def test_update_in():
assert update_in({"a": 0}, ["a"], inc) == {"a": 1}
assert update_in({"a": 0, "b": 1}, ["b"], str) == {"a": 0, "b": "1"}
assert (update_in({
"t": 1,
"v": {
"a": 0
}
}, ["v", "a"], inc) == {
"t": 1,
"v": {
"a": 1
}
})
# Handle missing element one deep:
assert update_in({}, ["z"], str) == {"z": "None"}
# Same semantics as Clojure, raises an error if going deeper than
# one level into a dict which doesn't have the initial key:
assert raises(AttributeError, lambda: update_in({}, ["z", "q"], str))
# Verify immutability:
d = {'x': 1}
oldd = d
update_in(d, ['x'], inc)
assert d is oldd
def update_config_data(name, value):
"""
Update config value to existing configuration
:param str name: Name is a . separated path to a configuration value
stored in a nested dictionary.
:param value: Value to be updated
"""
global _config_data
_config_data = update_in(_config_data, name.split('.'), lambda _: value)
def update_config_data(name, value):
"""
Update config value to existing configuration
:param str name: Name is a . separated path to a configuration value
stored in a nested dictionary.
:param value: Value to be updated
"""
global _config_data
_config_data = update_in(_config_data, name.split('.'), lambda _: value)
def _predict_action(state):
mine = shapely.geometry.Polygon(state['desc']['mine_shell'])
obstacles = [shapely.geometry.Polygon(sh) for sh in state['desc']['obstacle_shells']]
obstacle = shapely.ops.unary_union(obstacles)
situable = mine.difference(obstacle)
wrappeds = [shapely.geometry.Polygon(sh) for sh in state['wrapped_shells']]
wrapped = shapely.ops.unary_union(wrappeds)
not_wrapped = situable.difference(wrapped)
if not_wrapped.area < 1.0:
return None, state
last_move = state.get('last_move', 'W')
for move in [last_move, 'W', 'S', 'A', 'D']:
proj = _move_projection_center(state['worker']['pos'], move)
if not_wrapped.contains(proj):
return move, tzd.dissoc(state, 'path_pts_to_not_wrapped')
if not state.get('path_pts_to_not_wrapped'):
target_tile = tzf.thread_first(not_wrapped.representative_point(),
_shapely_point2pt,
_snap_to_tile)
print('Finding shortest path from tile {} to {}'.format(state['worker']['pos'], target_tile))
if tzd.get_in(['cache', 'incidence_m'], state) is None:
incidence_m = _incidence_matrix(situable)
state = tzd.assoc_in(state, ['cache', 'incidence_m'], incidence_m)
else:
incidence_m = state['cache']['incidence_m']
target_vertex_ind = _incidence_ind(target_tile[0], target_tile[1], x_size=math.ceil(situable.bounds[2]))
path_dists, path_predecessors = sp.sparse.csgraph.shortest_path(csgraph=incidence_m,
directed=False,
return_predecessors=True,
unweighted=True,
indices=target_vertex_ind)
start_vertex_ind = _incidence_ind(state['worker']['pos'][0],
state['worker']['pos'][1],
x_size=math.ceil(situable.bounds[2]))
path_inds = _path_inds(path_predecessors, start_vertex_ind)
path_pts = [_incidence_pt(ind, x_size=math.ceil(situable.bounds[2]))
for ind in path_inds]
print('Found path: {}'.format(path_pts))
state = tzd.assoc(state, 'path_pts_to_not_wrapped', path_pts)
path_move = _projection_pt_move(state['worker']['pos'], state['path_pts_to_not_wrapped'][0])
if path_move is not None:
return path_move, tzd.update_in(state, ['path_pts_to_not_wrapped'], lambda p: p[1:])
return 'Z', state
def send(image_id):
lc_type = self.group_config["launchConfiguration"]["type"]
if image_id is not None and lc_type == "launch_server":
self.group_config = update_in(
self.group_config,
["launchConfiguration", "args", "server", "imageRef"],
lambda _: image_id)
d = self.treq.post("%s/groups" % str(rcs.endpoints["otter"]),
json.dumps(self.group_config),
headers=headers(str(rcs.token)),
pool=self.pool)
d.addCallback(check_success, [201])
d.addCallback(self.treq.json_content)
return d.addCallback(record_results)
def send(image_id):
lc_type = self.group_config["launchConfiguration"]["type"]
if image_id is not None and lc_type == "launch_server":
self.group_config = update_in(
self.group_config,
["launchConfiguration", "args", "server", "imageRef"],
lambda _: image_id)
d = self.treq.post(
"%s/groups" % str(rcs.endpoints["otter"]),
json.dumps(self.group_config),
headers=headers(str(rcs.token)),
pool=self.pool)
d.addCallback(check_success, [201])
d.addCallback(self.treq.json_content)
return d.addCallback(record_results)
def test_update_in():
assert update_in({"a": 0}, ["a"], inc) == {"a": 1}
assert update_in({"a": 0, "b": 1}, ["b"], str) == {"a": 0, "b": "1"}
assert (update_in({"t": 1,
"v": {"a": 0}}, ["v", "a"], inc) ==
{"t": 1, "v": {"a": 1}})
# Handle missing element one deep:
assert update_in({}, ["z"], str) == {"z": "None"}
# Same semantics as Clojure, raises an error if going deeper than
# one level into a dict which doesn't have the initial key:
assert raises(AttributeError,
lambda: update_in({}, ["z", "q"], str))
# Verify immutability:
d = {'x': 1}
oldd = d
update_in(d, ['x'], inc)
assert d is oldd
def _update_value_in_nested_dict_by_keylist(dictionary: dict,
key_list: List[str],
new_value) -> dict:
"""Update the value of a nested-dictionary by a keylist with new value.
