date parameters."""
url = reverse(url_name, args=(pk,))
if date:
params = {'month': date.month, 'year': date.year}
return '?'.join((url, urlencode(params)))
return url | python | def _timesheet_url(url_name, pk, date=None):
"""Utility to create a time sheet URL with optional date parameters."""
url = reverse(url_name, args=(pk,))
if date:
params = {'month': date.month, 'year': date.year}
return '?'.join((url, urlencode(params)))
return url | [
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18,006 | caktus/django-timepiece | timepiece/crm/views.py | reject_user_timesheet | def reject_user_timesheet(request, user_id):
"""
This allows admins to reject all entries, instead of just one
"""
form = YearMonthForm(request.GET or request.POST)
user = User.objects.get(pk=user_id)
if form.is_valid():
from_date, to_date = form.save()
entries = Entry.no_join.fi... | python | def reject_user_timesheet(request, user_id):
"""
This allows admins to reject all entries, instead of just one
"""
form = YearMonthForm(request.GET or request.POST)
user = User.objects.get(pk=user_id)
if form.is_valid():
from_date, to_date = form.save()
entries = Entry.no_join.fi... | [
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18,007 | caktus/django-timepiece | setup.py | _is_requirement | def _is_requirement(line):
"""Returns whether the line is a valid package requirement."""
line = line.strip()
return line and not (line.startswith("-r") or line.startswith("#")) | python | def _is_requirement(line):
"""Returns whether the line is a valid package requirement."""
line = line.strip()
return line and not (line.startswith("-r") or line.startswith("#")) | [
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18,008 | caktus/django-timepiece | timepiece/utils/search.py | SearchMixin.render_to_response | def render_to_response(self, context):
"""
When the user makes a search and there is only one result, redirect
to the result's detail page rather than rendering the list.
"""
if self.redirect_if_one_result:
if self.object_list.count() == 1 and self.form.is_bound:
... | python | def render_to_response(self, context):
"""
When the user makes a search and there is only one result, redirect
to the result's detail page rather than rendering the list.
"""
if self.redirect_if_one_result:
if self.object_list.count() == 1 and self.form.is_bound:
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18,009 | caktus/django-timepiece | timepiece/entries/forms.py | ClockInForm.clean_start_time | def clean_start_time(self):
"""
Make sure that the start time doesn't come before the active entry
"""
start = self.cleaned_data.get('start_time')
if not start:
return start
active_entries = self.user.timepiece_entries.filter(
start_time__gte=start... | python | def clean_start_time(self):
"""
Make sure that the start time doesn't come before the active entry
"""
start = self.cleaned_data.get('start_time')
if not start:
return start
active_entries = self.user.timepiece_entries.filter(
start_time__gte=start... | [
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18,010 | caktus/django-timepiece | timepiece/entries/forms.py | AddUpdateEntryForm.clean | def clean(self):
"""
If we're not editing the active entry, ensure that this entry doesn't
conflict with or come after the active entry.
"""
active = utils.get_active_entry(self.user)
start_time = self.cleaned_data.get('start_time', None)
end_time = self.cleaned_d... | python | def clean(self):
"""
If we're not editing the active entry, ensure that this entry doesn't
conflict with or come after the active entry.
"""
active = utils.get_active_entry(self.user)
start_time = self.cleaned_data.get('start_time', None)
end_time = self.cleaned_d... | [
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18,011 | caktus/django-timepiece | timepiece/entries/views.py | clock_in | def clock_in(request):
"""For clocking the user into a project."""
user = request.user
# Lock the active entry for the duration of this transaction, to prevent
# creating multiple active entries.
active_entry = utils.get_active_entry(user, select_for_update=True)
initial = dict([(k, v) for k, v... | python | def clock_in(request):
"""For clocking the user into a project."""
user = request.user
# Lock the active entry for the duration of this transaction, to prevent
# creating multiple active entries.
active_entry = utils.get_active_entry(user, select_for_update=True)
initial = dict([(k, v) for k, v... | [
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18,012 | caktus/django-timepiece | timepiece/entries/views.py | toggle_pause | def toggle_pause(request):
"""Allow the user to pause and unpause the active entry."""
entry = utils.get_active_entry(request.user)
if not entry:
raise Http404
# toggle the paused state
entry.toggle_paused()
entry.save()
# create a message that can be displayed to the user
acti... | python | def toggle_pause(request):
"""Allow the user to pause and unpause the active entry."""
entry = utils.get_active_entry(request.user)
if not entry:
raise Http404
# toggle the paused state
entry.toggle_paused()
entry.save()
# create a message that can be displayed to the user
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18,013 | caktus/django-timepiece | timepiece/entries/views.py | reject_entry | def reject_entry(request, entry_id):
"""
Admins can reject an entry that has been verified or approved but not
invoiced to set its status to 'unverified' for the user to fix.
"""
return_url = request.GET.get('next', reverse('dashboard'))
try:
entry = Entry.no_join.get(pk=entry_id)
ex... | python | def reject_entry(request, entry_id):
"""
Admins can reject an entry that has been verified or approved but not
invoiced to set its status to 'unverified' for the user to fix.
"""
return_url = request.GET.get('next', reverse('dashboard'))
try:
entry = Entry.no_join.get(pk=entry_id)
ex... | [
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18,014 | caktus/django-timepiece | timepiece/entries/views.py | delete_entry | def delete_entry(request, entry_id):
"""
Give the user the ability to delete a log entry, with a confirmation
beforehand. If this method is invoked via a GET request, a form asking
for a confirmation of intent will be presented to the user. If this method
is invoked via a POST request, the entry wi... | python | def delete_entry(request, entry_id):
"""
Give the user the ability to delete a log entry, with a confirmation
beforehand. If this method is invoked via a GET request, a form asking
for a confirmation of intent will be presented to the user. If this method
is invoked via a POST request, the entry wi... | [
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18,015 | caktus/django-timepiece | timepiece/entries/views.py | Dashboard.get_hours_per_week | def get_hours_per_week(self, user=None):
"""Retrieves the number of hours the user should work per week."""
try:
profile = UserProfile.objects.get(user=user or self.user)
except UserProfile.DoesNotExist:
profile = None
return profile.hours_per_week if profile else... | python | def get_hours_per_week(self, user=None):
"""Retrieves the number of hours the user should work per week."""
try:
profile = UserProfile.objects.get(user=user or self.user)
except UserProfile.DoesNotExist:
profile = None
return profile.hours_per_week if profile else... | [
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18,016 | caktus/django-timepiece | timepiece/entries/views.py | ScheduleMixin.get_hours_for_week | def get_hours_for_week(self, week_start=None):
"""
Gets all ProjectHours entries in the 7-day period beginning on
week_start.
"""
week_start = week_start if week_start else self.week_start
week_end = week_start + relativedelta(days=7)
return ProjectHours.objects.... | python | def get_hours_for_week(self, week_start=None):
"""
Gets all ProjectHours entries in the 7-day period beginning on
week_start.
