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semeru

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code-text-galeras-code-summarization-3k-deduped

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Semeru Lab 7

get_annotations

def get_annotations(obj, *, globals=None, locals=None, eval_str=False): if isinstance(obj, type): # class obj_dict = getattr(obj, '__dict__', None) if obj_dict and hasattr(obj_dict, 'get'): ann = obj_dict.get('__annotations__', None) if isinstance(ann, types.GetSetDescriptorType): ann = None else: ann = None obj_globals = None module_name = getattr(obj, '__module__', None) if module_name: module = sys.modules.get(module_name, None) if module: obj_globals = getattr(module, '__dict__', None) obj_locals = dict(vars(obj)) unwrap = obj elif isinstance(obj, types.ModuleType): # module ann = getattr(obj, '__annotations__', None) obj_globals = getattr(obj, '__dict__') obj_locals = None unwrap = None elif callable(obj): # this includes types.Function, types.BuiltinFunctionType, # types.BuiltinMethodType, functools.partial, functools.singledispatch, # "class funclike" from Lib/test/test_inspect... on and on it goes. ann = getattr(obj, '__annotations__', None) obj_globals = getattr(obj, '__globals__', None) obj_locals = None unwrap = obj else: raise TypeError(f"{obj!r} is not a module, class, or callable.") if ann is None: return {} if not isinstance(ann, dict): raise ValueError(f"{obj!r}.__annotations__ is neither a dict nor None") if not ann: return {} if not eval_str: return dict(ann) if unwrap is not None: while True: if hasattr(unwrap, '__wrapped__'): unwrap = unwrap.__wrapped__ continue if isinstance(unwrap, functools.partial): unwrap = unwrap.func continue break if hasattr(unwrap, "__globals__"): obj_globals = unwrap.__globals__ if globals is None: globals = obj_globals if locals is None: locals = obj_locals return_value = {key: value if not isinstance(value, str) else eval(value, globals, locals) for key, value in ann.items() } return return_value # ----------------------------------------------------------- type-checking

8198943edd73a363c266633e1aa5b2a9e9c9f526

inspect.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/inspect.py

Python

https://github.com/XX-net/XX-Net.git

test_prefix_complex_ordering

def test_prefix_complex_ordering(self): vrf1, vrf2, vrf3 = list(VRF.objects.all()) prefixes = [ Prefix(status=PrefixStatusChoices.STATUS_CONTAINER, vrf=None, prefix=netaddr.IPNetwork('10.0.0.0/8')), Prefix(status=PrefixStatusChoices.STATUS_CONTAINER, vrf=None, prefix=netaddr.IPNetwork('10.0.0.0/16')), Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=None, prefix=netaddr.IPNetwork('10.1.0.0/16')), Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=None, prefix=netaddr.IPNetwork('192.168.0.0/16')), Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.0.0.0/24')), Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.0.1.0/24')), Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.0.1.0/25')), Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.1.0.0/24')), Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.1.1.0/24')), ] Prefix.objects.bulk_create(prefixes) # Test self._compare(Prefix.objects.all(), prefixes)

d4a231585ac9a25d9739552d8c9e433dbf9398af

test_ordering.py

Clean up tests

netbox

netbox/ipam/tests/test_ordering.py

Python

https://github.com/netbox-community/netbox.git

test_directed_partition

def test_directed_partition(): G = nx.DiGraph() H = nx.DiGraph() G.add_nodes_from(range(10)) H.add_nodes_from([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) G_edges = [ (0, 2), (0, 1), (1, 0), (2, 1), (2, 0), (3, 4), (4, 3), (7, 8), (8, 7), (9, 10), (10, 9), ] H_edges = [ (1, 2), (1, 6), (1, 9), (2, 3), (2, 4), (2, 5), (3, 4), (4, 3), (4, 5), (5, 4), (6, 7), (6, 8), (9, 10), (9, 11), (10, 11), (11, 10), ] G.add_edges_from(G_edges) H.add_edges_from(H_edges) G_expected_partition = [{0, 1, 2}, {3, 4}, {5}, {6}, {8, 7}, {9, 10}] G_partition = louvain_communities(G, seed=123, weight=None) H_expected_partition = [{2, 3, 4, 5}, {8, 1, 6, 7}, {9, 10, 11}] H_partition = louvain_communities(H, seed=123, weight=None) assert G_partition == G_expected_partition assert H_partition == H_expected_partition

8522eea3955f5cf3da43cacc27643d93768aeb03

test_louvain.py

Correct louvain formula, solve infinite loops (#5713) Fixes the formulae used to calculate gain and removal cost in calculation of one level of the Louvain partition tree. Errors here were causing infinite loops for some cases in the past, see gh-5175 and gh-5704. This PR also adds test cases to ensure infinite loops are not entered for these cases. Co-authored-by: Ross Barnowski <[email protected]>

networkx

networkx/algorithms/community/tests/test_louvain.py

Python

https://github.com/networkx/networkx.git

tobitmap

def tobitmap(self, name="image"): self.load() if self.mode != "1": msg = "not a bitmap" raise ValueError(msg) data = self.tobytes("xbm") return b"".join( [ f"#define {name}_width {self.size[0]}\n".encode("ascii"), f"#define {name}_height {self.size[1]}\n".encode("ascii"), f"static char {name}_bits[] = {{\n".encode("ascii"), data, b"};", ] )

2ae55ccbdad9c842929fb238ea1eb81d1f999024

Image.py

Improve exception traceback readability

Pillow

src/PIL/Image.py

Python

https://github.com/python-pillow/Pillow.git

set_fontsize

def set_fontsize(self, s=None): if s is None: s = mpl.rcParams["legend.fontsize"] self.prop = FontProperties(size=s) self.stale = True

438d30b227b1fef7e8733578f851e76a8e360f24

offsetbox.py

Get rcParams from mpl

matplotlib

lib/matplotlib/offsetbox.py

Python

https://github.com/matplotlib/matplotlib.git

slider_var

def slider_var(self) -> tk.IntVar: retval = self._vars["slider"] assert isinstance(retval, tk.IntVar) return retval

7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5

preview_tk.py

Training - Use custom preview pop-out

faceswap

lib/training/preview_tk.py

Python

https://github.com/deepfakes/faceswap.git

_make_pair_wise_relative_positions

def _make_pair_wise_relative_positions(self) -> None: device = self.tau.device coordinates = torch.stack(torch.meshgrid([ torch.arange(self.window_size[0], device=device), torch.arange(self.window_size[1], device=device)]), dim=0).flatten(1) relative_coordinates = coordinates[:, :, None] - coordinates[:, None, :] relative_coordinates = relative_coordinates.permute(1, 2, 0).reshape(-1, 2).float() relative_coordinates_log = torch.sign(relative_coordinates) * torch.log( 1.0 + relative_coordinates.abs()) self.register_buffer("relative_coordinates_log", relative_coordinates_log, persistent=False)

c6e4b7895a7dbcd9b98396cbef383dd1c72b0ad3

swin_transformer_v2_cr.py

Swin V2 CR impl refactor. * reformat and change some naming so closer to existing timm vision transformers * remove typing that wasn't adding clarity (or causing torchscript issues) * support non-square windows * auto window size adjust from image size * post-norm + main-branch no

pytorch-image-models

timm/models/swin_transformer_v2_cr.py

Python

https://github.com/huggingface/pytorch-image-models.git

_get_newest_folder

def _get_newest_folder(self) -> str: assert self._pathoutput is not None folders = [os.path.join(self._pathoutput, folder) for folder in os.listdir(self._pathoutput) if os.path.isdir(os.path.join(self._pathoutput, folder))] folders.sort(key=os.path.getmtime) retval = folders[-1] if folders else self._pathoutput logger.debug("sorted folders: %s, return value: %s", folders, retval) return retval

dc18c74eea0c7837a820d27628cb12b0824fa30e

utils.py

Bugfix: Preview for extract in batch mode

faceswap

lib/gui/utils.py

Python

https://github.com/deepfakes/faceswap.git

average_shortest_path_length

def average_shortest_path_length(G, weight=None, method=None): r single_source_methods = ["unweighted", "dijkstra", "bellman-ford"] all_pairs_methods = ["floyd-warshall", "floyd-warshall-numpy"] supported_methods = single_source_methods + all_pairs_methods if method is None: method = "unweighted" if weight is None else "dijkstra" if method not in supported_methods: raise ValueError(f"method not supported: {method}") n = len(G) # For the special case of the null graph, raise an exception, since # there are no paths in the null graph. if n == 0: msg = ( "the null graph has no paths, thus there is no average" "shortest path length" ) raise nx.NetworkXPointlessConcept(msg) # For the special case of the trivial graph, return zero immediately. if n == 1: return 0 # Shortest path length is undefined if the graph is disconnected. if G.is_directed() and not nx.is_weakly_connected(G): raise nx.NetworkXError("Graph is not weakly connected.") if not G.is_directed() and not nx.is_connected(G): raise nx.NetworkXError("Graph is not connected.") # Compute all-pairs shortest paths.

b5d41847b8db0c82372faf69cd3a339d11da7ef0

generic.py

DOC: Update documentation to include callables for weight argument (#5307) Update docs to include functions as valid input for weight argument.

networkx

networkx/algorithms/shortest_paths/generic.py

Python

https://github.com/networkx/networkx.git

assertDisallows

def assertDisallows(self, func_name): try: with self.assertRaises(Exception): yield except Exception as e: # pylint: disable=broad-except raise RuntimeError( f"Expected a transfer to be disallowed while running: {func_name}" ) from e

b7e1fec2500daec9e42e79c5983183c759e318ed

transfer_guard_test.py

Implement the JAX transfer guard API Adds `--jax_transfer_guard` flag and `jax.transfer_guard()` context manager that allows logging or disallowing unintended transfers. The API distinguishes between two types of transfers: * explicit transfers: `jax.device_put*()` and `jax.device_get()` calls. * implicit transfers: Other transfers (e.g., printing a `DeviceArray`). The transfer guard can take an action based on its guard level: * "allow": Silently allow all transfers (default; same as the previous behavior). * "log": Log and allow implicit transfers. Silently allow explicit transfers. * "disallow": Disallow implicit transfers. Silently allow explicit transfers. * "log_explicit": Log and allow all transfers. * "disallow_explicit": Disallow all transfers. The API also allows fine-control the transfer guard level of individual transfer directions. Their flag and context manager names are suffixed with the transfer direction: * "host_to_device": Converting a Python value into a `DeviceBuffer`. * "device_to_device": Copying a `DeviceBuffer` to a different device. * "device_to_host": Fetching the value of a `DeviceBuffer`. Example: ``` x = jnp.array(1) y = jnp.array(2) z = jnp.array(3) print(x) # No error with jax.transfer_guard("disallow"): print(x) # No error; x is already fetched print(jax.device_get(y)) # No error print(z) # Error! ``` PiperOrigin-RevId: 427562278

jax

tests/transfer_guard_test.py

Python

https://github.com/google/jax.git

onModuleEncounter

def onModuleEncounter(self, module_filename, module_name, module_kind): # Virtual method, pylint: disable=no-self-use,unused-argument return None

31e4a7edb61212d4dddafb281ea9c842e646e508

PluginBase.py

Cleanup, avoid "shlib" naming, and use "extension" instead. * This should make the code more clear for others to read.

