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12,100 | nschloe/optimesh | optimesh/cvt/lloyd.py | quasi_newton_uniform_lloyd | def quasi_newton_uniform_lloyd(points, cells, *args, omega=1.0, **kwargs):
"""Relaxed Lloyd's algorithm. omega=1 leads to Lloyd's algorithm, overrelaxation
omega=2 gives good results. Check out
Xiao Xiao,
Over-Relaxation Lloyd Method For Computing Centroidal Voronoi Tessellations,
Master's thesis,
... | python | def quasi_newton_uniform_lloyd(points, cells, *args, omega=1.0, **kwargs):
"""Relaxed Lloyd's algorithm. omega=1 leads to Lloyd's algorithm, overrelaxation
omega=2 gives good results. Check out
Xiao Xiao,
Over-Relaxation Lloyd Method For Computing Centroidal Voronoi Tessellations,
Master's thesis,
... | [
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... | Relaxed Lloyd's algorithm. omega=1 leads to Lloyd's algorithm, overrelaxation
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Xiao Xiao,
Over-Relaxation Lloyd Method For Computing Centroidal Voronoi Tessellations,
Master's thesis,
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12,101 | nschloe/optimesh | optimesh/cpt.py | _energy_uniform_per_node | def _energy_uniform_per_node(X, cells):
"""The CPT mesh energy is defined as
sum_i E_i,
E_i = 1/(d+1) * sum int_{omega_i} ||x - x_i||^2 rho(x) dx,
see Chen-Holst. This method gives the E_i and assumes uniform density, rho(x) = 1.
"""
dim = 2
mesh = MeshTri(X, cells)
star_inte... | python | def _energy_uniform_per_node(X, cells):
"""The CPT mesh energy is defined as
sum_i E_i,
E_i = 1/(d+1) * sum int_{omega_i} ||x - x_i||^2 rho(x) dx,
see Chen-Holst. This method gives the E_i and assumes uniform density, rho(x) = 1.
"""
dim = 2
mesh = MeshTri(X, cells)
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E_i = 1/(d+1) * sum int_{omega_i} ||x - x_i||^2 rho(x) dx,
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12,102 | nschloe/optimesh | optimesh/cpt.py | jac_uniform | def jac_uniform(X, cells):
"""The approximated Jacobian is
partial_i E = 2/(d+1) (x_i int_{omega_i} rho(x) dx - int_{omega_i} x rho(x) dx)
= 2/(d+1) sum_{tau_j in omega_i} (x_i - b_{j, rho}) int_{tau_j} rho,
see Chen-Holst. This method here assumes uniform density, rho(x) = 1, such tha... | python | def jac_uniform(X, cells):
"""The approximated Jacobian is
partial_i E = 2/(d+1) (x_i int_{omega_i} rho(x) dx - int_{omega_i} x rho(x) dx)
= 2/(d+1) sum_{tau_j in omega_i} (x_i - b_{j, rho}) int_{tau_j} rho,
see Chen-Holst. This method here assumes uniform density, rho(x) = 1, such tha... | [
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partial_i E = 2/(d+1) (x_i int_{omega_i} rho(x) dx - int_{omega_i} x rho(x) dx)
= 2/(d+1) sum_{tau_j in omega_i} (x_i - b_{j, rho}) int_{tau_j} rho,
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12,103 | nschloe/optimesh | optimesh/cpt.py | solve_hessian_approx_uniform | def solve_hessian_approx_uniform(X, cells, rhs):
"""As discussed above, the approximated Jacobian is
partial_i E = 2/(d+1) sum_{tau_j in omega_i} (x_i - b_j) |tau_j|.
To get the Hessian, we have to form its derivative. As a simplifications,
let us assume again that |tau_j| is independent of the node... | python | def solve_hessian_approx_uniform(X, cells, rhs):
"""As discussed above, the approximated Jacobian is
partial_i E = 2/(d+1) sum_{tau_j in omega_i} (x_i - b_j) |tau_j|.
To get the Hessian, we have to form its derivative. As a simplifications,
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partial_i E = 2/(d+1) sum_{tau_j in omega_i} (x_i - b_j) |tau_j|.