Wrapper around :func:`toolz.dicttoolz.update_in`.
Note:
Do not update the original dict, returns a new dict with same content
as original dict, but with update and required location.
Parameters:
dictionary: the dictionary to update.
key_list: list of subkeys where to update the dictionary.
new_value: the new value to update to.
Returns:
the updated dictionary.
"""
return update_in(dictionary, key_list, lambda x: new_value)
def test_update_in(self):
D, kw = self.D, self.kw
assert update_in(D({"a": 0}), ["a"], inc, **kw) == D({"a": 1})
assert update_in(D({"a": 0, "b": 1}), ["b"], str, **kw) == D({"a": 0, "b": "1"})
assert (update_in(D({"t": 1, "v": D({"a": 0})}), ["v", "a"], inc, **kw) ==
D({"t": 1, "v": D({"a": 1})}))
# Handle one missing key.
assert update_in(D({}), ["z"], str, None, **kw) == D({"z": "None"})
assert update_in(D({}), ["z"], inc, 0, **kw) == D({"z": 1})
assert update_in(D({}), ["z"], lambda x: x+"ar", default="b", **kw) == D({"z": "bar"})
# Same semantics as Clojure for multiple missing keys, ie. recursively
# create nested empty dictionaries to the depth specified by the
# keys with the innermost value set to f(default).
assert update_in(D({}), [0, 1], inc, default=-1, **kw) == D({0: D({1: 0})})
assert update_in(D({}), [0, 1], str, default=100, **kw) == D({0: D({1: "100"})})
assert (update_in(D({"foo": "bar", 1: 50}), ["d", 1, 0], str, 20, **kw) ==
D({"foo": "bar", 1: 50, "d": D({1: D({0: "20"})})}))
# Verify immutability:
d = D({'x': 1})
oldd = d
update_in(d, ['x'], inc, **kw)
assert d is oldd
def test_update_in(self):
D, kw = self.D, self.kw
assert update_in(D({"a": 0}), ["a"], inc, **kw) == D({"a": 1})
assert update_in(D({
"a": 0,
"b": 1
}), ["b"], str, **kw) == D({
"a": 0,
"b": "1"
})
assert (update_in(D({
"t": 1,
"v": D({"a": 0})
}), ["v", "a"], inc, **kw) == D({
"t": 1,
"v": D({"a": 1})
}))
# Handle one missing key.
assert update_in(D({}), ["z"], str, None, **kw) == D({"z": "None"})
assert update_in(D({}), ["z"], inc, 0, **kw) == D({"z": 1})
assert update_in(D({}), ["z"], lambda x: x + "ar", default="b",
**kw) == D({"z": "bar"})
# Same semantics as Clojure for multiple missing keys, ie. recursively
# create nested empty dictionaries to the depth specified by the
# keys with the innermost value set to f(default).
assert update_in(D({}), [0, 1], inc, default=-1,
**kw) == D({0: D({1: 0})})
assert update_in(D({}), [0, 1], str, default=100,
**kw) == D({0: D({1: "100"})})
assert (update_in(D({
"foo": "bar",
1: 50
}), ["d", 1, 0], str, 20, **kw) == D({
"foo": "bar",
1: 50,
"d": D({1: D({0: "20"})})
}))
# Verify immutability:
d = D({'x': 1})
oldd = d
update_in(d, ['x'], inc, **kw)
assert d is oldd
'--base_output_path',
type=str,
default='tmp',
help=
'When --split is True, this is the path of the folder report parts will be writen to.'