Nuitka

nuitka/plugins/PluginBase.py

Python

https://github.com/Nuitka/Nuitka.git

copy_placeholders_and_check_results

def copy_placeholders_and_check_results(self, placeholders): for original_placeholder in placeholders: # get the plugins original_plugins = original_placeholder.get_plugins() # copy them to a new placeholder copied_placeholder = Placeholder.objects.create(slot=original_placeholder.slot) copy_plugins_to( original_placeholder.get_plugins(), copied_placeholder ) copied_plugins = copied_placeholder.get_plugins() # we should find the same number of plugins in both placeholders self.assertEqual( original_plugins.count(), copied_plugins.count() ) # quick check: make sure the two querysets match: for original, copy in zip(original_plugins, copied_plugins): self.assertEqual( Text.objects.get(id=original.id).body, Text.objects.get(id=copy.id).body ) # Now build a *tree* of the plugins, and match those - it's not # enough just to compare querysets as above; we should *also* check # that when we build a tree, the various nodes are assembled as we # would expect. We will pump the trees into a pair of lists: original_plugins_list = [] copied_plugins_list = [] # This function builds the tree of plugins, starting from its roots. # In that respect it's like many of the plugin tree-building # routines elsewhere in the system.

c1290c9ff89cb00caa5469129fd527e9d82cd820

test_nested_plugins.py

ci: Added codespell (#7355) Co-authored-by: Christian Clauss <[email protected]> * ci: codespell config taken from #7292

django-cms

cms/tests/test_nested_plugins.py

Python

https://github.com/django-cms/django-cms.git

test_sqlite_error_codes

def test_sqlite_error_codes(self, code): pyvalue = getattr(sqlite3, f"SQLITE_{code.name}") assert pyvalue == code.value

ee4d6e0396a6b570f4d5592a9c4c1a9fee1027b6

test_sql.py

sql: Add *all* primary sqlite result codes For three reasons: - There are only 31 of them, and we don't really expect any more to turn up (last happened in 2013, and we have a test for it happening) - It makes for nicer debug output - It always felt strange to only have a small subset in the enum

qutebrowser

tests/unit/misc/test_sql.py

Python

https://github.com/qutebrowser/qutebrowser.git

get_latest_revision_as_object

def get_latest_revision_as_object(self): latest_revision = self.get_latest_revision() if latest_revision: return latest_revision.as_object() return self

cf3cea9a5b171efff525baefe7d25df6f7cd2c60

__init__.py

Add docs for RevisionMixin

wagtail

wagtail/models/__init__.py

Python

https://github.com/wagtail/wagtail.git

test_empty_objects

def test_empty_objects(call_ray_start_shared): objects = [0, b"", "", [], np.array(()), {}, set(), None] with ray_start_client_server_for_address(call_ray_start_shared) as ray: for obj in objects: ref = ray.put(obj) if isinstance(obj, np.ndarray): assert np.array_equal(ray.get(ref), obj) else: assert ray.get(ref) == obj

297341e107daee1ea3aff991ae8ea8c90993c683

test_client.py

[Test][Client] Only start ray once in client tests (#28835) It looks like we're frequently starting and shutting down Ray in this test because `ray_start_client_server` isn't connecting to the Ray created by `ray_start_regular_shared`, and is instead starting a new Ray head process every time it launches. Ray client tests are failing frequently with: ``` [2022-10-06 07:31:46,253 E 13235 13751] core_worker_process.cc:277: The core worker has already been shutdown. This happens when the language frontend accesses the Ray's worker after it is shutdown. The process will exit ``` Which is probably caused by having multiple ray clusters running simultaneous, with some shutting down asynchronously. This refactor forces all of the tests in the module to use the same Ray cluster. Also fixes two other sources of potential flakiness: * Joins the thread in test_client_thread_safe (seems like this has a bad interaction when the client server is cleaned up) * Calls ray.get in `test_stdout_log_stream`, to make sure that the remote function is done running before we try searching for its output Should also have the happy side effect of speeding up test_client. Ran the `Small & Client` tests (regular and external redis) twice each, no flakes, and windows version of test_client.

ray

python/ray/tests/test_client.py

Python

https://github.com/ray-project/ray.git

parse_multiple_json

def parse_multiple_json(json_file, offset=None): json_info_list = [] if not os.path.exists(json_file): return json_info_list try: with open(json_file, "r") as f: if offset: f.seek(offset) for line in f: if line[-1] != "\n": # Incomplete line break json_info = json.loads(line) json_info_list.append(json_info) offset += len(line) except BaseException as e: logging.error(e.message) return json_info_list, offset

d2f0c3b2f64b41f6541f6521e98cf3a37577c016

utils.py

Clean up docstyle in data, ml, and tune packages (#25188)

ray

python/ray/tune/automlboard/common/utils.py

Python

https://github.com/ray-project/ray.git

test_worker_duty_configs

def test_worker_duty_configs(self) -> None: worker1_config = self._make_worker_config( worker_app="synapse.app.generic_worker", worker_name="worker1", extras={ "notify_appservices_from_worker": "worker2", "update_user_directory_from_worker": "worker1", }, ) self.assertFalse(worker1_config.should_notify_appservices) self.assertTrue(worker1_config.should_update_user_directory) worker2_config = self._make_worker_config( worker_app="synapse.app.generic_worker", worker_name="worker2", extras={ "notify_appservices_from_worker": "worker2", "update_user_directory_from_worker": "worker1", }, ) self.assertTrue(worker2_config.should_notify_appservices) self.assertFalse(worker2_config.should_update_user_directory)

699192fc1a1055a4bec2345bc80f120f28470c73

test_workers.py

Add the `update_user_directory_from_worker` configuration option (superseding `update_user_directory`) to allow a generic worker to be designated as the worker to update the user directory. (#12654) Co-authored-by: Shay <[email protected]>

synapse

tests/config/test_workers.py

Python

https://github.com/matrix-org/synapse.git

upgrade

def upgrade(): try: with op.batch_alter_table('connection') as batch_op: batch_op.alter_column("conn_id", nullable=False, existing_type=sa.String(250, **COLLATION_ARGS)) batch_op.create_unique_constraint(constraint_name="unique_conn_id", columns=["conn_id"]) except sa.exc.IntegrityError: raise Exception("Make sure there are no duplicate connections with the same conn_id or null values")

69f6f9e01b6df76c3c8fa266d460324163957887

8d48763f6d53_add_unique_constraint_to_conn_id.py

Autogenerate migration reference doc (#21601) * document airflow version in each alembic migration module and use this to autogen the doc * update each migration module to have the same description used in migration ref (so it can be used in autogen)

airflow

airflow/migrations/versions/8d48763f6d53_add_unique_constraint_to_conn_id.py

Python

https://github.com/apache/airflow.git

classify_pde

def classify_pde(eq, func=None, dict=False, *, prep=True, **kwargs): if func and len(func.args) != 2: raise NotImplementedError("Right now only partial " "differential equations of two variables are supported") if prep or func is None: prep, func_ = _preprocess(eq, func) if func is None: func = func_ if isinstance(eq, Equality): if eq.rhs != 0: return classify_pde(eq.lhs - eq.rhs, func) eq = eq.lhs f = func.func x = func.args[0] y = func.args[1] fx = f(x,y).diff(x) fy = f(x,y).diff(y) # TODO : For now pde.py uses support offered by the ode_order function # to find the order with respect to a multi-variable function. An # improvement could be to classify the order of the PDE on the basis of # individual variables. order = ode_order(eq, f(x,y)) # hint:matchdict or hint:(tuple of matchdicts) # Also will contain "default":<default hint> and "order":order items. matching_hints = {'order': order} if not order: if dict: matching_hints["default"] = None return matching_hints else: return () eq = expand(eq) a = Wild('a', exclude = [f(x,y)]) b = Wild('b', exclude = [f(x,y), fx, fy, x, y]) c = Wild('c', exclude = [f(x,y), fx, fy, x, y]) d = Wild('d', exclude = [f(x,y), fx, fy, x, y]) e = Wild('e', exclude = [f(x,y), fx, fy]) n = Wild('n', exclude = [x, y]) # Try removing the smallest power of f(x,y) # from the highest partial derivatives of f(x,y) reduced_eq = None if eq.is_Add: var = set(combinations_with_replacement((x,y), order)) dummyvar = var.copy() power = None for i in var: coeff = eq.coeff(f(x,y).diff(*i)) if coeff != 1: match = coeff.match(a*f(x,y)**n) if match and match[a]: power = match[n] dummyvar.remove(i) break dummyvar.remove(i) for i in dummyvar: coeff = eq.coeff(f(x,y).diff(*i)) if coeff != 1: match = coeff.match(a*f(x,y)**n) if match and match[a] and match[n] < power: power = match[n] if power: den = f(x,y)**power reduced_eq = Add(*[arg/den for arg in eq.args]) if not reduced_eq: reduced_eq = eq if order == 1: reduced_eq = collect(reduced_eq, f(x, y)) r = reduced_eq.match(b*fx + c*fy + d*f(x,y) + e) if r: if not r[e]: ## Linear first-order homogeneous partial-differential ## equation with constant coefficients r.update({'b': b, 'c': c, 'd': d}) matching_hints["1st_linear_constant_coeff_homogeneous"] = r else: if r[b]**2 + r[c]**2 != 0: ## Linear first-order general partial-differential ## equation with constant coefficients r.update({'b': b, 'c': c, 'd': d, 'e': e}) matching_hints["1st_linear_constant_coeff"] = r matching_hints[ "1st_linear_constant_coeff_Integral"] = r else: b = Wild('b', exclude=[f(x, y), fx, fy]) c = Wild('c', exclude=[f(x, y), fx, fy]) d = Wild('d', exclude=[f(x, y), fx, fy]) r = reduced_eq.match(b*fx + c*fy + d*f(x,y) + e) if r: r.update({'b': b, 'c': c, 'd': d, 'e': e}) matching_hints["1st_linear_variable_coeff"] = r # Order keys based on allhints. retlist = [i for i in allhints if i in matching_hints] if dict: # Dictionaries are ordered arbitrarily, so make note of which # hint would come first for pdsolve(). Use an ordered dict in Py 3. matching_hints["default"] = None matching_hints["ordered_hints"] = tuple(retlist) for i in allhints: if i in matching_hints: matching_hints["default"] = i break return matching_hints else: return tuple(retlist)

6a9ff86786f73ca07fa9004913037de6ba5cb155

pde.py

More list comprehensions

sympy

sympy/solvers/pde.py

Python

https://github.com/sympy/sympy.git

getlength

def getlength(self, text, *args, **kwargs): width, height = self.font.getsize(text) return width ## # Wrapper for FreeType fonts. Application code should use the # <b>truetype</b> factory function to create font objects.

c854bf8d1c05022bec4309fbf6b547e494db9373

ImageFont.py

add getbbox and getlength to basic ImageFont and update related tests

Pillow

src/PIL/ImageFont.py

Python

https://github.com/python-pillow/Pillow.git

get_available_item_locations_for_batched_item

def get_available_item_locations_for_batched_item(item_code, from_warehouses, required_qty, company): warehouse_condition = 'and warehouse in %(warehouses)s' if from_warehouses else '' batch_locations = frappe.db.sql(.format(warehouse_condition=warehouse_condition), { #nosec 'item_code': item_code, 'company': company, 'today': today(), 'warehouses': from_warehouses }, as_dict=1) return batch_locations

517fbf1d1f0a7d44e817b3f22ae30142e7bdf4c8

pick_list.py

fix: Ambigous column in picklist query

erpnext

erpnext/stock/doctype/pick_list/pick_list.py

Python

https://github.com/frappe/erpnext.git

test_thermostat_hvac_modes

async def test_thermostat_hvac_modes(hass, hk_driver): entity_id = "climate.test" hass.states.async_set( entity_id, HVACMode.OFF, {ATTR_HVAC_MODES: [HVACMode.HEAT, HVACMode.OFF]} ) await hass.async_block_till_done() acc = Thermostat(hass, hk_driver, "Climate", entity_id, 1, None) hk_driver.add_accessory(acc) await acc.run() await hass.async_block_till_done() hap = acc.char_target_heat_cool.to_HAP() assert hap["valid-values"] == [0, 1] assert acc.char_target_heat_cool.value == 0 with pytest.raises(ValueError): acc.char_target_heat_cool.set_value(3) await hass.async_block_till_done() assert acc.char_target_heat_cool.value == 0 acc.char_target_heat_cool.set_value(1) await hass.async_block_till_done() assert acc.char_target_heat_cool.value == 1 with pytest.raises(ValueError): acc.char_target_heat_cool.set_value(2) await hass.async_block_till_done() assert acc.char_target_heat_cool.value == 1

f453726b1862d1d247f6aefdd5f23455b87c11cf

test_type_thermostats.py

Cleanup HVACAction and HVACMode in tests (#78813)

core

tests/components/homekit/test_type_thermostats.py

Python

https://github.com/home-assistant/core.git

test_datetime_fractional_seconds

def test_datetime_fractional_seconds(all_parsers): parser = all_parsers data = result = parser.read_csv( StringIO(data), header=0, date_parser=lambda x: pd.to_datetime(x, format="%Y %m %d %H %M %S.%f"), parse_dates={"ymdHMS": [0, 1, 2, 3, 4, 5]}, ) expected = DataFrame( [ [datetime(2001, 1, 5, 10, 0, 0, microsecond=123456), 0.0, 10.0], [datetime(2001, 1, 5, 10, 0, 0, microsecond=500000), 1.0, 11.0], ], columns=["ymdHMS", "a", "b"], ) tm.assert_frame_equal(result, expected) @xfail_pyarrow

d2e972301c099967ef3050c9feda1d116e1dd85a

@xfail_pyarrow

test_parse_dates.py

DEP: Enforce deprecation of date converters for csv (#49086) * DEP: Enforce deprecation of date converters for csv * Add whatsnew * Add check

pandas

pandas/tests/io/parser/test_parse_dates.py

Python

https://github.com/pandas-dev/pandas.git

_get_html_response

def _get_html_response(url, session): # type: (str, PipSession) -> Response if is_archive_file(Link(url).filename): _ensure_html_response(url, session=session) logger.debug('Getting page %s', redact_auth_from_url(url)) resp = session.get( url, headers={ "Accept": "text/html", # We don't want to blindly returned cached data for # /simple/, because authors generally expecting that # twine upload && pip install will function, but if # they've done a pip install in the last ~10 minutes # it won't. Thus by setting this to zero we will not # blindly use any cached data, however the benefit of # using max-age=0 instead of no-cache, is that we will # still support conditional requests, so we will still # minimize traffic sent in cases where the page hasn't # changed at all, we will just always incur the round # trip for the conditional GET now instead of only # once per 10 minutes. # For more information, please see pypa/pip#5670. "Cache-Control": "max-age=0", }, ) raise_for_status(resp) # The check for archives above only works if the url ends with # something that looks like an archive. However that is not a # requirement of an url. Unless we issue a HEAD request on every # url we cannot know ahead of time for sure if something is HTML # or not. However we can check after we've downloaded it. _ensure_html_header(resp) return resp