To get the Hessian, we have to form its derivative. As a simplifications,
let us assume again that |tau_j| is independent of the node positions. Then we get
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12,104 | nschloe/optimesh | optimesh/cpt.py | quasi_newton_uniform | def quasi_newton_uniform(points, cells, *args, **kwargs):
"""Like linear_solve above, but assuming rho==1. Note that the energy gradient
\\partial E_i = 2/(d+1) sum_{tau_j in omega_i} (x_i - b_j) \\int_{tau_j} rho
becomes
\\partial E_i = 2/(d+1) sum_{tau_j in omega_i} (x_i - b_j) |tau_j|.
... | python | def quasi_newton_uniform(points, cells, *args, **kwargs):
"""Like linear_solve above, but assuming rho==1. Note that the energy gradient
\\partial E_i = 2/(d+1) sum_{tau_j in omega_i} (x_i - b_j) \\int_{tau_j} rho
becomes
\\partial E_i = 2/(d+1) sum_{tau_j in omega_i} (x_i - b_j) |tau_j|.
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12,105 | nschloe/optimesh | optimesh/laplace.py | fixed_point | def fixed_point(points, cells, *args, **kwargs):
"""Perform k steps of Laplacian smoothing to the mesh, i.e., moving each
interior vertex to the arithmetic average of its neighboring points.
"""
def get_new_points(mesh):
# move interior points into average of their neighbors
num_neighbo... | python | def fixed_point(points, cells, *args, **kwargs):
"""Perform k steps of Laplacian smoothing to the mesh, i.e., moving each
interior vertex to the arithmetic average of its neighboring points.
"""
def get_new_points(mesh):
# move interior points into average of their neighbors
num_neighbo... | [
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12,106 | nschloe/optimesh | optimesh/odt.py | energy | def energy(mesh, uniform_density=False):
"""The mesh energy is defined as
E = int_Omega |u_l(x) - u(x)| rho(x) dx
where u(x) = ||x||^2 and u_l is its piecewise linearization on the mesh.
"""
# E = 1/(d+1) sum_i ||x_i||^2 |omega_i| - int_Omega_i ||x||^2
dim = mesh.cells["nodes"].shape[1] - 1
... | python | def energy(mesh, uniform_density=False):
"""The mesh energy is defined as
E = int_Omega |u_l(x) - u(x)| rho(x) dx
where u(x) = ||x||^2 and u_l is its piecewise linearization on the mesh.
"""
# E = 1/(d+1) sum_i ||x_i||^2 |omega_i| - int_Omega_i ||x||^2
dim = mesh.cells["nodes"].shape[1] - 1
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12,107 | nschloe/optimesh | optimesh/cvt/block_diagonal.py | quasi_newton_uniform_blocks | def quasi_newton_uniform_blocks(points, cells, *args, **kwargs):
"""Lloyd's algorithm can be though of a diagonal-only Hessian; this method
incorporates the diagonal blocks, too.
"""
def get_new_points(mesh):
# TODO need copy?
x = mesh.node_coords.copy()
x += update(mesh)
... | python | def quasi_newton_uniform_blocks(points, cells, *args, **kwargs):
"""Lloyd's algorithm can be though of a diagonal-only Hessian; this method
incorporates the diagonal blocks, too.
"""
def get_new_points(mesh):
# TODO need copy?
x = mesh.node_coords.copy()
x += update(mesh)
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12,108 | linnarsson-lab/loompy | loompy/loompy.py | new | def new(filename: str, *, file_attrs: Optional[Dict[str, str]] = None) -> LoomConnection:
"""
Create an empty Loom file, and return it as a context manager.
"""
if filename.startswith("~/"):
filename = os.path.expanduser(filename)
if file_attrs is None:
file_attrs = {}
# Create the file (empty).
# Yes, this... | python | def new(filename: str, *, file_attrs: Optional[Dict[str, str]] = None) -> LoomConnection:
"""
Create an empty Loom file, and return it as a context manager.
"""
if filename.startswith("~/"):
filename = os.path.expanduser(filename)
if file_attrs is None:
file_attrs = {}
# Create the file (empty).
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12,109 | linnarsson-lab/loompy | loompy/loompy.py | create | def create(filename: str, layers: Union[np.ndarray, Dict[str, np.ndarray], loompy.LayerManager], row_attrs: Union[loompy.AttributeManager, Dict[str, np.ndarray]], col_attrs: Union[loompy.AttributeManager, Dict[str, np.ndarray]], *, file_attrs: Dict[str, str] = None) -> None:
"""
Create a new Loom file from the given ... | python | def create(filename: str, layers: Union[np.ndarray, Dict[str, np.ndarray], loompy.LayerManager], row_attrs: Union[loompy.AttributeManager, Dict[str, np.ndarray]], col_attrs: Union[loompy.AttributeManager, Dict[str, np.ndarray]], *, file_attrs: Dict[str, str] = None) -> None:
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12,110 | linnarsson-lab/loompy | loompy/loompy.py | connect | def connect(filename: str, mode: str = 'r+', *, validate: bool = True, spec_version: str = "2.0.1") -> LoomConnection:
"""
Establish a connection to a .loom file.
