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1 | preprocess_input | def preprocess_input(x, data_format=None):
return x
@keras_export("keras.applications.efficientnet_v2.decode_predictions") | 3613c3defc39c236fb1592c4f7ba1a9cc887343a | @keras_export("keras.applications.efficientnet_v2.decode_predictions") | 7 | efficientnet_v2.py | 32 | Remove pylint comments.
PiperOrigin-RevId: 452353044 | 82,629 | 1 | 11 | 12 | 6 | 278,616 | 6 | keras | 4 | keras/applications/efficientnet_v2.py | Python | 2 | {
"docstring": "A placeholder method for backward compatibility.\n\n The preprocessing logic has been included in the EfficientNetV2 model\n implementation. Users are no longer required to call this method to\n normalize the input data. This method does nothing and only kept as a\n placeholder to align the API surface between old and new version of model.\n\n Args:\n x: A floating point `numpy.array` or a `tf.Tensor`.\n data_format: Optional data format of the image tensor/array. Defaults to\n None, in which case the global setting\n `tf.keras.backend.image_data_format()` is used (unless you changed it,\n it defaults to \"channels_last\").{mode}\n\n Returns:\n Unchanged `numpy.array` or `tf.Tensor`.\n ",
"language": "en",
"n_whitespaces": 152,
"n_words": 95,
"vocab_size": 76
} | https://github.com/keras-team/keras.git |
2 | make_increasing_ohlc | def make_increasing_ohlc(open, high, low, close, dates, **kwargs):
(flat_increase_x, flat_increase_y, text_increase) = _OHLC(
open, high, low, close, dates
).get_increase()
if "name" in kwargs:
showlegend = True
else:
kwargs.setdefault("name", "Increasing")
showlegend = False
kwargs.setdefault("line", dict(color=_DEFAULT_INCREASING_COLOR, width=1))
kwargs.setdefault("text", text_increase)
ohlc_incr = dict(
type="scatter",
x=flat_increase_x,
y=flat_increase_y,
mode="lines",
showlegend=showlegend,
**kwargs,
)
return ohlc_incr
| 43e3a4011080911901176aab919c0ecf5046ddd3 | 11 | _ohlc.py | 183 | switch to black .22 | 57,818 | 0 | 148 | 117 | 39 | 226,144 | 48 | plotly.py | 23 | packages/python/plotly/plotly/figure_factory/_ohlc.py | Python | 20 | {
"docstring": "\n Makes increasing ohlc sticks\n\n _make_increasing_ohlc() and _make_decreasing_ohlc separate the\n increasing trace from the decreasing trace so kwargs (such as\n color) can be passed separately to increasing or decreasing traces\n when direction is set to 'increasing' or 'decreasing' in\n FigureFactory.create_candlestick()\n\n :param (list) open: opening values\n :param (list) high: high values\n :param (list) low: low values\n :param (list) close: closing values\n :param (list) dates: list of datetime objects. Default: None\n :param kwargs: kwargs to be passed to increasing trace via\n plotly.graph_objs.Scatter.\n\n :rtype (trace) ohlc_incr_data: Scatter trace of all increasing ohlc\n sticks.\n ",
"language": "en",
"n_whitespaces": 146,
"n_words": 89,
"vocab_size": 59
} | https://github.com/plotly/plotly.py.git |
|
1 | test_tags_help_text_no_spaces_allowed | def test_tags_help_text_no_spaces_allowed(self):
widget = widgets.AdminTagWidget()
help_text = widget.get_context(None, None, {})["widget"]["help_text"]
html = widget.render("tags", None, {})
help_text_html_element = self.get_help_text_html_element(html)
self.assertEqual(
help_text, "Tags can only consist of a single word, no spaces allowed."
)
self.assertHTMLEqual(
help_text_html_element,
% help_text,
)
| 1822d7eee23cf5fceff8b1f58f3ca2f0a32c6e34 | 11 | test_widgets.py | 122 | display help text message for tag field
- resolves #1874
- ensure message is dynamic based on the setting TAG_SPACES_ALLOWED
- Update wagtail/admin/templates/wagtailadmin/widgets/tag_widget.html | 16,621 | 0 | 134 | 72 | 31 | 77,079 | 37 | wagtail | 13 | wagtail/admin/tests/test_widgets.py | Python | 12 | {
"docstring": "Checks that the tags help text html element content is correct when TAG_SPACES_ALLOWED is False<p class=\"help\">%s</p>",
"language": "en",
"n_whitespaces": 15,
"n_words": 16,
"vocab_size": 15
} | https://github.com/wagtail/wagtail.git |
|
3 | handle_template_exception | def handle_template_exception(ex, field):
if ex.args and ex.args[0].startswith("UndefinedError: 'None' has no attribute"):
# Common during HA startup - so just a warning
_LOGGER.warning(ex)
return
_LOGGER.error("Error parsing template for field %s", field, exc_info=ex)
| 73a368c24246b081cdb98923ca3180937d436c3b | 10 | helpers.py | 75 | Refactor history_stats to minimize database access (part 2) (#70255) | 95,827 | 0 | 85 | 44 | 31 | 296,853 | 31 | core | 9 | homeassistant/components/history_stats/helpers.py | Python | 5 | {
"docstring": "Log an error nicely if the template cannot be interpreted.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/home-assistant/core.git |
|
3 | find_profile_dir_by_name | def find_profile_dir_by_name(cls, ipython_dir, name=u'default', config=None):
dirname = u'profile_' + name
paths = [ipython_dir]
for p in paths:
profile_dir = os.path.join(p, dirname)
if os.path.isdir(profile_dir):
return cls(location=profile_dir, config=config)
else:
raise ProfileDirError('Profile directory not found in paths: %s' % dirname)
| 1ec91ebf328bdf3450130de4b4604c79dc1e19d9 | 12 | profiledir.py | 119 | FIX CVE-2022-21699
See https://github.com/ipython/ipython/security/advisories/GHSA-pq7m-3gw7-gq5x | 52,335 | 0 | 120 | 75 | 32 | 208,471 | 37 | ipython | 15 | IPython/core/profiledir.py | Python | 9 | {
"docstring": "Find an existing profile dir by profile name, return its ProfileDir.\n\n This searches through a sequence of paths for a profile dir. If it\n is not found, a :class:`ProfileDirError` exception will be raised.\n\n The search path algorithm is:\n 1. ``os.getcwd()`` # removed for security reason.\n 2. ``ipython_dir``\n\n Parameters\n ----------\n ipython_dir : unicode or str\n The IPython directory to use.\n name : unicode or str\n The name of the profile. The name of the profile directory\n will be \"profile_<profile>\".\n ",
"language": "en",
"n_whitespaces": 183,
"n_words": 78,
"vocab_size": 57
} | https://github.com/ipython/ipython.git |
|
11 | add_dep_paths | def add_dep_paths():
paths = []
if old_deps is not None:
for importer, modname, ispkg in pkgutil.iter_modules(
old_deps.__path__):
if not ispkg:
continue
try:
mod = importer.find_module(modname).load_module(modname)
except ImportError as e:
logging.warning(f"deps: Error importing dependency: {e}")
continue
if hasattr(mod, 'dep_bins'):
paths.extend(mod.dep_bins)
sys.path.extend(paths)
if kivy_deps is None:
return
paths = []
for importer, modname, ispkg in pkgutil.iter_modules(kivy_deps.__path__):
if not ispkg:
continue
try:
mod = importer.find_module(modname).load_module(modname)
except ImportError as e:
logging.warning(f"deps: Error importing dependency: {e}")
continue
if hasattr(mod, 'dep_bins'):
paths.extend(mod.dep_bins)
sys.path.extend(paths)
| e6c144b5423dada62fd13034c2d40bf48a2bc423 | 16 | __init__.py | 293 | Replace deprecated logging.warn with logging.warning (#7906) | 47,008 | 0 | 332 | 171 | 38 | 194,585 | 77 | kivy | 22 | kivy/tools/packaging/pyinstaller_hooks/__init__.py | Python | 29 | {
"docstring": "Should be called by the hook. It adds the paths with the binary\n dependencies to the system path so that pyinstaller can find the binaries\n during its crawling stage.\n ",
"language": "en",
"n_whitespaces": 38,
"n_words": 29,
"vocab_size": 25
} | https://github.com/kivy/kivy.git |
|
4 | _ln_exp_bound | def _ln_exp_bound(self):
# for 0.1 <= x <= 10 we use the inequalities 1-1/x <= ln(x) <= x-1
adj = self._exp + len(self._int) - 1
if adj >= 1:
# argument >= 10; we use 23/10 = 2.3 as a lower bound for ln(10)
return len(str(adj*23//10)) - 1
if adj <= -2:
# argument <= 0.1
return len(str((-1-adj)*23//10)) - 1
op = _WorkRep(self)
c, e = op.int, op.exp
if adj == 0:
# 1 < self < 10
num = str(c-10**-e)
den = str(c)
return len(num) - len(den) - (num < den)
# adj == -1, 0.1 <= self < 1
return e + len(str(10**-e - c)) - 1
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 17 | _pydecimal.py | 225 | add python 3.10.4 for windows | 55,682 | 0 | 267 | 126 | 59 | 219,652 | 109 | XX-Net | 15 | python3.10.4/Lib/_pydecimal.py | Python | 13 | {
"docstring": "Compute a lower bound for the adjusted exponent of self.ln().\n In other words, compute r such that self.ln() >= 10**r. Assumes\n that self is finite and positive and that self != 1.\n ",
"language": "en",
"n_whitespaces": 54,
"n_words": 32,
"vocab_size": 28
} | https://github.com/XX-net/XX-Net.git |
|
1 | test_orderline_query | def test_orderline_query(staff_api_client, permission_manage_orders, fulfilled_order):
order = fulfilled_order
query =
line = order.lines.first()
metadata_key = "md key"
metadata_value = "md value"
line.store_value_in_private_metadata({metadata_key: metadata_value})
line.store_value_in_metadata({metadata_key: metadata_value})
line.save()
staff_api_client.user.user_permissions.add(permission_manage_orders)
response = staff_api_client.post_graphql(query)
content = get_graphql_content(response)
order_data = content["data"]["orders"]["edges"][0]["node"]
first_order_data_line = order_data["lines"][0]
variant_id = graphene.Node.to_global_id("ProductVariant", line.variant.pk)
assert first_order_data_line["thumbnail"] is None
assert first_order_data_line["variant"]["id"] == variant_id
assert first_order_data_line["quantity"] == line.quantity
assert first_order_data_line["unitPrice"]["currency"] == line.unit_price.currency
assert first_order_data_line["metadata"] == [
{"key": metadata_key, "value": metadata_value}
]
assert first_order_data_line["privateMetadata"] == [
{"key": metadata_key, "value": metadata_value}
]
expected_unit_price = Money(
amount=str(first_order_data_line["unitPrice"]["gross"]["amount"]),
currency="USD",
)
assert first_order_data_line["totalPrice"]["currency"] == line.unit_price.currency
assert expected_unit_price == line.unit_price.gross
expected_total_price = Money(
amount=str(first_order_data_line["totalPrice"]["gross"]["amount"]),
currency="USD",
)
assert expected_total_price == line.unit_price.gross * line.quantity
allocation = line.allocations.first()
allocation_id = graphene.Node.to_global_id("Allocation", allocation.pk)
warehouse_id = graphene.Node.to_global_id(
"Warehouse", allocation.stock.warehouse.pk
)
assert first_order_data_line["allocations"] == [
{
"id": allocation_id,
"quantity": allocation.quantity_allocated,
"warehouse": {"id": warehouse_id},
}
]
| a68553e1a55e3a1bd32826cdce294d27f74175e9 | 15 | test_order.py | 595 | Metadata added to checkout and order lines (#10040)
* Metadata added to checkout and order lines
* CHANGELOG.md update
* Missing tests added | 5,130 | 0 | 330 | 349 | 78 | 27,800 | 129 | saleor | 45 | saleor/graphql/order/tests/test_order.py | Python | 93 | {
"docstring": "\n query OrdersQuery {\n orders(first: 1) {\n edges {\n node {\n lines {\n thumbnail(size: 540) {\n url\n }\n variant {\n id\n }\n quantity\n allocations {\n id\n quantity\n warehouse {\n id\n }\n }\n unitPrice {\n currency\n gross {\n amount\n }\n }\n totalPrice {\n currency\n gross {\n amount\n }\n }\n metadata {\n key\n value\n }\n privateMetadata {\n key\n value\n }\n }\n }\n }\n }\n }\n ",
"language": "en",
"n_whitespaces": 1222,
"n_words": 62,
"vocab_size": 26
} | https://github.com/saleor/saleor.git |
|
1 | test_login_view | def test_login_view(self):
# Get login page
response = self.client.get(reverse("wagtailadmin_login"))
# Check that the user received a login page
self.assertEqual(response.status_code, 200)
self.assertTemplateUsed(response, "wagtailadmin/login.html")
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 11 | test_account_management.py | 67 | Reformat with black | 15,736 | 0 | 64 | 37 | 19 | 71,769 | 22 | wagtail | 9 | wagtail/admin/tests/test_account_management.py | Python | 4 | {
"docstring": "\n This tests that the login view responds with a login page\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 11,
"vocab_size": 10
} | https://github.com/wagtail/wagtail.git |
|
8 | construct_change_message | def construct_change_message(form, formsets, add):
# Evaluating `form.changed_data` prior to disabling translations is required
# to avoid fields affected by localization from being included incorrectly,
# e.g. where date formats differ such as MM/DD/YYYY vs DD/MM/YYYY.
changed_data = form.changed_data
with translation_override(None):
# Deactivate translations while fetching verbose_name for form
# field labels and using `field_name`, if verbose_name is not provided.
# Translations will happen later on LogEntry access.
changed_field_labels = _get_changed_field_labels_from_form(form, changed_data)
change_message = []
if add:
change_message.append({"added": {}})
elif form.changed_data:
change_message.append({"changed": {"fields": changed_field_labels}})
if formsets:
with translation_override(None):
for formset in formsets:
for added_object in formset.new_objects:
change_message.append(
{
"added": {
"name": str(added_object._meta.verbose_name),
"object": str(added_object),
}
}
)
for changed_object, changed_fields in formset.changed_objects:
change_message.append(
{
"changed": {
"name": str(changed_object._meta.verbose_name),
"object": str(changed_object),
"fields": _get_changed_field_labels_from_form(
formset.forms[0], changed_fields
),
}
}
)
for deleted_object in formset.deleted_objects:
change_message.append(
{
"deleted": {
"name": str(deleted_object._meta.verbose_name),
"object": str(deleted_object),
}
}
)
return change_message
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 23 | utils.py | 352 | Refs #33476 -- Reformatted code with Black. | 50,436 | 0 | 979 | 206 | 101 | 203,539 | 144 | django | 22 | django/contrib/admin/utils.py | Python | 43 | {
"docstring": "\n Construct a JSON structure describing changes from a changed object.\n Translations are deactivated so that strings are stored untranslated.\n Translation happens later on LogEntry access.\n ",
"language": "en",
"n_whitespaces": 38,
"n_words": 25,
"vocab_size": 23
} | https://github.com/django/django.git |
|
9 | split_header_words | def split_header_words(header_values):
r
assert not isinstance(header_values, str)
result = []
for text in header_values:
orig_text = text
pairs = []
while text:
m = HEADER_TOKEN_RE.search(text)
if m:
text = unmatched(m)
name = m.group(1)
m = HEADER_QUOTED_VALUE_RE.search(text)
if m: # quoted value
text = unmatched(m)
value = m.group(1)
value = HEADER_ESCAPE_RE.sub(r"\1", value)
else:
m = HEADER_VALUE_RE.search(text)
if m: # unquoted value
text = unmatched(m)
value = m.group(1)
value = value.rstrip()
else:
# no value, a lone token
value = None
pairs.append((name, value))
elif text.lstrip().startswith(","):
# concatenated headers, as per RFC 2616 section 4.2
text = text.lstrip()[1:]
if pairs: result.append(pairs)
pairs = []
else:
# skip junk
non_junk, nr_junk_chars = re.subn(r"^[=\s;]*", "", text)
assert nr_junk_chars > 0, (
"split_header_words bug: '%s', '%s', %s" %
(orig_text, text, pairs))
text = non_junk
if pairs: result.append(pairs)
return result
HEADER_JOIN_ESCAPE_RE = re.compile(r"([\"\\])") | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 19 | cookiejar.py | 392 | add python 3.10.4 for windows | 54,932 | 0 | 700 | 227 | 78 | 217,784 | 136 | XX-Net | 29 | python3.10.4/Lib/http/cookiejar.py | Python | 81 | {
"docstring": "Parse header values into a list of lists containing key,value pairs.\n\n The function knows how to deal with \",\", \";\" and \"=\" as well as quoted\n values after \"=\". A list of space separated tokens are parsed as if they\n were separated by \";\".\n\n If the header_values passed as argument contains multiple values, then they\n are treated as if they were a single value separated by comma \",\".\n\n This means that this function is useful for parsing header fields that\n follow this syntax (BNF as from the HTTP/1.1 specification, but we relax\n the requirement for tokens).\n\n headers = #header\n header = (token | parameter) *( [\";\"] (token | parameter))\n\n token = 1*<any CHAR except CTLs or separators>\n separators = \"(\" | \")\" | \"<\" | \">\" | \"@\"\n | \",\" | \";\" | \":\" | \"\\\" | <\">\n | \"/\" | \"[\" | \"]\" | \"?\" | \"=\"\n | \"{\" | \"}\" | SP | HT\n\n quoted-string = ( <\"> *(qdtext | quoted-pair ) <\"> )\n qdtext = <any TEXT except <\">>\n quoted-pair = \"\\\" CHAR\n\n parameter = attribute \"=\" value\n attribute = token\n value = token | quoted-string\n\n Each header is represented by a list of key/value pairs. The value for a\n simple token (not part of a parameter) is None. Syntactically incorrect\n headers will not necessarily be parsed as you would want.\n\n This is easier to describe with some examples:\n\n >>> split_header_words(['foo=\"bar\"; port=\"80,81\"; discard, bar=baz'])\n [[('foo', 'bar'), ('port', '80,81'), ('discard', None)], [('bar', 'baz')]]\n >>> split_header_words(['text/html; charset=\"iso-8859-1\"'])\n [[('text/html', None), ('charset', 'iso-8859-1')]]\n >>> split_header_words([r'Basic realm=\"\\\"foo\\bar\\\"\"'])\n [[('Basic', None), ('realm', '\"foobar\"')]]\n\n ",
"language": "en",
"n_whitespaces": 527,
"n_words": 259,
"vocab_size": 161
} | https://github.com/XX-net/XX-Net.git |
|
2 | reparse | def reparse(self) -> None:
# Do this in a fresh Stylesheet so if there are errors we don't break self.
stylesheet = Stylesheet(variables=self.variables)
for css, path in self.source:
stylesheet.parse(css, path=path)
self._clone(stylesheet)
| e8636d0d86e596690647564b84a68d5e6d107dd0 | 10 | stylesheet.py | 71 | css reparse | 43,963 | 0 | 77 | 43 | 30 | 182,783 | 31 | textual | 10 | src/textual/css/stylesheet.py | Python | 12 | {
"docstring": "Re-parse source, applying new variables.\n\n Raises:\n StylesheetError: If the CSS could not be read.\n StylesheetParseError: If the CSS is invalid.\n\n ",
"language": "en",
"n_whitespaces": 56,
"n_words": 20,
"vocab_size": 17
} | https://github.com/Textualize/textual.git |
|
3 | _get_feature_encoder_or_decoder | def _get_feature_encoder_or_decoder(feature):
if DECODER in feature:
return feature[DECODER]
elif ENCODER in feature:
return feature[ENCODER]
else:
feature[ENCODER] = {}
return feature[ENCODER]
| 60197fe851aadfa51d18c16dd42b49f728ed7eaa | 10 | dataset_synthesizer.py | 65 | Adds registry to organize backward compatibility updates around versions and config sections (#2335)
* First pass implementation of VersionTransformation
* Remove test main.
* Refactors backward_compatibility.py to use version registration system
* Changed sort order to process outer first.
* Moves test_deprecated_field_aliases from test_defaults.py to test_backward_compatibility.py
* s/prefix/prefixes in test_version_transformation.py
* Removes comment, print statements.
* Adds docstrings.
* typo fix.
* Removes unused import.
* Small cleanup to backward_compatibility.py, removed redundant keys.
* Assume version 0.4 if no version present in the config.
* Updates dataset synthesis to work with nested encoder/decoders.
* Fixes test_server.py
* nesting image feature params in test_ray
* _get_feature_encoder_or_decoder in generate_category.
* oops, forgot random.choice.