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

collector.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/index/collector.py

Python

https://github.com/jindongwang/transferlearning.git

bcoo_update_layout

def bcoo_update_layout(mat, *, n_batch=None, n_dense=None, on_inefficient='error'): # TODO(jakevdp): allow specification of nse? # TODO(jakevdp): there is room for some improvements here: # - we could probably do better in the case of converting a dense dim to # a batch dim or vice-versa. Worth adding that special case? # - we could work to preserve broadcasted batch dimensions when possible. # - if indices are known to be unique, we can convert them to batch/dense # dimensions more efficiently. n_batch = mat.n_batch if n_batch is None else operator.index(n_batch) n_dense = mat.n_dense if n_dense is None else operator.index(n_dense) if (n_batch, n_dense) == (mat.n_batch, mat.n_dense): return mat n_sparse = mat.ndim - n_batch - n_dense if on_inefficient not in ['error', 'warn', None]: raise ValueError("on_inefficent={on_inefficient!r}; expected one of ['error', 'warn', None].") if n_batch < 0: raise ValueError(f"n_batch must be non-negative; got {n_batch}") if n_dense < 0: raise ValueError(f"n_dense must be non-negative; got {n_dense}") if n_sparse < 0: raise ValueError(f"sum of n_batch={n_batch} and n_dense={n_dense} " f"cannot be larger than mat.ndim={mat.ndim}.") def _maybe_err_or_warn(msg): if on_inefficient == 'error': msg += (" To disable this error, set the on_inefficient argument " "of bcoo_update_layout to 'warn' or None.") raise SparseEfficiencyError(msg) elif on_inefficient == 'warn': msg += (" To disable this warning, set the on_inefficient argument " "of bcoo_update_layout to None.") warnings.warn(msg, category=SparseEfficiencyWarning) # TODO(jakevdp): are efficiency warnings necessary when nse is 0 or 1? if (n_dense > mat.n_dense and any(d > 1 for d in mat.shape[-n_dense:mat.ndim - mat.n_dense])): _maybe_err_or_warn(f"For matrix of shape {mat.shape}, increasing n_dense from " f"{mat.n_dense} to {n_dense} results in inefficient storage.") if n_batch > mat.n_batch and any(d > 1 for d in mat.shape[mat.n_batch:n_batch]): _maybe_err_or_warn(f"For matrix of shape {mat.shape}, increasing n_batch from " f"{mat.n_batch} to {n_batch} results in inefficient storage.") new_data, new_indices = mat.data, mat.indices shape = mat.shape current_n_batch = mat.n_batch current_n_dense = mat.n_dense if n_dense < current_n_dense: n = current_n_dense - n_dense

bf4c3b64af43b86c3005c0f8bec450655ab47a8d

bcoo.py

[sparse] add bcoo_update_layout utility

jax

jax/experimental/sparse/bcoo.py

Python

https://github.com/google/jax.git

test_s3_zip

def test_s3_zip(self): unzipped_paths = _unzip_if_needed([self.s3_path + "/enormous.zip"], "json") self.assertEqual( str(Path(unzipped_paths[0]).absolute()), str(Path("./").absolute() / "enormous.json"), )

569fe0109629048d08e1d9e023f7769f10bd2244

test_dataset_reader.py

[RLlib] improved unittests for dataset_reader and fixed bugs (#26458)

ray

rllib/offline/tests/test_dataset_reader.py

Python

https://github.com/ray-project/ray.git

test_occupancy_sensor_read_state

async def test_occupancy_sensor_read_state(hass, utcnow): helper = await setup_test_component(hass, create_occupancy_sensor_service) await helper.async_update( ServicesTypes.OCCUPANCY_SENSOR, {CharacteristicsTypes.OCCUPANCY_DETECTED: False} ) state = await helper.poll_and_get_state() assert state.state == "off" await helper.async_update( ServicesTypes.OCCUPANCY_SENSOR, {CharacteristicsTypes.OCCUPANCY_DETECTED: True} ) state = await helper.poll_and_get_state() assert state.state == "on" assert state.attributes["device_class"] == BinarySensorDeviceClass.OCCUPANCY

58b8c30221a6f6e5acbbe98b7e3298b03fb741f5

test_binary_sensor.py

Improve homekit_controller tests (#65266)

core

tests/components/homekit_controller/test_binary_sensor.py

Python

https://github.com/home-assistant/core.git

get_diff_with_remote_resource

def get_diff_with_remote_resource(self) -> str: if not self.was_created: raise NonExistingResourceError("Cannot compute diff with a non existing remote resource.") current_config = self.configuration remote_config = self.remote_resource.connection_configuration diff = compute_diff(remote_config, current_config) return diff.pretty()

706d7f16868f062d89e9d24e37ab059ae1a6d8b2

resources.py

🐙 octavia-cli: implement `apply` (#10703)

airbyte

octavia-cli/octavia_cli/apply/resources.py

Python

https://github.com/airbytehq/airbyte.git

test_i18n_language_non_english_default

def test_i18n_language_non_english_default(self): with self.settings(LANGUAGE_CODE="fr"), translation.override("en-us"): response = self.client.get(reverse("admin:jsi18n")) self.assertNotContains(response, "Choisir une heure")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

https://github.com/django/django.git

callbacks

def callbacks(self, callbacks_class) -> "AlgorithmConfig": if callbacks_class is None: callbacks_class = DefaultCallbacks # Check, whether given `callbacks` is a callable. if not callable(callbacks_class): raise ValueError( "`config.callbacks_class` must be a callable method that " "returns a subclass of DefaultCallbacks, got " f"{callbacks_class}!" ) self.callbacks_class = callbacks_class return self

182744bbd151c166b8028355eae12a5da63fb3cc

algorithm_config.py

[RLlib] AlgorithmConfig: Next steps (volume 01); Algos, RolloutWorker, PolicyMap, WorkerSet use AlgorithmConfig objects under the hood. (#29395)

ray

rllib/algorithms/algorithm_config.py

Python

https://github.com/ray-project/ray.git

test_fed_filtering

def test_fed_filtering(self): fed_hostname = self.hs.hostname + "2" subspace = "#subspace:" + fed_hostname # Create a few rooms which will have different properties. public_room = "#public:" + fed_hostname knock_room = "#knock:" + fed_hostname not_invited_room = "#not_invited:" + fed_hostname invited_room = "#invited:" + fed_hostname restricted_room = "#restricted:" + fed_hostname restricted_accessible_room = "#restricted_accessible:" + fed_hostname world_readable_room = "#world_readable:" + fed_hostname joined_room = self.helper.create_room_as(self.user, tok=self.token) # Poke an invite over federation into the database. self._poke_fed_invite(invited_room, "@remote:" + fed_hostname) # Note that these entries are brief, but should contain enough info. children_rooms = ( ( public_room, { "room_id": public_room, "world_readable": False, "join_rules": JoinRules.PUBLIC, }, ), ( knock_room, { "room_id": knock_room, "world_readable": False, "join_rules": JoinRules.KNOCK, }, ), ( not_invited_room, { "room_id": not_invited_room, "world_readable": False, "join_rules": JoinRules.INVITE, }, ), ( invited_room, { "room_id": invited_room, "world_readable": False, "join_rules": JoinRules.INVITE, }, ), ( restricted_room, { "room_id": restricted_room, "world_readable": False, "join_rules": JoinRules.RESTRICTED, "allowed_room_ids": [], }, ), ( restricted_accessible_room, { "room_id": restricted_accessible_room, "world_readable": False, "join_rules": JoinRules.RESTRICTED, "allowed_room_ids": [self.room], }, ), ( world_readable_room, { "room_id": world_readable_room, "world_readable": True, "join_rules": JoinRules.INVITE, }, ), ( joined_room, { "room_id": joined_room, "world_readable": False, "join_rules": JoinRules.INVITE, }, ), ) subspace_room_entry = _RoomEntry( subspace, { "room_id": subspace, "world_readable": True, }, # Place each room in the sub-space. [ { "type": EventTypes.SpaceChild, "room_id": subspace, "state_key": room_id, "content": {"via": [fed_hostname]}, } for room_id, _ in children_rooms ], )

7754af24ab163a3666bc04c7df409e59ace0d763

test_room_summary.py

Remove the unstable `/spaces` endpoint. (#12073) ...and various code supporting it. The /spaces endpoint was from an old version of MSC2946 and included both a Client-Server and Server-Server API. Note that the unstable /hierarchy endpoint (from the final version of MSC2946) is not yet removed.

synapse

tests/handlers/test_room_summary.py

Python

https://github.com/matrix-org/synapse.git

require_soundfile

def require_soundfile(test_case): return unittest.skipUnless(is_soundfile_availble(), "test requires soundfile")(test_case)

57e6464ac9a31156f1c93e59107323e6ec01309e

testing_utils.py

Update all require decorators to use skipUnless when possible (#16999)

transformers

src/transformers/testing_utils.py

Python

https://github.com/huggingface/transformers.git

_resolve_project_threshold_config

def _resolve_project_threshold_config(self) -> SelectType: org_id = self.builder.params.get("organization_id") project_ids = self.builder.params.get("project_id") project_threshold_configs = ( ProjectTransactionThreshold.objects.filter( organization_id=org_id, project_id__in=project_ids, ) .order_by("project_id") .values_list("project_id", "threshold", "metric") ) transaction_threshold_configs = ( ProjectTransactionThresholdOverride.objects.filter( organization_id=org_id, project_id__in=project_ids, ) .order_by("project_id") .values_list("transaction", "project_id", "threshold", "metric") ) num_project_thresholds = project_threshold_configs.count() sentry_sdk.set_tag("project_threshold.count", num_project_thresholds) sentry_sdk.set_tag( "project_threshold.count.grouped", format_grouped_length(num_project_thresholds, [10, 100, 250, 500]), ) num_transaction_thresholds = transaction_threshold_configs.count() sentry_sdk.set_tag("txn_threshold.count", num_transaction_thresholds) sentry_sdk.set_tag( "txn_threshold.count.grouped", format_grouped_length(num_transaction_thresholds, [10, 100, 250, 500]), ) if ( num_project_thresholds + num_transaction_thresholds > constants.MAX_QUERYABLE_TRANSACTION_THRESHOLDS ): raise InvalidSearchQuery( f"Exceeded {constants.MAX_QUERYABLE_TRANSACTION_THRESHOLDS} configured transaction thresholds limit, try with fewer Projects." ) # Arrays need to have toUint64 casting because clickhouse will define the type as the narrowest possible type # that can store listed argument types, which means the comparison will fail because of mismatched types project_thresholds = {} project_threshold_config_keys = [] project_threshold_config_values = [] for project_id, threshold, metric in project_threshold_configs: metric = TRANSACTION_METRICS[metric] if ( threshold == constants.DEFAULT_PROJECT_THRESHOLD and metric == constants.DEFAULT_PROJECT_THRESHOLD_METRIC ): # small optimization, if the configuration is equal to the default, # we can skip it in the final query continue project_thresholds[project_id] = (metric, threshold) project_threshold_config_keys.append(Function("toUInt64", [project_id])) project_threshold_config_values.append((metric, threshold)) project_threshold_override_config_keys = [] project_threshold_override_config_values = [] for transaction, project_id, threshold, metric in transaction_threshold_configs: metric = TRANSACTION_METRICS[metric] if ( project_id in project_thresholds and threshold == project_thresholds[project_id][1] and metric == project_thresholds[project_id][0] ): # small optimization, if the configuration is equal to the project # configs, we can skip it in the final query continue elif ( project_id not in project_thresholds and threshold == constants.DEFAULT_PROJECT_THRESHOLD and metric == constants.DEFAULT_PROJECT_THRESHOLD_METRIC ): # small optimization, if the configuration is equal to the default # and no project configs were set, we can skip it in the final query continue transaction_id = self.resolve_tag_value(transaction) # Don't add to the config if we can't resolve it if transaction_id is None: continue project_threshold_override_config_keys.append( (Function("toUInt64", [project_id]), (Function("toUInt64", [transaction_id]))) ) project_threshold_override_config_values.append((metric, threshold)) project_threshold_config_index: SelectType = Function( "indexOf", [ project_threshold_config_keys, self.builder.column("project_id"), ], constants.PROJECT_THRESHOLD_CONFIG_INDEX_ALIAS, ) project_threshold_override_config_index: SelectType = Function( "indexOf", [ project_threshold_override_config_keys, (self.builder.column("project_id"), self.builder.column("transaction")), ], constants.PROJECT_THRESHOLD_OVERRIDE_CONFIG_INDEX_ALIAS, )

e1b25d625b185588fc7c2834dff5ea5bb3a98ce0

metrics.py

fix(mep): Use project thresholds for apdex calculation (#37256) - Currently apdex is always based on the satisfaction tags in the transaction.duration metrics. This updates the apdex function so we read the threshold config, and use that to determine which metric we should read the satisfaction tags from instead

sentry

src/sentry/search/events/datasets/metrics.py

Python

https://github.com/getsentry/sentry.git

test_validate_invalid_subscription_and_query

def test_validate_invalid_subscription_and_query(): result = validate_subscription_query(TEST_INVALID_MULTIPLE_SUBSCRIPTION_AND_QUERY) assert result is False TEST_INVALID_MULTIPLE_SUBSCRIPTION =

aca6418d6c36956bc1ab530e6ef7e146ec9df90c

test_create_deliveries_for_subscription.py

Add Webhook payload via graphql subscriptions (#9394) * Add PoC of webhook subscriptions * add async webhooks subscription payloads feature * remove unneeded file * add translations subscription handling, fixes after review * remove todo * add descriptions * add descriptions, move subsrciption_payloads.py * refactor * fix imports, add changelog * check_document_is_single_subscription refactor Co-authored-by: Maciej Korycinski <[email protected]> Co-authored-by: Marcin Gębala <[email protected]>

saleor

saleor/plugins/webhook/tests/subscription_webhooks/test_create_deliveries_for_subscription.py