Args:
filename: Path to the Loom file to open
mode: Read/write mode, 'r+' (read/write) or 'r' (read-only), defaults to 'r+'
validate: Validate ... | python | def connect(filename: str, mode: str = 'r+', *, validate: bool = True, spec_version: str = "2.0.1") -> LoomConnection:
"""
Establish a connection to a .loom file.
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filename: Path to the Loom file to open
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12,111 | linnarsson-lab/loompy | loompy/loompy.py | LoomConnection.last_modified | def last_modified(self) -> str:
"""
Return an ISO8601 timestamp indicating when the file was last modified
Returns:
An ISO8601 timestamp indicating when the file was last modified
Remarks:
If the file has no timestamp, and mode is 'r+', a new timestamp is created and returned.
Otherwise, the current ... | python | def last_modified(self) -> str:
"""
Return an ISO8601 timestamp indicating when the file was last modified
Returns:
An ISO8601 timestamp indicating when the file was last modified
Remarks:
If the file has no timestamp, and mode is 'r+', a new timestamp is created and returned.
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12,112 | linnarsson-lab/loompy | loompy/loompy.py | LoomConnection.get_changes_since | def get_changes_since(self, timestamp: str) -> Dict[str, List]:
"""
Get a summary of the parts of the file that changed since the given time
Args:
timestamp: ISO8601 timestamp
Return:
dict: Dictionary like ``{"row_graphs": rg, "col_graphs": cg, "row_attrs": ra, "col_attrs": ca, "layers": layers}`` listi... | python | def get_changes_since(self, timestamp: str) -> Dict[str, List]:
"""
Get a summary of the parts of the file that changed since the given time
Args:
timestamp: ISO8601 timestamp
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dict: Dictionary like ``{"row_graphs": rg, "col_graphs": cg, "row_attrs": ra, "col_attrs": ca, "layers": layers}`` listi... | [
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12,113 | linnarsson-lab/loompy | loompy/loompy.py | LoomConnection.sparse | def sparse(self, rows: np.ndarray = None, cols: np.ndarray = None, layer: str = None) -> scipy.sparse.coo_matrix:
"""
Return the main matrix or specified layer as a scipy.sparse.coo_matrix, without loading dense matrix in RAM
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rows: Rows to include, or None to include all
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"""
Return the main matrix or specified layer as a scipy.sparse.coo_matrix, without loading dense matrix in RAM
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12,114 | linnarsson-lab/loompy | loompy/loompy.py | LoomConnection.close | def close(self, suppress_warning: bool = False) -> None:
"""
Close the connection. After this, the connection object becomes invalid. Warns user if called after closing.
Args:
suppress_warning: Suppresses warning message if True (defaults to false)
"""
if self._file is None:
if not suppress_warning:
... | python | def close(self, suppress_warning: bool = False) -> None:
"""
Close the connection. After this, the connection object becomes invalid. Warns user if called after closing.
Args:
suppress_warning: Suppresses warning message if True (defaults to false)
"""
if self._file is None:
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12,115 | linnarsson-lab/loompy | loompy/loompy.py | LoomConnection.permute | def permute(self, ordering: np.ndarray, axis: int) -> None:
"""
Permute the dataset along the indicated axis.
Args:
ordering (list of int): The desired order along the axis
axis (int): The axis along which to permute
Returns:
Nothing.
"""
if self._file.__contains__("tiles"):
del self._fi... | python | def permute(self, ordering: np.ndarray, axis: int) -> None:
"""
Permute the dataset along the indicated axis.
Args:
ordering (list of int): The desired order along the axis
axis (int): The axis along which to permute
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Nothing.