)
parser.add_argument('--model_evaluation_file',
type=argparse.FileType('r'),
help='Path to the Make/Model evaluation file.')
args = parser.parse_args()
dataset = list(
map(
lambda elem: update_in(
elem, ['predictions'],
compose(list, partial(take, args.predictions_limit))),
ujson.load(args.dataset_file)))
sections = groupby(lambda x: tuple(map(x.get, ['make', 'model'])),
dataset).items()
evaluation_base_url = f'https://storage.cloud.google.com/dev_visual_search/evaluations/output/by-id/{args.evaluation_id}'
def link_to_page(key):
if key is None:
return None
make, model = key
return f'{evaluation_base_url}/prediction-{make}-{model}.html'
for prev, current, next in sliding_window(
def test_update_in():
assert update_in({"a": 0}, ["a"], inc) == {"a": 1}
assert update_in({"a": 0, "b": 1}, ["b"], str) == {"a": 0, "b": "1"}
assert (update_in({"t": 1, "v": {"a": 0}}, ["v", "a"], inc) ==
{"t": 1, "v": {"a": 1}})
# Handle one missing key.
assert update_in({}, ["z"], str, None) == {"z": "None"}
assert update_in({}, ["z"], inc, 0) == {"z": 1}
assert update_in({}, ["z"], lambda x: x+"ar", default="b") == {"z": "bar"}
# Same semantics as Clojure for multiple missing keys, ie. recursively
# create nested empty dictionaries to the depth specified by the
# keys with the innermost value set to f(default).
assert update_in({}, [0, 1], inc, default=-1) == {0: {1: 0}}
assert update_in({}, [0, 1], str, default=100) == {0: {1: "100"}}
assert (update_in({"foo": "bar", 1: 50}, ["d", 1, 0], str, 20) ==
{"foo": "bar", 1: 50, "d": {1: {0: "20"}}})
# Verify immutability:
d = {'x': 1}
oldd = d
update_in(d, ['x'], inc)
assert d is oldd
def test_update_in():
assert update_in({"a": 0}, ["a"], inc) == {"a": 1}
assert update_in({"a": 0, "b": 1}, ["b"], str) == {"a": 0, "b": "1"}
assert (update_in({"t": 1, "v": {"a": 0}}, ["v", "a"], inc) ==
{"t": 1, "v": {"a": 1}})
# Handle one missing key.
assert update_in({}, ["z"], str, None) == {"z": "None"}
assert update_in({}, ["z"], inc, 0) == {"z": 1}
assert update_in({}, ["z"], lambda x: x+"ar", default="b") == {"z": "bar"}
# Same semantics as Clojure for multiple missing keys, ie. recursively
# create nested empty dictionaries to the depth specified by the
# keys with the innermost value set to f(default).
assert update_in({}, [0, 1], inc, default=-1) == {0: {1: 0}}
assert update_in({}, [0, 1], str, default=100) == {0: {1: "100"}}
assert (update_in({"foo": "bar", 1: 50}, ["d", 1, 0], str, 20) ==
{"foo": "bar", 1: 50, "d": {1: {0: "20"}}})
# Verify immutability:
d = {'x': 1}
oldd = d
update_in(d, ['x'], inc)
assert d is oldd
# Test object support:
c = C()
c.a = 0
assert update_in(c, ["a"], inc).__dict__ == {"a": 1}
c = C()
c.a = 0
c.b = 1
assert update_in(c, ["b"], str).__dict__ == {"a": 0, "b": "1"}
v = C()
v.a = 0
c = C()
c.t = 1
c.v = v
assert update_in(c, ["v", "a"], inc).v.__dict__ == {"a": 1}
# Handle one missing key.
c = C()
assert update_in(c, ["z"], str, None).__dict__ == {"z": "None"}
assert update_in(c, ["z"], inc, 0).__dict__ == {"z": 1}
assert update_in(c, ["z"], lambda x: x + "ar",
default="b").__dict__ == {"z": "bar"}
# Allow AttributeError to be thrown if more than one missing key,
# because we don't know what type of object to create for nesting.
assert raises(AttributeError,
lambda: update_in(c, ["y", "z"], inc, default=0))
# Verify immutability:
o = C()
o.x = 1
update_in(o, ['x'], inc)
assert o.x == 1
def test_update_in():
assert update_in({"a": 0}, ["a"], inc) == {"a": 1}
assert update_in({"a": 0, "b": 1}, ["b"], str) == {"a": 0, "b": "1"}
assert (update_in({"t": 1, "v": {"a": 0}}, ["v", "a"], inc) ==
{"t": 1, "v": {"a": 1}})
# Handle one missing key.
assert update_in({}, ["z"], str, None) == {"z": "None"}
assert update_in({}, ["z"], inc, 0) == {"z": 1}
assert update_in({}, ["z"], lambda x: x+"ar", default="b") == {"z": "bar"}
# Same semantics as Clojure for multiple missing keys, ie. recursively
# create nested empty dictionaries to the depth specified by the
# keys with the innermost value set to f(default).
assert update_in({}, [0, 1], inc, default=-1) == {0: {1: 0}}
assert update_in({}, [0, 1], str, default=100) == {0: {1: "100"}}
assert (update_in({"foo": "bar", 1: 50}, ["d", 1, 0], str, 20) ==
{"foo": "bar", 1: 50, "d": {1: {0: "20"}}})
# Verify immutability:
d = {'x': 1}
oldd = d
update_in(d, ['x'], inc)
assert d is oldd