Python

https://github.com/saleor/saleor.git

_get_semantics_within_frame

def _get_semantics_within_frame(self, vnframe): semantics_within_single_frame = [] for pred in vnframe.findall("SEMANTICS/PRED"): arguments = [ {"type": arg.get("type"), "value": arg.get("value")} for arg in pred.findall("ARGS/ARG") ] semantics_within_single_frame.append( { "predicate_value": pred.get("value"), "arguments": arguments, "negated": pred.get("bool") == "!", } ) return semantics_within_single_frame

8b43b49b0cd8c12cae1d48df27edfdd98cf859fd

verbnet.py

Read 'bool' field from VerbNet

nltk

nltk/corpus/reader/verbnet.py

Python

https://github.com/nltk/nltk.git

doc_resample_reduce

def doc_resample_reduce(result, refer_to, params=None, compatibility_params=True): action = f"compute {result} for each group" params_substitution = ( ( ) if compatibility_params else "" ) if params: params_substitution = format_string( "{params}\n{params_substitution}", params=params, params_substitution=params_substitution, ) build_rules = f return doc_resample( action=action, extra_params=params_substitution, build_rules=build_rules, refer_to=refer_to, )

58bbcc37477866d19c8b092a0e1974a4f0baa586

doc_utils.py

REFACTOR-#2656: Update modin to fit algebra (code only) (#3717) Co-authored-by: Yaroslav Igoshev <[email protected]> Co-authored-by: Vasily Litvinov <[email protected]> Co-authored-by: Alexey Prutskov <[email protected]> Co-authored-by: Devin Petersohn <[email protected]> Signed-off-by: Rehan Durrani <[email protected]>

modin

modin/core/storage_formats/base/doc_utils.py

Python

https://github.com/modin-project/modin.git

quote_name_unless_alias

def quote_name_unless_alias(self, name): if name in self.quote_cache: return self.quote_cache[name] if ( (name in self.query.alias_map and name not in self.query.table_map) or name in self.query.extra_select or ( self.query.external_aliases.get(name) and name not in self.query.table_map ) ): self.quote_cache[name] = name return name r = self.connection.ops.quote_name(name) self.quote_cache[name] = r return r

9c19aff7c7561e3a82978a272ecdaad40dda5c00

compiler.py

Refs #33476 -- Reformatted code with Black.

django

django/db/models/sql/compiler.py

Python

https://github.com/django/django.git

formfield_for_manytomany

def formfield_for_manytomany(self, db_field, request, **kwargs): # If it uses an intermediary model that isn't auto created, don't show # a field in admin. if not db_field.remote_field.through._meta.auto_created: return None db = kwargs.get("using") if "widget" not in kwargs: autocomplete_fields = self.get_autocomplete_fields(request) if db_field.name in autocomplete_fields: kwargs["widget"] = AutocompleteSelectMultiple( db_field, self.admin_site, using=db, ) elif db_field.name in self.raw_id_fields: kwargs["widget"] = widgets.ManyToManyRawIdWidget( db_field.remote_field, self.admin_site, using=db, ) elif db_field.name in [*self.filter_vertical, *self.filter_horizontal]: kwargs["widget"] = widgets.FilteredSelectMultiple( db_field.verbose_name, db_field.name in self.filter_vertical ) if "queryset" not in kwargs: queryset = self.get_field_queryset(db, db_field, request) if queryset is not None: kwargs["queryset"] = queryset form_field = db_field.formfield(**kwargs) if isinstance(form_field.widget, SelectMultiple) and not isinstance( form_field.widget, (CheckboxSelectMultiple, AutocompleteSelectMultiple) ): msg = _( "Hold down “Control”, or “Command” on a Mac, to select more than one." ) help_text = form_field.help_text form_field.help_text = ( format_lazy("{} {}", help_text, msg) if help_text else msg ) return form_field

9c19aff7c7561e3a82978a272ecdaad40dda5c00

options.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/options.py

Python

https://github.com/django/django.git

serving

def serving(self, inputs): output = self.call(inputs) return self.serving_output(output) SWIN_START_DOCSTRING = r SWIN_INPUTS_DOCSTRING = r

8e8384663d716d4b5a4f510070ff954fc0ba4a52

modeling_tf_swin.py

Update serving code to enable `saved_model=True` (#18153) * Add serving_output and serving methods to some vision models * Add serving outputs for DeiT * Don't convert hidden states - differing shapes * Make saveable * Fix up * Make swin saveable * Add in tests * Fix funnel tests (can't convert to tensor) * Fix numpy call * Tidy up a bit * Add in hidden states - resnet * Remove numpy * Fix failing tests - tensor shape and skipping tests * Remove duplicated function * PR comments - formatting and var names * PR comments Add suggestions made by Joao Gante: * Use tf.shape instead of shape_list * Use @tooslow decorator on tests * Simplify some of the logic * PR comments Address Yih-Dar Sheih comments - making tensor names consistent and make types float * Types consistent with docs; disable test on swin (slow) * CI trigger * Change input_features to float32 * Add serving_output for segformer * Fixup Co-authored-by: Amy Roberts <[email protected]>

transformers

src/transformers/models/swin/modeling_tf_swin.py

Python

https://github.com/huggingface/transformers.git

task_group

def task_group(python_callable=None, **tg_kwargs): if callable(python_callable): return TaskGroupDecorator(function=python_callable, kwargs=tg_kwargs) return cast(Callable[[F], F], functools.partial(TaskGroupDecorator, kwargs=tg_kwargs))

8fe9783fcd813dced8de849c8130d0eb7f90bac3

task_group.py

Typing support for operator mapping functions (#21415)

airflow

airflow/decorators/task_group.py

Python

https://github.com/apache/airflow.git

get_tail

def get_tail(self, n=10, raw=True, output=False, include_latest=False): self.writeout_cache() if not include_latest: n += 1 cur = self._run_sql("ORDER BY session DESC, line DESC LIMIT ?", (n,), raw=raw, output=output) if not include_latest: return reversed(list(cur)[1:]) return reversed(list(cur))

ebea766ceb57ec0080300b246be0699f41957e26

history.py

Fix HistoryAccessor.get_tail bug (#13666) Current implementation of get_tail in HistoryAccessor assumes context present only in subclass , so it's moved there and the old implementation is restored.

ipython

IPython/core/history.py

Python

https://github.com/ipython/ipython.git

get_available_prefixes

def get_available_prefixes(self): params = { 'prefix__net_contained': str(self.prefix) } if hasattr(self, 'vrf'): params['vrf'] = self.vrf child_prefixes = Prefix.objects.filter(**params).values_list('prefix', flat=True) return netaddr.IPSet(self.prefix) - netaddr.IPSet(child_prefixes)

7ba0b420f181cffac86a9de384a1ec9d8a9a07dd

ip.py

Fixes #10109: Fix available prefixes calculation for container prefixes in the global table

netbox

netbox/ipam/models/ip.py

Python

https://github.com/netbox-community/netbox.git

to_sql

def to_sql(cls, qc, **kwargs): # we first insert an empty DF in order to create the full table in the database # This also helps to validate the input against pandas # we would like to_sql() to complete only when all rows have been inserted into the database # since the mapping operation is non-blocking, each partition will return an empty DF # so at the end, the blocking operation will be this empty DF to_pandas empty_df = qc.getitem_row_array([0]).to_pandas().head(0) empty_df.to_sql(**kwargs) # so each partition will append its respective DF kwargs["if_exists"] = "append" columns = qc.columns

0faf4675140415e17d4112f9d0d37cfe87770b9e

io.py

REFACTOR-#3871: move related to pandas functionality into 'PandasOnRayIO' class (#3872) Signed-off-by: Anatoly Myachev <[email protected]>

modin

modin/core/execution/ray/implementations/pandas_on_ray/io/io.py

Python

https://github.com/modin-project/modin.git

run_py

def run_py(executable, *code): if os.name == 'nt' and len(code) > 1: # Windows can't do newlines in arguments... oshandle, filename = tempfile.mkstemp() with os.fdopen(oshandle, 'w') as f: f.write('\n'.join(code)) cmd = [executable, filename] try: ret = subprocess.run(cmd, text=True, check=True, stdout=subprocess.PIPE).stdout finally: os.remove(filename) else: cmd = [executable, '-c', '\n'.join(code)] ret = subprocess.run(cmd, text=True, check=True, stdout=subprocess.PIPE).stdout return ret.rstrip()

ab7a2ee55811c1d25dc482f4d5126eb4d7bbe714

link_pyqt.py

Switch to Python 3.7 subprocess API Follow-up for #6905

qutebrowser

scripts/link_pyqt.py

Python

https://github.com/qutebrowser/qutebrowser.git

fingerprint

def fingerprint(self) -> Text: if self.is_dense(): f_as_text = self.features.tobytes() else: f_as_text = rasa.shared.nlu.training_data.util.sparse_matrix_to_string( self.features ) return rasa.shared.utils.io.deep_container_fingerprint( [self.type, self.origin, self.attribute, f_as_text] )

4cdceaab5271a5b51463ec562c8eb55f96b771c5

features.py

Bump numpy from 1.19.5 to 1.21.6 (#11078) * Bump numpy from 1.19.5 to 1.21.6 Bumps [numpy](https://github.com/numpy/numpy) from 1.19.5 to 1.21.6. - [Release notes](https://github.com/numpy/numpy/releases) - [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst.txt) - [Commits](https://github.com/numpy/numpy/compare/v1.19.5...v1.21.6) --- updated-dependencies: - dependency-name: numpy dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <[email protected]> * fixed mypy errors for numpy 1.21.6 upgrade * removed duplicate np.array call Signed-off-by: dependabot[bot] <[email protected]> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Thomas Werkmeister <[email protected]> Co-authored-by: melindaloubser1 <[email protected]>

rasa

rasa/shared/nlu/training_data/features.py

Python

https://github.com/RasaHQ/rasa.git

test_stop_by_max_time_mins

def test_stop_by_max_time_mins(): tpot_obj = TPOTClassifier(config_dict='TPOT light') tpot_obj._start_datetime = datetime.now() sleep(0.11) tpot_obj.max_time_mins = 0.1/60. assert_raises(KeyboardInterrupt, tpot_obj._stop_by_max_time_mins)

388616b6247ca4ea8de4e2f340d6206aee523541

tpot_tests.py

Revert "Deployed 7ccda9a with MkDocs version: 1.3.0" This reverts commit bd9629c40e01241766197119b581a99409b07068.

tpot

tests/tpot_tests.py

Python

https://github.com/EpistasisLab/tpot.git

get_requires_python

def get_requires_python(dist): # type: (pkg_resources.Distribution) -> Optional[str] pkg_info_dict = get_metadata(dist) requires_python = pkg_info_dict.get("Requires-Python") if requires_python is not None: # Convert to a str to satisfy the type checker, since requires_python # can be a Header object. requires_python = str(requires_python) return requires_python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

packaging.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/utils/packaging.py

Python

https://github.com/jindongwang/transferlearning.git

test_remove_failure

def test_remove_failure(): fileset_pkg_name = "info_fake" fileset_lslpp_error = lslpp_call = MagicMock(return_value=fileset_lslpp_error) list_pkgs_mock = MagicMock( side_effect=[ {"bos.net.tcp.tcpdump": "7.2.4.1"}, {"bos.net.tcp.tcpdump": "7.2.4.1"}, ] ) with patch.dict( aixpkg.__salt__, { "cmd.run_all": lslpp_call, "config.get": MagicMock(return_value=False), }, ), patch.object(aixpkg, "list_pkgs", list_pkgs_mock): expected = { "changes": {}, "errors": [f"Fileset {fileset_pkg_name} not installed."], } with pytest.raises(CommandExecutionError) as exc_info: result = aixpkg.remove(fileset_pkg_name) assert exc_info.value.info == expected, exc_info.value.info assert lslpp_call.call_count == 1 lslpp_call.assert_any_call( ["/usr/bin/lslpp", "-Lc", f"{fileset_pkg_name}"], python_shell=False, )

b2f8271fed3f05160431c55ad7c4e8f3e3e95c3e

test_aixpkg.py

Complete intial tests for AIX yum and dnf support

salt

tests/pytests/unit/modules/test_aixpkg.py

Python

https://github.com/saltstack/salt.git

test_evaluated_individuals_

def test_evaluated_individuals_(): tpot_obj = TPOTClassifier( random_state=42, population_size=2, offspring_size=4, generations=1, verbosity=0, config_dict='TPOT light' ) tpot_obj.fit(training_features, training_target) assert isinstance(tpot_obj.evaluated_individuals_, dict) for pipeline_string in sorted(tpot_obj.evaluated_individuals_.keys()): deap_pipeline = creator.Individual.from_string(pipeline_string, tpot_obj._pset) sklearn_pipeline = tpot_obj._toolbox.compile(expr=deap_pipeline) operator_count = tpot_obj._operator_count(deap_pipeline) try: cv_scores = model_selection.cross_val_score(sklearn_pipeline, training_features, training_target, cv=5, scoring='accuracy', verbose=0) mean_cv_scores = np.mean(cv_scores) except Exception: mean_cv_scores = -float('inf') assert np.allclose(tpot_obj.evaluated_individuals_[pipeline_string]['internal_cv_score'], mean_cv_scores) assert np.allclose(tpot_obj.evaluated_individuals_[pipeline_string]['operator_count'], operator_count)