Co-authored-by: Daniel Treiman <daniel@predibase.com> | 1,274 | 0 | 60 | 40 | 14 | 7,812 | 20 | ludwig | 4 | ludwig/data/dataset_synthesizer.py | Python | 8 | {
"docstring": "Returns the nested decoder or encoder dictionary for a feature.\n\n If neither encoder nor decoder is present, creates an empty encoder dict and returns it.\n ",
"language": "en",
"n_whitespaces": 31,
"n_words": 25,
"vocab_size": 22
} | https://github.com/ludwig-ai/ludwig.git |
|
1 | test_ContinuousSelector_4 | def test_ContinuousSelector_4():
cs = ContinuousSelector()
assert_raises(ValueError, cs.transform, iris_data[0:10,:])
| 388616b6247ca4ea8de4e2f340d6206aee523541 | 9 | feature_transformers_tests.py | 45 | Revert "Deployed 7ccda9a with MkDocs version: 1.3.0"
This reverts commit bd9629c40e01241766197119b581a99409b07068. | 43,430 | 0 | 17 | 27 | 8 | 181,642 | 8 | tpot | 7 | tests/feature_transformers_tests.py | Python | 3 | {
"docstring": "Assert that ContinuousSelector rasies ValueError without categorical features.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/EpistasisLab/tpot.git |
|
6 | dpm_solver_first_update | def dpm_solver_first_update(self, x, s, t, model_s=None, return_intermediate=False):
ns = self.noise_schedule
dims = x.dim()
lambda_s, lambda_t = ns.marginal_lambda(s), ns.marginal_lambda(t)
h = lambda_t - lambda_s
log_alpha_s, log_alpha_t = ns.marginal_log_mean_coeff(s), ns.marginal_log_mean_coeff(t)
sigma_s, sigma_t = ns.marginal_std(s), ns.marginal_std(t)
alpha_t = torch.exp(log_alpha_t)
if self.predict_x0:
phi_1 = torch.expm1(-h)
if model_s is None:
model_s = self.model_fn(x, s)
x_t = (
expand_dims(sigma_t / sigma_s, dims) * x
- expand_dims(alpha_t * phi_1, dims) * model_s
)
if return_intermediate:
return x_t, {'model_s': model_s}
else:
return x_t
else:
phi_1 = torch.expm1(h)
if model_s is None:
model_s = self.model_fn(x, s)
x_t = (
expand_dims(torch.exp(log_alpha_t - log_alpha_s), dims) * x
- expand_dims(sigma_t * phi_1, dims) * model_s
)
if return_intermediate:
return x_t, {'model_s': model_s}
else:
return x_t
| ca86da3a30c4e080d4db8c25fca73de843663cb4 | 17 | dpm_solver.py | 371 | release more models | 36,909 | 0 | 481 | 235 | 57 | 157,369 | 113 | stablediffusion | 30 | ldm/models/diffusion/dpm_solver/dpm_solver.py | Python | 32 | {
"docstring": "\n DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`.\n Args:\n x: A pytorch tensor. The initial value at time `s`.\n s: A pytorch tensor. The starting time, with the shape (x.shape[0],).\n t: A pytorch tensor. The ending time, with the shape (x.shape[0],).\n model_s: A pytorch tensor. The model function evaluated at time `s`.\n If `model_s` is None, we evaluate the model by `x` and `s`; otherwise we directly use it.\n return_intermediate: A `bool`. If true, also return the model value at time `s`.\n Returns:\n x_t: A pytorch tensor. The approximated solution at time `t`.\n ",
"language": "en",
"n_whitespaces": 205,
"n_words": 95,
"vocab_size": 54
} | https://github.com/Stability-AI/stablediffusion.git |
|
3 | _asarray_with_order | def _asarray_with_order(array, dtype=None, order=None, copy=None, xp=None):
if xp is None:
xp, _ = get_namespace(array)
if xp.__name__ in {"numpy", "numpy.array_api"}:
# Use NumPy API to support order
array = numpy.asarray(array, order=order, dtype=dtype)
return xp.asarray(array, copy=copy)
else:
return xp.asarray(array, dtype=dtype, copy=copy)
| 2710a9e7eefd2088ce35fd2fb6651d5f97e5ef8b | 11 | _array_api.py | 139 | ENH Adds Array API support to LinearDiscriminantAnalysis (#22554)
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> | 76,628 | 0 | 86 | 90 | 34 | 261,023 | 39 | scikit-learn | 11 | sklearn/utils/_array_api.py | Python | 8 | {
"docstring": "Helper to support the order kwarg only for NumPy-backed arrays\n\n Memory layout parameter `order` is not exposed in the Array API standard,\n however some input validation code in scikit-learn needs to work both\n for classes and functions that will leverage Array API only operations\n and for code that inherently relies on NumPy backed data containers with\n specific memory layout constraints (e.g. our own Cython code). The\n purpose of this helper is to make it possible to share code for data\n container validation without memory copies for both downstream use cases:\n the `order` parameter is only enforced if the input array implementation\n is NumPy based, otherwise `order` is just silently ignored.\n ",
"language": "en",
"n_whitespaces": 140,
"n_words": 110,
"vocab_size": 77
} | https://github.com/scikit-learn/scikit-learn.git |
|
1 | test_bound_blocks_are_available_on_template | def test_bound_blocks_are_available_on_template(self):
block = SectionBlock()
value = block.to_python({"title": "Hello", "body": "<i>italic</i> world"})
result = block.render(value)
self.assertEqual(result, )
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 11 | test_blocks.py | 81 | Reformat with black | 16,226 | 0 | 52 | 43 | 15 | 74,164 | 17 | wagtail | 9 | wagtail/core/tests/test_blocks.py | Python | 5 | {
"docstring": "\n Test that we are able to use value.bound_blocks within templates\n to access a child block's own HTML rendering\n <h1>Hello</h1><i>italic</i> world",
"language": "en",
"n_whitespaces": 41,
"n_words": 20,
"vocab_size": 19
} | https://github.com/wagtail/wagtail.git |
|
2 | _genName | def _genName(cls, name):
if not name:
name = "frame_" + str(uuid.uuid4()).replace("-", "")
# TODO: reword name in case of caller's mistake
return name
| 1c0935c1bc0856d43f69c1e32498636ee24ebc85 | 15 | base_worker.py | 62 | FEAT-#4913: Enabling pyhdk (#4900)
Co-authored-by: ienkovich <ilya.enkovich@intel.com>
Signed-off-by: izamyati <igor.zamyatin@intel.com> | 35,956 | 0 | 62 | 33 | 21 | 154,395 | 23 | modin | 7 | modin/experimental/core/execution/native/implementations/omnisci_on_native/base_worker.py | Python | 4 | {
"docstring": "\n Generate or mangle a table name.\n\n Parameters\n ----------\n name : str or None\n Table name to mangle or None to generate a unique\n table name.\n\n Returns\n -------\n str\n Table name.\n ",
"language": "en",
"n_whitespaces": 120,
"n_words": 30,
"vocab_size": 18
} | https://github.com/modin-project/modin.git |
|
11 | sort_graph_by_row_values | def sort_graph_by_row_values(graph, copy=False, warn_when_not_sorted=True):
if not issparse(graph):
raise TypeError(f"Input graph must be a sparse matrix, got {graph!r} instead.")
if graph.format == "csr" and _is_sorted_by_data(graph):
return graph
if warn_when_not_sorted:
warnings.warn(
"Precomputed sparse input was not sorted by row values. Use the function"
" sklearn.neighbors.sort_graph_by_row_values to sort the input by row"
" values, with warn_when_not_sorted=False to remove this warning.",
EfficiencyWarning,
)
if graph.format not in ("csr", "csc", "coo", "lil"):
raise TypeError(
f"Sparse matrix in {graph.format!r} format is not supported due to "
"its handling of explicit zeros"
)
elif graph.format != "csr":
if not copy:
raise ValueError(
"The input graph is not in CSR format. Use copy=True to allow "
"the conversion to CSR format."
)
graph = graph.asformat("csr")
elif copy: # csr format with copy=True
graph = graph.copy()
row_nnz = np.diff(graph.indptr)
if row_nnz.max() == row_nnz.min():
# if each sample has the same number of provided neighbors
n_samples = graph.shape[0]
distances = graph.data.reshape(n_samples, -1)
order = np.argsort(distances, kind="mergesort")
order += np.arange(n_samples)[:, None] * row_nnz[0]
order = order.ravel()
graph.data = graph.data[order]
graph.indices = graph.indices[order]
else:
for start, stop in zip(graph.indptr, graph.indptr[1:]):
order = np.argsort(graph.data[start:stop], kind="mergesort")
graph.data[start:stop] = graph.data[start:stop][order]
graph.indices[start:stop] = graph.indices[start:stop][order]
return graph
| b94bc5ea6821607d1e9826ce2d084c76379820ba | 15 | _base.py | 503 | ENH add new function sort_graph_by_row_values (#23139)
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> | 75,959 | 0 | 501 | 297 | 125 | 259,865 | 190 | scikit-learn | 33 | sklearn/neighbors/_base.py | Python | 41 | {
"docstring": "Sort a sparse graph such that each row is stored with increasing values.\n\n .. versionadded:: 1.2\n\n Parameters\n ----------\n graph : sparse matrix of shape (n_samples, n_samples)\n Distance matrix to other samples, where only non-zero elements are\n considered neighbors. Matrix is converted to CSR format if not already.\n\n copy : bool, default=False\n If True, the graph is copied before sorting. If False, the sorting is\n performed inplace. If the graph is not of CSR format, `copy` must be\n True to allow the conversion to CSR format, otherwise an error is\n raised.\n\n warn_when_not_sorted : bool, default=True\n If True, a :class:`~sklearn.exceptions.EfficiencyWarning` is raised\n when the input graph is not sorted by row values.\n\n Returns\n -------\n graph : sparse matrix of shape (n_samples, n_samples)\n Distance matrix to other samples, where only non-zero elements are\n considered neighbors. Matrix is in CSR format.\n ",
"language": "en",
"n_whitespaces": 237,
"n_words": 137,
"vocab_size": 78
} | https://github.com/scikit-learn/scikit-learn.git |
|
1 | add_and_show_greeks | def add_and_show_greeks(price, implied_volatility, strike, days, side):
# Add in hedge option
delta, gamma, vega = hedge_model.add_hedge_option(
price, implied_volatility, strike, days, side
)
# Show the added delta, gamma and vega positions. Next to that, also show the inputted
# implied volatility and strike
positions = pd.DataFrame(
[delta, gamma, vega, implied_volatility, strike],
index=["Delta", "Gamma", "Vega", "Implied Volatility", "Strike Price"],
columns=["Positions"],
)
# Show table
print_rich_table(positions, show_index=True, headers=list(positions.columns))
console.print()
return delta, gamma, vega
| 54a1b6f545a0016c576e9e00eef5c003d229dacf | 11 | hedge_view.py | 154 | Feature/hedge (#1768)
* [Bug] Incorrect log for reddit keys. #1733 fix
* Create new feature-hedge
* Significantly improve code of hedge menu
* More robust
* Robustness
* Fix tests
* Fix can't multiply sequence by non-int of type 'numpy.float64' error
* Temporary fix of singular matrix error. Return first feasible solution
* Update Hugo Documentation
* Combining menus and cleaning up code
* Tidy up call_exp
* Update tests Round 1
* Update tests Round 2
* Fix linting error
* Fix linting?
* Fixed glitch
Co-authored-by: JerBouma <jer.bouma@gmail.com>
Co-authored-by: James Maslek <jmaslek11@gmail.com>
Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>
Co-authored-by: colin99d <colin99delahunty@gmail.com>
Co-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt> | 84,766 | 0 | 135 | 101 | 53 | 284,500 | 71 | OpenBBTerminal | 22 | openbb_terminal/stocks/options/hedge/hedge_view.py | Python | 12 | {
"docstring": "Determine the delta, gamma and vega value of the portfolio and/or options and show them.\n\n Parameters\n ----------\n price: int\n The price.\n implied_volatility: float\n The implied volatility.\n strike: float\n The strike price.\n days: float\n The amount of days until expiration. Use annual notation thus a month would be 30 / 360.\n sign: int\n Whether you have a long (1) or short (-1) position\n\n Returns\n -------\n delta: float\n gamma: float\n vega: float\n ",
"language": "en",
"n_whitespaces": 144,
"n_words": 70,
"vocab_size": 56
} | https://github.com/OpenBB-finance/OpenBBTerminal.git |
|
1 | test_acknowledged_new | def test_acknowledged_new(self) -> None:
expected_topic = "Test policy name (1234)"
expected_message = .strip()
self.check_webhook(
"incident_acknowledged_new",
expected_topic,
expected_message,
content_type="application/json",
)
| bfd9fc86223c2446e8b38d2cdd5876caed50bfda | 9 | tests.py | 57 | integration: Fix integration with newrelic.
Newrelic updated the payload that's sent via the webhook incoming call
causing a bug in the newrelic webhook endpoint.
This fixes the bug by updating the endpoint to respect the new format
of the payload as well as the old format. This should be updated once
the old format is EOLed.
Fixes #22338. | 17,831 | 0 | 90 | 32 | 18 | 84,412 | 19 | zulip | 7 | zerver/webhooks/newrelic/tests.py | Python | 11 | {
"docstring": "\n[Incident](https://alerts.newrelic.com/accounts/2941966/incidents/1234) **acknowledged** by **Alice** for condition: **Server Down**\n",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/zulip/zulip.git |
|
2 | _get_vhost_block | def _get_vhost_block(self, vhost):
try:
span_val = self.parser.aug.span(vhost.path)
except ValueError:
logger.critical("Error while reading the VirtualHost %s from "
"file %s", vhost.name, vhost.filep, exc_info=True)
raise errors.PluginError("Unable to read VirtualHost from file")
span_filep = span_val[0]
span_start = span_val[5]
span_end = span_val[6]
with open(span_filep, 'r') as fh:
fh.seek(span_start)
vh_contents = fh.read(span_end-span_start).split("\n")
self._remove_closing_vhost_tag(vh_contents)
return vh_contents
| eeca208c8f57304590ac1af80b496e61021aaa45 | 13 | configurator.py | 187 | Various clean-ups in certbot-apache. Use f-strings. (#9132)
* Various clean-ups in certbot-apache. Use f-strings.
* Smaller tweaks | 45,465 | 0 | 195 | 110 | 43 | 186,369 | 50 | certbot | 26 | certbot-apache/certbot_apache/_internal/configurator.py | Python | 15 | {
"docstring": " Helper method to get VirtualHost contents from the original file.\n This is done with help of augeas span, which returns the span start and\n end positions\n\n :returns: `list` of VirtualHost block content lines without closing tag\n ",
"language": "en",
"n_whitespaces": 65,
"n_words": 36,
"vocab_size": 33
} | https://github.com/certbot/certbot.git |
|
3 | __call__ | def __call__(self, string):
texts = []
floats = []
for i, part in enumerate(self._FLOAT_RE.split(string)):
if i % 2 == 0:
texts.append(part)
else:
floats.append(float(part))
return texts, np.array(floats)
| 84afc5193d38057e2e2badf9c889ea87d80d8fbf | 14 | keras_doctest_lib.py | 109 | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | 81,626 | 0 | 113 | 66 | 24 | 276,313 | 26 | keras | 14 | keras/testing_infra/keras_doctest_lib.py | Python | 9 | {
"docstring": "Extracts floats from a string.\n\n >>> text_parts, floats = _FloatExtractor()(\"Text 1.0 Text\")\n >>> text_parts\n ['Text ', ' Text']\n >>> floats\n array([1.])\n\n Args:\n string: the string to extract floats from.\n\n Returns:\n A (string, array) pair, where `string` has each float replaced by \"...\"\n and `array` is a `float32` `numpy.array` containing the extracted floats.\n ",
"language": "en",
"n_whitespaces": 135,
"n_words": 52,
"vocab_size": 45
} | https://github.com/keras-team/keras.git |
|
7 | parse_boundary_stream | def parse_boundary_stream(stream, max_header_size):
# Stream at beginning of header, look for end of header
# and parse it if found. The header must fit within one
# chunk.
chunk = stream.read(max_header_size)
# 'find' returns the top of these four bytes, so we'll
# need to munch them later to prevent them from polluting
# the payload.
header_end = chunk.find(b"\r\n\r\n")
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 9 | multipartparser.py | 53 | Refs #33476 -- Reformatted code with Black. | 51,350 | 0 | 86 | 149 | 47 | 206,065 | 59 | django | 7 | django/http/multipartparser.py | Python | 24 | {
"docstring": "\n Parse one and exactly one stream that encapsulates a boundary.\n ",
"language": "en",
"n_whitespaces": 17,
"n_words": 10,
"vocab_size": 9
} | https://github.com/django/django.git |
|
12 | slice_with_int_dask_array | def slice_with_int_dask_array(x, index):
from dask.array.core import Array
assert len(index) == x.ndim
fancy_indexes = [
isinstance(idx, (tuple, list))
or (isinstance(idx, (np.ndarray, Array)) and idx.ndim > 0)
for idx in index
]
if sum(fancy_indexes) > 1:
raise NotImplementedError("Don't yet support nd fancy indexing")
out_index = []
dropped_axis_cnt = 0
for in_axis, idx in enumerate(index):
out_axis = in_axis - dropped_axis_cnt
if isinstance(idx, Array) and idx.dtype.kind in "iu":
if idx.ndim == 0:
idx = idx[np.newaxis]
x = slice_with_int_dask_array_on_axis(x, idx, out_axis)
x = x[tuple(0 if i == out_axis else slice(None) for i in range(x.ndim))]
dropped_axis_cnt += 1
elif idx.ndim == 1:
x = slice_with_int_dask_array_on_axis(x, idx, out_axis)
out_index.append(slice(None))
else:
raise NotImplementedError(
"Slicing with dask.array of ints only permitted when "
"the indexer has zero or one dimensions"
)
else:
out_index.append(idx)
return x, tuple(out_index)
| cccb9d8d8e33a891396b1275c2448c352ef40c27 | 19 | slicing.py | 344 | absolufy-imports - No relative - PEP8 (#8796)
Conversation in https://github.com/dask/distributed/issues/5889 | 36,524 | 0 | 408 | 219 | 89 | 156,059 | 127 | dask | 31 | dask/array/slicing.py | Python | 31 | {
"docstring": "Slice x with at most one 1D dask arrays of ints.\n\n This is a helper function of :meth:`Array.__getitem__`.\n\n Parameters\n ----------\n x: Array\n index: tuple with as many elements as x.ndim, among which there are\n one or more Array's with dtype=int\n\n Returns\n -------\n tuple of (sliced x, new index)\n\n where the new index is the same as the input, but with slice(None)\n replaced to the original slicer where a 1D filter has been applied and\n one less element where a zero-dimensional filter has been applied.\n ",
"language": "en",
"n_whitespaces": 130,
"n_words": 84,
"vocab_size": 61
} | https://github.com/dask/dask.git |
|
1 | get_edit_upload_response_data | def get_edit_upload_response_data(self):
return {
"success": True,
self.context_upload_id_name: self.upload_object.id,
"form": render_to_string(
self.edit_form_template_name,
self.get_edit_upload_form_context_data(),
request=self.request,
),
}
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 11 | multiple_upload.py | 72 | Reformat with black | 15,889 | 0 | 125 | 45 | 15 | 72,418 | 15 | wagtail | 9 | wagtail/admin/views/generic/multiple_upload.py | Python | 10 | {
"docstring": "\n Return the JSON response data for an object that has been uploaded to an\n upload object and now needs extra metadata to become a final object\n ",
"language": "en",
"n_whitespaces": 48,
"n_words": 26,
"vocab_size": 22
} | https://github.com/wagtail/wagtail.git |
|
1 | peek | def peek(self, n=0):
self._check_can_read()
# Relies on the undocumented fact that BufferedReader.peek()
# always returns at least one byte (except at EOF), independent
# of the value of n
return self._buffer.peek(n)
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 8 | bz2.py | 44 | add python 3.10.4 for windows | 56,263 | 0 | 73 | 24 | 26 | 221,193 | 31 | XX-Net | 5 | python3.10.4/Lib/bz2.py | Python | 3 | {
"docstring": "Return buffered data without advancing the file position.\n\n Always returns at least one byte of data, unless at EOF.\n The exact number of bytes returned is unspecified.\n ",
"language": "en",
"n_whitespaces": 48,
"n_words": 27,
"vocab_size": 25
} | https://github.com/XX-net/XX-Net.git |
|
3 | _get_boot_time_aix | def _get_boot_time_aix():
res = __salt__["cmd.run_all"]("ps -o etime= -p 1")
if res["retcode"] > 0:
raise CommandExecutionError("Unable to find boot_time for pid 1.")
bt_time = res["stdout"]
match = re.match(r"\s*(?:(\d+)-)?(?:(\d\d):)?(\d\d):(\d\d)\s*", bt_time)
if not match:
raise CommandExecutionError("Unexpected time format.")
groups = match.groups(default="00")
boot_secs = (
_number(groups[0]) * 86400
+ _number(groups[1]) * 3600
+ _number(groups[2]) * 60
+ _number(groups[3])
)
return boot_secs
| 7fabb22f3e361bfff3fdbca01c12659591d15109 | 14 | status.py | 182 | Fix uptime on AIX systems when less than 24 hours | 54,364 | 0 | 129 | 106 | 46 | 216,058 | 57 | salt | 11 | salt/modules/status.py | Python | 16 | {
"docstring": "\n Return the number of seconds since boot time on AIX\n\n t=$(LC_ALL=POSIX ps -o etime= -p 1)\n d=0 h=0\n case $t in *-*) d=${t%%-*}; t=${t#*-};; esac\n case $t in *:*:*) h=${t%%:*}; t=${t#*:};; esac\n s=$((d*86400 + h*3600 + ${t%%:*}*60 + ${t#*:}))\n ",
"language": "en",
"n_whitespaces": 61,
"n_words": 39,
"vocab_size": 33
} | https://github.com/saltstack/salt.git |
|
3 | _matches_get_other_nodes | def _matches_get_other_nodes(dictionary, nodes, node_ind):
ind_node = nodes[node_ind]
return [ind for ind in dictionary if nodes[ind] == ind_node]
| 9d58006fc0a23afcba38f641c9472917c436428a | 9 | mul.py | 47 | Code cleanup | 48,956 | 0 | 38 | 31 | 17 | 198,477 | 17 | sympy | 6 | sympy/core/mul.py | Python | 3 | {
"docstring": "Find other wildcards that may have already been matched.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | https://github.com/sympy/sympy.git |
|
1 | test_uncancellable_disconnect | def test_uncancellable_disconnect(self) -> None:
channel = make_request(
self.reactor, self.site, "POST", "/sleep", await_result=False
)
self._test_disconnect(
self.reactor,
channel,
expect_cancellation=False,
expected_body={"result": True},
)
| dffecade7df8a88caced2a7707c51e2de3407c0d | 11 | test_server.py | 81 | Respect the `@cancellable` flag for `DirectServe{Html,Json}Resource`s (#12698)
`DirectServeHtmlResource` and `DirectServeJsonResource` both inherit
from `_AsyncResource`. These classes expect to be subclassed with
`_async_render_*` methods.