"""
week_start = week_start if week_start else self.week_start
week_end = week_start + relativedelta(days=7)
return ProjectHours.objects.... | [
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18,017 | caktus/django-timepiece | timepiece/entries/views.py | ScheduleView.get_users_from_project_hours | def get_users_from_project_hours(self, project_hours):
"""
Gets a list of the distinct users included in the project hours
entries, ordered by name.
"""
name = ('user__first_name', 'user__last_name')
users = project_hours.values_list('user__id', *name).distinct()\
... | python | def get_users_from_project_hours(self, project_hours):
"""
Gets a list of the distinct users included in the project hours
entries, ordered by name.
"""
name = ('user__first_name', 'user__last_name')
users = project_hours.values_list('user__id', *name).distinct()\
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18,018 | caktus/django-timepiece | timepiece/management/commands/check_entries.py | Command.check_all | def check_all(self, all_entries, *args, **kwargs):
"""
Go through lists of entries, find overlaps among each, return the total
"""
all_overlaps = 0
while True:
try:
user_entries = all_entries.next()
except StopIteration:
ret... | python | def check_all(self, all_entries, *args, **kwargs):
"""
Go through lists of entries, find overlaps among each, return the total
"""
all_overlaps = 0
while True:
try:
user_entries = all_entries.next()
except StopIteration:
ret... | [
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18,019 | caktus/django-timepiece | timepiece/management/commands/check_entries.py | Command.check_entry | def check_entry(self, entries, *args, **kwargs):
"""
With a list of entries, check each entry against every other
"""
verbosity = kwargs.get('verbosity', 1)
user_total_overlaps = 0
user = ''
for index_a, entry_a in enumerate(entries):
# Show the name t... | python | def check_entry(self, entries, *args, **kwargs):
"""
With a list of entries, check each entry against every other
"""
verbosity = kwargs.get('verbosity', 1)
user_total_overlaps = 0
user = ''
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18,020 | caktus/django-timepiece | timepiece/management/commands/check_entries.py | Command.find_start | def find_start(self, **kwargs):
"""
Determine the starting point of the query using CLI keyword arguments
"""
week = kwargs.get('week', False)
month = kwargs.get('month', False)
year = kwargs.get('year', False)
days = kwargs.get('days', 0)
# If no flags ar... | python | def find_start(self, **kwargs):
"""
Determine the starting point of the query using CLI keyword arguments
"""
week = kwargs.get('week', False)
month = kwargs.get('month', False)
year = kwargs.get('year', False)
days = kwargs.get('days', 0)
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18,021 | caktus/django-timepiece | timepiece/management/commands/check_entries.py | Command.find_users | def find_users(self, *args):
"""
Returns the users to search given names as args.
Return all users if there are no args provided.
"""
if args:
names = reduce(lambda query, arg: query |
(Q(first_name__icontains=arg) | Q(last_name__icontains=arg)),
... | python | def find_users(self, *args):
"""
Returns the users to search given names as args.
Return all users if there are no args provided.
"""
if args:
names = reduce(lambda query, arg: query |
(Q(first_name__icontains=arg) | Q(last_name__icontains=arg)),
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18,022 | caktus/django-timepiece | timepiece/management/commands/check_entries.py | Command.find_entries | def find_entries(self, users, start, *args, **kwargs):
"""
Find all entries for all users, from a given starting point.
If no starting point is provided, all entries are returned.
"""
forever = kwargs.get('all', False)
for user in users:
if forever:
... | python | def find_entries(self, users, start, *args, **kwargs):
"""
Find all entries for all users, from a given starting point.
If no starting point is provided, all entries are returned.
"""
forever = kwargs.get('all', False)
for user in users:
if forever:
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18,023 | caktus/django-timepiece | timepiece/utils/views.py | cbv_decorator | def cbv_decorator(function_decorator):
"""Allows a function-based decorator to be used on a CBV."""
def class_decorator(View):
View.dispatch = method_decorator(function_decorator)(View.dispatch)
return View
return class_decorator | python | def cbv_decorator(function_decorator):
"""Allows a function-based decorator to be used on a CBV."""
def class_decorator(View):
View.dispatch = method_decorator(function_decorator)(View.dispatch)
return View
return class_decorator | [
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18,024 | caktus/django-timepiece | timepiece/reports/utils.py | date_totals | def date_totals(entries, by):
"""Yield a user's name and a dictionary of their hours"""
date_dict = {}
for date, date_entries in groupby(entries, lambda x: x['date']):
if isinstance(date, datetime.datetime):
date = date.date()
d_entries = list(date_entries)
if by == 'use... | python | def date_totals(entries, by):
"""Yield a user's name and a dictionary of their hours"""
date_dict = {}
for date, date_entries in groupby(entries, lambda x: x['date']):
if isinstance(date, datetime.datetime):
date = date.date()
d_entries = list(date_entries)
if by == 'use... | [
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18,025 | caktus/django-timepiece | timepiece/reports/utils.py | get_project_totals | def get_project_totals(entries, date_headers, hour_type=None, overtime=False,
total_column=False, by='user'):
"""
Yield hour totals grouped by user and date. Optionally including overtime.
"""
totals = [0 for date in date_headers]
rows = []
for thing, thing_entries in grou... | python | def get_project_totals(entries, date_headers, hour_type=None, overtime=False,
total_column=False, by='user'):
"""
Yield hour totals grouped by user and date. Optionally including overtime.
"""
totals = [0 for date in date_headers]
rows = []
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18,026 | stanfordnlp/stanza | stanza/research/learner.py | Learner.validate | def validate(self, validation_instances, metrics, iteration=None):
'''
Evaluate this model on `validation_instances` during training and
output a report.
:param validation_instances: The data to use to validate the model.
:type validation_instances: list(instance.Instance)
... | python | def validate(self, validation_instances, metrics, iteration=None):
'''
Evaluate this model on `validation_instances` during training and
output a report.
:param validation_instances: The data to use to validate the model.
:type validation_instances: list(instance.Instance)
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18,027 | stanfordnlp/stanza | stanza/research/learner.py | Learner.predict_and_score | def predict_and_score(self, eval_instances, random=False, verbosity=0):
'''
Return most likely outputs and scores for the particular set of
outputs given in `eval_instances`, as a tuple. Return value should
be equivalent to the default implementation of
return (self.predict(... | python | def predict_and_score(self, eval_instances, random=False, verbosity=0):
'''
Return most likely outputs and scores for the particular set of
outputs given in `eval_instances`, as a tuple. Return value should
be equivalent to the default implementation of
return (self.predict(... | [
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18,028 | stanfordnlp/stanza | stanza/research/learner.py | Learner.load | def load(self, infile):
'''
Deserialize a model from a stored file.
By default, unpickle an entire object. If `dump` is overridden to
use a different storage format, `load` should be as well.
:param file outfile: A file-like object from which to retrieve the
seriali... | python | def load(self, infile):
'''
Deserialize a model from a stored file.
By default, unpickle an entire object. If `dump` is overridden to
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18,029 | stanfordnlp/stanza | stanza/research/iterators.py | iter_batches | def iter_batches(iterable, batch_size):
'''
Given a sequence or iterable, yield batches from that iterable until it
runs out. Note that this function returns a generator, and also each
batch will be a generator.