388616b6247ca4ea8de4e2f340d6206aee523541

tpot_tests.py

Revert "Deployed 7ccda9a with MkDocs version: 1.3.0" This reverts commit bd9629c40e01241766197119b581a99409b07068.

tpot

tests/tpot_tests.py

Python

https://github.com/EpistasisLab/tpot.git

user_can_delete_obj

def user_can_delete_obj(self, user, obj): perm_codename = self.get_perm_codename("delete") return self.user_has_specific_permission(user, perm_codename)

d10f15e55806c6944827d801cd9c2d53f5da4186

permission.py

Reformat with black

wagtail

wagtail/contrib/modeladmin/helpers/permission.py

Python

https://github.com/wagtail/wagtail.git

test_draw_edges_toggling_with_arrows_kwarg

def test_draw_edges_toggling_with_arrows_kwarg(): import matplotlib.collections import matplotlib.patches UG = nx.path_graph(3) DG = nx.path_graph(3, create_using=nx.DiGraph) pos = {n: (n, n) for n in UG} # Use FancyArrowPatches when arrows=True, regardless of graph type for G in (UG, DG): edges = nx.draw_networkx_edges(G, pos, arrows=True) assert len(edges) == len(G.edges) assert isinstance(edges[0], mpl.patches.FancyArrowPatch) # Use LineCollection when arrows=False, regardless of graph type for G in (UG, DG): edges = nx.draw_networkx_edges(G, pos, arrows=False) assert isinstance(edges, mpl.collections.LineCollection) # Default behavior when arrows=None: FAPs for directed, LC's for undirected edges = nx.draw_networkx_edges(UG, pos) assert isinstance(edges, mpl.collections.LineCollection) edges = nx.draw_networkx_edges(DG, pos) assert len(edges) == len(G.edges) assert isinstance(edges[0], mpl.patches.FancyArrowPatch) @pytest.mark.parametrize("drawing_func", (nx.draw, nx.draw_networkx))

5c0b11afb4c0882a070d522ef3fa41482ba935d3

@pytest.mark.parametrize("drawing_func", (nx.draw, nx.draw_networkx))

test_pylab.py

Use isort with pre-commit to enforce import guidelines (#5659) * Add isort to pre-commit * Run isort on all python files (except __init__.py ones)

networkx

networkx/drawing/tests/test_pylab.py

Python

https://github.com/networkx/networkx.git

test_unknown_filter

def test_unknown_filter(self): # Insert session metrics: self.store_session(self.build_session(project_id=self.project.id)) response = self.get_response( self.organization.slug, field="sum(sentry.sessions.session)", statsPeriod="1h", interval="1h", datasource="snuba", query="foo:123", # Unknown tag key ) assert response.status_code == 400 response = self.get_success_response( self.organization.slug, field="sum(sentry.sessions.session)", statsPeriod="1h", interval="1h", datasource="snuba", query="release:123", # Unknown tag value is fine. ) groups = response.data["groups"] assert len(groups) == 0

8f22ac2a9290cb173f1dcdcf7b680c7992c6d4ad

test_organization_metrics.py

fix: remove print statement (#31046)

sentry

tests/sentry/api/endpoints/test_organization_metrics.py

Python

https://github.com/getsentry/sentry.git

get_user_input

def get_user_input(): model_types = list(auto_module.configuration_auto.MODEL_NAMES_MAPPING.keys()) # Get old model type valid_model_type = False while not valid_model_type: old_model_type = input( "What is the model you would like to duplicate? Please provide the lowercase `model_type` (e.g. roberta): " ) if old_model_type in model_types: valid_model_type = True else: print(f"{old_model_type} is not a valid model type.") near_choices = difflib.get_close_matches(old_model_type, model_types) if len(near_choices) >= 1: if len(near_choices) > 1: near_choices = " or ".join(near_choices) print(f"Did you mean {near_choices}?") old_model_info = retrieve_info_for_model(old_model_type) old_tokenizer_class = old_model_info["model_patterns"].tokenizer_class old_feature_extractor_class = old_model_info["model_patterns"].feature_extractor_class old_processor_class = old_model_info["model_patterns"].processor_class old_frameworks = old_model_info["frameworks"] old_checkpoint = None if len(old_model_info["model_patterns"].checkpoint) == 0: old_checkpoint = get_user_field( "We couldn't find the name of the base checkpoint for that model, please enter it here." ) model_name = get_user_field( "What is the name (with no special casing) for your new model in the paper (e.g. RoBERTa)? " ) default_patterns = ModelPatterns(model_name, model_name) model_type = get_user_field( "What identifier would you like to use for the `model_type` of this model? ", default_value=default_patterns.model_type, ) model_lower_cased = get_user_field( "What lowercase name would you like to use for the module (folder) of this model? ", default_value=default_patterns.model_lower_cased, ) model_camel_cased = get_user_field( "What prefix (camel-cased) would you like to use for the model classes of this model (e.g. Roberta)? ", default_value=default_patterns.model_camel_cased, ) model_upper_cased = get_user_field( "What prefix (upper-cased) would you like to use for the constants relative to this model? ", default_value=default_patterns.model_upper_cased, ) config_class = get_user_field( "What will be the name of the config class for this model? ", default_value=f"{model_camel_cased}Config" ) checkpoint = get_user_field( "Please give a checkpoint identifier (on the model Hub) for this new model (e.g. facebook/roberta-base): " ) old_processing_classes = [ c for c in [old_feature_extractor_class, old_tokenizer_class, old_processor_class] if c is not None ] old_processing_classes = ", ".join(old_processing_classes) keep_processing = get_user_field( f"Will your new model use the same processing class as {old_model_type} ({old_processing_classes}) (yes/no)? ", convert_to=convert_to_bool, fallback_message="Please answer yes/no, y/n, true/false or 1/0. ", ) if keep_processing: feature_extractor_class = old_feature_extractor_class processor_class = old_processor_class tokenizer_class = old_tokenizer_class else: if old_tokenizer_class is not None: tokenizer_class = get_user_field( "What will be the name of the tokenizer class for this model? ", default_value=f"{model_camel_cased}Tokenizer", ) else: tokenizer_class = None if old_feature_extractor_class is not None: feature_extractor_class = get_user_field( "What will be the name of the feature extractor class for this model? ", default_value=f"{model_camel_cased}FeatureExtractor", ) else: feature_extractor_class = None if old_processor_class is not None: processor_class = get_user_field( "What will be the name of the processor class for this model? ", default_value=f"{model_camel_cased}Processor", ) else: processor_class = None model_patterns = ModelPatterns( model_name, checkpoint, model_type=model_type, model_lower_cased=model_lower_cased, model_camel_cased=model_camel_cased, model_upper_cased=model_upper_cased, config_class=config_class, tokenizer_class=tokenizer_class, feature_extractor_class=feature_extractor_class, processor_class=processor_class, ) add_copied_from = get_user_field( "Should we add # Copied from statements when creating the new modeling file (yes/no)? ", convert_to=convert_to_bool, default_value="yes", fallback_message="Please answer yes/no, y/n, true/false or 1/0.", ) all_frameworks = get_user_field( "Should we add a version of your new model in all the frameworks implemented by" f" {old_model_type} ({old_frameworks}) (yes/no)? ", convert_to=convert_to_bool, default_value="yes", fallback_message="Please answer yes/no, y/n, true/false or 1/0.", ) if all_frameworks: frameworks = None else: frameworks = get_user_field( "Please enter the list of framworks you want (pt, tf, flax) separated by spaces", is_valid_answer=lambda x: all(p in ["pt", "tf", "flax"] for p in x.split(" ")), ) frameworks = list(set(frameworks.split(" "))) return (old_model_type, model_patterns, add_copied_from, frameworks, old_checkpoint)

fc21c9be62483d06adae6239ebe6ca77c2cb6269

add_new_model_like.py

[CookieCutter] Clarify questions (#18959) * Clarify cookiecutter questions * Update first question Co-authored-by: Niels Rogge <[email protected]>

transformers

src/transformers/commands/add_new_model_like.py

Python

https://github.com/huggingface/transformers.git

__enter__

def __enter__(self): return_value = super().__enter__() try: os.makedirs(self.settings.value_of(PREFECT_HOME), exist_ok=True) except OSError: warnings.warn( "Failed to create the Prefect home directory at " f"{self.settings.value_of(PREFECT_HOME)}", stacklevel=2, ) return return_value

4adc737611ffa284d9952779ba2f68174a7e73cc

context.py

Squash issues with tests

prefect

src/prefect/context.py

Python

https://github.com/PrefectHQ/prefect.git

get_name

def get_name(self): r if self._name: return self._name elif self._parent: par = self._parent()

f3166e673fe8d40277b804d35d77dcdb760fc3b3

results.py

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

pipenv

pipenv/patched/notpip/_vendor/pyparsing/results.py

Python

https://github.com/pypa/pipenv.git

get_party_shipping_address

def get_party_shipping_address(doctype, name): out = frappe.db.sql( "SELECT dl.parent " "from `tabDynamic Link` dl join `tabAddress` ta on dl.parent=ta.name " "where " "dl.link_doctype=%s " "and dl.link_name=%s " 'and dl.parenttype="Address" ' "and ifnull(ta.disabled, 0) = 0 and" '(ta.address_type="Shipping" or ta.is_shipping_address=1) ' "order by ta.is_shipping_address desc, ta.address_type desc limit 1", (doctype, name), ) if out: return out[0][0] else: return ""

494bd9ef78313436f0424b918f200dab8fc7c20b

party.py

style: format code with black

erpnext

erpnext/accounts/party.py

Python

https://github.com/frappe/erpnext.git

_trainable_name

def _trainable_name(self, include_trial_id=False): if self.custom_trial_name: return self.custom_trial_name if "env" in self.config: env = self.config["env"] if isinstance(env, type): env = env.__name__ identifier = "{}_{}".format(self.trainable_name, env) else: identifier = self.trainable_name if include_trial_id: identifier += "_" + self.trial_id return identifier.replace("/", "_")

8a2f6bda62378c07a66169ee49504cc3703f7d35

trial.py

[tune/structure] Introduce experiment package (#26033) Experiment, Trial, and config parsing moves into an `experiment` package. Notably, the new public facing APIs will be ``` from ray.tune.experiment import Experiment from ray.tune.experiment import Trial ```

ray

python/ray/tune/experiment/trial.py

Python

https://github.com/ray-project/ray.git

class_distribution

def class_distribution(y, sample_weight=None): classes = [] n_classes = [] class_prior = [] n_samples, n_outputs = y.shape if sample_weight is not None: sample_weight = np.asarray(sample_weight) if issparse(y): y = y.tocsc() y_nnz = np.diff(y.indptr) for k in range(n_outputs): col_nonzero = y.indices[y.indptr[k] : y.indptr[k + 1]] # separate sample weights for zero and non-zero elements if sample_weight is not None: nz_samp_weight = sample_weight[col_nonzero] zeros_samp_weight_sum = np.sum(sample_weight) - np.sum(nz_samp_weight) else: nz_samp_weight = None zeros_samp_weight_sum = y.shape[0] - y_nnz[k] classes_k, y_k = np.unique( y.data[y.indptr[k] : y.indptr[k + 1]], return_inverse=True ) class_prior_k = np.bincount(y_k, weights=nz_samp_weight) # An explicit zero was found, combine its weight with the weight # of the implicit zeros if 0 in classes_k: class_prior_k[classes_k == 0] += zeros_samp_weight_sum # If an there is an implicit zero and it is not in classes and # class_prior, make an entry for it if 0 not in classes_k and y_nnz[k] < y.shape[0]: classes_k = np.insert(classes_k, 0, 0) class_prior_k = np.insert(class_prior_k, 0, zeros_samp_weight_sum) classes.append(classes_k) n_classes.append(classes_k.shape[0]) class_prior.append(class_prior_k / class_prior_k.sum()) else: for k in range(n_outputs): classes_k, y_k = np.unique(y[:, k], return_inverse=True) classes.append(classes_k) n_classes.append(classes_k.shape[0]) class_prior_k = np.bincount(y_k, weights=sample_weight) class_prior.append(class_prior_k / class_prior_k.sum()) return (classes, n_classes, class_prior)

e4a7edc4aec597cba8b2bbce704772c7872e55f8

multiclass.py

DOC ensures sklearn.utils.multiclass.class_distribution passes numpydoc validation (#24452)

scikit-learn

sklearn/utils/multiclass.py

Python

https://github.com/scikit-learn/scikit-learn.git

evaluate

def evaluate(self) -> float | None | Tuple[float, Any] | Tuple[None, Any]: # Note that the first item of the returned value will be used as the default metric used by NNI. raise NotImplementedError