"""
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12,116 | linnarsson-lab/loompy | loompy/loompy.py | LoomConnection.aggregate | def aggregate(self, out_file: str = None, select: np.ndarray = None, group_by: Union[str, np.ndarray] = "Clusters", aggr_by: str = "mean", aggr_ca_by: Dict[str, str] = None) -> np.ndarray:
"""
Aggregate the Loom file by applying aggregation functions to the main matrix as well as to the column attributes
Args:
... | python | def aggregate(self, out_file: str = None, select: np.ndarray = None, group_by: Union[str, np.ndarray] = "Clusters", aggr_by: str = "mean", aggr_ca_by: Dict[str, str] = None) -> np.ndarray:
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Aggregate the Loom file by applying aggregation functions to the main matrix as well as to the column attributes
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12,117 | linnarsson-lab/loompy | loompy/file_attribute_manager.py | FileAttributeManager.get | def get(self, name: str, default: Any = None) -> np.ndarray:
"""
Return the value for a named attribute if it exists, else default.
If default is not given, it defaults to None, so that this method never raises a KeyError.
"""
if name in self:
return self[name]
else:
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"""
Return the value for a named attribute if it exists, else default.
If default is not given, it defaults to None, so that this method never raises a KeyError.
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if name in self:
return self[name]
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12,118 | linnarsson-lab/loompy | loompy/color.py | cat_colors | def cat_colors(N: int = 1, *, hue: str = None, luminosity: str = None, bgvalue: int = None, loop: bool = False, seed: str = "cat") -> Union[List[Any], colors.LinearSegmentedColormap]:
"""
Return a colormap suitable for N categorical values, optimized to be both aesthetically pleasing and perceptually distinct.
Args... | python | def cat_colors(N: int = 1, *, hue: str = None, luminosity: str = None, bgvalue: int = None, loop: bool = False, seed: str = "cat") -> Union[List[Any], colors.LinearSegmentedColormap]:
"""
Return a colormap suitable for N categorical values, optimized to be both aesthetically pleasing and perceptually distinct.
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12,119 | linnarsson-lab/loompy | loompy/graph_manager.py | _renumber | def _renumber(a: np.ndarray, keys: np.ndarray, values: np.ndarray) -> np.ndarray:
"""
Renumber 'a' by replacing any occurrence of 'keys' by the corresponding 'values'
"""
ordering = np.argsort(keys)
keys = keys[ordering]
values = keys[ordering]
index = np.digitize(a.ravel(), keys, right=True)
return(values[inde... | python | def _renumber(a: np.ndarray, keys: np.ndarray, values: np.ndarray) -> np.ndarray:
"""
Renumber 'a' by replacing any occurrence of 'keys' by the corresponding 'values'
"""
ordering = np.argsort(keys)
keys = keys[ordering]
values = keys[ordering]
index = np.digitize(a.ravel(), keys, right=True)
return(values[inde... | [
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12,120 | linnarsson-lab/loompy | loompy/loom_validator.py | LoomValidator.validate | def validate(self, path: str, strictness: str = "speconly") -> bool:
"""
Validate a file for conformance to the Loom specification
Args:
path: Full path to the file to be validated
strictness: "speconly" or "conventions"
Remarks:
In "speconly" mode, conformance is assessed relative to the file fo... | python | def validate(self, path: str, strictness: str = "speconly") -> bool:
"""
Validate a file for conformance to the Loom specification
Args:
path: Full path to the file to be validated
strictness: "speconly" or "conventions"
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12,121 | linnarsson-lab/loompy | loompy/attribute_manager.py | AttributeManager._permute | def _permute(self, ordering: np.ndarray) -> None:
"""
Permute all the attributes in the collection
Remarks:
This permutes the order of the values for each attribute in the file
"""
for key in self.keys():
self[key] = self[key][ordering] | python | def _permute(self, ordering: np.ndarray) -> None:
"""
Permute all the attributes in the collection
Remarks:
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"""
for key in self.keys():
self[key] = self[key][ordering] | [
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12,122 | linnarsson-lab/loompy | loompy/attribute_manager.py | AttributeManager.get | def get(self, name: str, default: np.ndarray) -> np.ndarray:
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Default has to be a numpy array of correct size.