This commit has no effect on `JsonResource`, despite inheriting from
`_AsyncResource`. `JsonResource` has its own `_async_render` override
which will need to be updated separately.
Signed-off-by: Sean Quah <seanq@element.io> | 72,162 | 0 | 110 | 51 | 18 | 248,229 | 20 | synapse | 10 | tests/test_server.py | Python | 11 | {
"docstring": "Test that handlers without the `@cancellable` flag cannot be cancelled.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/matrix-org/synapse.git |
|
1 | test_del_store_not_found | def test_del_store_not_found(certutil, cert_file):
with pytest.raises(salt.exceptions.CommandExecutionError) as exc:
certutil.del_store(
source=str(cert_file.parent / "absent.cer"),
store="TrustedPublisher",
)
assert "cert_file not found" in exc.value.message
| a8d2d1e1397cdc79b2c5f1ad7f6e3b729dcf8857 | 14 | test_win_certutil.py | 88 | Add tests, fix state module | 54,234 | 0 | 64 | 50 | 19 | 215,899 | 19 | salt | 16 | tests/pytests/functional/modules/test_win_certutil.py | Python | 7 | {
"docstring": "\n Test del_store with a missing certificate\n ",
"language": "en",
"n_whitespaces": 13,
"n_words": 6,
"vocab_size": 6
} | https://github.com/saltstack/salt.git |
|
2 | __next__ | def __next__(self):
line = self.readline()
if line:
return line
raise StopIteration
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 8 | codecs.py | 36 | add python 3.10.4 for windows | 56,375 | 0 | 50 | 20 | 10 | 221,360 | 11 | XX-Net | 5 | python3.10.4/Lib/codecs.py | Python | 5 | {
"docstring": " Return the next decoded line from the input stream.",
"language": "en",
"n_whitespaces": 9,
"n_words": 9,
"vocab_size": 8
} | https://github.com/XX-net/XX-Net.git |
|
1 | datetime_cast_date_sql | def datetime_cast_date_sql(self, field_name, tzname):
raise NotImplementedError(
"subclasses of BaseDatabaseOperations may require a "
"datetime_cast_date_sql() method."
)
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 9 | operations.py | 31 | Refs #33476 -- Reformatted code with Black. | 50,949 | 0 | 59 | 16 | 16 | 204,876 | 16 | django | 5 | django/db/backends/base/operations.py | Python | 5 | {
"docstring": "\n Return the SQL to cast a datetime value to date value.\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 11,
"vocab_size": 10
} | https://github.com/django/django.git |
|
1 | test_empty | def test_empty(self) -> None:
id_gen = self._create_id_generator()
# The table is empty so we expect an empty map for positions
self.assertEqual(id_gen.get_positions(), {})
| 9d21ecf7ceab55bc19c4457b8b07401b0b1623a7 | 9 | test_id_generators.py | 50 | Add type hints to tests files. (#12256) | 71,933 | 0 | 50 | 28 | 21 | 247,800 | 22 | synapse | 6 | tests/storage/test_id_generators.py | Python | 6 | {
"docstring": "Test an ID generator against an empty database gives sensible\n current positions.\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 12,
"vocab_size": 11
} | https://github.com/matrix-org/synapse.git |
|
3 | nodata_value | def nodata_value(self, value):
if value is None:
capi.delete_band_nodata_value(self._ptr)
elif not isinstance(value, (int, float)):
raise ValueError("Nodata value must be numeric or None.")
else:
capi.set_band_nodata_value(self._ptr, value)
self._flush()
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 11 | band.py | 93 | Refs #33476 -- Reformatted code with Black. | 50,605 | 0 | 93 | 56 | 24 | 204,001 | 25 | django | 12 | django/contrib/gis/gdal/raster/band.py | Python | 8 | {
"docstring": "\n Set the nodata value for this band.\n ",
"language": "en",
"n_whitespaces": 22,
"n_words": 7,
"vocab_size": 7
} | https://github.com/django/django.git |
|
1 | test_has_module_permission | def test_has_module_permission(self):
self.client.force_login(self.superuser)
response = self.client.get(self.index_url)
self.assertContains(response, "admin_views")
self.assertContains(response, "Articles")
self.client.logout()
self.client.force_login(self.viewuser)
response = self.client.get(self.index_url)
self.assertContains(response, "admin_views")
self.assertContains(response, "Articles")
self.client.logout()
self.client.force_login(self.adduser)
response = self.client.get(self.index_url)
self.assertContains(response, "admin_views")
self.assertContains(response, "Articles")
self.client.logout()
self.client.force_login(self.changeuser)
response = self.client.get(self.index_url)
self.assertContains(response, "admin_views")
self.assertContains(response, "Articles")
self.client.logout()
self.client.force_login(self.deleteuser)
response = self.client.get(self.index_url)
self.assertContains(response, "admin_views")
self.assertContains(response, "Articles")
| 9c19aff7c7561e3a82978a272ecdaad40dda5c00 | 9 | tests.py | 376 | Refs #33476 -- Reformatted code with Black. | 52,077 | 0 | 221 | 224 | 14 | 207,737 | 46 | django | 14 | tests/admin_views/tests.py | Python | 25 | {
"docstring": "\n has_module_permission() returns True for all users who\n have any permission for that module (add, change, or delete), so that\n the module is displayed on the admin index page.\n ",
"language": "en",
"n_whitespaces": 57,
"n_words": 28,
"vocab_size": 24
} | https://github.com/django/django.git |
|
2 | _supports_universal_builds | def _supports_universal_builds():
# As an approximation, we assume that if we are running on 10.4 or above,
# then we are running with an Xcode environment that supports universal
# builds, in particular -isysroot and -arch arguments to the compiler. This
# is in support of allowing 10.4 universal builds to run on 10.3.x systems.
osx_version = _get_system_version_tuple()
return bool(osx_version >= (10, 4)) if osx_version else False
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 10 | _osx_support.py | 46 | add python 3.10.4 for windows | 55,636 | 0 | 88 | 25 | 51 | 219,598 | 67 | XX-Net | 4 | python3.10.4/Lib/_osx_support.py | Python | 3 | {
"docstring": "Returns True if universal builds are supported on this system",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/XX-net/XX-Net.git |
|
1 | mock_smile_adam_2 | def mock_smile_adam_2() -> Generator[None, MagicMock, None]:
chosen_env = "m_adam_heating"
with patch(
"homeassistant.components.plugwise.gateway.Smile", autospec=True
) as smile_mock:
smile = smile_mock.return_value
smile.gateway_id = "da224107914542988a88561b4452b0f6"
smile.heater_id = "056ee145a816487eaa69243c3280f8bf"
smile.smile_version = "3.6.4"
smile.smile_type = "thermostat"
smile.smile_hostname = "smile98765"
smile.smile_name = "Adam"
smile.connect.return_value = True
smile.notifications = _read_json(chosen_env, "notifications")
smile.async_update.return_value = _read_json(chosen_env, "all_data")
yield smile
@pytest.fixture | 2667f0b792b1f936aeb5958cc40d5dee26350bf6 | @pytest.fixture | 11 | conftest.py | 180 | Bump plugwise to v0.21.3, add related new features (#76610)
Co-authored-by: Franck Nijhof <frenck@frenck.nl> | 87,135 | 1 | 146 | 95 | 39 | 287,952 | 51 | core | 21 | tests/components/plugwise/conftest.py | Python | 17 | {
"docstring": "Create a 2nd Mock Adam environment for testing exceptions.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | https://github.com/home-assistant/core.git |
1 | get_tables | def get_tables(self) -> StatusResponse:
query =
result = self.native_query(query)
df = result.data_frame
df = df[['TABLE_NAME' 'TABLE_TYPE']]
result.data_frame = df.rename(columns={'TABLE_NAME': 'table_name', 'TABLE_TYPE': 'table_type'})
return result
| 9a0e918bba3439959112a7fd8e5210276b5ac255 | 12 | druid_handler.py | 103 | implemented the get_tables() and get_columns() methods | 25,698 | 0 | 74 | 55 | 17 | 116,214 | 24 | mindsdb | 10 | mindsdb/integrations/handlers/druid_handler/druid_handler.py | Python | 15 | {
"docstring": "\n Return list of entities that will be accessible as tables.\n Returns:\n HandlerResponse\n \n SELECT *\n FROM INFORMATION_SCHEMA.TABLES\n ",
"language": "en",
"n_whitespaces": 79,
"n_words": 16,
"vocab_size": 16
} | https://github.com/mindsdb/mindsdb.git |
|
4 | _add_unique_metric_name | def _add_unique_metric_name(self, metric_name, metric_fn, output_index):
# For multi-output models, prepend the output names to the metric name.
if len(self.output_names) > 1:
# If we're loading from an already-serialized model, we've already
# prepended the output name, and we don't want to do it again.
#
# Alternatively, we may be receiving a stateless metric (e.g. the
# string "accuracy") rather than a `Metric` object, in which case we
# want to prepend the output name even if we are loading a
# serialized model.
if not getattr(metric_fn, "_from_serialized", False):
metric_name = "%s_%s" % (
self.output_names[output_index],
metric_name,
)
j = 1
base_metric_name = metric_name
while metric_name in self.metrics_names:
metric_name = "%s_%d" % (base_metric_name, j)
j += 1
return metric_name
| fa6d9107a498f7c2403ff28c7b389a1a0c5cc083 | 14 | training_v1.py | 128 | reduct too long lines | 82,051 | 0 | 345 | 75 | 80 | 277,470 | 118 | keras | 11 | keras/engine/training_v1.py | Python | 13 | {
"docstring": "Makes the metric name unique.\n\n If there are multiple outputs for which the metrics are calculated,\n the metric names have to be made unique by appending an integer.\n\n Args:\n metric_name: Metric name that corresponds to the metric specified by\n the user. For example: 'acc'.\n metric_fn: The Metric object.\n output_index: The index of the model output for which the metric name\n is being added.\n\n Returns:\n string, name of the model's unique metric name\n ",
"language": "en",
"n_whitespaces": 169,
"n_words": 72,
"vocab_size": 48
} | https://github.com/keras-team/keras.git |
|
1 | test_statistics_duplicated | def test_statistics_duplicated(hass_recorder, caplog):
hass = hass_recorder()
recorder = hass.data[DATA_INSTANCE]
setup_component(hass, "sensor", {})
zero, four, states = record_states(hass)
hist = history.get_significant_states(hass, zero, four)
assert dict(states) == dict(hist)
wait_recording_done(hass)
assert "Compiling statistics for" not in caplog.text
assert "Statistics already compiled" not in caplog.text
with patch(
"homeassistant.components.sensor.recorder.compile_statistics",
return_value=statistics.PlatformCompiledStatistics([], {}),
) as compile_statistics:
recorder.do_adhoc_statistics(start=zero)
wait_recording_done(hass)
assert compile_statistics.called
compile_statistics.reset_mock()
assert "Compiling statistics for" in caplog.text
assert "Statistics already compiled" not in caplog.text
caplog.clear()
recorder.do_adhoc_statistics(start=zero)
wait_recording_done(hass)
assert not compile_statistics.called
compile_statistics.reset_mock()
assert "Compiling statistics for" not in caplog.text
assert "Statistics already compiled" in caplog.text
caplog.clear()
| 3737b58e85d834728fe27fefa05e8a0526e66d12 | 14 | test_statistics.py | 304 | Avoid fetching metadata multiple times during stat compile (#70397) | 97,291 | 0 | 236 | 181 | 44 | 298,347 | 88 | core | 28 | tests/components/recorder/test_statistics.py | Python | 28 | {
"docstring": "Test statistics with same start time is not compiled.",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | https://github.com/home-assistant/core.git |
|
2 | test_push | def test_push(self):
filename = "/saltines/test.file"
if salt.utils.platform.is_windows():
filename = "C:\\saltines\\test.file"
with patch(
"salt.modules.cp.os.path",
MagicMock(isfile=Mock(return_value=True), wraps=cp.os.path),
), patch(
"salt.modules.cp.os.path",
MagicMock(getsize=MagicMock(return_value=10), wraps=cp.os.path),
), patch.multiple(
"salt.modules.cp",
_auth=MagicMock(**{"return_value.gen_token.return_value": "token"}),
__opts__={"id": "abc", "file_buffer_size": 10},
), patch(
"salt.utils.files.fopen", mock_open(read_data=b"content")
) as m_open, patch(
"salt.channel.client.ReqChannel.factory", MagicMock()
) as req_channel_factory_mock:
response = cp.push(filename)
assert response, response
num_opens = len(m_open.filehandles[filename])
assert num_opens == 1, num_opens
fh_ = m_open.filehandles[filename][0]
assert fh_.read.call_count == 2, fh_.read.call_count
req_channel_factory_mock().__enter__().send.assert_called_once_with(
dict(
loc=fh_.tell(), # pylint: disable=resource-leakage
cmd="_file_recv",
tok="token",
path=["saltines", "test.file"],
size=10,
data=b"", # data is empty here because load['data'] is overwritten
id="abc",
)
)
| 68ab9eeae6899b7ff14fb3489b012862d62653c6 | 16 | test_cp.py | 403 | Fix more tests | 54,034 | 0 | 514 | 241 | 63 | 215,571 | 88 | salt | 43 | tests/unit/modules/test_cp.py | Python | 36 | {
"docstring": "\n Test if push works with good posix path.\n ",
"language": "en",
"n_whitespaces": 23,
"n_words": 8,
"vocab_size": 8
} | https://github.com/saltstack/salt.git |
|
23 | in1d | def in1d(ar1, ar2, assume_unique=False, invert=False, kind=None):
# Ravel both arrays, behavior for the first array could be different
ar1 = np.asarray(ar1).ravel()
ar2 = np.asarray(ar2).ravel()
# Ensure that iteration through object arrays yields size-1 arrays
if ar2.dtype == object:
ar2 = ar2.reshape(-1, 1)
# Convert booleans to uint8 so we can use the fast integer algorithm
if ar1.dtype == bool:
ar1 = ar1.view(np.uint8)
if ar2.dtype == bool:
ar2 = ar2.view(np.uint8)
# Check if we can use a fast integer algorithm:
integer_arrays = (np.issubdtype(ar1.dtype, np.integer) and
np.issubdtype(ar2.dtype, np.integer))
if kind not in {None, 'sort', 'dictionary'}:
raise ValueError(
"Invalid kind: {0}. ".format(kind)
+ "Please use None, 'sort' or 'dictionary'.")
if integer_arrays and kind in {None, 'dictionary'}:
ar2_min = np.min(ar2)
ar2_max = np.max(ar2)
ar1_size = ar1.size
ar2_size = ar2.size
# Check for integer overflow
with np.errstate(over='raise'):
try:
ar2_range = ar2_max - ar2_min
# Optimal performance is for approximately
# log10(size) > (log10(range) - 2.27) / 0.927.
# However, here we set the requirement that
# the intermediate array can only be 6x
# the combined memory allocation of the original
# arrays.
# (see discussion on
# https://github.com/numpy/numpy/pull/12065)
below_memory_constraint = (
ar2_range <= 6 * (ar1_size + ar2_size)
)
except FloatingPointError:
below_memory_constraint = False
# Use the fast integer algorithm
if below_memory_constraint or kind == 'dictionary':
if invert:
outgoing_array = np.ones_like(ar1, dtype=bool)
else:
outgoing_array = np.zeros_like(ar1, dtype=bool)
# Make elements 1 where the integer exists in ar2
if invert:
isin_helper_ar = np.ones(ar2_range + 1, dtype=bool)
isin_helper_ar[ar2 - ar2_min] = 0
else:
isin_helper_ar = np.zeros(ar2_range + 1, dtype=bool)
isin_helper_ar[ar2 - ar2_min] = 1
# Mask out elements we know won't work
basic_mask = (ar1 <= ar2_max) & (ar1 >= ar2_min)
outgoing_array[basic_mask] = isin_helper_ar[ar1[basic_mask] -
ar2_min]
return outgoing_array
elif kind == 'dictionary':
raise ValueError(
"The 'dictionary' method is only "
"supported for boolean or integer arrays. "
"Please select 'sort' or None for kind."
)
# Check if one of the arrays may contain arbitrary objects
contains_object = ar1.dtype.hasobject or ar2.dtype.hasobject
# This code is run when
# a) the first condition is true, making the code significantly faster
# b) the second condition is true (i.e. `ar1` or `ar2` may contain
# arbitrary objects), since then sorting is not guaranteed to work
if len(ar2) < 10 * len(ar1) ** 0.145 or contains_object:
if invert:
mask = np.ones(len(ar1), dtype=bool)
for a in ar2:
mask &= (ar1 != a)
else:
mask = np.zeros(len(ar1), dtype=bool)
for a in ar2:
mask |= (ar1 == a)
return mask
# Otherwise use sorting
if not assume_unique:
ar1, rev_idx = np.unique(ar1, return_inverse=True)
ar2 = np.unique(ar2)
ar = np.concatenate((ar1, ar2))
# We need this to be a stable sort, so always use 'mergesort'
# here. The values from the first array should always come before
# the values from the second array.
order = ar.argsort(kind='mergesort')
sar = ar[order]
if invert:
bool_ar = (sar[1:] != sar[:-1])
else:
bool_ar = (sar[1:] == sar[:-1])
flag = np.concatenate((bool_ar, [invert]))
ret = np.empty(ar.shape, dtype=bool)
ret[order] = flag
if assume_unique:
return ret[:len(ar1)]
else:
return ret[rev_idx]
| cde60cee195660f2dafb2993e609d66559525fe8 | 17 | arraysetops.py | 955 | MAINT: Switch parameter name to 'kind' over 'method' | 38,719 | 0 | 1,384 | 585 | 258 | 160,766 | 496 | numpy | 57 | numpy/lib/arraysetops.py | Python | 77 | {
"docstring": "\n Test whether each element of a 1-D array is also present in a second array.\n\n Returns a boolean array the same length as `ar1` that is True\n where an element of `ar1` is in `ar2` and False otherwise.\n\n We recommend using :func:`isin` instead of `in1d` for new code.\n\n Parameters\n ----------\n ar1 : (M,) array_like\n Input array.\n ar2 : array_like\n The values against which to test each value of `ar1`.\n assume_unique : bool, optional\n If True, the input arrays are both assumed to be unique, which\n can speed up the calculation. Default is False.\n invert : bool, optional\n If True, the values in the returned array are inverted (that is,\n False where an element of `ar1` is in `ar2` and True otherwise).\n Default is False. ``np.in1d(a, b, invert=True)`` is equivalent\n to (but is faster than) ``np.invert(in1d(a, b))``.\n kind : {None, 'sort', 'dictionary'}, optional\n The algorithm to use. This will not affect the final result,\n but will affect the speed. Default will select automatically\n based on memory considerations.\n\n - If 'sort', will use a mergesort-based approach. This will have\n a memory usage of roughly 6 times the sum of the sizes of\n `ar1` and `ar2`, not accounting for size of dtypes.\n - If 'dictionary', will use a key-dictionary approach similar\n to a counting sort. This is only available for boolean and\n integer arrays. This will have a memory usage of the\n size of `ar1` plus the max-min value of `ar2`. This tends\n to be the faster method if the following formula is true:\n `log10(len(ar2)) > (log10(max(ar2)-min(ar2)) - 2.27) / 0.927`,\n but may use greater memory.\n - If `None`, will automatically choose 'dictionary' if\n the required memory allocation is less than or equal to\n 6 times the sum of the sizes of `ar1` and `ar2`,\n otherwise will use 'sort'. This is done to not use\n a large amount of memory by default, even though\n 'dictionary' may be faster in most cases.\n\n .. versionadded:: 1.8.0\n\n Returns\n -------\n in1d : (M,) ndarray, bool\n The values `ar1[in1d]` are in `ar2`.\n\n See Also\n --------\n isin : Version of this function that preserves the\n shape of ar1.\n numpy.lib.arraysetops : Module with a number of other functions for\n performing set operations on arrays.\n\n Notes\n -----\n `in1d` can be considered as an element-wise function version of the\n python keyword `in`, for 1-D sequences. ``in1d(a, b)`` is roughly\n equivalent to ``np.array([item in b for item in a])``.\n However, this idea fails if `ar2` is a set, or similar (non-sequence)\n container: As ``ar2`` is converted to an array, in those cases\n ``asarray(ar2)`` is an object array rather than the expected array of\n contained values.\n\n .. versionadded:: 1.4.0\n\n Examples\n --------\n >>> test = np.array([0, 1, 2, 5, 0])\n >>> states = [0, 2]\n >>> mask = np.in1d(test, states)\n >>> mask\n array([ True, False, True, False, True])\n >>> test[mask]\n array([0, 2, 0])\n >>> mask = np.in1d(test, states, invert=True)\n >>> mask\n array([False, True, False, True, False])\n >>> test[mask]\n array([1, 5])\n ",
"language": "en",
"n_whitespaces": 921,
"n_words": 485,
"vocab_size": 256
} | https://github.com/numpy/numpy.git |
|
1 | center_of_mass | def center_of_mass(mask, esp=1e-6):
h, w = mask.shape
grid_h = torch.arange(h, device=mask.device)[:, None]
grid_w = torch.arange(w, device=mask.device)
normalizer = mask.sum().float().clamp(min=esp)
center_h = (mask * grid_h).sum() / normalizer
center_w = (mask * grid_w).sum() / normalizer
return center_h, center_w
| fa77be290460e84ce7da975831cb7e687a419177 | 12 | misc.py | 156 | Refactor package | 70,747 | 0 | 60 | 100 | 25 | 245,290 | 36 | mmdetection | 18 | mmdet/models/utils/misc.py | Python | 8 | {
"docstring": "Calculate the centroid coordinates of the mask.\n\n Args:\n mask (Tensor): The mask to be calculated, shape (h, w).\n esp (float): Avoid dividing by zero. Default: 1e-6.\n\n Returns:\n tuple[Tensor]: the coordinates of the center point of the mask.\n\n - center_h (Tensor): the center point of the height.\n - center_w (Tensor): the center point of the width.\n ",
"language": "en",
"n_whitespaces": 107,
"n_words": 55,
"vocab_size": 33
} | https://github.com/open-mmlab/mmdetection.git |
|
23 | streams | def streams(self, stream_types=None, sorting_excludes=None):
try:
ostreams = self._get_streams()
if isinstance(ostreams, dict):
ostreams = ostreams.items()