5a3d82e842906dc8f695fafe52434fde781615be

evaluator.py

[Compression] lightning & legacy evaluator - step 1 (#4950)

nni

nni/algorithms/compression/v2/pytorch/utils/evaluator.py

Python

https://github.com/microsoft/nni.git

_get_gradients

def _get_gradients(self, tape, loss, var_list, grad_loss=None): grads = tape.gradient(loss, var_list, grad_loss) return list(zip(grads, var_list))

84afc5193d38057e2e2badf9c889ea87d80d8fbf

optimizer_v2.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/optimizers/optimizer_v2/optimizer_v2.py

Python

https://github.com/keras-team/keras.git

p_mean_variance

def p_mean_variance(self, model, x, t, transformer_out, clip_denoised=True, model_kwargs=None): if model_kwargs is None: model_kwargs = {} B, C = x.shape[:2] assert t.shape == (B,) model_output = model(x, t, transformer_out) assert model_output.shape == (B, C * 2, *x.shape[2:]) model_output, model_var_values = torch.split(model_output, C, dim=1) min_log = _extract_into_tensor(self.noise_scheduler.posterior_log_variance_clipped, t, x.shape) max_log = _extract_into_tensor(np.log(self.noise_scheduler.betas), t, x.shape) # The model_var_values is [-1, 1] for [min_var, max_var]. frac = (model_var_values + 1) / 2 model_log_variance = frac * max_log + (1 - frac) * min_log model_variance = torch.exp(model_log_variance) pred_xstart = self._predict_xstart_from_eps(x_t=x, t=t, eps=model_output) if clip_denoised: pred_xstart = pred_xstart.clamp(-1, 1) model_mean, _, _ = self.q_posterior_mean_variance(x_start=pred_xstart, x_t=x, t=t) assert model_mean.shape == model_log_variance.shape == pred_xstart.shape == x.shape return model_mean, model_variance, model_log_variance, pred_xstart

1e21f061601dda0aa9740e88bfce68bf4aac4acd

modeling_glide.py

Classifier-free guidance scheduler + GLIDe pipeline

diffusers

models/vision/glide/modeling_glide.py

Python

https://github.com/huggingface/diffusers.git

button_platform_only

def button_platform_only(): with patch( "homeassistant.components.zha.PLATFORMS", ( Platform.BINARY_SENSOR, Platform.BUTTON, Platform.DEVICE_TRACKER, Platform.NUMBER, Platform.SELECT, Platform.SENSOR, ), ): yield @pytest.fixture

4bc5d7bfed07c20d6f3438ab91c734a620505a33

@pytest.fixture

test_button.py

Speed up zha tests (#73627)

core

tests/components/zha/test_button.py

Python

https://github.com/home-assistant/core.git

get_blocks_with_metadata

def get_blocks_with_metadata(self) -> List[Tuple[ObjectRef[Block], BlockMetadata]]: self.get_blocks() # Force bulk evaluation in LazyBlockList. return list(self.iter_blocks_with_metadata())

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

block_list.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

python/ray/data/impl/block_list.py

Python

https://github.com/ray-project/ray.git

get_setters

def get_setters(self): setters = [] for name in dir(self.o): if not name.startswith('set_'): continue func = getattr(self.o, name) if (not callable(func) or self.number_of_parameters(func) < 2 or self.is_alias(func)): continue setters.append(name[4:]) return setters

87197156eb299c1f37ac23c16c83ecb000e9872b

artist.py

improve matplotlib import time by caching ArtistInspector

matplotlib

lib/matplotlib/artist.py

Python

https://github.com/matplotlib/matplotlib.git

test_cable_cannot_have_the_same_terminination_on_both_ends

def test_cable_cannot_have_the_same_terminination_on_both_ends(self): cable = Cable(a_terminations=[self.interface1], b_terminations=[self.interface1]) with self.assertRaises(ValidationError): cable.clean()

3a461d02793e6f9d41c2b1a92647e691de1abaac

test_models.py

Update Cable instantiations to match new signature

netbox

netbox/dcim/tests/test_models.py

Python

https://github.com/netbox-community/netbox.git

_parse_img_level_ann

def _parse_img_level_ann(self, image_level_ann_file): item_lists = defaultdict(list) with self.file_client.get_local_path( image_level_ann_file) as local_path: with open(local_path, 'r') as f: reader = csv.reader(f) i = -1 for line in reader: i += 1 if i == 0: continue else: img_id = line[0] label_id = line[1] assert label_id in self.label_id_mapping image_level_label = int( self.label_id_mapping[label_id]) confidence = float(line[2]) item_lists[img_id].append( dict( image_level_label=image_level_label, confidence=confidence)) return item_lists

36c1f477b273cb2fb0dea3c921ec267db877c039

openimages.py

Refactor OpenImages.

mmdetection

mmdet/datasets/openimages.py

Python

https://github.com/open-mmlab/mmdetection.git

stride_pool_pos

def stride_pool_pos(self, pos_id, block_index): if self.separate_cls: # Under separate <cls>, we treat the <cls> as the first token in # the previous block of the 1st real block. Since the 1st real # block always has position 1, the position of the previous block # will be at `1 - 2 ** block_index`. cls_pos = tf.constant([-(2**block_index) + 1], dtype=pos_id.dtype) pooled_pos_id = pos_id[1:-1] if self.truncate_seq else pos_id[1:] return tf.concat([cls_pos, pooled_pos_id[::2]], 0) else: return pos_id[::2]

7732d0fe7a759c9844215920e9f1c5540eafb1a6

modeling_tf_funnel.py

Upgrade black to version ~=22.0 (#15565) * Upgrade black to version ~=22.0 * Check copies * Fix code

transformers

src/transformers/models/funnel/modeling_tf_funnel.py

Python

https://github.com/huggingface/transformers.git

_mark_func_graph_as_unsaveable

def _mark_func_graph_as_unsaveable(graph, learning_phase): if graph.building_function and is_placeholder(learning_phase): graph.mark_as_unsaveable( "The keras learning phase placeholder was used inside a function. " "Exporting placeholders is not supported when saving out a SavedModel. " "Please call `tf.keras.backend.set_learning_phase(0)` in the function " "to set the learning phase to a constant value." )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

https://github.com/keras-team/keras.git

maybe_fsdp_wrap

def maybe_fsdp_wrap(opt): if not should_use_fsdp(opt): # make a no-op yield return # zero3 not supported at this time. Throw an exception if opt['ddp_backend'] == 'zero3': raise NotImplementedError( '--ddp-backend zero3 is not supported at this time. For details, see ' 'https://github.com/facebookresearch/ParlAI/issues/3753.' ) reshard_after_forward = opt['ddp_backend'] == 'zero3' compute_dtype = torch.float16 if opt['fp16'] else torch.float32 mixed_precision = opt['fp16'] and opt['fp16_impl'] == 'safe' fsdp_args = dict( reshard_after_forward=reshard_after_forward, mixed_precision=mixed_precision, compute_dtype=compute_dtype, state_dict_device=torch.device('cpu'), flatten_parameters=False, process_group=get_dist_group(), ) with fairscale_enable_wrap(wrapper_cls=FSDP, **fsdp_args): yield

5322cd4f5821e339bf1edab98d93b5a008b97a2b

fsdp.py

[circle] Fixing broken unit tests (#4343)

ParlAI

parlai/utils/fsdp.py

Python

https://github.com/facebookresearch/ParlAI.git

apply

def apply(self, X): X = self._validate_X_predict(X) results = Parallel( n_jobs=self.n_jobs, verbose=self.verbose, prefer="threads", )(delayed(tree.apply)(X, check_input=False) for tree in self.estimators_) return np.array(results).T

5f75acdd12d77b973471961ad716367c6199d01c

_forest.py

MNT Bump joblib version dependency to 1.0.0 (#22365)

scikit-learn

sklearn/ensemble/_forest.py

Python

https://github.com/scikit-learn/scikit-learn.git

_get_all_ret_events_after_time

def _get_all_ret_events_after_time(masters, minions, event_listener, start_time): minion_pattern = "salt/job/*/ret/{}" events = [] for minion in minions: tag = minion_pattern.format(minion.id) matchers = [(master.id, tag) for master in masters] ret_events = event_listener.get_events(matchers, after_time=start_time) events.append([event for event in ret_events if event.data["fun"] == "test.echo"]) return tuple(events)

fbecbe82483ffed562c0d2673d5a5e792553aec2

test_multimaster.py

fix multimaster tests failing

salt

tests/pytests/scenarios/multimaster/test_multimaster.py

Python

https://github.com/saltstack/salt.git

test_not_recorded_if_not_used

def test_not_recorded_if_not_used(self, dag_maker, xcom_value): with dag_maker(dag_id="test_not_recorded_for_unused") as dag:

197cff3194e855b9207c3c0da8ae093a0d5dda55

test_taskinstance.py

Ensure TaskMap only checks "relevant" dependencies (#23053) When looking for "mapped dependants" of a task, we only want a task if it not only is a direct downstream of the task, but also it actually "uses" the task's pushed XCom for task mapping. So we need to peek into the mapped downstream task's expansion kwargs, and only count it as a mapped dependant if the upstream is referenced there.

airflow

tests/models/test_taskinstance.py

Python

https://github.com/apache/airflow.git

get_active_users

def get_active_users(browser, username, posts, boundary, logger): user_link = "https://www.instagram.com/{}/".format(username) # check URL of the webpage, if it already is user's profile page, # then do not navigate to it again web_address_navigator(browser, user_link) try: total_posts = browser.execute_script( "return window._sharedData.entry_data." "ProfilePage[0].graphql.user.edge_owner_to_timeline_media.count" ) except WebDriverException: try: topCount_elements = browser.find_elements( By.XPATH, read_xpath(get_active_users.__name__, "topCount_elements") ) if topCount_elements: # prevent an empty string scenario total_posts = format_number(topCount_elements[0].text) else: logger.info("Failed to get posts count on your profile! ~empty string") total_posts = None except NoSuchElementException: logger.info("Failed to get posts count on your profile!") total_posts = None # if posts > total user posts, assume total posts posts = ( posts if total_posts is None else total_posts if posts > total_posts else posts ) active_users = [] sc_rolled = 0 start_time = time.time() too_many_requests = 0 # helps to prevent misbehaviours when requests # list of active users repeatedly within less than 10 min of breaks message = ( "~collecting the entire usernames from posts without a boundary!\n" if boundary is None else "~collecting only the visible usernames from posts without scrolling " "at the boundary of zero..\n" if boundary == 0 else "~collecting the usernames from posts with the boundary of {}" "\n".format(boundary) ) # posts argument is the number of posts to collect usernames logger.info( "Getting active users who liked the latest {} posts:\n {}".format( posts, message ) ) count = 1 checked_posts = 0 user_list = [] while count <= posts: # load next post try: latest_post = browser.find_element( By.XPATH, read_xpath(get_active_users.__name__, "profile_posts").format(count), ) # avoid no posts if latest_post: click_element(browser, latest_post) except (NoSuchElementException, WebDriverException): logger.warning("Failed to click on the latest post to grab active likers!") return [] try: checked_posts += 1 sleep_actual(2) try: likers_count = browser.find_element( By.XPATH, read_xpath(get_active_users.__name__, "likers_count") ).text if likers_count: # prevent an empty string scenarios likers_count = format_number(likers_count) # liked by 'username' AND 165 others (166 in total) likers_count += 1 else: logger.info( "Failed to get likers count on your post {} " "~empty string".format(count) ) likers_count = None except NoSuchElementException: logger.info("Failed to get likers count on your post {}".format(count)) likers_count = None try: likes_button = browser.find_elements( By.XPATH, read_xpath(get_active_users.__name__, "likes_button") ) if likes_button != []: if likes_button[1] is not None: likes_button = likes_button[1] else: likes_button = likes_button[0] click_element(browser, likes_button) sleep_actual(3) else: raise NoSuchElementException except (IndexError, NoSuchElementException): # Video have no likes button / no posts in page logger.info("Video found, try next post until we run out of posts") # edge case of account having only videos, or last post is a video. if checked_posts >= total_posts: break # if not reached posts(parameter) value, continue (but load next post) browser.back() # go to next post count += 1 continue # get a reference to the 'Likes' dialog box dialog = browser.find_element( By.XPATH, read_xpath("class_selectors", "likes_dialog_body_xpath") ) scroll_it = True try_again = 0 start_time = time.time() if likers_count: amount = ( likers_count if boundary is None else None if boundary == 0 else (boundary if boundary < likers_count else likers_count) ) else: amount = None tmp_scroll_height = 0 user_list_len = -1 while scroll_it is not False and boundary != 0: scroll_height = browser.execute_script( ) # check if it should keep scrolling down or exit if ( scroll_height >= tmp_scroll_height and len(user_list) > user_list_len ): tmp_scroll_height = scroll_height user_list_len = len(user_list) scroll_it = True else: scroll_it = False if scroll_it is True: scroll_it = browser.execute_script("window.scrollBy(0, 1000)") update_activity(browser, state=None) if sc_rolled > 91 or too_many_requests > 1: # old value 100 print("\n") logger.info("Too Many Requests sent! ~will sleep some :>\n") sleep_actual(600) sc_rolled = 0 too_many_requests = ( 0 if too_many_requests >= 1 else too_many_requests ) else: sleep_actual(1.2) # old value 5.6 sc_rolled += 1 user_list = get_users_from_dialog(user_list, dialog, logger) # write & update records at Progress Tracker if amount: progress_tracker(len(user_list), amount, start_time, None) print("\n") if boundary is not None: if len(user_list) >= boundary: break if ( scroll_it is False and likers_count and likers_count - 1 > len(user_list) ): if ( boundary is not None and likers_count - 1 > boundary ) or boundary is None: if try_again <= 1: # can increase the amount of tries logger.info( "Failed to get the desired amount of " "usernames but trying again..." "\t|> post: {} |> attempt: {}\n".format( posts, try_again + 1 ) ) try_again += 1 too_many_requests += 1 scroll_it = True nap_it = 4 if try_again == 0 else 7 sleep_actual(nap_it) user_list = get_users_from_dialog(user_list, dialog, logger) logger.info( "Post {} | Likers: found {}, catched {}\n\n".format( count, likers_count, len(user_list) ) ) except NoSuchElementException as exc: logger.error( "Ku-ku! There is an error searching active users" "~\t{}\n\n".format(str(exc).encode("utf-8")) ) for user in user_list: active_users.append(user) sleep_actual(1) # if not reached posts(parameter) value, continue if count != posts + 1: try: # click close button close_dialog_box(browser) browser.back() except Exception: logger.error("Unable to go to next profile post") count += 1 real_time = time.time() diff_in_minutes = int((real_time - start_time) / 60) diff_in_seconds = int((real_time - start_time) % 60) # delete duplicated users active_users = list(set(active_users)) logger.info( "Gathered total of {} unique active followers from the latest {} " "posts in {} minutes and {} seconds".format( len(active_users), posts, diff_in_minutes, diff_in_seconds ) ) return active_users