:param iterable: The sequence or iterable to split into batches
:param int batch_si... | python | def iter_batches(iterable, batch_size):
'''
Given a sequence or iterable, yield batches from that iterable until it
runs out. Note that this function returns a generator, and also each
batch will be a generator.
:param iterable: The sequence or iterable to split into batches
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18,030 | stanfordnlp/stanza | stanza/research/iterators.py | gen_batches | def gen_batches(iterable, batch_size):
'''
Returns a generator object that yields batches from `iterable`.
See `iter_batches` for more details and caveats.
Note that `iter_batches` returns an iterator, which never supports `len()`,
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18,031 | stanfordnlp/stanza | stanza/research/instance.py | Instance.inverted | def inverted(self):
'''
Return a version of this instance with inputs replaced by outputs and vice versa.
'''
return Instance(input=self.output, output=self.input,
annotated_input=self.annotated_output,
annotated_output=self.annotated_input... | python | def inverted(self):
'''
Return a version of this instance with inputs replaced by outputs and vice versa.
'''
return Instance(input=self.output, output=self.input,
annotated_input=self.annotated_output,
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18,032 | stanfordnlp/stanza | stanza/util/resource.py | get_data_or_download | def get_data_or_download(dir_name, file_name, url='', size='unknown'):
"""Returns the data. if the data hasn't been downloaded, then first download the data.
:param dir_name: directory to look in
:param file_name: file name to retrieve
:param url: if the file is not found, then download it from this ur... | python | def get_data_or_download(dir_name, file_name, url='', size='unknown'):
"""Returns the data. if the data hasn't been downloaded, then first download the data.
:param dir_name: directory to look in
:param file_name: file name to retrieve
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18,033 | stanfordnlp/stanza | stanza/text/vocab.py | Vocab.add | def add(self, word, count=1):
"""Add a word to the vocabulary and return its index.
:param word: word to add to the dictionary.
:param count: how many times to add the word.
:return: index of the added word.
WARNING: this function assumes that if the Vocab currently has N wor... | python | def add(self, word, count=1):
"""Add a word to the vocabulary and return its index.
:param word: word to add to the dictionary.
:param count: how many times to add the word.
:return: index of the added word.
WARNING: this function assumes that if the Vocab currently has N wor... | [
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18,034 | stanfordnlp/stanza | stanza/text/vocab.py | Vocab.subset | def subset(self, words):
"""Get a new Vocab containing only the specified subset of words.
If w is in words, but not in the original vocab, it will NOT be in the subset vocab.
Indices will be in the order of `words`. Counts from the original vocab are preserved.
:return (Vocab): a new ... | python | def subset(self, words):
"""Get a new Vocab containing only the specified subset of words.
If w is in words, but not in the original vocab, it will NOT be in the subset vocab.
Indices will be in the order of `words`. Counts from the original vocab are preserved.
:return (Vocab): a new ... | [
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18,035 | stanfordnlp/stanza | stanza/text/vocab.py | Vocab._index2word | def _index2word(self):
"""Mapping from indices to words.
WARNING: this may go out-of-date, because it is a copy, not a view into the Vocab.
:return: a list of strings
"""
# TODO(kelvinguu): it would be nice to just use `dict.viewkeys`, but unfortunately those are not indexable
... | python | def _index2word(self):
"""Mapping from indices to words.
WARNING: this may go out-of-date, because it is a copy, not a view into the Vocab.
:return: a list of strings
"""
# TODO(kelvinguu): it would be nice to just use `dict.viewkeys`, but unfortunately those are not indexable
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18,036 | stanfordnlp/stanza | stanza/text/vocab.py | Vocab.from_dict | def from_dict(cls, word2index, unk, counts=None):
"""Create Vocab from an existing string to integer dictionary.
All counts are set to 0.
:param word2index: a dictionary representing a bijection from N words to the integers 0 through N-1.
UNK must be assigned the 0 index.
... | python | def from_dict(cls, word2index, unk, counts=None):
"""Create Vocab from an existing string to integer dictionary.
All counts are set to 0.
:param word2index: a dictionary representing a bijection from N words to the integers 0 through N-1.
UNK must be assigned the 0 index.
... | [
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18,037 | stanfordnlp/stanza | stanza/text/vocab.py | Vocab.to_file | def to_file(self, f):
"""Write vocab to a file.
:param (file) f: a file object, e.g. as returned by calling `open`
File format:
word0<TAB>count0
word1<TAB>count1
...
word with index 0 is on the 0th line and so on...
"""
for word in s... | python | def to_file(self, f):
"""Write vocab to a file.
:param (file) f: a file object, e.g. as returned by calling `open`
File format:
word0<TAB>count0
word1<TAB>count1
...
word with index 0 is on the 0th line and so on...
"""
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18,038 | stanfordnlp/stanza | stanza/text/vocab.py | EmbeddedVocab.backfill_unk_emb | def backfill_unk_emb(self, E, filled_words):
""" Backfills an embedding matrix with the embedding for the unknown token.
:param E: original embedding matrix of dimensions `(vocab_size, emb_dim)`.
:param filled_words: these words will not be backfilled with unk.
NOTE: this function is f... | python | def backfill_unk_emb(self, E, filled_words):
""" Backfills an embedding matrix with the embedding for the unknown token.
:param E: original embedding matrix of dimensions `(vocab_size, emb_dim)`.
:param filled_words: these words will not be backfilled with unk.
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18,039 | stanfordnlp/stanza | stanza/cluster/pick_gpu.py | best_gpu | def best_gpu(max_usage=USAGE_THRESHOLD, verbose=False):
'''
Return the name of a device to use, either 'cpu' or 'gpu0', 'gpu1',...
The least-used GPU with usage under the constant threshold will be chosen;
ties are broken randomly.
'''
try:
proc = subprocess.Popen("nvidia-smi", stdout=su... | python | def best_gpu(max_usage=USAGE_THRESHOLD, verbose=False):
'''
Return the name of a device to use, either 'cpu' or 'gpu0', 'gpu1',...
The least-used GPU with usage under the constant threshold will be chosen;
ties are broken randomly.
'''
try:
proc = subprocess.Popen("nvidia-smi", stdout=su... | [
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18,040 | stanfordnlp/stanza | stanza/research/evaluate.py | evaluate | def evaluate(learner, eval_data, metrics, metric_names=None, split_id=None,
write_data=False):
'''
Evaluate `learner` on the instances in `eval_data` according to each
metric in `metric`, and return a dictionary summarizing the values of
the metrics.
Dump the predictions, scores, and m... | python | def evaluate(learner, eval_data, metrics, metric_names=None, split_id=None,
write_data=False):
'''
Evaluate `learner` on the instances in `eval_data` according to each
metric in `metric`, and return a dictionary summarizing the values of
the metrics.