# Flatten the iterator to a list so we can reuse it.
if ostreams:
ostreams = list(ostreams)
except NoStreamsError:
return {}
except (OSError, ValueError) as err:
raise PluginError(err)
if not ostreams:
return {}
if stream_types is None:
stream_types = self.default_stream_types(ostreams)
# Add streams depending on stream type and priorities
sorted_streams = sorted(iterate_streams(ostreams),
key=partial(stream_type_priority,
stream_types))
streams = {}
for name, stream in sorted_streams:
stream_type = type(stream).shortname()
# Use * as wildcard to match other stream types
if "*" not in stream_types and stream_type not in stream_types:
continue
# drop _alt from any stream names
if name.endswith("_alt"):
name = name[:-len("_alt")]
existing = streams.get(name)
if existing:
existing_stream_type = type(existing).shortname()
if existing_stream_type != stream_type:
name = "{0}_{1}".format(name, stream_type)
if name in streams:
name = "{0}_alt".format(name)
num_alts = len(list(filter(lambda n: n.startswith(name), streams.keys())))
# We shouldn't need more than 2 alt streams
if num_alts >= 2:
continue
elif num_alts > 0:
name = "{0}{1}".format(name, num_alts + 1)
# Validate stream name and discard the stream if it's bad.
match = re.match("([A-z0-9_+]+)", name)
if match:
name = match.group(1)
else:
self.logger.debug(f"The stream '{name}' has been ignored since it is badly named.")
continue
# Force lowercase name and replace space with underscore.
streams[name.lower()] = stream
# Create the best/worst synonyms | b72f23fd699de9730e9009ac319b84da68f15a73 | 21 | plugin.py | 506 | docs: update API page, add type annotations | 45,676 | 0 | 907 | 482 | 135 | 187,036 | 215 | streamlink | 44 | src/streamlink/plugin/plugin.py | Python | 68 | {
"docstring": "\n Attempts to extract available streams.\n\n Returns a :class:`dict` containing the streams, where the key is\n the name of the stream (most commonly the quality name), with the value\n being a :class:`Stream` instance.\n\n The result can contain the synonyms **best** and **worst** which\n point to the streams which are likely to be of highest and\n lowest quality respectively.\n\n If multiple streams with the same name are found, the order of\n streams specified in *stream_types* will determine which stream\n gets to keep the name while the rest will be renamed to\n \"<name>_<stream type>\".\n\n The synonyms can be fine-tuned with the *sorting_excludes*\n parameter, which can be one of these types:\n\n - A list of filter expressions in the format\n ``[operator]<value>``. For example the filter \">480p\" will\n exclude streams ranked higher than \"480p\" from the list\n used in the synonyms ranking. Valid operators are ``>``, ``>=``, ``<``\n and ``<=``. If no operator is specified then equality will be tested.\n\n - A function that is passed to :meth:`filter` with a list of\n stream names as input.\n\n\n :param stream_types: A list of stream types to return\n :param sorting_excludes: Specify which streams to exclude from the best/worst synonyms\n :returns: A :class:`dict` of stream names and :class:`streamlink.stream.Stream` instances\n ",
"language": "en",
"n_whitespaces": 407,
"n_words": 200,
"vocab_size": 112
} | https://github.com/streamlink/streamlink.git |
|
18 | insert_predictor_answer | def insert_predictor_answer(self, insert):
model_interface = self.session.model_interface
data_store = self.session.data_store
select_data_query = insert.get('select_data_query')
if isinstance(select_data_query, str) is False or len(select_data_query) == 0:
self.packet(
ErrPacket,
err_code=ERR.ER_WRONG_ARGUMENTS,
msg="'select_data_query' should not be empty"
).send()
return
models = model_interface.get_models()
if insert['name'] in [x['name'] for x in models]:
self.packet(
ErrPacket,
err_code=ERR.ER_WRONG_ARGUMENTS,
msg=f"predictor with name '{insert['name']}'' already exists"
).send()
return
kwargs = {}
if isinstance(insert.get('training_options'), str) \
and len(insert['training_options']) > 0:
try:
kwargs = json.loads(insert['training_options'])
except Exception:
self.packet(
ErrPacket,
err_code=ERR.ER_WRONG_ARGUMENTS,
msg='training_options should be in valid JSON string'
).send()
return
integration = self.session.integration
if isinstance(integration, str) is False or len(integration) == 0:
self.packet(
ErrPacket,
err_code=ERR.ER_WRONG_ARGUMENTS,
msg='select_data_query can be used only in query from database'
).send()
return
insert['select_data_query'] = insert['select_data_query'].replace(r"\'", "'")
ds_name = data_store.get_vacant_name(insert['name'])
ds = data_store.save_datasource(ds_name, integration, {'query': insert['select_data_query']})
insert['predict'] = [x.strip() for x in insert['predict'].split(',')]
ds_data = data_store.get_datasource(ds_name)
if ds_data is None:
raise Exception(f"DataSource '{ds_name}' does not exists")
ds_columns = [x['name'] for x in ds_data['columns']]
for col in insert['predict']:
if col not in ds_columns:
data_store.delete_datasource(ds_name)
raise Exception(f"Column '{col}' not exists")
try:
insert['predict'] = self._check_predict_columns(insert['predict'], ds_columns)
except Exception:
data_store.delete_datasource(ds_name)
raise
model_interface.learn(
insert['name'], ds, insert['predict'], ds_data['id'], kwargs=kwargs, delete_ds_on_fail=True
)
self.packet(OkPacket).send()
| 551205a18ac2ac19626f4e4ffb2ed88fcad705b9 | 16 | mysql_proxy.py | 713 | fix | 25,051 | 0 | 833 | 445 | 109 | 113,876 | 181 | mindsdb | 42 | mindsdb/api/mysql/mysql_proxy/mysql_proxy.py | Python | 63 | {
"docstring": " Start learn new predictor.\n Parameters:\n - insert - dict with keys as columns of mindsb.predictors table.\n ",
"language": "en",
"n_whitespaces": 47,
"n_words": 16,
"vocab_size": 15
} | https://github.com/mindsdb/mindsdb.git |
|
3 | _remove_long_seq | def _remove_long_seq(maxlen, seq, label):
new_seq, new_label = [], []
for x, y in zip(seq, label):
if len(x) < maxlen:
new_seq.append(x)
new_label.append(y)
return new_seq, new_label
@keras_export('keras.preprocessing.sequence.TimeseriesGenerator') | f1aa8b7d2a0c89591c5c42eca5b6f013114a7bbd | @keras_export('keras.preprocessing.sequence.TimeseriesGenerator') | 11 | sequence.py | 99 | Copy sequence utils from keras_preprocessing directly into core keras
PiperOrigin-RevId: 424915569 | 79,741 | 1 | 41 | 55 | 22 | 268,873 | 25 | keras | 12 | keras/preprocessing/sequence.py | Python | 7 | {
"docstring": "Removes sequences that exceed the maximum length.\n\n Args:\n maxlen: Int, maximum length of the output sequences.\n seq: List of lists, where each sublist is a sequence.\n label: List where each element is an integer.\n\n Returns:\n new_seq, new_label: shortened lists for `seq` and `label`.\n ",
"language": "en",
"n_whitespaces": 66,
"n_words": 43,
"vocab_size": 36
} | https://github.com/keras-team/keras.git |
7 | remove_xml_tags | def remove_xml_tags(buf):
filtered = bytearray()
in_tag = False
prev = 0
buf = memoryview(buf).cast("c")
for curr, buf_char in enumerate(buf):
# Check if we're coming out of or entering an XML tag
if buf_char == b">":
prev = curr + 1
in_tag = False
elif buf_char == b"<":
if curr > prev and not in_tag:
# Keep everything after last non-extended-ASCII,
# non-alphabetic character
filtered.extend(buf[prev:curr])
# Output a space to delimit stretch we kept
filtered.extend(b" ")
in_tag = True
# If we're not in a tag...
if not in_tag:
# Keep everything after last non-extended-ASCII, non-alphabetic
# character
filtered.extend(buf[prev:])
return filtered
| cd5a9683be69c86c8f3adcd13385a9bc5db198ec | 16 | charsetprober.py | 180 | Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir. | 4,089 | 0 | 384 | 103 | 62 | 21,893 | 100 | pipenv | 12 | pipenv/patched/pip/_vendor/chardet/charsetprober.py | Python | 17 | {
"docstring": "\n Returns a copy of ``buf`` that retains only the sequences of English\n alphabet and high byte characters that are not between <> characters.\n This filter can be applied to all scripts which contain both English\n characters and extended ASCII characters, but is currently only used by\n ``Latin1Prober``.\n ",
"language": "en",
"n_whitespaces": 90,
"n_words": 47,
"vocab_size": 41
} | https://github.com/pypa/pipenv.git |
|
1 | test_rich_text_is_safe | def test_rich_text_is_safe(self):
stream_block = blocks.StreamBlock(
[
(
"paragraph",
blocks.RichTextBlock(template="tests/jinja2/rich_text.html"),
)
]
)
stream_value = stream_block.to_python(
[
{
"type": "paragraph",
"value": '<p>Merry <a linktype="page" id="4">Christmas</a>!</p>',
},
]
)
result = render_to_string(
"tests/jinja2/stream.html",
{
"value": stream_value,
},
)
self.assertIn(
'<p>Merry <a href="/events/christmas/">Christmas</a>!</p>', result
)
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 14 | test_jinja2.py | 125 | Reformat with black | 16,234 | 0 | 344 | 70 | 27 | 74,208 | 42 | wagtail | 12 | wagtail/core/tests/test_jinja2.py | Python | 26 | {
"docstring": "\n Ensure that RichText values are marked safe\n so that they don't get double-escaped when inserted into a parent template (#2542)\n ",
"language": "en",
"n_whitespaces": 42,
"n_words": 20,
"vocab_size": 19
} | https://github.com/wagtail/wagtail.git |
|
6 | getWindowsDLLVersion | def getWindowsDLLVersion(filename):
# Get size needed for buffer (0 if no info)
import ctypes.wintypes
if type(filename) is unicode:
GetFileVersionInfoSizeW = ctypes.windll.version.GetFileVersionInfoSizeW
GetFileVersionInfoSizeW.argtypes = [
ctypes.wintypes.LPCWSTR,
ctypes.wintypes.LPDWORD,
]
GetFileVersionInfoSizeW.restype = ctypes.wintypes.HANDLE
size = GetFileVersionInfoSizeW(filename, None)
else:
size = ctypes.windll.version.GetFileVersionInfoSizeA(filename, None)
if not size:
return (0, 0, 0, 0)
# Create buffer
res = ctypes.create_string_buffer(size)
# Load file information into buffer res
if type(filename) is unicode:
# Python3 needs our help here.
GetFileVersionInfo = ctypes.windll.version.GetFileVersionInfoW
GetFileVersionInfo.argtypes = [
ctypes.wintypes.LPCWSTR,
ctypes.wintypes.DWORD,
ctypes.wintypes.DWORD,
ctypes.wintypes.LPVOID,
]
GetFileVersionInfo.restype = ctypes.wintypes.BOOL
else:
# Python2 just works.
GetFileVersionInfo = ctypes.windll.version.GetFileVersionInfoA
success = GetFileVersionInfo(filename, 0, size, res)
# This cannot really fail anymore.
assert success
# Look for codepages
VerQueryValueA = ctypes.windll.version.VerQueryValueA
VerQueryValueA.argtypes = [
ctypes.wintypes.LPCVOID,
ctypes.wintypes.LPCSTR,
ctypes.wintypes.LPVOID,
ctypes.POINTER(ctypes.c_uint32),
]
VerQueryValueA.restype = ctypes.wintypes.BOOL
file_info = ctypes.POINTER(VsFixedFileInfoStructure)()
uLen = ctypes.c_uint32(ctypes.sizeof(file_info))
b = VerQueryValueA(res, br"\\", ctypes.byref(file_info), ctypes.byref(uLen))
if not b:
return (0, 0, 0, 0)
if file_info.contents.dwSignature != 0xFEEF04BD:
return (0, 0, 0, 0)
ms = file_info.contents.dwFileVersionMS
ls = file_info.contents.dwFileVersionLS
return (ms >> 16) & 0xFFFF, ms & 0xFFFF, (ls >> 16) & 0xFFFF, ls & 0xFFFF
_readelf_usage = "The 'readelf' is used to analyse dependencies on ELF using systems and required to be found."
| 982929807fdc5838554cf302a2013a28e7707514 | 13 | SharedLibraries.py | 537 | macOS: Avoid references to original install paths as library ids | 42,769 | 0 | 480 | 351 | 118 | 178,629 | 194 | Nuitka | 43 | nuitka/utils/SharedLibraries.py | Python | 46 | {
"docstring": "Return DLL version information from a file.\n\n If not present, it will be (0, 0, 0, 0), otherwise it will be\n a tuple of 4 numbers.\n ",
"language": "en",
"n_whitespaces": 35,
"n_words": 26,
"vocab_size": 21
} | https://github.com/Nuitka/Nuitka.git |
|
1 | test_rollback_cursor_consistency | def test_rollback_cursor_consistency(self):
con = sqlite.connect(":memory:")
cur = con.cursor()
cur.execute("create table test(x)")
cur.execute("insert into test(x) values (5)")
cur.execute("select 1 union select 2 union select 3")
con.rollback()
self.assertEqual(cur.fetchall(), [(1,), (2,), (3,)])
| 9d6a239a34a66e16188d76c23a3a770515ca44ca | 9 | test_transactions.py | 123 | bpo-44092: Don't reset statements/cursors before rollback (GH-26026)
In SQLite versions pre 3.7.11, pending statements would block a rollback. This is no longer the case, so remove the workaround. | 41,562 | 0 | 85 | 71 | 26 | 175,168 | 29 | cpython | 11 | Lib/test/test_sqlite3/test_transactions.py | Python | 8 | {
"docstring": "Check that cursors behave correctly after rollback.",
"language": "en",
"n_whitespaces": 6,
"n_words": 7,
"vocab_size": 7
} | https://github.com/python/cpython.git |
|
1 | is_package | def is_package(cls, fullname):
return False
load_module = classmethod(_load_module_shim)
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 6 | _bootstrap.py | 28 | add python 3.10.4 for windows | 55,099 | 0 | 25 | 10 | 8 | 218,049 | 8 | XX-Net | 6 | python3.10.4/Lib/importlib/_bootstrap.py | Python | 2 | {
"docstring": "Return False as built-in modules are never packages.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/XX-net/XX-Net.git |
|
2 | get_ind_under_point | def get_ind_under_point(self, event):
xy = self.pathpatch.get_path().vertices
xyt = self.pathpatch.get_transform().transform(xy) # to display coords
xt, yt = xyt[:, 0], xyt[:, 1]
d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)
ind = d.argmin()
return ind if d[ind] < self.epsilon else None
| 1068a6faa19767724437461bcfb88c6852ec435c | 13 | path_editor.py | 152 | Remove unnecessary np.{,as}array / astype calls.
Quite often numpy will call asarray for us, saving us the need to call
asarray explicitly.
When we do call asarray (or array) ourselves, a dtype can directly be
passed in, rather than immediately calling astype immediately after.
Passing the dtype makes it unnecessary for asarray to infer the dtype
of the passed-in container, and can also save an extra array allocation
if asarray first has to allocate an array of a type and astype
immediately has to allocate an array of another type. | 23,885 | 0 | 90 | 96 | 33 | 110,014 | 40 | matplotlib | 20 | examples/event_handling/path_editor.py | Python | 7 | {
"docstring": "\n Return the index of the point closest to the event position or *None*\n if no point is within ``self.epsilon`` to the event position.\n ",
"language": "en",
"n_whitespaces": 45,
"n_words": 23,
"vocab_size": 17
} | https://github.com/matplotlib/matplotlib.git |
|
3 | round_filters | def round_filters(filters, global_params):
multiplier = global_params.width_coefficient
if not multiplier:
return filters
divisor = global_params.depth_divisor
filters *= multiplier
new_filters = int(filters + divisor / 2) // divisor * divisor
if new_filters < 0.9 * filters:
new_filters += divisor
return int(new_filters)
| 6e607a0fa1cefbf0388dac86c84debf4781cec48 | 12 | rec_efficientb3_pren.py | 92 | [Feature] Add PREN Scene Text Recognition Model(Accepted in CVPR2021) (#5563)
* [Feature] add PREN scene text recognition model
* [Patch] Optimize yml File
* [Patch] Save Label/Pred Preprocess Time Cost
* [BugFix] Modify Shape Conversion to Fit for Inference Model Exportion
* [Patch] ?
* [Patch] ?
* 啥情况... | 4,587 | 0 | 117 | 56 | 26 | 23,387 | 39 | PaddleOCR | 9 | ppocr/modeling/backbones/rec_efficientb3_pren.py | Python | 10 | {
"docstring": "Calculate and round number of filters based on depth multiplier.",
"language": "en",
"n_whitespaces": 9,
"n_words": 10,
"vocab_size": 10
} | https://github.com/PaddlePaddle/PaddleOCR.git |
|
6 | assert_lca_dicts_same | def assert_lca_dicts_same(self, d1, d2, G=None):
if G is None:
G = self.DG
root_distance = self.root_distance
else:
roots = [n for n, deg in G.in_degree if deg == 0]
assert len(roots) == 1
root_distance = nx.shortest_path_length(G, source=roots[0])
for a, b in ((min(pair), max(pair)) for pair in chain(d1, d2)):
assert (
root_distance[get_pair(d1, a, b)] == root_distance[get_pair(d2, a, b)]
)
| b2f91c34a23058dd70b41784af0d87890216026a | 13 | test_lowest_common_ancestors.py | 183 | Naive lowest common ancestor implementation (#5736)
* Add naive lca methods
* Naive algorithm implementation for LCA
* Modify naive lca functions
* Correct parameters of nx.ancestors
* Update lowest_common_ancestors.py
* Parametrize tests
* Apply suggestions from code review
Co-authored-by: Dan Schult <dschult@colgate.edu>
* Yield instead of append
* Tests for naive lca
* Correct test cases for naive lca algorithms
* Apply suggestions from code review
Co-authored-by: Mridul Seth <mail@mriduls.com>
* Fix function name -when calling
* Make requested changes
* Inlining _get_a_lowest_common_ancestor
Co-authored-by: dtuncturk <dilaramemis@sabanciuniv.edu>
Co-authored-by: Dan Schult <dschult@colgate.edu>
Co-authored-by: Mridul Seth <mail@mriduls.com> | 42,227 | 0 | 177 | 124 | 40 | 177,015 | 57 | networkx | 22 | networkx/algorithms/tests/test_lowest_common_ancestors.py | Python | 12 | {
"docstring": "Checks if d1 and d2 contain the same pairs and\n have a node at the same distance from root for each.\n If G is None use self.DG.",
"language": "en",
"n_whitespaces": 40,
"n_words": 27,
"vocab_size": 24
} | https://github.com/networkx/networkx.git |
|
6 | _prepare_socket_file | def _prepare_socket_file(self, socket_path, default_prefix):
result = socket_path
is_mac = sys.platform.startswith("darwin")
if sys.platform == "win32":
if socket_path is None:
result = f"tcp://{self._localhost}" f":{self._get_unused_port()}"
else:
if socket_path is None:
result = self._make_inc_temp(
prefix=default_prefix, directory_name=self._sockets_dir
)
else:
try_to_create_directory(os.path.dirname(socket_path))
# Check socket path length to make sure it's short enough
maxlen = (104 if is_mac else 108) - 1 # sockaddr_un->sun_path
if len(result.split("://", 1)[-1].encode("utf-8")) > maxlen:
raise OSError(
"AF_UNIX path length cannot exceed "
"{} bytes: {!r}".format(maxlen, result)
)
return result
| 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | 17 | node.py | 234 | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | 29,375 | 0 | 333 | 127 | 56 | 130,803 | 77 | ray | 25 | python/ray/node.py | Python | 20 | {
"docstring": "Prepare the socket file for raylet and plasma.\n\n This method helps to prepare a socket file.\n 1. Make the directory if the directory does not exist.\n 2. If the socket file exists, do nothing (this just means we aren't the\n first worker on the node).\n\n Args:\n socket_path (string): the socket file to prepare.\n ",
"language": "en",
"n_whitespaces": 109,
"n_words": 53,
"vocab_size": 40
} | https://github.com/ray-project/ray.git |
|
1 | test_user_message_already_unlinked | def test_user_message_already_unlinked(self):
IdentityProvider.objects.create(type="slack", external_id="TXXXXXXX1", config={})
responses.add(responses.POST, "https://slack.com/api/chat.postMessage", json={"ok": True})
resp = self.post_webhook(event_data=json.loads(MESSAGE_IM_EVENT_UNLINK))
assert resp.status_code == 200, resp.content
request = responses.calls[0].request
assert request.headers["Authorization"] == "Bearer xoxb-xxxxxxxxx-xxxxxxxxxx-xxxxxxxxxxxx"
data = json.loads(request.body)
assert "You do not have a linked identity to unlink" in get_response_text(data)
| b7d894b56953153cf33008ae7d33e1e41b175eb7 | 11 | test_message_im.py | 174 | ref(tests): Split up large files (#31828) | 19,302 | 0 | 103 | 104 | 35 | 96,313 | 40 | sentry | 25 | tests/sentry/integrations/slack/endpoints/events/test_message_im.py | Python | 9 | {
"docstring": "\n Test that when a user without an Identity types in \"unlink\" to the DM we\n reply with the correct response.\n ",
"language": "en",
"n_whitespaces": 42,
"n_words": 20,
"vocab_size": 19
} | https://github.com/getsentry/sentry.git |
|
1 | test_subscribe_to_stream_post_policy_moderators_stream | def test_subscribe_to_stream_post_policy_moderators_stream(self) -> None:
member = self.example_user("AARON")
stream = self.make_stream("stream1")
# Make sure that we are testing this with full member which is just below the moderator
# in the role hierarchy.
self.assertFalse(member.is_provisional_member)
do_change_stream_post_policy(
stream, Stream.STREAM_POST_POLICY_MODERATORS, acting_user=member
)
result = self.common_subscribe_to_streams(member, ["stream1"])
self.assert_json_success(result)
json = result.json()
self.assertEqual(json["subscribed"], {member.email: ["stream1"]})
self.assertEqual(json["already_subscribed"], {})
| c30458e1740c7878e436037f61431884e54b349d | 11 | test_subs.py | 172 | streams: Add notifications for posting policy changes.