2a157d452611d37cf50ccb7d56ff1a06e9790ecb

util.py

PR - Fix `extract_text_from_element()`and `find_element*()` to `find_element()` (#6438) * Updated getUserData() and find_element* Signed-off-by: elulcao <[email protected]> Thanks @breuerfelix for reviewing, 🚀 People in this thread please let me know if something is not OK, IG changed a lot these days. 🤗 @her

InstaPy

instapy/util.py

Python

https://github.com/InstaPy/InstaPy.git

test_complex_pipeline_with_shared_prompt_model_yaml

def test_complex_pipeline_with_shared_prompt_model_yaml(tmp_path): with open(tmp_path / "tmp_config.yml", "w") as tmp_file: tmp_file.write( f ) pipeline = Pipeline.load_from_yaml(path=tmp_path / "tmp_config.yml") result = pipeline.run(query="not relevant", documents=[Document("Berlin is an amazing city.")]) assert "Berlin" in result["results"][0] assert len(result["meta"]["invocation_context"]) > 0

9ebf164cfdfb320503b7161493420c1b0ec577a3

test_prompt_node.py

feat: Expand LLM support with PromptModel, PromptNode, and PromptTemplate (#3667) Co-authored-by: ZanSara <[email protected]>

haystack

test/nodes/test_prompt_node.py

Python

https://github.com/deepset-ai/haystack.git

test_new_export

def test_new_export(self): payload = self.make_payload("issue") with self.feature("organizations:discover-query"): response = self.get_success_response(self.org.slug, status_code=201, **payload) data_export = ExportedData.objects.get(id=response.data["id"]) assert response.data == { "id": data_export.id, "user": { "id": str(self.user.id), "email": self.user.email, "username": self.user.username, }, "dateCreated": data_export.date_added, "dateFinished": None, "dateExpired": None, "query": { "type": payload["query_type"], "info": payload["query_info"], }, "status": ExportStatus.Early, "checksum": None, "fileName": None, }

096b5511e244eecd8799b2a0324655207ce8985e

test_data_export.py

ref(tests): Remove `get_valid_response()` (#34822)

sentry

tests/sentry/data_export/endpoints/test_data_export.py

Python

https://github.com/getsentry/sentry.git

test_masked_unmasked_combinations

def test_masked_unmasked_combinations(self): cases = [ (TEST_SECRET, TEST_SECRET, None), (TEST_SECRET, MASKED_TEST_SECRET2, None), (TEST_SECRET, None, TEST_SECRET), (TEST_SECRET, None, MASKED_TEST_SECRET2), (MASKED_TEST_SECRET1, TEST_SECRET, None), (MASKED_TEST_SECRET1, MASKED_TEST_SECRET2, None), (MASKED_TEST_SECRET1, None, TEST_SECRET), (MASKED_TEST_SECRET1, None, MASKED_TEST_SECRET2), ] for args in cases: with self.subTest(args=args): cookie, post_token, meta_token = args req = self._get_POST_csrf_cookie_request( cookie=cookie, post_token=post_token, meta_token=meta_token, ) mw = CsrfViewMiddleware(token_view) mw.process_request(req) resp = mw.process_view(req, token_view, (), {}) self.assertIsNone(resp)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/csrf_tests/tests.py

Python

https://github.com/django/django.git

mode

def mode(self, **kwargs): # noqa: PR02 return DataFrameDefault.register(pandas.DataFrame.mode)(self, **kwargs)

57e29bc5d82348006c5170ef9ac0a9eedcd9acf9

query_compiler.py

REFACTOR-#4513: Fix spelling mistakes in docs and docstrings (#4514) Co-authored-by: Rehan Sohail Durrani <[email protected]> Signed-off-by: jeffreykennethli <[email protected]>

modin

modin/core/storage_formats/base/query_compiler.py

Python

https://github.com/modin-project/modin.git

reduce_using_automaton

def reduce_using_automaton(self, word): # Modify the automaton if new rules are found. if self._new_rules: self._add_to_automaton(self._new_rules) self._new_rules = {} flag = 1 while flag: flag = 0 current_state = self.reduction_automaton.states['start'] for i, s in enumerate(word.letter_form_elm): next_state_name = current_state.transitions[s] next_state = self.reduction_automaton.states[next_state_name] if next_state.state_type == 'd': subst = next_state.rh_rule word = word.substituted_word(i - len(next_state_name) + 1, i+1, subst) flag = 1 break current_state = next_state return word

7d773eb18daaef3c54f34d1ac6cbc5b83a5bb16c

rewritingsystem.py

Cleanup loops and ranges

sympy

sympy/combinatorics/rewritingsystem.py

Python

https://github.com/sympy/sympy.git

_format

def _format(val, valtype, floatfmt, missingval="", has_invisible=True): # noqa if val is None: return missingval if valtype in [int, _text_type]: return "{0}".format(val) elif valtype is _binary_type: try: return _text_type(val, "ascii") except TypeError: return _text_type(val) elif valtype is float: is_a_colored_number = has_invisible and isinstance( val, (_text_type, _binary_type) ) if is_a_colored_number: raw_val = _strip_invisible(val) formatted_val = format(float(raw_val), floatfmt) return val.replace(raw_val, formatted_val) else: return format(float(val), floatfmt) else: return "{0}".format(val)

adf24bfa9723b0621183bb27f0c889b813c06e8a

tabulate.py

[State Observability] Use a table format by default (#26159) NOTE: tabulate is copied/pasted to the codebase for table formatting. This PR changes the default layout to be the table format for both summary and list APIs.

ray

python/ray/_private/thirdparty/tabulate/tabulate.py

Python

https://github.com/ray-project/ray.git

test_single_ignore_dates_set

def test_single_ignore_dates_set(self): test_cases = [ ("1985-05-01", [datetime.date(1985, 5, 1)]), ( "1985-05-01,1991-12-05", [datetime.date(1985, 5, 1), datetime.date(1991, 12, 5)], ), ("2010-12-13", [datetime.date(2010, 12, 13)]), ] for env_str, expected_dates in test_cases: expected_date_set = set() for expected_date in expected_dates: expected_date_set.add(expected_date) self.assertSetEqual( _parse_ignore_dates(env_str), expected_date_set, )

8a6aaf4e2d05021a14adc681c66dff6a815aa2a0

test_settings.py

Adds additional testing for both date parsing and consumed document created date

paperless-ngx

src/paperless/tests/test_settings.py

Python

https://github.com/paperless-ngx/paperless-ngx.git

get_version

def get_version(name, members): # the expression ending for versions must start as # '.so.[0-9]', i.e., *.so.[at least one digit] # while multiple, more specific expressions could be specified # to search for .so.X, .so.X.Y and .so.X.Y.Z # after the first required 'dot' digit # any combination of additional 'dot' digits pairs are accepted # anything more than libFOO.so.digits.digits.digits # should be seen as a member name outside normal expectations exprs = [rf'lib{name}\.so\.[0-9]+[0-9.]*', rf'lib{name}_?64\.so\.[0-9]+[0-9.]*'] for expr in exprs: versions = [] for line in members: m = re.search(expr, line) if m: versions.append(m.group(0)) if versions: return _last_version(versions, '.') return None

8198943edd73a363c266633e1aa5b2a9e9c9f526

_aix.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/ctypes/_aix.py

Python

https://github.com/XX-net/XX-Net.git

result_list

def result_list(context): view = context["view"] object_list = context["object_list"] headers = list(result_headers(view)) num_sorted_fields = 0 for h in headers: if h["sortable"] and h["sorted"]: num_sorted_fields += 1 context.update( { "result_headers": headers, "num_sorted_fields": num_sorted_fields, "results": list(results(view, object_list, context["request"])), } ) return context @register.simple_tag

d10f15e55806c6944827d801cd9c2d53f5da4186

@register.simple_tag

modeladmin_tags.py

Reformat with black

wagtail

wagtail/contrib/modeladmin/templatetags/modeladmin_tags.py

Python

https://github.com/wagtail/wagtail.git

test_wrapped_bleak_client_raises_device_missing

async def test_wrapped_bleak_client_raises_device_missing(hass, enable_bluetooth): switchbot_device = BLEDevice("44:44:33:11:23:45", "wohand") client = HaBleakClientWrapper(switchbot_device) assert client.is_connected is False with pytest.raises(bleak.BleakError): await client.connect() assert client.is_connected is False await client.disconnect()

1b144c0e4dd683e3b47668a89da5eb6da4ae5e08

test_models.py

Update to bleak 0.18.0 (#79008)

core

tests/components/bluetooth/test_models.py

Python

https://github.com/home-assistant/core.git

add_exomw

def add_exomw(self): from nltk.corpus import extended_omw self._exomw_reader = extended_omw self.add_provs(self._exomw_reader)

8ffd0d8190552d45f8b92e18da3fc41639e5185d

wordnet.py

Initialize empty provenance for default English

nltk

nltk/corpus/reader/wordnet.py

Python

https://github.com/nltk/nltk.git

log_status_change_thread

def log_status_change_thread(log_queue, request_iterator): std_handler = StdStreamHandler(log_queue) current_handler = None root_logger = logging.getLogger("ray") default_level = root_logger.getEffectiveLevel() try: for req in request_iterator: if current_handler is not None: root_logger.setLevel(default_level) root_logger.removeHandler(current_handler) std_handler.unregister_global() if not req.enabled: current_handler = None continue current_handler = LogstreamHandler(log_queue, req.loglevel) std_handler.register_global() root_logger.addHandler(current_handler) root_logger.setLevel(req.loglevel) except grpc.RpcError as e: logger.debug(f"closing log thread " f"grpc error reading request_iterator: {e}") finally: if current_handler is not None: root_logger.setLevel(default_level) root_logger.removeHandler(current_handler) std_handler.unregister_global() log_queue.put(None)

608276bb96b5b49769cd8816414c280c5431d843

logservicer.py

Simplify logging configuration. (#30863)

ray

python/ray/util/client/server/logservicer.py

Python

https://github.com/ray-project/ray.git

set_to_context

def set_to_context(self, name): attribute = self.fattributes[name] if isinstance(attribute, NonInheritableFieldAttribute): # setting to sentinel will trigger 'default/default()' on getter setattr(self, name, Sentinel) else: try: setattr(self, name, self._get_parent_attribute(name, omit=True)) except AttributeError: # mostly playcontext as only tasks/handlers/blocks really resolve parent setattr(self, name, Sentinel)

ff6e4da36addccb06001f7b05b1a9c04ae1d7984

base.py

fixes to FA inheritance (#78990) finalized applies to all field attributes fix getting parent value also remove unused/needed extend/prepend signature moar testing

ansible

lib/ansible/playbook/base.py

Python

https://github.com/ansible/ansible.git

device2_info

def device2_info() -> str: return load_fixture("soundtouch/device2_info.xml") @pytest.fixture(scope="session")

efbd47c828c6c2e1cd967df2a4cefd2b00c60c25

@pytest.fixture(scope="session")

conftest.py

Rewrite SoundTouch tests to use mocked payloads (#72984)

core

tests/components/soundtouch/conftest.py

Python

https://github.com/home-assistant/core.git

autoscale

def autoscale(self, A): A = np.asanyarray(A) self.halfrange = max(self._vcenter-A.min(), A.max()-self._vcenter)