Dump the predictions, scores, and m... | [
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18,041 | stanfordnlp/stanza | stanza/nlp/protobuf_json.py | json2pb | def json2pb(pb, js, useFieldNumber=False):
''' convert JSON string to google.protobuf.descriptor instance '''
for field in pb.DESCRIPTOR.fields:
if useFieldNumber:
key = field.number
else:
key = field.name
if key not in js:
continue
if field.ty... | python | def json2pb(pb, js, useFieldNumber=False):
''' convert JSON string to google.protobuf.descriptor instance '''
for field in pb.DESCRIPTOR.fields:
if useFieldNumber:
key = field.number
else:
key = field.name
if key not in js:
continue
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18,042 | stanfordnlp/stanza | stanza/nlp/corenlp.py | CoreNLPClient.annotate_json | def annotate_json(self, text, annotators=None):
"""Return a JSON dict from the CoreNLP server, containing annotations of the text.
:param (str) text: Text to annotate.
:param (list[str]) annotators: a list of annotator names
:return (dict): a dict of annotations
"""
# W... | python | def annotate_json(self, text, annotators=None):
"""Return a JSON dict from the CoreNLP server, containing annotations of the text.
:param (str) text: Text to annotate.
:param (list[str]) annotators: a list of annotator names
:return (dict): a dict of annotations
"""
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18,043 | stanfordnlp/stanza | stanza/nlp/corenlp.py | CoreNLPClient.annotate_proto | def annotate_proto(self, text, annotators=None):
"""Return a Document protocol buffer from the CoreNLP server, containing annotations of the text.
:param (str) text: text to be annotated
:param (list[str]) annotators: a list of annotator names
:return (CoreNLP_pb2.Document): a Document... | python | def annotate_proto(self, text, annotators=None):
"""Return a Document protocol buffer from the CoreNLP server, containing annotations of the text.
:param (str) text: text to be annotated
:param (list[str]) annotators: a list of annotator names
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18,044 | stanfordnlp/stanza | stanza/nlp/corenlp.py | CoreNLPClient.annotate | def annotate(self, text, annotators=None):
"""Return an AnnotatedDocument from the CoreNLP server.
:param (str) text: text to be annotated
:param (list[str]) annotators: a list of annotator names
See a list of valid annotator names here:
http://stanfordnlp.github.io/CoreNLP/a... | python | def annotate(self, text, annotators=None):
"""Return an AnnotatedDocument from the CoreNLP server.
:param (str) text: text to be annotated
:param (list[str]) annotators: a list of annotator names
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18,045 | stanfordnlp/stanza | stanza/nlp/corenlp.py | ProtobufBacked.from_pb | def from_pb(cls, pb):
"""Instantiate the object from a protocol buffer.
Args:
pb (protobuf)
Save a reference to the protocol buffer on the object.
"""
obj = cls._from_pb(pb)
obj._pb = pb
return obj | python | def from_pb(cls, pb):
"""Instantiate the object from a protocol buffer.
Args:
pb (protobuf)
Save a reference to the protocol buffer on the object.
"""
obj = cls._from_pb(pb)
obj._pb = pb
return obj | [
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18,046 | stanfordnlp/stanza | stanza/nlp/corenlp.py | AnnotatedEntity.character_span | def character_span(self):
"""
Returns the character span of the token
"""
begin, end = self.token_span
return (self.sentence[begin].character_span[0], self.sentence[end-1].character_span[-1]) | python | def character_span(self):
"""
Returns the character span of the token
"""
begin, end = self.token_span
return (self.sentence[begin].character_span[0], self.sentence[end-1].character_span[-1]) | [
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18,047 | stanfordnlp/stanza | stanza/research/summary_basic.py | TensorBoardLogger.log_proto | def log_proto(self, proto, step_num):
"""Log a Summary protobuf to the event file.
:param proto: a Summary protobuf
:param step_num: the iteration number at which this value was logged
"""
self.summ_writer.add_summary(proto, step_num)
return proto | python | def log_proto(self, proto, step_num):
"""Log a Summary protobuf to the event file.
:param proto: a Summary protobuf
:param step_num: the iteration number at which this value was logged
"""
self.summ_writer.add_summary(proto, step_num)
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18,048 | stanfordnlp/stanza | stanza/research/summary_basic.py | TensorBoardLogger.log | def log(self, key, val, step_num):
"""Directly log a scalar value to the event file.
:param string key: a name for the value
:param val: a float
:param step_num: the iteration number at which this value was logged
"""
try:
ph, summ = self.summaries[key]
... | python | def log(self, key, val, step_num):
"""Directly log a scalar value to the event file.
:param string key: a name for the value
:param val: a float
:param step_num: the iteration number at which this value was logged
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18,049 | stanfordnlp/stanza | stanza/monitoring/summary.py | read_events | def read_events(stream):
'''
Read and return as a generator a sequence of Event protos from
file-like object `stream`.
'''
header_size = struct.calcsize('<QI')
len_size = struct.calcsize('<Q')
footer_size = struct.calcsize('<I')
while True:
header = stream.read(header_size)
... | python | def read_events(stream):
'''
Read and return as a generator a sequence of Event protos from
file-like object `stream`.
'''
header_size = struct.calcsize('<QI')
len_size = struct.calcsize('<Q')
footer_size = struct.calcsize('<I')
while True:
header = stream.read(header_size)
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18,050 | stanfordnlp/stanza | stanza/monitoring/summary.py | write_events | def write_events(stream, events):
'''
Write a sequence of Event protos to file-like object `stream`.
'''
for event in events:
data = event.SerializeToString()
len_field = struct.pack('<Q', len(data))
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data_crc = struct.pac... | python | def write_events(stream, events):
'''
Write a sequence of Event protos to file-like object `stream`.
'''
for event in events:
data = event.SerializeToString()
len_field = struct.pack('<Q', len(data))
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18,051 | stanfordnlp/stanza | stanza/monitoring/summary.py | SummaryWriter.log_image | def log_image(self, step, tag, val):
'''
Write an image event.
:param int step: Time step (x-axis in TensorBoard graphs)
:param str tag: Label for this value
:param numpy.ndarray val: Image in RGB format with values from
0 to 255; a 3-D array with index order (row, c... | python | def log_image(self, step, tag, val):
'''
Write an image event.
:param int step: Time step (x-axis in TensorBoard graphs)
:param str tag: Label for this value
:param numpy.ndarray val: Image in RGB format with values from
0 to 255; a 3-D array with index order (row, c... | [
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18,052 | stanfordnlp/stanza | stanza/monitoring/summary.py | SummaryWriter.log_scalar | def log_scalar(self, step, tag, val):
'''
Write a scalar event.
:param int step: Time step (x-axis in TensorBoard graphs)
:param str tag: Label for this value
:param float val: Scalar to graph at this time step (y-axis)
'''
summary = Summary(value=[Summary.Value(... | python | def log_scalar(self, step, tag, val):
'''
Write a scalar event.
:param int step: Time step (x-axis in TensorBoard graphs)
:param str tag: Label for this value
:param float val: Scalar to graph at this time step (y-axis)
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18,053 | stanfordnlp/stanza | stanza/monitoring/summary.py | SummaryWriter.log_histogram | def log_histogram(self, step, tag, val):
'''
Write a histogram event.