An explanatory note on the changes in zulip.yaml and
curl_param_value_generators is warranted here. In our automated
tests for our curl examples, the test for the API endpoint that
changes the posting permissions of a stream comes before our
existing curl test for adding message reactions.
Since there is an extra notification message due to the change in
posting permissions, the message IDs used in tests that come after
need to be incremented by 1.
This is a part of #20289. | 17,579 | 0 | 153 | 100 | 45 | 83,023 | 51 | zulip | 18 | zerver/tests/test_subs.py | Python | 15 | {
"docstring": "\n Members can subscribe to streams where only admins and moderators can post\n ",
"language": "en",
"n_whitespaces": 27,
"n_words": 12,
"vocab_size": 11
} | https://github.com/zulip/zulip.git |
|
1 | test_overwrite_storage_path | def test_overwrite_storage_path(self):
call_command("document_retagger", "--storage_path", "--overwrite")
d_first, d_second, d_unrelated, d_auto = self.get_updated_docs()
self.assertEqual(d_first.storage_path, self.sp2)
self.assertEqual(d_auto.storage_path, self.sp1)
self.assertIsNone(d_second.storage_path)
self.assertEqual(d_unrelated.storage_path, self.sp2)
| c8e838e3a0828e82efac1fd93ebb9aba6a000ff8 | 8 | test_management_retagger.py | 116 | Adds the storage paths to the re-tagger command | 117,022 | 0 | 67 | 71 | 17 | 319,934 | 18 | paperless-ngx | 13 | src/documents/tests/test_management_retagger.py | Python | 7 | {
"docstring": "\n GIVEN:\n - 2 storage paths with documents which match them\n - 1 document which matches but has a storage path\n WHEN:\n - document retagger is called with overwrite\n THEN:\n - Matching document's storage paths updated\n - Non-matching documents have no storage path\n - Existing storage patch overwritten\n ",
"language": "en",
"n_whitespaces": 142,
"n_words": 47,
"vocab_size": 32
} | https://github.com/paperless-ngx/paperless-ngx.git |
|
1 | hashkey | def hashkey(cls, *args, **kwargs):
return cachetools.keys.hashkey(f"<{cls.__name__}>", *args, **kwargs)
| 21972c91dd2b52cd206bf71ea038ab0e1f478b32 | 10 | settings.py | 52 | add lock to cachetools usage
* We observed daphne giving tracebacks when accessing logging settings.
Originally, configure tower in tower settings was no a suspect because
daphne is not multi-process. We've had issues with configure tower in
tower settings and multi-process before. We later learned that Daphne
is multi-threaded. Configure tower in tower was back to being a
suspect. We constructed a minimal reproducer to show that multiple
threads accessing settings can cause the same traceback that we saw in
daphne. See
https://gist.github.com/chrismeyersfsu/7aa4bdcf76e435efd617cb078c64d413
for that recreator. These fixes stop the recreation. | 17,168 | 0 | 22 | 28 | 7 | 81,176 | 8 | awx | 7 | awx/conf/settings.py | Python | 2 | {
"docstring": "\n Usage of @cachetools.cached has changed to @cachetools.cachedmethod\n The previous cachetools decorator called the hash function and passed in (self, key).\n The new cachtools decorator calls the hash function with just (key).\n Ideally, we would continue to pass self, however, the cachetools decorator interface\n does not allow us to.\n\n This hashkey function is to maintain that the key generated looks like\n ('<SettingsWrapper>', key). The thought is that maybe it is important to namespace\n our cache to the SettingsWrapper scope in case some other usage of this cache exists.\n I can not think of how any other system could and would use our private cache, but\n for safety sake we are ensuring the key schema does not change.\n ",
"language": "en",
"n_whitespaces": 194,
"n_words": 116,
"vocab_size": 82
} | https://github.com/ansible/awx.git |
|
2 | link_entity | def link_entity(props):
id_ = props.get("id")
link_props = {}
if id_ is not None:
link_props["linktype"] = "page"
link_props["id"] = id_
else:
link_props["href"] = check_url(props.get("url"))
return DOM.create_element("a", link_props, props["children"])
| d10f15e55806c6944827d801cd9c2d53f5da4186 | 14 | contentstate.py | 121 | Reformat with black | 15,641 | 0 | 66 | 66 | 21 | 71,201 | 27 | wagtail | 8 | wagtail/admin/rich_text/converters/contentstate.py | Python | 9 | {
"docstring": "\n <a linktype=\"page\" id=\"1\">internal page link</a>\n ",
"language": "en",
"n_whitespaces": 12,
"n_words": 5,
"vocab_size": 5
} | https://github.com/wagtail/wagtail.git |
|
14 | _suggest_semantic_version | def _suggest_semantic_version(s):
result = s.strip().lower()
for pat, repl in _REPLACEMENTS:
result = pat.sub(repl, result)
if not result:
result = '0.0.0'
# Now look for numeric prefix, and separate it out from
# the rest.
#import pdb; pdb.set_trace()
m = _NUMERIC_PREFIX.match(result)
if not m:
prefix = '0.0.0'
suffix = result
else:
prefix = m.groups()[0].split('.')
prefix = [int(i) for i in prefix]
while len(prefix) < 3:
prefix.append(0)
if len(prefix) == 3:
suffix = result[m.end():]
else:
suffix = '.'.join([str(i) for i in prefix[3:]]) + result[m.end():]
prefix = prefix[:3]
prefix = '.'.join([str(i) for i in prefix])
suffix = suffix.strip()
if suffix:
#import pdb; pdb.set_trace()
# massage the suffix.
for pat, repl in _SUFFIX_REPLACEMENTS:
suffix = pat.sub(repl, suffix)
if not suffix:
result = prefix
else:
sep = '-' if 'dev' in suffix else '+'
result = prefix + sep + suffix
if not is_semver(result):
result = None
return result
| f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | 19 | version.py | 411 | upd; format | 12,903 | 0 | 370 | 242 | 67 | 62,242 | 144 | transferlearning | 26 | .venv/lib/python3.8/site-packages/pip/_vendor/distlib/version.py | Python | 33 | {
"docstring": "\n Try to suggest a semantic form for a version for which\n _suggest_normalized_version couldn't come up with anything.\n ",
"language": "en",
"n_whitespaces": 27,
"n_words": 17,
"vocab_size": 15
} | https://github.com/jindongwang/transferlearning.git |
|
1 | test_previewing_subprocess_deployment | def test_previewing_subprocess_deployment():
result = invoke_and_assert(
[
"deployment",
"preview",
"./tests/deployment_test_files/single_deployment.py",
],
expected_output_contains="prefect.engine",
)
assert result.stdout.endswith("\n")
preview = result.stdout.strip()
# spot-check some variables and the command-line
assert "\nPREFECT_TEST_MODE=True \\" in preview
assert "\nPREFECT_LOGGING_LEVEL=DEBUG \\" in preview
assert preview.endswith(" -m prefect.engine 00000000000000000000000000000000")
| 5afded9fe6724d9e336f59792ee1d60656a2d94d | 10 | test_deployment_preview.py | 110 | Add a CLI command to preview how a FlowRun will appear in any FlowRunner's execution environment (PrefectHQ/orion#1971)
Co-authored-by: Terrence Dorsey <terrence@prefect.io>
Co-authored-by: Michael Adkins <madkinszane@gmail.com> | 11,495 | 0 | 120 | 56 | 31 | 56,284 | 39 | prefect | 8 | tests/cli/test_deployment_preview.py | Python | 14 | {
"docstring": "`prefect deployment preview my-flow-file.py` should render the\n shell command that will be run for the subprocess",
"language": "en",
"n_whitespaces": 18,
"n_words": 16,
"vocab_size": 15
} | https://github.com/PrefectHQ/prefect.git |
|
4 | completion_item_yank | def completion_item_yank(self, sel=False):
text = self._cmd.selectedText()
if not text:
index = self.currentIndex()
if not index.isValid():
raise cmdutils.CommandError("No item selected!")
text = self._model().data(index)
if not utils.supports_selection():
sel = False
utils.set_clipboard(text, selection=sel)
| a20bb67a878b2e68abf8268c1b0a27f018d01352 | 12 | completionwidget.py | 133 | mypy: Upgrade to PyQt5-stubs 5.15.6.0
For some unknown reason, those new stubs cause a *lot* of things now to be
checked by mypy which formerly probably got skipped due to Any being implied
somewhere.
The stubs themselves mainly improved, with a couple of regressions too.
In total, there were some 337 (!) new mypy errors. This commit fixes almost all
of them, and the next commit improves a fix to get things down to 0 errors
again.
Overview of the changes:
==== qutebrowser/app.py
- Drop type ignore due to improved stubs.
==== qutebrowser/browser/browsertab.py
- Specify the type of _widget members more closely than just QWidget.
This is debatable: I suppose the abstract stuff shouldn't need to know
anything about the concrete backends at all. But it seems like we cut some
corners when initially implementing things, and put some code in browsertab.py
just because the APIs of both backends happened to be compatible. Perhaps
something to reconsider once we drop QtWebKit and hopefully implement a dummy
backend.
- Add an additional assertion in AbstractAction.run_string. This is already
covered by the isinstance(member, self.action_base) above it, but that's too
dynamic for mypy to understand.
- Fix the return type of AbstractScroller.pos_px, which is a QPoint (with x
and y components), not a single int.
- Fix the return type of AbstractScroller.pos_perc, which is a Tuple (with x
and y components), not a single int.
- Fix the argument types of AbstractScroller.to_perc, as it's possible to pass
fractional percentages too.
- Specify the type for AbstractHistoryPrivate._history. See above (_widget) re
this being debatable.
- Fix the return type of AbstractTabPrivate.event_target(), which can be None
(see #3888).
- Fix the return type of AbstractTabPrivate.run_js_sync, which is Any (the JS
return value), not None.
- Fix the argument type for AbstractTabPrivate.toggle_inspector: position can
be None to use the last used position.
- Declare the type of sub-objects of AbstractTab.
- Fix the return value of AbstractTab.icon(), which is the QIcon, not None.
==== qutebrowser/browser/commands.py
- Make sure the active window is a MainWindow (with a .win_id attribute).
==== qutebrowser/browser/downloadview.py
- Add _model() which makes sure that self.model() is a DownloadModel, not None
or any other model. This is needed because other methods access a variety of
custom attributes on it, e.g. last_index().
==== qutebrowser/browser/greasemonkey.py
- Add an ignore for AbstractDownload.requested_url which we patch onto the
downloads. Probably would be nicer to add it as a proper attribute which always
gets set by the DownloadManager.
==== qutebrowser/browser/hints.py
- Remove type ignores for QUrl.toString().
- Add a new type ignore for combining different URL flags (which works, but is
not exactly type safe... still probably a regression in the stubs).
- Make sure the things we get back from self._get_keyparser are what we actually
expect. Probably should introduce a TypedDict (and/or overloads for
_get_keyparser with typing.Literal) to teach mypy about the exact return value.
See #7098.
This is needed because we access Hint/NormalKeyParser-specific attributes such
as .set_inhibited_timout() or .update_bindings().
==== qutebrowser/browser/inspector.py
- Similar changes than in browsertab.py to make some types where we share API
(e.g. .setPage()) more concrete. Didn't work out unfortunately, see next
commit.
==== qutebrowser/browser/network/pac.py
- Remove now unneeded type ignore for signal.
==== qutebrowser/browser/qtnetworkdownloads.py
- Make sure that downloads is a qtnetworkdownloads.DownloadItem (rather than an
AbstractDownload), so that we can call ._uses_nam() on it.
==== qutebrowser/browser/qutescheme.py
- Remove now unneeded type ignore for QUrl flags.
==== qutebrowser/browser/urlmarks.py
- Specify the type of UrlMarkManager._lineparser, as those only get initialized
in _init_lineparser of subclasses, so mypy doesn't know it's supposed to exist.
==== qutebrowser/browser/webelem.py
- New casts to turn single KeyboardModifier (enum) entries into
KeyboardModifiers (flags). Might not be needed anymore with Qt 6.
- With that, casting the final value is now unneeded.
==== qutebrowser/browser/webengine/notification.py
- Remove now unneeded type ignore for signal.
- Make sure the self.sender() we get in HerbeNotificationAdapter._on_finished()
is a QProcess, not just any QObject.
==== qutebrowser/browser/webengine/webenginedownloads.py
- Remove now unneeded type ignores for signals.
==== qutebrowser/browser/webengine/webengineelem.py
- Specify the type of WebEngineElement._tab.
- Remove now unneeded type ignore for mixed flags.
==== qutebrowser/browser/webengine/webengineinspector.py
- See changes to inspector.py and next commit.
- Remove now unneeded type ignore for signal.
==== qutebrowser/browser/webengine/webenginequtescheme.py
- Remove now unneeded type ignore for mixed flags.
==== qutebrowser/browser/webengine/webenginesettings.py
- Ignore access of .setter attribute which we patch onto QWebEngineProfile.
Would be nice to have a subclass or wrapper-class instead.
==== qutebrowser/browser/webengine/webenginetab.py
- Specified the type of _widget members more closely than just QWidget.
See browsertab.py changes for details.
- Remove some now-unneeded type ignores for creating FindFlags.
- Specify more concrete types for WebEngineTab members where we actually need to
access WebEngine-specific attributes.
- Make sure the page we get is our custom WebEnginePage subclass, not just any
QWebEnginePage. This is needed because we access custom attributes on it.
==== qutebrowser/browser/webengine/webview.py
- Make sure the page we get is our custom WebEnginePage subclass, not just any
QWebEnginePage. This is needed because we access custom attributes on it.
==== qutebrowser/browser/webkit/network/networkreply.py
- Remove now unneeded type ignores for signals.
==== qutebrowser/browser/webkit/webkitinspector.py
- See changes to inspector.py and next commit.
==== qutebrowser/browser/webkit/webkittab.py
- Specify the type of _widget members more closely than just QWidget.
See browsertab.py changes for details.
- Add a type ignore for WebKitAction because our workaround needs to
treat them as ints (which is allowed by PyQt, even if not type-safe).
- Add new ignores for findText calls: The text is a QString and can be None; the
flags are valid despite mypy thinking they aren't (stubs regression?).
- Specify the type for WebKitHistoryPrivate._history, because we access
WebKit-specific attributes. See above (_widget) re this being debatable.
- Make mypy aware that .currentFrame() and .frameAt() can return None (stubs
regression?).
- Make sure the .page() and .page().networkAccessManager() are our subclasses
rather than the more generic QtWebKit objects, as we use custom attributes.
- Add new type ignores for signals (stubs regression!)
==== qutebrowser/browser/webkit/webpage.py
- Make sure the .networkAccessManager() is our subclass rather than the more
generic QtWebKit object, as we use custom attributes.
- Replace a cast by a type ignore. The cast didn't work anymore.
==== qutebrowser/browser/webkit/webview.py
- Make sure the .page() is our subclass rather than the more generic QtWebKit
object, as we use custom attributes.
==== qutebrowser/commands/userscripts.py
- Remove now unneeded type ignore for signal.
==== qutebrowser/completion/completer.py
- Add a new _completion() getter (which ensures it actually gets the completion
view) rather than accessing the .parent() directly (which could be any QObject).
==== qutebrowser/completion/completiondelegate.py
- Make sure self.parent() is a CompletionView (no helper method as there is only
one instance).
- Remove a now-unneeded type ignore for adding QSizes.
==== qutebrowser/completion/completionwidget.py
- Add a ._model() getter which ensures that we get a CompletionModel (with
custom attributes) rather than Qt's .model() which can be any QAbstractItemModel
(or None).
- Removed a now-unneeded type ignore for OR-ing flags.
==== qutebrowser/completion/models/completionmodel.py
- Remove now unneeded type ignores for signals.
- Ignore a complaint about .set_pattern() not being defined. Completion
categories don't share any common parent class, so it would be good to introduce
a typing.Protocol for this. See #7098.
==== qutebrowser/components/misccommands.py
- Removed a now-unneeded type ignore for OR-ing flags.
==== qutebrowser/components/readlinecommands.py
- Make sure QApplication.instance() is a QApplication (and not just a
QCoreApplication). This includes the former "not None" check.
==== qutebrowser/components/scrollcommands.py
- Add basic annotation for "funcs" dict. Could have a callable protocol to
specify it needs a count kwarg, see #7098.
==== qutebrowser/config/stylesheet.py
- Correctly specify that stylesheet apply to QWidgets, not any QObject.
- Ignore an attr-defined for obj.STYLESHEET. Perhaps could somehow teach mypy
about this with overloads and protocols (stylesheet for set_register being None
=> STYLESHEET needs to be defined, otherwise anything goes), but perhaps not
worth the troble. See #7098.
==== qutebrowser/keyinput/keyutils.py
- Remove some now-unneeded type ignores and add a cast for using a single enum
value as flags. Might need to look at this again with Qt 6 support.
==== qutebrowser/keyinput/modeman.py
- Add a FIXME for using a TypedDict, see comments for hints.py above.
==== qutebrowser/mainwindow/mainwindow.py
- Remove now-unneeded type ignores for calling with OR-ed flags.
- Improve where we cast from WindowType to WindowFlags, no int needed
- Use new .tab_bar() getter, see below.
==== qutebrowser/mainwindow/prompt.py
- Remove now-unneeded type ignores for calling with OR-ed flags.
==== qutebrowser/mainwindow/statusbar/bar.py
- Adjust type ignores around @pyqtProperty. The fact one is still needed seems
like a stub regression.
==== qutebrowser/mainwindow/statusbar/command.py
- Fix type for setText() override (from QLineEdit): text can be None
(QString in C++).
==== qutebrowser/mainwindow/statusbar/url.py
- Adjust type ignores around @pyqtProperty. The fact one is still needed seems
like a stub regression.
==== qutebrowser/mainwindow/tabbedbrowser.py
- Specify that TabDeque manages browser tabs, not any QWidgets. It accesses
AbstractTab-specific attributes.
- Make sure that the .tabBar() we get is a tabwidget.TabBar, as we access
.maybe_hide.
- Fix the annotations for stored marks: Scroll positions are a QPoint, not int.
- Add _current_tab() and _tab_by_idx() wrappers for .currentWidget() and
.widget(), which ensures that the return values are valid AbstractTabs (or None
for _tab_by_idx). This is needed because we access AbstractTab-specific
attributes.
- For some places, where the tab can be None, continue using .currentTab() but
add asserts.
- Remove some now-unneeded [unreachable] ignores, as mypy knows about the None
possibility now.