84def85c848a172afab987298eb402bd39aceeaa

colors.py

FIX: CenteredNorm use vmin/vmax for halfrange This changes CenteredNorm to use vmin and vmax to represent the halfrange rather than storing it separately and needing to update the vmin/vmax in all of the methods. Additionally, if you now change vcenter, the halfrange does not automatically update.

matplotlib

lib/matplotlib/colors.py

Python

https://github.com/matplotlib/matplotlib.git

test_pss_evaluate_metric_batch_counter

def test_pss_evaluate_metric_batch_counter(self): strategy = tf.distribute.ParameterServerStrategy( self.cluster_resolver, variable_partitioner=None, )

062073cfc4a5fe4c24ed3e326c673951c040982f

parameter_server_training_metric_test.py

Use Model metrics as logs in `fit` and `evaluate` instead of last worker train or test step result Currently the model evaluate returns the last scheduled worker metrics. This is troublesome when using distributed workers as the last one could fail. in Parameter Server Strategy, the last worker may finish sooner than earlier scheduled worker resulting in incorrect metrics being returned. So always rely on current model metrics. PiperOrigin-RevId: 471137058

keras

keras/integration_test/parameter_server_training_metric_test.py

Python

https://github.com/keras-team/keras.git

_handle_mouse_press

def _handle_mouse_press(self, e): is_rocker_gesture = (config.val.input.mouse.rocker_gestures and e.buttons() == Qt.MouseButton.LeftButton | Qt.MouseButton.RightButton) if e.button() in [Qt.MouseButton.XButton1, Qt.MouseButton.XButton2] or is_rocker_gesture: self._mousepress_backforward(e) return True self._ignore_wheel_event = True pos = e.pos() if pos.x() < 0 or pos.y() < 0: log.mouse.warning("Ignoring invalid click at {}".format(pos)) return False if e.button() != Qt.MouseButton.NoButton: self._tab.elements.find_at_pos(pos, self._mousepress_insertmode_cb) return False

0877fb0d78635692e481c8bde224fac5ad0dd430

eventfilter.py

Run scripts/dev/rewrite_enums.py

qutebrowser

qutebrowser/browser/eventfilter.py

Python

https://github.com/qutebrowser/qutebrowser.git

_calc_open_trade_value

def _calc_open_trade_value(self) -> float: open_trade = Decimal(self.amount) * Decimal(self.open_rate) fees = open_trade * Decimal(self.fee_open) if self.is_short: return float(open_trade - fees) else: return float(open_trade + fees)

b58e811b1486ae62e835cbea3e40cf88128243a0

trade_model.py

Move trade/order Models to their own class

freqtrade

freqtrade/persistence/trade_model.py

Python

https://github.com/freqtrade/freqtrade.git

test_file_upload_authed

def test_file_upload_authed(self) -> None: self.login("hamlet") fp = StringIO("zulip!") fp.name = "zulip.txt" result = self.client_post("/json/user_uploads", {"file": fp}) self.assert_json_success(result) self.assertIn("uri", result.json()) uri = result.json()["uri"] base = "/user_uploads/" self.assertEqual(base, uri[: len(base)]) # In the future, local file requests will follow the same style as S3 # requests; they will be first authenthicated and redirected self.assert_streaming_content(self.client_get(uri), b"zulip!") # check if DB has attachment marked as unclaimed entry = Attachment.objects.get(file_name="zulip.txt") self.assertEqual(entry.is_claimed(), False) self.subscribe(self.example_user("hamlet"), "Denmark") body = "First message ...[zulip.txt](http://localhost:9991" + uri + ")" self.send_stream_message(self.example_user("hamlet"), "Denmark", body, "test") # Now try the endpoint that's supposed to return a temporary URL for access # to the file. result = self.client_get("/json" + uri) self.assert_json_success(result) data = result.json() url_only_url = data["url"] # Ensure this is different from the original uri: self.assertNotEqual(url_only_url, uri) self.assertIn("user_uploads/temporary/", url_only_url) self.assertTrue(url_only_url.endswith("zulip.txt")) # The generated URL has a token authorizing the requestor to access the file # without being logged in. self.logout() self.assert_streaming_content(self.client_get(url_only_url), b"zulip!") # The original uri shouldn't work when logged out: result = self.client_get(uri) self.assertEqual(result.status_code, 401)

ba7ea7cc809ace3e8ecf25311e54d78f62b0d0c8

test_upload.py

test_classes: Extract assert_streaming_content helper. This also fixes a warning from RealmExportTest.test_endpoint_local_uploads: “ResourceWarning: unclosed file <_io.BufferedReader name='/srv/zulip/var/…/test-export.tar.gz'>”. Signed-off-by: Anders Kaseorg <[email protected]>

zulip

zerver/tests/test_upload.py

Python

https://github.com/zulip/zulip.git

get_current_branch

def get_current_branch(cls, location): # type: (str) -> Optional[str] # git-symbolic-ref exits with empty stdout if "HEAD" is a detached # HEAD rather than a symbolic ref. In addition, the -q causes the # command to exit with status code 1 instead of 128 in this case # and to suppress the message to stderr. args = ['symbolic-ref', '-q', 'HEAD'] output = cls.run_command( args, extra_ok_returncodes=(1, ), show_stdout=False, stdout_only=True, cwd=location, ) ref = output.strip() if ref.startswith('refs/heads/'): return ref[len('refs/heads/'):] return None

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

git.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/vcs/git.py

Python

https://github.com/jindongwang/transferlearning.git

localize_tag

def localize_tag(parser, token): use_l10n = None bits = list(token.split_contents()) if len(bits) == 1: use_l10n = True elif len(bits) > 2 or bits[1] not in ("on", "off"): raise TemplateSyntaxError("%r argument should be 'on' or 'off'" % bits[0]) else: use_l10n = bits[1] == "on" nodelist = parser.parse(("endlocalize",)) parser.delete_first_token() return LocalizeNode(nodelist, use_l10n)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

l10n.py

Refs #33476 -- Reformatted code with Black.

django

django/templatetags/l10n.py

Python

https://github.com/django/django.git

flush

def flush(self) -> None: self._write_to_log_file() self._write_to_devtools() self._buffer.clear()

3b40eb828b5217fd023c07694a02f148664b9588

redirect_output.py

Redirecting stdout to both devtools and logfile

textual

src/textual/devtools/redirect_output.py

Python

https://github.com/Textualize/textual.git

get_execution_info

def get_execution_info(self, job_id, function_descriptor): function_id = function_descriptor.function_id # If the function has already been loaded, # There's no need to load again if function_id in self._function_execution_info: return self._function_execution_info[function_id] if self._worker.load_code_from_local: # Load function from local code. if not function_descriptor.is_actor_method(): # If the function is not able to be loaded, # try to load it from GCS, # even if load_code_from_local is set True if self._load_function_from_local(function_descriptor) is True: return self._function_execution_info[function_id] # Load function from GCS. # Wait until the function to be executed has actually been # registered on this worker. We will push warnings to the user if # we spend too long in this loop. # The driver function may not be found in sys.path. Try to load # the function from GCS. with profiling.profile("wait_for_function"): self._wait_for_function(function_descriptor, job_id) try: function_id = function_descriptor.function_id info = self._function_execution_info[function_id] except KeyError as e: message = ( "Error occurs in get_execution_info: " "job_id: %s, function_descriptor: %s. Message: %s" % (job_id, function_descriptor, e) ) raise KeyError(message) return info

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

function_manager.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

python/ray/_private/function_manager.py

Python

https://github.com/ray-project/ray.git

_enable_task_listeners

def _enable_task_listeners(): if get_listener_manager().has_listeners: register_task_instance_state_events()

dba00ce6a32b7f50153887c6974f62985ca8023f

local_task_job.py

Add Listener Plugin API that tracks TaskInstance state changes (#20443) This adds new Plugin API - "listeners". It enables plugin authors to write [pluggy hook implementation][1] that will be called on certain formalized extension points. To differentiate between current Airflow extension points, like plugins, and current Airflow hooks, implementations of those hooks are called listeners. The API is ment to be called across all dags, and all operators - in contrast to current on_success_callback, pre_execute and related family which are meant to provide callbacks for particular dag authors, or operator creators. pluggy mechanism enables us to execute multiple, or none, listeners that implement particular extension point, so that users can use multiple listeners seamlessly. In this PR, three such extension points are added. When TaskInstance's state is changed to RUNNING, on_task_instance_running hook is called. On change toSUCCESS on_task_instance_success is called, similarly on FAILED on_task_instance_failed is called. Actual notification mechanism is be implemented using [SQLAlchemy’s events mechanism][2]. This ensures that plugins will get every change of state, regardless of where in the codebase it happened, and not require manual annotation of TI state changes across the codebase. To make sure that this change is not affecting performance, running this mechanism on scheduler is disabled by default. The SQLAlchemy event mechanism is also not affected by default - the event listener is only added if we have any plugin which actually provides any listener. [1]: https://pluggy.readthedocs.io/en/stable/ [2]: https://docs.sqlalchemy.org/en/13/orm/session_events.html#after-flush Signed-off-by: Maciej Obuchowski <[email protected]>

airflow

airflow/jobs/local_task_job.py

Python

https://github.com/apache/airflow.git

get_binance_available_quotes_for_each_coin

def get_binance_available_quotes_for_each_coin() -> dict: trading_pairs = _get_trading_pairs() results = defaultdict(list) for pair in trading_pairs: results[pair["baseAsset"]].append(pair["quoteAsset"]) return results @log_start_end(log=logger) @check_api_key(["API_BINANCE_KEY", "API_BINANCE_SECRET"])

59d8b36bb0467a1a99513b10e8b8471afaa56fd6

@log_start_end(log=logger) @check_api_key(["API_BINANCE_KEY", "API_BINANCE_SECRET"])

binance_model.py

[IMPROVE] Fix Docstring formatting/Fix missing, incomplete type hints (#3412) * Fixes * Update stocks_helper.py * update git-actions set-output to new format * Update stocks_helper.py * Update terminal_helper.py * removed LineAnnotateDrawer from qa_view * lint * few changes * updates * sdk auto gen modules done * Update stocks_helper.py * updates to changed imports, and remove first sdk_modules * Update generate_sdk.py * Update generate_sdk.py * pylint * revert stocks_helper * Update generate_sdk.py * Update sdk.py * Update generate_sdk.py * full auto generation, added sdk.py/controllers creation * missed enable forecasting * added running black in subprocess after sdk files generation completes * removed deleted sdk_arg_logger * comment out tests * property doc fix * clean up * Update generate_sdk.py * make trailmap classes useable for doc generation * Update generate_sdk.py * added lineon to trailmap class for linking to func in markdown * changed lineon to dict * added full_path to trailmap for linking in docs * updated portfolio * feat: initial files * feat: added meta head * feat: added funcdef * added func_def to trailmap attributes for markdown in docs, added missing type hints to covid functions * feat: added view and merged with jaun * Update generate_sdk.py * Update generate_sdk.py * Update generate_sdk.py * Update generate_sdk.py * init * fix returns * fix: random stuff * fix: random * fixed encoding issue on windows * fix: generate tabs * update * Update generate_sdk_markdown.py * Create .pydocstyle.ini * added type hint classes for views * fixes * alt, ba * alt-economy * Update finviz_compare_model.py * fixs * Update substack_model.py * Update generate_sdk.py * last of my section * porfolio * po * Update optimizer_model.py * fixing more things * few more * keys done * update * fixes * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * mypy forecast fix * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * fixes * forecast fixes * one more fix * Update coinbase_model.py * Update generate_sdk_markdown.py Co-authored-by: Colin Delahunty <[email protected]> Co-authored-by: James Maslek <[email protected]> Co-authored-by: jose-donato <[email protected]> Co-authored-by: andrewkenreich <[email protected]>

OpenBBTerminal

openbb_terminal/cryptocurrency/due_diligence/binance_model.py

Python

https://github.com/OpenBB-finance/OpenBBTerminal.git

nunique_approx

def nunique_approx(self, split_every=None): from dask.dataframe import hyperloglog # here to avoid circular import issues return aca( [self], chunk=hyperloglog.compute_hll_array, combine=hyperloglog.reduce_state, aggregate=hyperloglog.estimate_count, split_every=split_every, b=16, meta=float, )

cccb9d8d8e33a891396b1275c2448c352ef40c27

core.py

absolufy-imports - No relative - PEP8 (#8796) Conversation in https://github.com/dask/distributed/issues/5889

dask

dask/dataframe/core.py

Python

https://github.com/dask/dask.git