:param int step: Time step (x-axis in TensorBoard graphs)
:param str tag: Label for this value
:param numpy.ndarray val: Arbitrary-dimensional array containing
values to be aggregated in the result... | python | def log_histogram(self, step, tag, val):
'''
Write a histogram event.
:param int step: Time step (x-axis in TensorBoard graphs)
:param str tag: Label for this value
:param numpy.ndarray val: Arbitrary-dimensional array containing
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18,054 | stanfordnlp/stanza | stanza/research/config.py | options | def options(allow_partial=False, read=False):
'''
Get the object containing the values of the parsed command line options.
:param bool allow_partial: If `True`, ignore unrecognized arguments and allow
the options to be re-parsed next time `options` is called. This
also suppresses overwrite ... | python | def options(allow_partial=False, read=False):
'''
Get the object containing the values of the parsed command line options.
:param bool allow_partial: If `True`, ignore unrecognized arguments and allow
the options to be re-parsed next time `options` is called. This
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18,055 | stanfordnlp/stanza | stanza/ml/embeddings.py | Embeddings.inner_products | def inner_products(self, vec):
"""Get the inner product of a vector with every embedding.
:param (np.array) vector: the query vector
:return (list[tuple[str, float]]): a map of embeddings to inner products
"""
products = self.array.dot(vec)
return self._word_to_score(np... | python | def inner_products(self, vec):
"""Get the inner product of a vector with every embedding.
:param (np.array) vector: the query vector
:return (list[tuple[str, float]]): a map of embeddings to inner products
"""
products = self.array.dot(vec)
return self._word_to_score(np... | [
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18,056 | stanfordnlp/stanza | stanza/ml/embeddings.py | Embeddings._word_to_score | def _word_to_score(self, ids, scores):
"""Return a map from each word to its score.
:param (np.array) ids: a vector of word ids
:param (np.array) scores: a vector of scores
:return (dict[unicode, float]): a map from each word (unicode) to its score (float)
"""
# should ... | python | def _word_to_score(self, ids, scores):
"""Return a map from each word to its score.
:param (np.array) ids: a vector of word ids
:param (np.array) scores: a vector of scores
:return (dict[unicode, float]): a map from each word (unicode) to its score (float)
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18,057 | stanfordnlp/stanza | stanza/ml/embeddings.py | Embeddings._init_lsh_forest | def _init_lsh_forest(self):
"""Construct an LSH forest for nearest neighbor search."""
import sklearn.neighbors
lshf = sklearn.neighbors.LSHForest()
lshf.fit(self.array)
return lshf | python | def _init_lsh_forest(self):
"""Construct an LSH forest for nearest neighbor search."""
import sklearn.neighbors
lshf = sklearn.neighbors.LSHForest()
lshf.fit(self.array)
return lshf | [
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18,058 | stanfordnlp/stanza | stanza/ml/embeddings.py | Embeddings.to_dict | def to_dict(self):
"""Convert to dictionary.
:return (dict): A dict mapping from strings to vectors.
"""
d = {}
for word, idx in self.vocab.iteritems():
d[word] = self.array[idx].tolist()
return d | python | def to_dict(self):
"""Convert to dictionary.
:return (dict): A dict mapping from strings to vectors.
"""
d = {}
for word, idx in self.vocab.iteritems():
d[word] = self.array[idx].tolist()
return d | [
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18,059 | stanfordnlp/stanza | stanza/ml/embeddings.py | Embeddings.to_files | def to_files(self, array_file, vocab_file):
"""Write the embedding matrix and the vocab to files.
:param (file) array_file: file to write array to
:param (file) vocab_file: file to write vocab to
"""
logging.info('Writing array...')
np.save(array_file, self.array)
... | python | def to_files(self, array_file, vocab_file):
"""Write the embedding matrix and the vocab to files.
:param (file) array_file: file to write array to
:param (file) vocab_file: file to write vocab to
"""
logging.info('Writing array...')
np.save(array_file, self.array)
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18,060 | stanfordnlp/stanza | stanza/ml/embeddings.py | Embeddings.from_files | def from_files(cls, array_file, vocab_file):
"""Load the embedding matrix and the vocab from files.
:param (file) array_file: file to read array from
:param (file) vocab_file: file to read vocab from
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"""
logging.info('Loading a... | python | def from_files(cls, array_file, vocab_file):
"""Load the embedding matrix and the vocab from files.
:param (file) array_file: file to read array from
:param (file) vocab_file: file to read vocab from
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18,061 | stanfordnlp/stanza | stanza/research/codalab.py | get_uuids | def get_uuids():
"""List all bundle UUIDs in the worksheet."""
result = shell('cl ls -w {} -u'.format(worksheet))
uuids = result.split('\n')
uuids = uuids[1:-1] # trim non uuids
return uuids | python | def get_uuids():
"""List all bundle UUIDs in the worksheet."""
result = shell('cl ls -w {} -u'.format(worksheet))
uuids = result.split('\n')
uuids = uuids[1:-1] # trim non uuids
return uuids | [
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18,062 | stanfordnlp/stanza | stanza/research/codalab.py | open_file | def open_file(uuid, path):
"""Get the raw file content within a particular bundle at a particular path.
Path have no leading slash.
"""
# create temporary file just so we can get an unused file path
f = tempfile.NamedTemporaryFile()
f.close() # close and delete right away
fname = f.... | python | def open_file(uuid, path):
"""Get the raw file content within a particular bundle at a particular path.
Path have no leading slash.
"""
# create temporary file just so we can get an unused file path
f = tempfile.NamedTemporaryFile()
f.close() # close and delete right away
fname = f.... | [
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18,063 | stanfordnlp/stanza | stanza/research/codalab.py | Bundle.load_img | def load_img(self, img_path):
"""
Return an image object that can be immediately plotted with matplotlib
"""
with open_file(self.uuid, img_path) as f:
return mpimg.imread(f) | python | def load_img(self, img_path):
"""
Return an image object that can be immediately plotted with matplotlib
"""
with open_file(self.uuid, img_path) as f:
return mpimg.imread(f) | [
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18,064 | stanfordnlp/stanza | stanza/research/output.py | output_results | def output_results(results, split_id='results', output_stream=None):
'''
Log `results` readably to `output_stream`, with a header
containing `split_id`.
:param results: a dictionary of summary statistics from an evaluation
:type results: dict(str -> object)
:param str split_id: an identifier f... | python | def output_results(results, split_id='results', output_stream=None):
'''
Log `results` readably to `output_stream`, with a header
containing `split_id`.
:param results: a dictionary of summary statistics from an evaluation
:type results: dict(str -> object)
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18,065 | stanfordnlp/stanza | stanza/ml/tensorflow_utils.py | labels_to_onehots | def labels_to_onehots(labels, num_classes):
"""Convert a vector of integer class labels to a matrix of one-hot target vectors.
:param labels: a vector of integer labels, 0 to num_classes. Has shape (batch_size,).
:param num_classes: the total number of classes
:return: has shape (batch_size, num_classe... | python | def labels_to_onehots(labels, num_classes):
"""Convert a vector of integer class labels to a matrix of one-hot target vectors.