==== qutebrowser/mainwindow/tabwidget.py
- Add new tab_bar() and _tab_by_idx() helpers which check that the .tabBar() and
.widget() are of type TabBar and AbstractTab, respectively.
- Add additional assertions where we expect ._tab_by_idx() to never be None.
- Remove dead code in get_tab_fields for handling a None y scroll position. I
was unable to find any place in the code where this could be set to None.
- Remove some now-unneeded type ignores and casts, as mypy now knows that
_type_by_idx() could be None.
- Work around a strange instance where mypy complains about not being able to
find the type of TabBar.drag_in_progress from TabWidget._toggle_visibility,
despite it clearly being shown as a bool *inside* that class without any
annotation.
- Add a ._tab_widget() getter in TabBar which ensures that the .parent() is in
fact a TabWidget.
==== qutebrowser/misc/crashsignal.py
- Remove now unneeded type ignores for signals.
==== qutebrowser/misc/editor.py
- Remove now unneeded type ignores for signals.
==== qutebrowser/misc/ipc.py
- Remove now unneeded type ignores for signals.
- Add new type ignores for .error() which is both a signal and a getter
(stub regression?). Won't be relevant for Qt 6 anymore, as the signal was
renamed to errorOccurred in 5.15.
==== qutebrowser/misc/objects.py
- Make sure mypy knows that objects.app is our custom Application (with custom
attributes) rather than any QApplication.
==== qutebrowser/utils/objreg.py
- Ignore attr-defined for .win_id attributes. Maybe could add a typing.Protocol,
but ideally, the whole objreg stuff should die one day anyways.
==== tests/unit/completion/test_completer.py
- Make CompletionWidgetStub inherit from CompletionView so that it passes the
new isinstance() asserts in completer.py (see above). | 117,342 | 0 | 124 | 78 | 22 | 320,775 | 30 | qutebrowser | 17 | qutebrowser/completion/completionwidget.py | Python | 10 | {
"docstring": "Yank the current completion item into the clipboard.\n\n Args:\n sel: Use the primary selection instead of the clipboard.\n ",
"language": "en",
"n_whitespaces": 43,
"n_words": 18,
"vocab_size": 14
} | https://github.com/qutebrowser/qutebrowser.git |
|
1 | get_index_and_columns | def _get_index_and_columns(df):
return len(df.index), len(df.columns)
@ray.remote(num_returns=4) | e7cb2e82f8b9c7a68f82abdd3b6011d661230b7e | @ray.remote(num_returns=4) | 9 | partition.py | 50 | REFACTOR-#4251: define public interfaces in `modin.core.execution.ray` module (#3868)
Signed-off-by: Anatoly Myachev <anatoly.myachev@intel.com> | 35,381 | 1 | 11 | 20 | 6 | 153,345 | 6 | modin | 8 | modin/core/execution/ray/implementations/pandas_on_ray/partitioning/partition.py | Python | 2 | {
"docstring": "\n Get the number of rows and columns of a pandas DataFrame.\n\n Parameters\n ----------\n df : pandas.DataFrame\n A pandas DataFrame which dimensions are needed.\n\n Returns\n -------\n int\n The number of rows.\n int\n The number of columns.\n ",
"language": "en",
"n_whitespaces": 84,
"n_words": 35,
"vocab_size": 27
} | https://github.com/modin-project/modin.git |
2 | test_extra_tags | def test_extra_tags(self):
for extra_tags in ['', None, 'some tags']:
with self.subTest(extra_tags=extra_tags):
self.assertEqual(
self.encode_decode('message', extra_tags=extra_tags).extra_tags,
extra_tags,
)
| efb4478e484ae61c5fc23563d4e9df1f8f49df49 | 15 | test_cookie.py | 80 | Fixed #33458 -- Fixed encoding of messages with empty string as extra_tags. | 50,236 | 0 | 109 | 47 | 16 | 203,144 | 16 | django | 6 | tests/messages_tests/test_cookie.py | Python | 7 | {
"docstring": "\n A message's extra_tags attribute is correctly preserved when retrieved\n from the message storage.\n ",
"language": "en",
"n_whitespaces": 35,
"n_words": 13,
"vocab_size": 13
} | https://github.com/django/django.git |
|
2 | compile_helper | def compile_helper():
import os
import subprocess
path = os.path.abspath(os.path.dirname(__file__))
ret = subprocess.run(['make', '-C', path])
if ret.returncode != 0:
print("Making C++ dataset helpers module failed, exiting.")
import sys
sys.exit(1)
| 1d930169e118c325c03343b6acd7d9c05eab1f85 | 11 | dataset_utils.py | 105 | [Pre-training] Optional for nsp task, support multi-datasets in ERNIE-1.0 pre-training (#1621)
* add no nsp training.
* support for multi-dataset
* fix test sample nums. | 118,235 | 0 | 67 | 59 | 25 | 322,771 | 28 | PaddleNLP | 13 | examples/language_model/data_tools/dataset_utils.py | Python | 9 | {
"docstring": "Compile helper function ar runtime. Make sure this\n is invoked on a single process.",
"language": "en",
"n_whitespaces": 16,
"n_words": 14,
"vocab_size": 14
} | https://github.com/PaddlePaddle/PaddleNLP.git |
|
5 | variable | def variable(value, dtype=None, name=None, constraint=None):
if dtype is None:
dtype = floatx()
if hasattr(value, "tocoo"):
sparse_coo = value.tocoo()
indices = np.concatenate(
(
np.expand_dims(sparse_coo.row, 1),
np.expand_dims(sparse_coo.col, 1),
),
1,
)
v = tf.SparseTensor(
indices=indices,
values=sparse_coo.data,
dense_shape=sparse_coo.shape,
)
v._keras_shape = sparse_coo.shape
return v
v = tf.Variable(
value, dtype=tf.as_dtype(dtype), name=name, constraint=constraint
)
if isinstance(value, np.ndarray):
v._keras_shape = value.shape
elif hasattr(value, "shape"):
v._keras_shape = int_shape(value)
track_variable(v)
return v
| 84afc5193d38057e2e2badf9c889ea87d80d8fbf | 14 | backend.py | 265 | Reformatting the codebase with black.
PiperOrigin-RevId: 450093126 | 80,150 | 0 | 264 | 173 | 44 | 269,521 | 64 | keras | 29 | keras/backend.py | Python | 28 | {
"docstring": "Instantiates a variable and returns it.\n\n Args:\n value: Numpy array, initial value of the tensor.\n dtype: Tensor type.\n name: Optional name string for the tensor.\n constraint: Optional projection function to be\n applied to the variable after an optimizer update.\n\n Returns:\n A variable instance (with Keras metadata included).\n\n Examples:\n\n >>> val = np.array([[1, 2], [3, 4]])\n >>> kvar = tf.keras.backend.variable(value=val, dtype='float64',\n ... name='example_var')\n >>> tf.keras.backend.dtype(kvar)\n 'float64'\n >>> print(kvar)\n <tf.Variable 'example_var:...' shape=(2, 2) dtype=float64, numpy=\n array([[1., 2.],\n [3., 4.]])>\n\n ",
"language": "en",
"n_whitespaces": 206,
"n_words": 77,
"vocab_size": 66
} | https://github.com/keras-team/keras.git |
|
1 | test_conversation_chain_errors_bad_variable | def test_conversation_chain_errors_bad_variable() -> None:
llm = FakeLLM()
prompt = PromptTemplate(input_variables=["foo"], template="{foo}")
memory = ConversationBufferMemory(dynamic_key="foo")
with pytest.raises(ValueError):
ConversationChain(llm=llm, prompt=prompt, memory=memory, input_key="foo")
@pytest.mark.parametrize(
"memory",
[
ConversationBufferMemory(dynamic_key="baz"),
ConversationSummaryMemory(llm=FakeLLM(), dynamic_key="baz"),
],
) | a408ed3ea39dfa47e8b522a9e153b259f25df54e | @pytest.mark.parametrize(
"memory",
[
ConversationBufferMemory(dynamic_key="baz"),
ConversationSummaryMemory(llm=FakeLLM(), dynamic_key="baz"),
],
) | 12 | test_conversation.py | 161 | Samantha/add conversation chain (#166)
Add MemoryChain and ConversationChain as chains that take a docstore in
addition to the prompt, and use the docstore to stuff context into the
prompt. This can be used to have an ongoing conversation with a chatbot.
Probably needs a bit of refactoring for code quality
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> | 46,692 | 1 | 71 | 60 | 26 | 191,569 | 28 | langchain | 18 | tests/unit_tests/chains/test_conversation.py | Python | 7 | {
"docstring": "Test that conversation chain works in basic setting.",
"language": "en",
"n_whitespaces": 7,
"n_words": 8,
"vocab_size": 8
} | https://github.com/hwchase17/langchain.git |
8 | register | async def register(cls):
for field in cls.__fields__.values():
if Block.is_block_class(field.type_):
await field.type_.register()
if get_origin(field.type_) is Union:
for type in get_args(field.type_):
if Block.is_block_class(type):
await type.register()
| 1c74cd08aaa8eb7759490fc156abb18f916b0764 | 16 | core.py | 116 | Renames method from install to register | 11,452 | 0 | 131 | 178 | 18 | 56,177 | 23 | prefect | 12 | src/prefect/blocks/core.py | Python | 27 | {
"docstring": "\n Makes block available for configuration with current Orion server.\n Recursively registers all nested blocks. Registration is idempotent.\n ",
"language": "en",
"n_whitespaces": 39,
"n_words": 17,
"vocab_size": 17
} | https://github.com/PrefectHQ/prefect.git |
|
14 | get_input | def get_input(self, field_name, **kwargs):
if self.credential_type.kind != 'external' and field_name in self.dynamic_input_fields:
return self._get_dynamic_input(field_name)
if field_name in self.credential_type.secret_fields:
try:
return decrypt_field(self, field_name)
except AttributeError:
for field in self.credential_type.inputs.get('fields', []):
if field['id'] == field_name and 'default' in field:
return field['default']
if 'default' in kwargs:
return kwargs['default']
raise AttributeError(field_name)
if field_name in self.inputs:
return self.inputs[field_name]
if 'default' in kwargs:
return kwargs['default']
for field in self.credential_type.inputs.get('fields', []):
if field['id'] == field_name and 'default' in field:
return field['default']
raise AttributeError(field_name)
| 871175f97fb177ad3c6d6f150e2b685dc11893ce | 16 | __init__.py | 279 | Sending field_name in AttributeError | 17,314 | 0 | 327 | 166 | 35 | 82,077 | 76 | awx | 14 | awx/main/models/credential/__init__.py | Python | 21 | {
"docstring": "\n Get an injectable and decrypted value for an input field.\n\n Retrieves the value for a given credential input field name. Return\n values for secret input fields are decrypted. If the credential doesn't\n have an input value defined for the given field name, an AttributeError\n is raised unless a default value is provided.\n\n :param field_name(str): The name of the input field.\n :param default(optional[str]): A default return value to use.\n ",
"language": "en",
"n_whitespaces": 132,
"n_words": 68,
"vocab_size": 43
} | https://github.com/ansible/awx.git |
|
1 | synchronized_update_sequences | def synchronized_update_sequences(self) -> tuple[str, str]:
return (
self._synchronized_update_start_sequence(),
self._synchronized_update_end_sequence(),
)
| d14659c1a3760eade2dd3479b66eb8b2e7711db0 | 8 | _terminal_features.py | 45 | [terminal buffering] Add support for the "mode 2026"
That task is definitely way more complicated that it seemed to be 😅 | 44,251 | 0 | 53 | 28 | 10 | 183,562 | 10 | textual | 6 | src/textual/_terminal_features.py | Python | 14 | {
"docstring": "\n Returns the ANSI sequence that we should send to the terminal to tell it that\n it should buffer the content we're about to send, as well as the ANIS sequence to end the buffering.\n If the terminal doesn't seem to support synchronised updates both strings will be empty.\n\n Returns:\n tuple[str, str]: the start and end ANSI sequences, respectively. They will both be empty strings\n if the terminal emulator doesn't seem to support the \"synchronised updates\" mode.\n ",
"language": "en",
"n_whitespaces": 138,
"n_words": 76,
"vocab_size": 47
} | https://github.com/Textualize/textual.git |
|
8 | do_for | def do_for(parser, token):
bits = token.split_contents()
if len(bits) < 4:
raise TemplateSyntaxError(
"'for' statements should have at least four words: %s" % token.contents
)
is_reversed = bits[-1] == 'reversed'
in_index = -3 if is_reversed else -2
if bits[in_index] != 'in':
raise TemplateSyntaxError("'for' statements should use the format"
" 'for x in y': %s" % token.contents)
invalid_chars = frozenset((' ', '"', "'", FILTER_SEPARATOR))
loopvars = re.split(r' *, *', ' '.join(bits[1:in_index]))
for var in loopvars:
if not var or not invalid_chars.isdisjoint(var):
raise TemplateSyntaxError(
"'for' tag received an invalid argument: %s" % token.contents
)
sequence = parser.compile_filter(bits[in_index + 1])
nodelist_loop = parser.parse(('empty', 'endfor',))
token = parser.next_token()
if token.contents == 'empty':
nodelist_empty = parser.parse(('endfor',))
parser.delete_first_token()
else:
nodelist_empty = None
return ForNode(loopvars, sequence, is_reversed, nodelist_loop, nodelist_empty)
| c5cd8783825b5f6384417dac5f3889b4210b7d08 | 13 | defaulttags.py | 343 | Refs #33476 -- Refactored problematic code before reformatting by Black.
In these cases Black produces unexpected results, e.g.
def make_random_password(
self,
length=10,
allowed_chars='abcdefghjkmnpqrstuvwxyz' 'ABCDEFGHJKLMNPQRSTUVWXYZ' '23456789',
):
or
cursor.execute("""
SELECT ...
""",
[table name],
) | 50,268 | 0 | 296 | 203 | 89 | 203,240 | 121 | django | 27 | django/template/defaulttags.py | Python | 27 | {
"docstring": "\n Loop over each item in an array.\n\n For example, to display a list of athletes given ``athlete_list``::\n\n <ul>\n {% for athlete in athlete_list %}\n <li>{{ athlete.name }}</li>\n {% endfor %}\n </ul>\n\n You can loop over a list in reverse by using\n ``{% for obj in list reversed %}``.\n\n You can also unpack multiple values from a two-dimensional array::\n\n {% for key,value in dict.items %}\n {{ key }}: {{ value }}\n {% endfor %}\n\n The ``for`` tag can take an optional ``{% empty %}`` clause that will\n be displayed if the given array is empty or could not be found::\n\n <ul>\n {% for athlete in athlete_list %}\n <li>{{ athlete.name }}</li>\n {% empty %}\n <li>Sorry, no athletes in this list.</li>\n {% endfor %}\n <ul>\n\n The above is equivalent to -- but shorter, cleaner, and possibly faster\n than -- the following::\n\n <ul>\n {% if athlete_list %}\n {% for athlete in athlete_list %}\n <li>{{ athlete.name }}</li>\n {% endfor %}\n {% else %}\n <li>Sorry, no athletes in this list.</li>\n {% endif %}\n </ul>\n\n The for loop sets a number of variables available within the loop:\n\n ========================== ================================================\n Variable Description\n ========================== ================================================\n ``forloop.counter`` The current iteration of the loop (1-indexed)\n ``forloop.counter0`` The current iteration of the loop (0-indexed)\n ``forloop.revcounter`` The number of iterations from the end of the\n loop (1-indexed)\n ``forloop.revcounter0`` The number of iterations from the end of the\n loop (0-indexed)\n ``forloop.first`` True if this is the first time through the loop\n ``forloop.last`` True if this is the last time through the loop\n ``forloop.parentloop`` For nested loops, this is the loop \"above\" the\n current one\n ========================== ================================================\n ",
"language": "en",
"n_whitespaces": 764,
"n_words": 262,
"vocab_size": 121
} | https://github.com/django/django.git |
|
2 | set_global_relative_scale_factor | def set_global_relative_scale_factor(self, scale_factor, reference_quantity):
from sympy.physics.units import UnitSystem
scale_factor = sympify(scale_factor)
if isinstance(scale_factor, Prefix):
self._is_prefixed = True
# replace all prefixes by their ratio to canonical units:
scale_factor = scale_factor.replace(
lambda x: isinstance(x, Prefix),
lambda x: x.scale_factor
)
scale_factor = sympify(scale_factor)
UnitSystem._quantity_scale_factors_global[self] = (scale_factor, reference_quantity)
UnitSystem._quantity_dimensional_equivalence_map_global[self] = reference_quantity
| 40a89803dbe877edc8ab6672819715f959273e60 | 11 | quantities.py | 133 | feat(physics.units): add `is_prefixed` property to `Quantity` | 48,646 | 0 | 151 | 86 | 38 | 197,624 | 48 | sympy | 16 | sympy/physics/units/quantities.py | Python | 12 | {
"docstring": "\n Setting a scale factor that is valid across all unit system.\n ",
"language": "en",
"n_whitespaces": 26,
"n_words": 11,
"vocab_size": 11
} | https://github.com/sympy/sympy.git |
|
14 | validate_expense_against_budget | def validate_expense_against_budget(args):
args = frappe._dict(args)
if args.get("company") and not args.fiscal_year:
args.fiscal_year = get_fiscal_year(args.get("posting_date"), company=args.get("company"))[0]
frappe.flags.exception_approver_role = frappe.get_cached_value(
"Company", args.get("company"), "exception_budget_approver_role"
)
if not args.account:
args.account = args.get("expense_account")
if not (args.get("account") and args.get("cost_center")) and args.item_code:
args.cost_center, args.account = get_item_details(args)
if not args.account:
return
for budget_against in ["project", "cost_center"] + get_accounting_dimensions():
if (
args.get(budget_against)
and args.account
and frappe.db.get_value("Account", {"name": args.account, "root_type": "Expense"})
):
doctype = frappe.unscrub(budget_against)
if frappe.get_cached_value("DocType", doctype, "is_tree"):
lft, rgt = frappe.db.get_value(doctype, args.get(budget_against), ["lft", "rgt"])
condition = % (
doctype,
lft,
rgt,
budget_against,
) # nosec
args.is_tree = True
else:
condition = "and b.%s=%s" % (budget_against, frappe.db.escape(args.get(budget_against)))
args.is_tree = False
args.budget_against_field = budget_against
args.budget_against_doctype = doctype
budget_records = frappe.db.sql(
.format(
condition=condition, budget_against_field=budget_against
),
(args.fiscal_year, args.account),
as_dict=True,
) # nosec
if budget_records:
validate_budget_records(args, budget_records)
| 494bd9ef78313436f0424b918f200dab8fc7c20b | 19 | budget.py | 538 | style: format code with black | 13,727 | 0 | 83 | 324 | 82 | 64,811 | 123 | erpnext | 33 | erpnext/accounts/doctype/budget/budget.py | Python | 59 | {
"docstring": "and exists(select name from `tab%s`\n\t\t\t\t\twhere lft<=%s and rgt>=%s and name=b.%s)\n\t\t\t\tselect\n\t\t\t\t\tb.{budget_against_field} as budget_against, ba.budget_amount, b.monthly_distribution,\n\t\t\t\t\tifnull(b.applicable_on_material_request, 0) as for_material_request,\n\t\t\t\t\tifnull(applicable_on_purchase_order, 0) as for_purchase_order,\n\t\t\t\t\tifnull(applicable_on_booking_actual_expenses,0) as for_actual_expenses,\n\t\t\t\t\tb.action_if_annual_budget_exceeded, b.action_if_accumulated_monthly_budget_exceeded,\n\t\t\t\t\tb.action_if_annual_budget_exceeded_on_mr, b.action_if_accumulated_monthly_budget_exceeded_on_mr,\n\t\t\t\t\tb.action_if_annual_budget_exceeded_on_po, b.action_if_accumulated_monthly_budget_exceeded_on_po\n\t\t\t\tfrom\n\t\t\t\t\t`tabBudget` b, `tabBudget Account` ba\n\t\t\t\twhere\n\t\t\t\t\tb.name=ba.parent and b.fiscal_year=%s\n\t\t\t\t\tand ba.account=%s and b.docstatus=1\n\t\t\t\t\t{condition}\n\t\t\t",
"language": "en",
"n_whitespaces": 33,
"n_words": 49,
"vocab_size": 38
} | https://github.com/frappe/erpnext.git |
|
5 | load_macros | def load_macros(self, version):
vsbase = r"Software\Microsoft\VisualStudio\%0.1f" % version
self.set_macro("VCInstallDir", vsbase + r"\Setup\VC", "productdir")
self.set_macro("VSInstallDir", vsbase + r"\Setup\VS", "productdir")
net = r"Software\Microsoft\.NETFramework"
self.set_macro("FrameworkDir", net, "installroot")
try:
if version > 7.0:
self.set_macro("FrameworkSDKDir", net, "sdkinstallrootv1.1")
else:
self.set_macro("FrameworkSDKDir", net, "sdkinstallroot")
except KeyError as exc: #
raise DistutilsPlatformError(
)
p = r"Software\Microsoft\NET Framework Setup\Product"
for base in HKEYS:
try:
h = RegOpenKeyEx(base, p)
except RegError:
continue
key = RegEnumKey(h, 0)
d = read_values(base, r"%s\%s" % (p, key))
self.macros["$(FrameworkVersion)"] = d["version"]
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 13 | msvccompiler.py | 255 | add python 3.10.4 for windows | 56,835 | 0 | 296 | 151 | 58 | 222,984 | 75 | XX-Net | 20 | python3.10.4/Lib/distutils/msvccompiler.py | Python | 26 | {
"docstring": "Python was built with Visual Studio 2003;\nextensions must be built with a compiler than can generate compatible binaries.\nVisual Studio 2003 was not found on this system. If you have Cygwin installed,\nyou can try compiling with MingW32, by passing \"-c mingw32\" to setup.py.",
"language": "en",
"n_whitespaces": 41,
"n_words": 45,
"vocab_size": 37
} | https://github.com/XX-net/XX-Net.git |
|
2 | samestat | def samestat(s1, s2):
return (s1.st_ino == s2.st_ino and
s1.st_dev == s2.st_dev)
# Are two filenames really pointing to the same file? | 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 9 | genericpath.py | 43 | add python 3.10.4 for windows | 54,829 | 0 | 37 | 26 | 20 | 217,516 | 21 | XX-Net | 5 | python3.10.4/Lib/genericpath.py | Python | 3 | {
"docstring": "Test whether two stat buffers reference the same file",
"language": "en",
"n_whitespaces": 8,
"n_words": 9,
"vocab_size": 9
} | https://github.com/XX-net/XX-Net.git |
|
11 | batch | def batch(_func=None, max_batch_size=10, batch_wait_timeout_s=0.0):
# `_func` will be None in the case when the decorator is parametrized.
# See the comment at the end of this function for a detailed explanation.
if _func is not None:
if not callable(_func):
raise TypeError(
"@serve.batch can only be used to decorate functions or methods."