"""
if name in self:
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12,123 | linnarsson-lab/loompy | loompy/normalize.py | normalize_attr_array | def normalize_attr_array(a: Any) -> np.ndarray:
"""
Take all kinds of array-like inputs and normalize to a one-dimensional np.ndarray
"""
if type(a) is np.ndarray:
return a
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return np.array(a)[0, :]
elif a.shape[1] == 1:
return np.array(a)[:, 0]
else:
... | python | def normalize_attr_array(a: Any) -> np.ndarray:
"""
Take all kinds of array-like inputs and normalize to a one-dimensional np.ndarray
"""
if type(a) is np.ndarray:
return a
elif type(a) is np.matrix:
if a.shape[0] == 1:
return np.array(a)[0, :]
elif a.shape[1] == 1:
return np.array(a)[:, 0]
else:
... | [
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12,124 | linnarsson-lab/loompy | loompy/to_html.py | to_html | def to_html(ds: Any) -> str:
"""
Return an HTML representation of the loom file or view, showing the upper-left 10x10 corner.
"""
rm = min(10, ds.shape[0])
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"""
Return an HTML representation of the loom file or view, showing the upper-left 10x10 corner.
"""
rm = min(10, ds.shape[0])
cm = min(10, ds.shape[1])
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12,125 | linnarsson-lab/loompy | loompy/loom_view.py | LoomView.permute | def permute(self, ordering: np.ndarray, *, axis: int) -> None:
"""
Permute the view, by permuting its layers, attributes and graphs
Args:
ordering (np.ndarray): The desired ordering along the axis
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"""
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"""
Permute the view, by permuting its layers, attributes and graphs
Args:
ordering (np.ndarray): The desired ordering along the axis
axis (int): 0, permute rows; 1, permute columns
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12,126 | linnarsson-lab/loompy | loompy/loom_layer.py | MemoryLoomLayer.permute | def permute(self, ordering: np.ndarray, *, axis: int) -> None:
"""
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axis: The axis to permute (0, permute the rows; 1, permute the columns)
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self.values ... | python | def permute(self, ordering: np.ndarray, *, axis: int) -> None:
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Permute the layer along an axis
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axis: The axis to permute (0, permute the rows; 1, permute the columns)
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12,127 | linnarsson-lab/loompy | loompy/loom_layer.py | LoomLayer._resize | def _resize(self, size: Tuple[int, int], axis: int = None) -> None:
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The dataset must be stored in chunked format; it can be resized up to the "maximum shape" (keyword maxshape) specified at creation time.
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"""Resize the dataset, or the specified axis.
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12,128 | optimizely/python-sdk | optimizely/helpers/validator.py | is_datafile_valid | def is_datafile_valid(datafile):
""" Given a datafile determine if it is valid or not.
Args:
datafile: JSON string representing the project.
Returns:
Boolean depending upon whether datafile is valid or not.
"""
try:
datafile_json = json.loads(datafile)
except:
return False
try:
jso... | python | def is_datafile_valid(datafile):
""" Given a datafile determine if it is valid or not.
Args:
datafile: JSON string representing the project.
Returns:
Boolean depending upon whether datafile is valid or not.
"""
try:
datafile_json = json.loads(datafile)
except:
return False
try:
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12,129 | optimizely/python-sdk | optimizely/helpers/validator.py | is_user_profile_valid | def is_user_profile_valid(user_profile):
""" Determine if provided user profile is valid or not.
Args:
user_profile: User's profile which needs to be validated.
Returns:
Boolean depending upon whether profile is valid or not.
"""
if not user_profile:
return False
if not type(user_profile) is... | python | def is_user_profile_valid(user_profile):
""" Determine if provided user profile is valid or not.
Args:
user_profile: User's profile which needs to be validated.
Returns:
Boolean depending upon whether profile is valid or not.
"""
if not user_profile:
return False
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12,130 | optimizely/python-sdk | optimizely/helpers/validator.py | is_attribute_valid | def is_attribute_valid(attribute_key, attribute_value):
""" Determine if given attribute is valid.
Args:
attribute_key: Variable which needs to be validated
attribute_value: Variable which needs to be validated
Returns:
False if attribute_key is not a string
False if attribute_value is not one o... | python | def is_attribute_valid(attribute_key, attribute_value):
""" Determine if given attribute is valid.
Args:
attribute_key: Variable which needs to be validated
attribute_value: Variable which needs to be validated
Returns:
False if attribute_key is not a string
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12,131 | optimizely/python-sdk | optimizely/helpers/validator.py | is_finite_number | def is_finite_number(value):
""" Validates if the given value is a number, enforces
absolute limit of 2^53 and restricts NAN, INF, -INF.
Args:
value: Value to be validated.