:param labels: a vector of integer labels, 0 to num_classes. Has shape (batch_size,).
:param num_classes: the total number of classes
:return: has shape (batch_size, num_classe... | [
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18,066 | stanfordnlp/stanza | stanza/monitoring/progress.py | ProgressMonitor.start_task | def start_task(self, name, size):
'''
Add a task to the stack. If, for example, `name` is `'Iteration'` and
`size` is 10, progress on that task will be shown as
..., Iteration <p> of 10, ...
:param str name: A descriptive name for the type of subtask that is
bei... | python | def start_task(self, name, size):
'''
Add a task to the stack. If, for example, `name` is `'Iteration'` and
`size` is 10, progress on that task will be shown as
..., Iteration <p> of 10, ...
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18,067 | stanfordnlp/stanza | stanza/monitoring/progress.py | ProgressMonitor.progress | def progress(self, p):
'''
Update the current progress on the task at the top of the stack.
:param int p: The current subtask number, between 0 and `size`
(passed to `start_task`), inclusive.
'''
self.task_stack[-1] = self.task_stack[-1]._replace(progress=p)
... | python | def progress(self, p):
'''
Update the current progress on the task at the top of the stack.
:param int p: The current subtask number, between 0 and `size`
(passed to `start_task`), inclusive.
'''
self.task_stack[-1] = self.task_stack[-1]._replace(progress=p)
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18,068 | stanfordnlp/stanza | stanza/monitoring/progress.py | ProgressMonitor.end_task | def end_task(self):
'''
Remove the current task from the stack.
'''
self.progress(self.task_stack[-1].size)
self.task_stack.pop() | python | def end_task(self):
'''
Remove the current task from the stack.
'''
self.progress(self.task_stack[-1].size)
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18,069 | stanfordnlp/stanza | stanza/monitoring/progress.py | ProgressMonitor.progress_report | def progress_report(self, force=False):
'''
Print the current progress.
:param bool force: If `True`, print the report regardless of the
elapsed time since the last progress report.
'''
now = datetime.datetime.now()
if (len(self.task_stack) > 1 or self.task_s... | python | def progress_report(self, force=False):
'''
Print the current progress.
:param bool force: If `True`, print the report regardless of the
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'''
now = datetime.datetime.now()
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18,070 | stanfordnlp/stanza | stanza/text/dataset.py | Dataset.write_conll | def write_conll(self, fname):
"""
Serializes the dataset in CONLL format to fname
"""
if 'label' not in self.fields:
raise InvalidFieldsException("dataset is not in CONLL format: missing label field")
def instance_to_conll(inst):
tab = [v for k, v in inst... | python | def write_conll(self, fname):
"""
Serializes the dataset in CONLL format to fname
"""
if 'label' not in self.fields:
raise InvalidFieldsException("dataset is not in CONLL format: missing label field")
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18,071 | stanfordnlp/stanza | stanza/text/dataset.py | Dataset.convert | def convert(self, converters, in_place=False):
"""
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:param converters: A dictionary specifying the function to apply to each field. If a field is missing from the dictionary, then it will not be transformed.
:param in_place: Whether to perform the... | python | def convert(self, converters, in_place=False):
"""
Applies transformations to the dataset.
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18,072 | stanfordnlp/stanza | stanza/text/dataset.py | Dataset.shuffle | def shuffle(self):
"""
Re-indexes the dataset in random order
:return: the shuffled dataset instance
"""
order = range(len(self))
random.shuffle(order)
for name, data in self.fields.items():
reindexed = []
for _, i in enumerate(order):
... | python | def shuffle(self):
"""
Re-indexes the dataset in random order
:return: the shuffled dataset instance
"""
order = range(len(self))
random.shuffle(order)
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18,073 | stanfordnlp/stanza | stanza/text/dataset.py | Dataset.pad | def pad(cls, sequences, padding, pad_len=None):
"""
Pads a list of sequences such that they form a matrix.
:param sequences: a list of sequences of varying lengths.
:param padding: the value of padded cells.
:param pad_len: the length of the maximum padded sequence.
"""
... | python | def pad(cls, sequences, padding, pad_len=None):
"""
Pads a list of sequences such that they form a matrix.
:param sequences: a list of sequences of varying lengths.
:param padding: the value of padded cells.
:param pad_len: the length of the maximum padded sequence.
"""
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18,074 | stanfordnlp/stanza | stanza/research/metrics.py | bleu | def bleu(eval_data, predictions, scores='ignored', learner='ignored'):
'''
Return corpus-level BLEU score of `predictions` using the `output`
field of the instances in `eval_data` as references. This is returned
as a length-1 list of floats.
This uses the NLTK unsmoothed implementation, which has b... | python | def bleu(eval_data, predictions, scores='ignored', learner='ignored'):
'''
Return corpus-level BLEU score of `predictions` using the `output`
field of the instances in `eval_data` as references. This is returned
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18,075 | stanfordnlp/stanza | stanza/research/metrics.py | squared_error | def squared_error(eval_data, predictions, scores='ignored', learner='ignored'):
'''
Return the squared error of each prediction in `predictions` with respect
to the correct output in `eval_data`.
>>> data = [Instance('input', (0., 0., 1.)),
... Instance('input', (0., 1., 1.)),
... ... | python | def squared_error(eval_data, predictions, scores='ignored', learner='ignored'):
'''
Return the squared error of each prediction in `predictions` with respect
to the correct output in `eval_data`.
>>> data = [Instance('input', (0., 0., 1.)),
... Instance('input', (0., 1., 1.)),
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18,076 | drdoctr/doctr | doctr/local.py | encrypt_variable | def encrypt_variable(variable, build_repo, *, tld='.org', public_key=None,
travis_token=None, **login_kwargs):
"""
Encrypt an environment variable for ``build_repo`` for Travis
``variable`` should be a bytes object, of the form ``b'ENV=value'``.
``build_repo`` is the repo that ``doctr deploy`` wil... | python | def encrypt_variable(variable, build_repo, *, tld='.org', public_key=None,
travis_token=None, **login_kwargs):
"""
Encrypt an environment variable for ``build_repo`` for Travis
``variable`` should be a bytes object, of the form ``b'ENV=value'``.
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18,077 | drdoctr/doctr | doctr/local.py | encrypt_to_file | def encrypt_to_file(contents, filename):
"""
Encrypts ``contents`` and writes it to ``filename``.
``contents`` should be a bytes string. ``filename`` should end with
``.enc``.
Returns the secret key used for the encryption.
Decrypt the file with :func:`doctr.travis.decrypt_file`.
"""
... | python | def encrypt_to_file(contents, filename):
"""
Encrypts ``contents`` and writes it to ``filename``.
``contents`` should be a bytes string. ``filename`` should end with
``.enc``.
Returns the secret key used for the encryption.
Decrypt the file with :func:`doctr.travis.decrypt_file`.
"""
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18,078 | drdoctr/doctr | doctr/local.py | GitHub_login | def GitHub_login(*, username=None, password=None, OTP=None, headers=None):
"""
Login to GitHub.