)
if not iscoroutinefunction(_func):
raise TypeError("Functions decorated with @serve.batch must be 'async def'")
if not isinstance(max_batch_size, int):
if isinstance(max_batch_size, float) and max_batch_size.is_integer():
max_batch_size = int(max_batch_size)
else:
raise TypeError("max_batch_size must be integer >= 1")
if max_batch_size < 1:
raise ValueError("max_batch_size must be an integer >= 1")
if not isinstance(batch_wait_timeout_s, (float, int)):
raise TypeError("batch_wait_timeout_s must be a float >= 0")
if batch_wait_timeout_s < 0:
raise ValueError("batch_wait_timeout_s must be a float >= 0")
| e5a8b1dd55817305ac85237cd99d8b6ed23df294 | 13 | batching.py | 206 | [Serve] Add API Annotations And Move to _private (#27058) | 28,055 | 0 | 264 | 136 | 78 | 126,078 | 121 | ray | 12 | python/ray/serve/batching.py | Python | 21 | {
"docstring": "Converts a function to asynchronously handle batches.\n\n The function can be a standalone function or a class method. In both\n cases, the function must be `async def` and take a list of objects as\n its sole argument and return a list of the same length as a result.\n\n When invoked, the caller passes a single object. These will be batched\n and executed asynchronously once there is a batch of `max_batch_size`\n or `batch_wait_timeout_s` has elapsed, whichever occurs first.\n\n Example:\n >>> from ray import serve\n >>> @serve.batch(max_batch_size=50, batch_wait_timeout_s=0.5) # doctest: +SKIP\n ... async def handle_batch(batch: List[str]): # doctest: +SKIP\n ... return [s.lower() for s in batch] # doctest: +SKIP\n\n >>> async def handle_single(s: str): # doctest: +SKIP\n ... # Returns s.lower().\n ... return await handle_batch(s) # doctest: +SKIP\n\n Arguments:\n max_batch_size: the maximum batch size that will be executed in\n one call to the underlying function.\n batch_wait_timeout_s: the maximum duration to wait for\n `max_batch_size` elements before running the underlying function.\n ",
"language": "en",
"n_whitespaces": 253,
"n_words": 157,
"vocab_size": 97
} | https://github.com/ray-project/ray.git |
|
3 | convert_example | def convert_example(example, tokenizer, max_seq_length=512, is_test=False):
text_a = example['text_a']
text_b = example.get('text_b', None)
text_a = _tokenize_special_chars(_normalize(text_a))
if text_b is not None:
text_b = _tokenize_special_chars(_normalize(text_b))
encoded_inputs = tokenizer(
text=text_a,
text_pair=text_b,
max_seq_len=max_seq_length,
return_position_ids=True)
input_ids = encoded_inputs['input_ids']
token_type_ids = encoded_inputs['token_type_ids']
position_ids = encoded_inputs['position_ids']
if is_test:
return input_ids, token_type_ids, position_ids
label = np.array([example['label']], dtype='int64')
return input_ids, token_type_ids, position_ids, label
| 15f0aa8f4515ae6cf2ee3ef71f90d533bc9e61b2 | 12 | utils.py | 205 | [ehealth] add sequence classification example | 118,112 | 0 | 132 | 128 | 37 | 322,284 | 54 | PaddleNLP | 22 | examples/biomedical/cblue/sequence_classification/utils.py | Python | 18 | {
"docstring": "\n Builds model inputs from a sequence or a pair of sequences for sequence\n classification tasks by concatenating and adding special tokens. And\n creates a mask from the two sequences for sequence-pair classification\n tasks.\n\n The convention in Electra/EHealth is:\n\n - single sequence:\n input_ids: ``[CLS] X [SEP]``\n token_type_ids: `` 0 0 0``\n position_ids: `` 0 1 2``\n\n - a senquence pair:\n input_ids: ``[CLS] X [SEP] Y [SEP]``\n token_type_ids: `` 0 0 0 1 1``\n position_ids: `` 0 1 2 3 4``\n\n Args:\n example (obj:`dict`):\n A dictionary of input data, containing text and label if it has.\n tokenizer (obj:`PretrainedTokenizer`):\n A tokenizer inherits from :class:`paddlenlp.transformers.PretrainedTokenizer`.\n Users can refer to the superclass for more information.\n max_seq_length (obj:`int`):\n The maximum total input sequence length after tokenization.\n Sequences longer will be truncated, and the shorter will be padded.\n is_test (obj:`bool`, default to `False`):\n Whether the example contains label or not.\n\n Returns:\n input_ids (obj:`list[int]`):\n The list of token ids.\n token_type_ids (obj:`list[int]`):\n List of sequence pair mask.\n position_ids (obj:`list[int]`):\n List of position ids.\n label(obj:`numpy.array`, data type of int64, optional):\n The input label if not is_test.\n ",
"language": "en",
"n_whitespaces": 457,
"n_words": 176,
"vocab_size": 116
} | https://github.com/PaddlePaddle/PaddleNLP.git |
|
4 | accepted_pairs | def accepted_pairs(self) -> List[Dict[str, Any]]:
final = []
for pair, info in self._cached_pairs.items():
if (info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and
info.winrate > float(self.edge_config.get('minimum_winrate', 0.60))):
final.append({
'Pair': pair,
'Winrate': info.winrate,
'Expectancy': info.expectancy,
'Stoploss': info.stoploss,
})
return final
| 6024fa482e1b09bae8e85b3afc9fc58e483c1512 | 15 | edge_positioning.py | 168 | Use brackets to break IF lines | 34,375 | 0 | 199 | 107 | 32 | 149,135 | 35 | freqtrade | 18 | freqtrade/edge/edge_positioning.py | Python | 15 | {
"docstring": "\n return a list of accepted pairs along with their winrate, expectancy and stoploss\n ",
"language": "en",
"n_whitespaces": 28,
"n_words": 13,
"vocab_size": 13
} | https://github.com/freqtrade/freqtrade.git |
|
1 | get_remote_url | def get_remote_url(cls, location):
# type: (str) -> str
raise NotImplementedError
| f638f5d0e6c8ebed0e69a6584bc7f003ec646580 | 6 | versioncontrol.py | 19 | upd; format | 12,560 | 0 | 31 | 10 | 10 | 61,416 | 10 | transferlearning | 4 | .venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py | Python | 2 | {
"docstring": "\n Return the url used at location\n\n Raises RemoteNotFoundError if the repository does not have a remote\n url configured.\n ",
"language": "en",
"n_whitespaces": 47,
"n_words": 18,
"vocab_size": 16
} | https://github.com/jindongwang/transferlearning.git |
|
12 | answer_drop_tables | def answer_drop_tables(self, statement):
if statement.if_exists is False:
for table in statement.tables:
if len(table.parts) > 1:
db_name = table.parts[0]
else:
db_name = self.session.database
if db_name not in ['files', 'mindsdb']:
raise SqlApiException(f"Cannot delete a table from database '{db_name}'")
table_name = table.parts[-1]
dn = self.session.datahub[db_name]
if dn.has_table(table_name) is False:
raise SqlApiException(f"Cannot delete a table from database '{db_name}': table does not exists")
for table in statement.tables:
if len(table.parts) > 1:
db_name = table.parts[0]
else:
db_name = self.session.database
if db_name not in ['files', 'mindsdb']:
raise SqlApiException(f"Cannot delete a table from database '{db_name}'")
table_name = table.parts[-1]
dn = self.session.datahub[db_name]
if dn.has_table(table_name):
if db_name == 'mindsdb':
self.session.datahub['mindsdb'].delete_predictor(table_name)
elif db_name == 'files':
self.session.data_store.delete_file(table_name)
return SQLAnswer(ANSWER_TYPE.OK)
| 01b47406a29d17781356badb20f49f2fdc24d00e | 16 | mysql_proxy.py | 366 | 'drop table' query | 25,199 | 0 | 491 | 217 | 46 | 114,473 | 107 | mindsdb | 22 | mindsdb/api/mysql/mysql_proxy/mysql_proxy.py | Python | 28 | {
"docstring": " answer on 'drop table [if exists] {name}'\n Args:\n statement: ast\n ",
"language": "en",
"n_whitespaces": 44,
"n_words": 10,
"vocab_size": 10
} | https://github.com/mindsdb/mindsdb.git |
|
2 | validate | def validate(self, num_steps=None, profile=False, reduce_results=True, info=None):
worker_stats = self.worker_group.validate(
num_steps=num_steps, profile=profile, info=info
)
if reduce_results:
return self._process_stats(worker_stats)
else:
return worker_stats
| 7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065 | 9 | torch_trainer.py | 85 | [CI] Format Python code with Black (#21975)
See #21316 and #21311 for the motivation behind these changes. | 29,985 | 0 | 88 | 56 | 18 | 133,353 | 20 | ray | 9 | python/ray/util/sgd/torch/torch_trainer.py | Python | 8 | {
"docstring": "Evaluates the model on the validation data set.\n\n Args:\n num_steps (int): Number of batches to compute update steps on\n per worker. This corresponds also to the number of times\n ``TrainingOperator.validate_batch`` is called per worker.\n profile (bool): Returns time stats for the evaluation procedure.\n reduce_results (bool): Whether to average all metrics across\n all workers into one dict. If a metric is a non-numerical\n value (or nested dictionaries), one value will be randomly\n selected among the workers. If False, returns a list of dicts.\n info (dict): Optional dictionary passed to the training\n operator for `validate` and `validate_batch`.\n\n Returns:\n A dictionary of metrics for validation.\n You can provide custom metrics by passing in a custom\n ``training_operator_cls``.\n ",
"language": "en",
"n_whitespaces": 309,
"n_words": 113,
"vocab_size": 84
} | https://github.com/ray-project/ray.git |
|
2 | _Net_set_input_arrays | def _Net_set_input_arrays(self, data, labels):
if labels.ndim == 1:
labels = np.ascontiguousarray(labels[:, np.newaxis, np.newaxis,
np.newaxis])
return self._set_input_arrays(data, labels)
| cc4d0564756ca067516f71718a3d135996525909 | 12 | pycaffe.py | 74 | Balanced joint maximum mean discrepancy for deep transfer learning | 12,064 | 0 | 77 | 49 | 16 | 60,284 | 17 | transferlearning | 9 | code/deep/BJMMD/caffe/python/caffe/pycaffe.py | Python | 5 | {
"docstring": "\n Set input arrays of the in-memory MemoryDataLayer.\n (Note: this is only for networks declared with the memory data layer.)\n ",
"language": "en",
"n_whitespaces": 29,
"n_words": 19,
"vocab_size": 18
} | https://github.com/jindongwang/transferlearning.git |
|
1 | test_multi_trial_reuse | def test_multi_trial_reuse(ray_start_4_cpus_extra):
os.environ["TUNE_MAX_PENDING_TRIALS_PG"] = "2"
register_trainable("foo2", MyResettableClass)
# We sleep here for one second so that the third actor
# does not finish training before the fourth can be scheduled.
# This helps ensure that both remote runners are re-used and
# not just one.
[trial1, trial2, trial3, trial4] = tune.run(
"foo2",
config={
"message": tune.grid_search(["First", "Second", "Third", "Fourth"]),
"id": -1,
"sleep": 2,
},
reuse_actors=True,
resources_per_trial={"cpu": 2},
).trials
assert trial3.last_result["num_resets"] == 1
assert trial4.last_result["num_resets"] == 1
| 1510fb2cd631b2776092fb45ee4082e5e65f16f8 | 16 | test_actor_reuse.py | 175 | [air/tune] Internal resource management 2 - Ray Tune to use new Ray AIR resource manager (#30016)
Includes/depends on #30777
TLDR: This PR refactors Ray Tune's resource management to use a central AIR resource management package instead of the tightly coupled PlacementGroupManager.
Ray Tune's resource management currently uses a tightly coupled placement group manager. This leads to a number of shortcomings:
- The tight coupling on the manager side (e.g. PG manager keeps track of trials) prevents re-usability
- The tight coupling on the trial executor side prevents using different resource management strategies (e.g. shared or budget-based)
- It's hard to test independently. Tests for the resource management require a simulated tune setup.
To improve stability, extensibility, and maintainability, this PR moves the resource management logic into a central `ray.air.execution.resources` subpackage. The resource management has a simple API that works with `ResourceRequest`s and `AllocatedResources` to manage requested and assigned resources, respectively. The actual resource management can then be anything - per default it is a placement group based manager, but this PR also introduces a PoC budget-based manager that can be plugged in.
The PR does not substantially change existing tests, so we can be certain that the new resource model is a fully compatible replacement for the old placement group manager.
Signed-off-by: Kai Fricke <kai@anyscale.com> | 31,311 | 0 | 176 | 100 | 65 | 138,087 | 75 | ray | 18 | python/ray/tune/tests/test_actor_reuse.py | Python | 15 | {
"docstring": "Test that actors from multiple trials running in parallel will be reused.\n\n - 2 trials can run at the same time\n - Trial 3 will be scheduled after trial 1 succeeded, so will reuse actor\n - Trial 4 will be scheduled after trial 2 succeeded, so will reuse actor\n ",
"language": "en",
"n_whitespaces": 61,
"n_words": 49,
"vocab_size": 31
} | https://github.com/ray-project/ray.git |
|
1 | test_get_dynamic_sampling_default_biases | def test_get_dynamic_sampling_default_biases(self):
with Feature(
{
self.new_ds_flag: True,
}
):
response = self.get_success_response(
self.organization.slug, self.project.slug, method="get"
)
assert response.data["dynamicSamplingBiases"] == DEFAULT_BIASES
| 6fc6106b6a57149a5bae3c0f4677349cfbae1155 | 12 | test_project_details.py | 84 | fix(dyn-sampling): Backend code clean up (#42001)
We are consolidating server-side-sampling and dynamic-sampling flags
into only dynamic-sampling. The flag is being controlled by plan | 18,532 | 0 | 126 | 50 | 20 | 89,350 | 20 | sentry | 12 | tests/sentry/api/endpoints/test_project_details.py | Python | 10 | {
"docstring": "\n Tests the case when organization on AM2 plan, but haven't manipulated the bias toggles\n yet, so they get the default biases.\n ",
"language": "en",
"n_whitespaces": 43,
"n_words": 21,
"vocab_size": 19
} | https://github.com/getsentry/sentry.git |
|
6 | remove_widget | def remove_widget(self, widget):
if widget not in self.children:
return
self.children.remove(widget)
if widget.canvas in self.canvas.children:
self.canvas.remove(widget.canvas)
elif widget.canvas in self.canvas.after.children:
self.canvas.after.remove(widget.canvas)
elif widget.canvas in self.canvas.before.children:
self.canvas.before.remove(widget.canvas)
for type_id in widget.motion_filter:
self.unregister_for_motion_event(type_id, widget)
widget.funbind('motion_filter', self._update_motion_filter)
widget.parent = None
widget.dec_disabled(self._disabled_count)
| 1830123ba3edf7290b7c6cb1c6f406ccf1d0e5d4 | 12 | widget.py | 213 | Feature: EventManagerBase (#7658)
* Added EventManagerBase class and event_managers attribute to WindowBase class.
* Added on_motion event to Widget class.
* Updated post_dispatch_input in EventLoopBase to skip non-touch events.
* Using type ids in MouseMotionEventProvider.
* Added on_motion method to Widget subclasses.
* Updated Widget.on_motion method to dispatch to filtered widgets if 'pos' is not in me.profile.
* Changed motion_filter property in Widget to store key to list values.
* Updated Widget.on_motion to not dispatch event to children if widget is disabled.
* Widget: Using flags to control dispatching in on_motion method.
* Widget: Don't dispatch on_motion to children if only self is registered.
* Widget: Removed collision on disabled check from on_motion method.
* Widget: Added docstrings for motion_filter and related methods.
* EventManager: Moved motion event flags to eventmanager/__init__.py module.
* ScreenManager: Overrode the on_motion method.
* WindowBase: Using attributes event_managers and event_managers_dict.
* WindowBase: Added doc for register_event_manager and unregister_event_manager methods.
* Widget: Improved default dispatch to stop after the last registered widgets.
* EventManagerBase: Added initial docs class and module.
* Widget: Added experimental warnings to motion_filter property and to on_motion and (un)register_for_motion_event methods.
* WindowBase: Added docs for event_managers and event_managers_dict attributes.
* MotionEvent: Added type_id and flags to push_attrs list.
* EventManagerBase: Added versionadded tag on all flags.
* EventManagerBase: Use dispatch modes instead of flags. | 46,984 | 0 | 162 | 134 | 29 | 194,460 | 37 | kivy | 16 | kivy/uix/widget.py | Python | 15 | {
"docstring": "Remove a widget from the children of this widget.\n\n :Parameters:\n `widget`: :class:`Widget`\n Widget to remove from our children list.\n\n .. code-block:: python\n\n >>> from kivy.uix.button import Button\n >>> root = Widget()\n >>> button = Button()\n >>> root.add_widget(button)\n >>> root.remove_widget(button)\n ",
"language": "en",
"n_whitespaces": 117,
"n_words": 39,
"vocab_size": 31
} | https://github.com/kivy/kivy.git |
|
3 | mixin_base_ppr_parser | def mixin_base_ppr_parser(parser):
mixin_essential_parser(parser)
gp = add_arg_group(parser, title='Base Deployment')
gp.add_argument(
'--extra-search-paths',
type=str,
default=[],
nargs='*',
help='Extra search paths to be used when loading modules and finding YAML config files.'
if _SHOW_ALL_ARGS
else argparse.SUPPRESS,
)
gp.add_argument(
'--timeout-ctrl',
type=int,
default=int(os.getenv('JINA_DEFAULT_TIMEOUT_CTRL', '60')),
help='The timeout in milliseconds of the control request, -1 for waiting forever',
)
parser.add_argument(
'--k8s-namespace',
type=str,
help='Name of the namespace where Kubernetes deployment should be deployed, to be filled by flow name'
if _SHOW_ALL_ARGS
else argparse.SUPPRESS,
)
gp.add_argument(
'--polling',
type=str,
default=PollingType.ANY.name,
help=,
)
| a3b71c7208b3cd48aa7bc978c3343a074947e3d9 | 13 | base.py | 202 | fix(parsers): clearify flow args (#4701) | 2,215 | 0 | 253 | 123 | 64 | 12,207 | 80 | jina | 21 | jina/parsers/orchestrate/base.py | Python | 41 | {
"docstring": "Mixing in arguments required by pod/deployment/runtime module into the given parser.\n :param parser: the parser instance to which we add arguments\n \n The polling strategy of the Deployment and its endpoints (when `shards>1`).\n Can be defined for all endpoints of a Deployment or by endpoint.\n Define per Deployment:\n - ANY: only one (whoever is idle) Pod polls the message\n - ALL: all Pods poll the message (like a broadcast)\n Define per Endpoint:\n JSON dict, {endpoint: PollingType}\n {'/custom': 'ALL', '/search': 'ANY', '*': 'ANY'}\n \n ",
"language": "en",
"n_whitespaces": 119,
"n_words": 81,
"vocab_size": 66
} | https://github.com/jina-ai/jina.git |
|
7 | calc | def calc(term):
# This part is for reading and converting arithmetic terms.
term = term.replace(" ", "")
term = term.replace("^", "**")
term = term.replace("=", "")
term = term.replace("?", "")
term = term.replace("%", "/100.00")
term = term.replace("rad", "radians")
term = term.replace("mod", "%")
term = term.replace("aval", "abs")
functions = [
"sin",
"cos",
"tan",
"pow",
"cosh",
"sinh",
"tanh",
"sqrt",
"pi",
"radians",
"e",
]
# This part is for reading and converting function expressions.
term = term.lower()
for func in functions:
if func in term:
withmath = "math." + func
term = term.replace(func, withmath)
try:
# here goes the actual evaluating.
term = eval(term)
# here goes to the error cases.
except ZeroDivisionError:
print("Can't divide by 0. Please try again.")
except NameError:
print("Invalid input. Please try again")
except AttributeError:
print("Please check usage method and try again.")