If no username, password, or OTP (2-factor authentication code) are
provided, they will be requested from the command line.
Returns a dict of kwargs that can be passed to functions that require
auth... | python | def GitHub_login(*, username=None, password=None, OTP=None, headers=None):
"""
Login to GitHub.
If no username, password, or OTP (2-factor authentication code) are
provided, they will be requested from the command line.
Returns a dict of kwargs that can be passed to functions that require
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If no username, password, or OTP (2-factor authentication code) are
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18,079 | drdoctr/doctr | doctr/local.py | GitHub_post | def GitHub_post(data, url, *, auth, headers):
"""
POST the data ``data`` to GitHub.
Returns the json response from the server, or raises on error status.
"""
r = requests.post(url, auth=auth, headers=headers, data=json.dumps(data))
GitHub_raise_for_status(r)
return r.json() | python | def GitHub_post(data, url, *, auth, headers):
"""
POST the data ``data`` to GitHub.
Returns the json response from the server, or raises on error status.
"""
r = requests.post(url, auth=auth, headers=headers, data=json.dumps(data))
GitHub_raise_for_status(r)
return r.json() | [
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18,080 | drdoctr/doctr | doctr/local.py | get_travis_token | def get_travis_token(*, GitHub_token=None, **login_kwargs):
"""
Generate a temporary token for authenticating with Travis
The GitHub token can be passed in to the ``GitHub_token`` keyword
argument. If no token is passed in, a GitHub token is generated
temporarily, and then immediately deleted.
... | python | def get_travis_token(*, GitHub_token=None, **login_kwargs):
"""
Generate a temporary token for authenticating with Travis
The GitHub token can be passed in to the ``GitHub_token`` keyword
argument. If no token is passed in, a GitHub token is generated
temporarily, and then immediately deleted.
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18,081 | drdoctr/doctr | doctr/local.py | generate_GitHub_token | def generate_GitHub_token(*, note="Doctr token for pushing to gh-pages from Travis", scopes=None, **login_kwargs):
"""
Generate a GitHub token for pushing from Travis
The scope requested is public_repo.
If no password or OTP are provided, they will be requested from the
command line.
The toke... | python | def generate_GitHub_token(*, note="Doctr token for pushing to gh-pages from Travis", scopes=None, **login_kwargs):
"""
Generate a GitHub token for pushing from Travis
The scope requested is public_repo.
If no password or OTP are provided, they will be requested from the
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18,082 | drdoctr/doctr | doctr/local.py | delete_GitHub_token | def delete_GitHub_token(token_id, *, auth, headers):
"""Delete a temporary GitHub token"""
r = requests.delete('https://api.github.com/authorizations/{id}'.format(id=token_id), auth=auth, headers=headers)
GitHub_raise_for_status(r) | python | def delete_GitHub_token(token_id, *, auth, headers):
"""Delete a temporary GitHub token"""
r = requests.delete('https://api.github.com/authorizations/{id}'.format(id=token_id), auth=auth, headers=headers)
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18,083 | drdoctr/doctr | doctr/local.py | upload_GitHub_deploy_key | def upload_GitHub_deploy_key(deploy_repo, ssh_key, *, read_only=False,
title="Doctr deploy key for pushing to gh-pages from Travis", **login_kwargs):
"""
Uploads a GitHub deploy key to ``deploy_repo``.
If ``read_only=True``, the deploy_key will not be able to write to the
repo.
"""
DEPLOY_K... | python | def upload_GitHub_deploy_key(deploy_repo, ssh_key, *, read_only=False,
title="Doctr deploy key for pushing to gh-pages from Travis", **login_kwargs):
"""
Uploads a GitHub deploy key to ``deploy_repo``.
If ``read_only=True``, the deploy_key will not be able to write to the
repo.
"""
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18,084 | drdoctr/doctr | doctr/local.py | generate_ssh_key | def generate_ssh_key():
"""
Generates an SSH deploy public and private key.
Returns (private key, public key), a tuple of byte strings.
"""
key = rsa.generate_private_key(
backend=default_backend(),
public_exponent=65537,
key_size=4096
)
private_key = key.privat... | python | def generate_ssh_key():
"""
Generates an SSH deploy public and private key.
Returns (private key, public key), a tuple of byte strings.
"""
key = rsa.generate_private_key(
backend=default_backend(),
public_exponent=65537,
key_size=4096
)
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18,085 | drdoctr/doctr | doctr/local.py | guess_github_repo | def guess_github_repo():
"""
Guesses the github repo for the current directory
Returns False if no guess can be made.
"""
p = subprocess.run(['git', 'ls-remote', '--get-url', 'origin'],
stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=False)
if p.stderr or p.returncode:
ret... | python | def guess_github_repo():
"""
Guesses the github repo for the current directory
Returns False if no guess can be made.
"""
p = subprocess.run(['git', 'ls-remote', '--get-url', 'origin'],
stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=False)
if p.stderr or p.returncode:
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18,086 | drdoctr/doctr | doctr/__main__.py | get_config | def get_config():
"""
This load some configuration from the ``.travis.yml``, if file is present,
``doctr`` key if present.
"""
p = Path('.travis.yml')
if not p.exists():
return {}
with p.open() as f:
travis_config = yaml.safe_load(f.read())
config = travis_config.get('do... | python | def get_config():
"""
This load some configuration from the ``.travis.yml``, if file is present,
``doctr`` key if present.
"""
p = Path('.travis.yml')
if not p.exists():
return {}
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travis_config = yaml.safe_load(f.read())
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] | 0f19ff78c8239efcc98d417f36b0a31d9be01ba5 | https://github.com/drdoctr/doctr/blob/0f19ff78c8239efcc98d417f36b0a31d9be01ba5/doctr/__main__.py#L219-L234 |
18,087 | drdoctr/doctr | doctr/travis.py | decrypt_file | def decrypt_file(file, key):
"""
Decrypts the file ``file``.
The encrypted file is assumed to end with the ``.enc`` extension. The
decrypted file is saved to the same location without the ``.enc``
extension.
The permissions on the decrypted file are automatically set to 0o600.
See also :f... | python | def decrypt_file(file, key):
"""
Decrypts the file ``file``.
The encrypted file is assumed to end with the ``.enc`` extension. The
decrypted file is saved to the same location without the ``.enc``
extension.
The permissions on the decrypted file are automatically set to 0o600.
See also :f... | [
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The permissions on the decrypted file are automatically set to 0o600.
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18,088 | drdoctr/doctr | doctr/travis.py | setup_deploy_key | def setup_deploy_key(keypath='github_deploy_key', key_ext='.enc', env_name='DOCTR_DEPLOY_ENCRYPTION_KEY'):
"""
Decrypts the deploy key and configures it with ssh
The key is assumed to be encrypted as keypath + key_ext, and the
encryption key is assumed to be set in the environment variable
``env_na... | python | def setup_deploy_key(keypath='github_deploy_key', key_ext='.enc', env_name='DOCTR_DEPLOY_ENCRYPTION_KEY'):
"""
Decrypts the deploy key and configures it with ssh
The key is assumed to be encrypted as keypath + key_ext, and the
encryption key is assumed to be set in the environment variable
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18,089 | drdoctr/doctr | doctr/travis.py | get_token | def get_token():
"""
Get the encrypted GitHub token in Travis.