except TypeError:
print("please enter inputs of correct datatype ")
return term
| f0af0c43340763724f139fa68aa1e5a9ffe458b4 | 12 | calculator.py | 345 | refactor: clean code
Signed-off-by: slowy07 <slowy.arfy@gmail.com> | 4,373 | 0 | 359 | 182 | 93 | 22,594 | 143 | Python | 13 | calculator.py | Python | 38 | {
"docstring": "\n input: term of type str\n output: returns the result of the computed term.\n purpose: This function is the actual calculator and the heart of the application\n ",
"language": "en",
"n_whitespaces": 39,
"n_words": 26,
"vocab_size": 20
} | https://github.com/geekcomputers/Python.git |
|
1 | test_song_from_dict | def test_song_from_dict():
song = Song.from_dict(
{
"name": "Ropes",
"artists": ["Dirty Palm", "Chandler Jewels"],
"album_name": "Ropes",
"album_artist": "Dirty Palm",
"genres": ["gaming edm", "melbourne bounce international"],
"disc_number": 1,
"duration": 188,
"year": 2021,
"date": "2021-10-28",
"track_number": 1,
"tracks_count": 1,
"isrc": "GB2LD2110301",
"song_id": "1t2qKa8K72IBC8yQlhD9bU",
"cover_url": "https://i.scdn.co/image/ab67616d0000b273fe2cb38e4d2412dbb0e54332",
"explicit": False,
"download_url": None,
"artist": "Dirty Palm",
"disc_count": 1,
"copyright": "",
"publisher": "",
"url": "https://open.spotify.com/track/1t2qKa8K72IBC8yQlhD9bU",
}
)
assert song.name == "Ropes"
assert song.artists == ["Dirty Palm", "Chandler Jewels"]
assert song.album_name == "Ropes"
assert song.album_artist == "Dirty Palm"
assert song.genres == ["gaming edm", "melbourne bounce international"]
assert song.disc_number == 1
assert song.duration == 188
assert song.year == 2021
assert song.date == "2021-10-28"
assert song.track_number == 1
assert song.tracks_count == 1
assert song.isrc == "GB2LD2110301"
assert song.song_id == "1t2qKa8K72IBC8yQlhD9bU"
assert (
song.cover_url
== "https://i.scdn.co/image/ab67616d0000b273fe2cb38e4d2412dbb0e54332"
)
assert song.explicit == False
| fa2ad657482aca9dc628e6d7062b8badf2706bb6 | 12 | test_song.py | 384 | v4 init | 5,349 | 0 | 445 | 206 | 81 | 30,148 | 129 | spotify-downloader | 19 | tests/types/test_song.py | Python | 44 | {
"docstring": "\n Tests if Song.from_dict() works correctly.\n ",
"language": "en",
"n_whitespaces": 12,
"n_words": 5,
"vocab_size": 5
} | https://github.com/spotDL/spotify-downloader.git |
|
3 | _get_states_count_upstream_ti | def _get_states_count_upstream_ti(ti, finished_tis):
counter = Counter(task.state for task in finished_tis if task.task_id in ti.task.upstream_task_ids)
return (
counter.get(State.SUCCESS, 0),
counter.get(State.SKIPPED, 0),
counter.get(State.FAILED, 0),
counter.get(State.UPSTREAM_FAILED, 0),
sum(counter.values()),
)
| 99f86ccfa59df6aa1aa33afce5e0b66dd5df9a3d | 12 | trigger_rule_dep.py | 127 | Some refactoring work on scheduling code (#21414) | 8,298 | 0 | 109 | 86 | 22 | 44,559 | 26 | airflow | 17 | airflow/ti_deps/deps/trigger_rule_dep.py | Python | 9 | {
"docstring": "\n This function returns the states of the upstream tis for a specific ti in order to determine\n whether this ti can run in this iteration\n\n :param ti: the ti that we want to calculate deps for\n :param finished_tis: all the finished tasks of the dag_run\n ",
"language": "en",
"n_whitespaces": 81,
"n_words": 45,
"vocab_size": 33
} | https://github.com/apache/airflow.git |
|
2 | fit | def fit(self, X, y=None):
# Validating the scalar parameters.
check_scalar(
self.threshold,
"threshold",
target_type=numbers.Real,
min_val=0.0,
include_boundaries="neither",
)
check_scalar(
self.branching_factor,
"branching_factor",
target_type=numbers.Integral,
min_val=1,
include_boundaries="neither",
)
if isinstance(self.n_clusters, numbers.Number):
check_scalar(
self.n_clusters,
"n_clusters",
target_type=numbers.Integral,
min_val=1,
)
# TODO: Remove deprecated flags in 1.2
self._deprecated_fit, self._deprecated_partial_fit = True, False
return self._fit(X, partial=False)
| ee5a1b69d1dfa99635a10f0a5b54ec263cedf866 | 11 | _birch.py | 171 | DOC, MNT Typos found by codespell (#22906) | 75,706 | 0 | 309 | 113 | 39 | 259,315 | 47 | scikit-learn | 20 | sklearn/cluster/_birch.py | Python | 24 | {
"docstring": "\n Build a CF Tree for the input data.\n\n Parameters\n ----------\n X : {array-like, sparse matrix} of shape (n_samples, n_features)\n Input data.\n\n y : Ignored\n Not used, present here for API consistency by convention.\n\n Returns\n -------\n self\n Fitted estimator.\n ",
"language": "en",
"n_whitespaces": 135,
"n_words": 38,
"vocab_size": 35
} | https://github.com/scikit-learn/scikit-learn.git |
|
3 | load | def load(self):
for key in sorted(self._alignments.data):
this_frame_faces = []
for item in self._alignments.data[key]["faces"]:
face = DetectedFace()
face.from_alignment(item, with_thumb=True)
face.load_aligned(None)
_ = face.aligned.average_distance # cache the distances
this_frame_faces.append(face)
self._frame_faces.append(this_frame_faces)
self._sorted_frame_names = sorted(self._alignments.data)
| 23d92c1f0d83ce1cdcc51480cfe37af074a981b3 | 12 | detected_faces.py | 149 | Bugfixes
- Sort - Fix rare help-text parsing bug
- Manual - Fix issue where frame count is incorrect when een > 1 used on extract | 19,790 | 0 | 161 | 91 | 26 | 100,289 | 31 | faceswap | 19 | tools/manual/detected_faces.py | Python | 11 | {
"docstring": " Load the faces from the alignments file, convert to\n :class:`~lib.align.DetectedFace`. objects and add to :attr:`_frame_faces`. ",
"language": "en",
"n_whitespaces": 23,
"n_words": 15,
"vocab_size": 13
} | https://github.com/deepfakes/faceswap.git |
|
1 | get_assessment_criteria | def get_assessment_criteria(course):
return frappe.get_all(
"Course Assessment Criteria",
fields=["assessment_criteria", "weightage"],
filters={"parent": course},
order_by="idx",
)
@frappe.whitelist() | 494bd9ef78313436f0424b918f200dab8fc7c20b | @frappe.whitelist() | 11 | api.py | 72 | style: format code with black | 14,035 | 1 | 6 | 34 | 14 | 65,846 | 14 | erpnext | 8 | erpnext/education/api.py | Python | 7 | {
"docstring": "Returns Assessmemt Criteria and their Weightage from Course Master.\n\n\t:param Course: Course\n\t",
"language": "en",
"n_whitespaces": 10,
"n_words": 12,
"vocab_size": 11
} | https://github.com/frappe/erpnext.git |
7 | new_compiler | def new_compiler(plat=None, compiler=None, verbose=0, dry_run=0, force=0):
if plat is None:
plat = os.name
try:
if compiler is None:
compiler = get_default_compiler(plat)
(module_name, class_name, long_description) = compiler_class[compiler]
except KeyError:
msg = "don't know how to compile C/C++ code on platform '%s'" % plat
if compiler is not None:
msg = msg + " with '%s' compiler" % compiler
raise DistutilsPlatformError(msg)
try:
module_name = "distutils." + module_name
__import__ (module_name)
module = sys.modules[module_name]
klass = vars(module)[class_name]
except ImportError:
raise DistutilsModuleError(
"can't compile C/C++ code: unable to load module '%s'" % \
module_name)
except KeyError:
raise DistutilsModuleError(
"can't compile C/C++ code: unable to find class '%s' "
"in module '%s'" % (class_name, module_name))
# XXX The None is necessary to preserve backwards compatibility
# with classes that expect verbose to be the first positional
# argument.
return klass(None, dry_run, force)
| 8198943edd73a363c266633e1aa5b2a9e9c9f526 | 14 | ccompiler.py | 242 | add python 3.10.4 for windows | 56,657 | 0 | 329 | 148 | 83 | 222,589 | 136 | XX-Net | 24 | python3.10.4/Lib/distutils/ccompiler.py | Python | 26 | {
"docstring": "Generate an instance of some CCompiler subclass for the supplied\n platform/compiler combination. 'plat' defaults to 'os.name'\n (eg. 'posix', 'nt'), and 'compiler' defaults to the default compiler\n for that platform. Currently only 'posix' and 'nt' are supported, and\n the default compilers are \"traditional Unix interface\" (UnixCCompiler\n class) and Visual C++ (MSVCCompiler class). Note that it's perfectly\n possible to ask for a Unix compiler object under Windows, and a\n Microsoft compiler object under Unix -- if you supply a value for\n 'compiler', 'plat' is ignored.\n ",
"language": "en",
"n_whitespaces": 113,
"n_words": 83,
"vocab_size": 59
} | https://github.com/XX-net/XX-Net.git |
|
1 | register | def register(config_class, feature_extractor_class):
FEATURE_EXTRACTOR_MAPPING.register(config_class, feature_extractor_class)
| 2e11a043374a6229ec129a4765ee4ba7517832b9 | 7 | feature_extraction_auto.py | 27 | Register feature extractor (#15634)
* Rework AutoFeatureExtractor.from_pretrained internal
* Custom feature extractor
* Add more tests
* Add support for custom feature extractor code
* Clean up
* Add register API to AutoFeatureExtractor | 6,418 | 0 | 19 | 16 | 5 | 35,173 | 5 | transformers | 4 | src/transformers/models/auto/feature_extraction_auto.py | Python | 2 | {
"docstring": "\n Register a new feature extractor for this class.\n\n Args:\n config_class ([`PretrainedConfig`]):\n The configuration corresponding to the model to register.\n feature_extractor_class ([`FeatureExtractorMixin`]): The feature extractor to register.\n ",
"language": "en",
"n_whitespaces": 85,
"n_words": 26,
"vocab_size": 20
} | https://github.com/huggingface/transformers.git |
|
8 | execute | def execute():
if not frappe.get_all("Pricing Rule", limit=1):
return
frappe.reload_doc("accounts", "doctype", "pricing_rule_detail")
doctypes = {
"Supplier Quotation": "buying",
"Purchase Order": "buying",
"Purchase Invoice": "accounts",
"Purchase Receipt": "stock",
"Quotation": "selling",
"Sales Order": "selling",
"Sales Invoice": "accounts",
"Delivery Note": "stock",
}
for doctype, module in doctypes.items():
frappe.reload_doc(module, "doctype", frappe.scrub(doctype))
child_doc = frappe.scrub(doctype) + "_item"
frappe.reload_doc(module, "doctype", child_doc, force=True)
child_doctype = doctype + " Item"
frappe.db.sql(
.format(
child_doctype=child_doctype
)
)
data = frappe.db.sql(
.format(
child_doc=child_doctype
),
as_dict=1,
)
values = []
for d in data:
values.append(
(
d.pricing_rule,
d.name,
d.parent,
"pricing_rules",
d.parenttype,
d.creation,
d.modified,
d.docstatus,
d.modified_by,
d.owner,
frappe.generate_hash("", 10),
)
)
if values:
frappe.db.sql(
.format(
values=", ".join(["%s"] * len(values))
),
tuple(values),
)
frappe.reload_doc("accounts", "doctype", "pricing_rule")
for doctype, apply_on in {
"Pricing Rule Item Code": "Item Code",
"Pricing Rule Item Group": "Item Group",
"Pricing Rule Brand": "Brand",
}.items():
frappe.reload_doc("accounts", "doctype", frappe.scrub(doctype))
field = frappe.scrub(apply_on)
data = frappe.get_all(
"Pricing Rule",
fields=[field, "name", "creation", "modified", "owner", "modified_by"],
filters={"apply_on": apply_on},
)
values = []
for d in data:
values.append(
(
d.get(field),
d.name,
parentfield.get(field),
"Pricing Rule",
d.creation,
d.modified,
d.owner,
d.modified_by,
frappe.generate_hash("", 10),
)
)
if values:
frappe.db.sql(
.format(
doctype=doctype, field=field, values=", ".join(["%s"] * len(values))
),
tuple(values),
)
| 494bd9ef78313436f0424b918f200dab8fc7c20b | 19 | update_pricing_rule_fields.py | 756 | style: format code with black | 14,303 | 0 | 99 | 450 | 106 | 66,703 | 188 | erpnext | 40 | erpnext/patches/v12_0/update_pricing_rule_fields.py | Python | 100 | {
"docstring": " UPDATE `tab{child_doctype}` SET pricing_rules = pricing_rule\n\t\t\tWHERE docstatus < 2 and pricing_rule is not null and pricing_rule != ''\n\t\t SELECT pricing_rule, name, parent,\n\t\t\t\tparenttype, creation, modified, docstatus, modified_by, owner, name\n\t\t\tFROM `tab{child_doc}` where docstatus < 2 and pricing_rule is not null\n\t\t\tand pricing_rule != '' INSERT INTO\n\t\t\t\t`tabPricing Rule Detail` (`pricing_rule`, `child_docname`, `parent`, `parentfield`, `parenttype`,\n\t\t\t\t`creation`, `modified`, `docstatus`, `modified_by`, `owner`, `name`)\n\t\t\tVALUES {values} INSERT INTO\n\t\t\t\t`tab{doctype}` ({field}, parent, parentfield, parenttype, creation, modified,\n\t\t\t\t\towner, modified_by, name)\n\t\t\tVALUES {values} ",
"language": "en",
"n_whitespaces": 69,
"n_words": 77,
"vocab_size": 52
} | https://github.com/frappe/erpnext.git |
|
2 | test_state_aggregate_option_behavior | def test_state_aggregate_option_behavior(master_opts):
minion_opts = salt.config.DEFAULT_MINION_OPTS.copy()
possible = [None, True, False, ["pkg"]]
expected_result = [
True,
False,
["pkg"],
True,
True,
["pkg"],
False,
True,
["pkg"],
["pkg"],
True,
["pkg"],
]
for idx, combo in enumerate(itertools.permutations(possible, 2)):
master_opts["state_aggregate"], minion_opts["state_aggregate"] = combo
state_obj = salt.state.BaseHighState
state_obj.client = MockBaseHighStateClient(master_opts)
return_result = state_obj(minion_opts)._BaseHighState__gen_opts(minion_opts)
assert expected_result[idx] == return_result["state_aggregate"]
| 8168b25fe5906883a07de5bfdfefabc6d1f57784 | 12 | test_state_options.py | 209 | fixes saltstack/salt#61478 state_aggregate minion option not respected | 54,314 | 0 | 187 | 132 | 32 | 215,998 | 50 | salt | 21 | tests/pytests/unit/state/test_state_options.py | Python | 23 | {
"docstring": "\n Ensure state_aggregate can be overridden on the minion\n ",
"language": "en",
"n_whitespaces": 15,
"n_words": 8,
"vocab_size": 8
} | https://github.com/saltstack/salt.git |
|
2 | register | def register(cls, map_function, reduce_function=None, **kwargs):
if reduce_function is None:
reduce_function = map_function
return cls.call(map_function, reduce_function, **kwargs)
| 58bbcc37477866d19c8b092a0e1974a4f0baa586 | 8 | tree_reduce.py | 54 | REFACTOR-#2656: Update modin to fit algebra (code only) (#3717)
Co-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>
Co-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com>
Co-authored-by: Alexey Prutskov <alexey.prutskov@intel.com>
Co-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>
Signed-off-by: Rehan Durrani <rehan@ponder.io> | 35,228 | 0 | 48 | 35 | 15 | 153,044 | 16 | modin | 6 | modin/core/dataframe/algebra/tree_reduce.py | Python | 4 | {
"docstring": "\n Build TreeReduce function.\n\n Parameters\n ----------\n map_function : callable(pandas.DataFrame) -> [pandas.DataFrame, pandas.Series]\n Source map function.\n reduce_function : callable(pandas.DataFrame) -> pandas.Series, optional\n Source reduce function. If not specified `map_function` will be used.\n **kwargs : dict\n Additional parameters to pass to the builder function.\n\n Returns\n -------\n callable\n Function that takes query compiler and executes passed functions\n with TreeReduce algorithm.\n ",
"language": "en",
"n_whitespaces": 182,
"n_words": 56,
"vocab_size": 46
} | https://github.com/modin-project/modin.git |
|
3 | trustworthiness | def trustworthiness(X, X_embedded, *, n_neighbors=5, metric="euclidean"):
r
n_samples = X.shape[0]
if n_neighbors >= n_samples / 2:
raise ValueError(
f"n_neighbors ({n_neighbors}) should be less than n_samples / 2"
f" ({n_samples / 2})"
)
dist_X = pairwise_distances(X, metric=metric)
if metric == "precomputed":
dist_X = dist_X.copy()
# we set the diagonal to np.inf to exclude the points themselves from
# their own neighborhood
np.fill_diagonal(dist_X, np.inf)
ind_X = np.argsort(dist_X, axis=1)
# `ind_X[i]` is the index of sorted distances between i and other samples
ind_X_embedded = (
NearestNeighbors(n_neighbors=n_neighbors)
.fit(X_embedded)
.kneighbors(return_distance=False)
)
# We build an inverted index of neighbors in the input space: For sample i,
# we define `inverted_index[i]` as the inverted index of sorted distances:
# inverted_index[i][ind_X[i]] = np.arange(1, n_sample + 1)
inverted_index = np.zeros((n_samples, n_samples), dtype=int)
ordered_indices = np.arange(n_samples + 1)
inverted_index[ordered_indices[:-1, np.newaxis], ind_X] = ordered_indices[1:]
ranks = (
inverted_index[ordered_indices[:-1, np.newaxis], ind_X_embedded] - n_neighbors
)
t = np.sum(ranks[ranks > 0])
t = 1.0 - t * (
2.0 / (n_samples * n_neighbors * (2.0 * n_samples - 3.0 * n_neighbors - 1.0))
)
return t
| ade90145c9c660a1a7baf2315185995899b0f356 | 16 | _t_sne.py | 352 | FIX Raise error when n_neighbors >= n_samples / 2 in manifold.trustworthiness (#23033)
Co-authored-by: Shao Yang Hong <hongsy2006@gmail.com>
Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> | 75,842 | 0 | 322 | 228 | 115 | 259,640 | 173 | scikit-learn | 32 | sklearn/manifold/_t_sne.py | Python | 84 | {
"docstring": "Expresses to what extent the local structure is retained.\n\n The trustworthiness is within [0, 1]. It is defined as\n\n .. math::\n\n T(k) = 1 - \\frac{2}{nk (2n - 3k - 1)} \\sum^n_{i=1}\n \\sum_{j \\in \\mathcal{N}_{i}^{k}} \\max(0, (r(i, j) - k))\n\n where for each sample i, :math:`\\mathcal{N}_{i}^{k}` are its k nearest\n neighbors in the output space, and every sample j is its :math:`r(i, j)`-th\n nearest neighbor in the input space. In other words, any unexpected nearest\n neighbors in the output space are penalised in proportion to their rank in\n the input space.\n\n Parameters\n ----------\n X : ndarray of shape (n_samples, n_features) or (n_samples, n_samples)\n If the metric is 'precomputed' X must be a square distance\n matrix. Otherwise it contains a sample per row.\n\n X_embedded : ndarray of shape (n_samples, n_components)\n Embedding of the training data in low-dimensional space.\n\n n_neighbors : int, default=5\n The number of neighbors that will be considered. Should be fewer than\n `n_samples / 2` to ensure the trustworthiness to lies within [0, 1], as\n mentioned in [1]_. An error will be raised otherwise.\n\n metric : str or callable, default='euclidean'\n Which metric to use for computing pairwise distances between samples\n from the original input space. If metric is 'precomputed', X must be a\n matrix of pairwise distances or squared distances. Otherwise, for a list\n of available metrics, see the documentation of argument metric in\n `sklearn.pairwise.pairwise_distances` and metrics listed in\n `sklearn.metrics.pairwise.PAIRWISE_DISTANCE_FUNCTIONS`. Note that the\n \"cosine\" metric uses :func:`~sklearn.metrics.pairwise.cosine_distances`.\n\n .. versionadded:: 0.20\n\n Returns\n -------\n trustworthiness : float\n Trustworthiness of the low-dimensional embedding.\n\n References\n ----------\n .. [1] Jarkko Venna and Samuel Kaski. 2001. Neighborhood\n Preservation in Nonlinear Projection Methods: An Experimental Study.\n In Proceedings of the International Conference on Artificial Neural Networks\n (ICANN '01). Springer-Verlag, Berlin, Heidelberg, 485-491.\n\n .. [2] Laurens van der Maaten. Learning a Parametric Embedding by Preserving\n Local Structure. Proceedings of the Twelth International Conference on\n Artificial Intelligence and Statistics, PMLR 5:384-391, 2009.\n ",
"language": "en",
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} | https://github.com/scikit-learn/scikit-learn.git |