Make sure the contents this variable do not leak. The ``run()`` function
will remove this from the output, so always use it.
"""
token = os.environ.get("GH_TOKEN", None)
if not token:
token = "GH_TOKEN environment variab... | python | def get_token():
"""
Get the encrypted GitHub token in Travis.
Make sure the contents this variable do not leak. The ``run()`` function
will remove this from the output, so always use it.
"""
token = os.environ.get("GH_TOKEN", None)
if not token:
token = "GH_TOKEN environment variab... | [
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18,090 | drdoctr/doctr | doctr/travis.py | run | def run(args, shell=False, exit=True):
"""
Run the command ``args``.
Automatically hides the secret GitHub token from the output.
If shell=False (recommended for most commands), args should be a list of
strings. If shell=True, args should be a string of the command to run.
If exit=True, it ex... | python | def run(args, shell=False, exit=True):
"""
Run the command ``args``.
Automatically hides the secret GitHub token from the output.
If shell=False (recommended for most commands), args should be a list of
strings. If shell=True, args should be a string of the command to run.
If exit=True, it ex... | [
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18,091 | drdoctr/doctr | doctr/travis.py | get_current_repo | def get_current_repo():
"""
Get the GitHub repo name for the current directory.
Assumes that the repo is in the ``origin`` remote.
"""
remote_url = subprocess.check_output(['git', 'config', '--get',
'remote.origin.url']).decode('utf-8')
# Travis uses the https clone url
_, org, git... | python | def get_current_repo():
"""
Get the GitHub repo name for the current directory.
Assumes that the repo is in the ``origin`` remote.
"""
remote_url = subprocess.check_output(['git', 'config', '--get',
'remote.origin.url']).decode('utf-8')
# Travis uses the https clone url
_, org, git... | [
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18,092 | drdoctr/doctr | doctr/travis.py | get_travis_branch | def get_travis_branch():
"""Get the name of the branch that the PR is from.
Note that this is not simply ``$TRAVIS_BRANCH``. the ``push`` build will
use the correct branch (the branch that the PR is from) but the ``pr``
build will use the _target_ of the PR (usually master). So instead, we ask
for ... | python | def get_travis_branch():
"""Get the name of the branch that the PR is from.
Note that this is not simply ``$TRAVIS_BRANCH``. the ``push`` build will
use the correct branch (the branch that the PR is from) but the ``pr``
build will use the _target_ of the PR (usually master). So instead, we ask
for ... | [
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18,093 | drdoctr/doctr | doctr/travis.py | set_git_user_email | def set_git_user_email():
"""
Set global user and email for git user if not already present on system
"""
username = subprocess.run(shlex.split('git config user.name'), stdout=subprocess.PIPE).stdout.strip().decode('utf-8')
if not username or username == "Travis CI User":
run(['git', 'config... | python | def set_git_user_email():
"""
Set global user and email for git user if not already present on system
"""
username = subprocess.run(shlex.split('git config user.name'), stdout=subprocess.PIPE).stdout.strip().decode('utf-8')
if not username or username == "Travis CI User":
run(['git', 'config... | [
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18,094 | drdoctr/doctr | doctr/travis.py | checkout_deploy_branch | def checkout_deploy_branch(deploy_branch, canpush=True):
"""
Checkout the deploy branch, creating it if it doesn't exist.
"""
# Create an empty branch with .nojekyll if it doesn't already exist
create_deploy_branch(deploy_branch, push=canpush)
remote_branch = "doctr_remote/{}".format(deploy_bran... | python | def checkout_deploy_branch(deploy_branch, canpush=True):
"""
Checkout the deploy branch, creating it if it doesn't exist.
"""
# Create an empty branch with .nojekyll if it doesn't already exist
create_deploy_branch(deploy_branch, push=canpush)
remote_branch = "doctr_remote/{}".format(deploy_bran... | [
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18,095 | drdoctr/doctr | doctr/travis.py | deploy_branch_exists | def deploy_branch_exists(deploy_branch):
"""
Check if there is a remote branch with name specified in ``deploy_branch``.
Note that default ``deploy_branch`` is ``gh-pages`` for regular repos and
``master`` for ``github.io`` repos.
This isn't completely robust. If there are multiple remotes and you... | python | def deploy_branch_exists(deploy_branch):
"""
Check if there is a remote branch with name specified in ``deploy_branch``.
Note that default ``deploy_branch`` is ``gh-pages`` for regular repos and
``master`` for ``github.io`` repos.
This isn't completely robust. If there are multiple remotes and you... | [
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18,096 | drdoctr/doctr | doctr/travis.py | create_deploy_branch | def create_deploy_branch(deploy_branch, push=True):
"""
If there is no remote branch with name specified in ``deploy_branch``,
create one.
Note that default ``deploy_branch`` is ``gh-pages`` for regular
repos and ``master`` for ``github.io`` repos.
Return True if ``deploy_branch`` was created,... | python | def create_deploy_branch(deploy_branch, push=True):
"""
If there is no remote branch with name specified in ``deploy_branch``,
create one.
Note that default ``deploy_branch`` is ``gh-pages`` for regular
repos and ``master`` for ``github.io`` repos.
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18,097 | drdoctr/doctr | doctr/travis.py | find_sphinx_build_dir | def find_sphinx_build_dir():
"""
Find build subfolder within sphinx docs directory.
This is called by :func:`commit_docs` if keyword arg ``built_docs`` is not
specified on the command line.
"""
build = glob.glob('**/*build/html', recursive=True)
if not build:
raise RuntimeError("Cou... | python | def find_sphinx_build_dir():
"""
Find build subfolder within sphinx docs directory.
This is called by :func:`commit_docs` if keyword arg ``built_docs`` is not
specified on the command line.
"""
build = glob.glob('**/*build/html', recursive=True)
if not build:
raise RuntimeError("Cou... | [
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18,098 | drdoctr/doctr | doctr/travis.py | copy_to_tmp | def copy_to_tmp(source):
"""
Copies ``source`` to a temporary directory, and returns the copied
location.
If source is a file, the copied location is also a file.
"""
tmp_dir = tempfile.mkdtemp()
# Use pathlib because os.path.basename is different depending on whether
# the path ends in... | python | def copy_to_tmp(source):
"""
Copies ``source`` to a temporary directory, and returns the copied
location.
If source is a file, the copied location is also a file.
"""
tmp_dir = tempfile.mkdtemp()
# Use pathlib because os.path.basename is different depending on whether
# the path ends in... | [
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18,099 | drdoctr/doctr | doctr/travis.py | is_subdir | def is_subdir(a, b):
"""
Return true if a is a subdirectory of b
"""
a, b = map(os.path.abspath, [a, b])
return os.path.commonpath([a, b]) == b | python | def is_subdir(a, b):
"""
Return true if a is a subdirectory of b
"""
a, b = map(os.path.abspath, [a, b])
return os.path.commonpath([a, b]) == b | [
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