Returns:
Boolean: True if value is a number and not NAN, INF, -INF or
greater than absolute limit of 2^53 else Fals... | python | def is_finite_number(value):
""" Validates if the given value is a number, enforces
absolute limit of 2^53 and restricts NAN, INF, -INF.
Args:
value: Value to be validated.
Returns:
Boolean: True if value is a number and not NAN, INF, -INF or
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12,132 | optimizely/python-sdk | optimizely/helpers/validator.py | are_values_same_type | def are_values_same_type(first_val, second_val):
""" Method to verify that both values belong to same type. Float and integer are
considered as same type.
Args:
first_val: Value to validate.
second_Val: Value to validate.
Returns:
Boolean: True if both values belong to same type. Otherwise False.
... | python | def are_values_same_type(first_val, second_val):
""" Method to verify that both values belong to same type. Float and integer are
considered as same type.
Args:
first_val: Value to validate.
second_Val: Value to validate.
Returns:
Boolean: True if both values belong to same type. Otherwise False.
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12,133 | optimizely/python-sdk | optimizely/logger.py | reset_logger | def reset_logger(name, level=None, handler=None):
"""
Make a standard python logger object with default formatter, handler, etc.
Defaults are:
- level == logging.INFO
- handler == logging.StreamHandler()
Args:
name: a logger name.
level: an optional initial log level for this logger.
handl... | python | def reset_logger(name, level=None, handler=None):
"""
Make a standard python logger object with default formatter, handler, etc.
Defaults are:
- level == logging.INFO
- handler == logging.StreamHandler()
Args:
name: a logger name.
level: an optional initial log level for this logger.
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12,134 | optimizely/python-sdk | optimizely/logger.py | adapt_logger | def adapt_logger(logger):
"""
Adapt our custom logger.BaseLogger object into a standard logging.Logger object.
Adaptations are:
- NoOpLogger turns into a logger with a single NullHandler.
- SimpleLogger turns into a logger with a StreamHandler and level.
Args:
logger: Possibly a logger.BaseLogger,... | python | def adapt_logger(logger):
"""
Adapt our custom logger.BaseLogger object into a standard logging.Logger object.
Adaptations are:
- NoOpLogger turns into a logger with a single NullHandler.
- SimpleLogger turns into a logger with a StreamHandler and level.
Args:
logger: Possibly a logger.BaseLogger,... | [
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12,135 | optimizely/python-sdk | optimizely/user_profile.py | UserProfile.get_variation_for_experiment | def get_variation_for_experiment(self, experiment_id):
""" Helper method to retrieve variation ID for given experiment.
Args:
experiment_id: ID for experiment for which variation needs to be looked up for.
Returns:
Variation ID corresponding to the experiment. None if no decision available.
... | python | def get_variation_for_experiment(self, experiment_id):
""" Helper method to retrieve variation ID for given experiment.
Args:
experiment_id: ID for experiment for which variation needs to be looked up for.
Returns:
Variation ID corresponding to the experiment. None if no decision available.
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12,136 | optimizely/python-sdk | optimizely/helpers/event_tag_utils.py | get_numeric_value | def get_numeric_value(event_tags, logger=None):
"""
A smart getter of the numeric value from the event tags.
Args:
event_tags: A dictionary of event tags.
logger: Optional logger.
Returns:
A float numeric metric value is returned when the provided numeric
metric value is in the followi... | python | def get_numeric_value(event_tags, logger=None):
"""
A smart getter of the numeric value from the event tags.
Args:
event_tags: A dictionary of event tags.
logger: Optional logger.
Returns:
A float numeric metric value is returned when the provided numeric
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12,137 | optimizely/python-sdk | optimizely/lib/pymmh3.py | hash | def hash( key, seed = 0x0 ):
''' Implements 32bit murmur3 hash. '''
key = bytearray( xencode(key) )
def fmix( h ):
h ^= h >> 16
h = ( h * 0x85ebca6b ) & 0xFFFFFFFF
h ^= h >> 13
h = ( h * 0xc2b2ae35 ) & 0xFFFFFFFF
h ^= h >> 16
return h
length = len( ke... | python | def hash( key, seed = 0x0 ):
''' Implements 32bit murmur3 hash. '''
key = bytearray( xencode(key) )
def fmix( h ):
h ^= h >> 16
h = ( h * 0x85ebca6b ) & 0xFFFFFFFF
h ^= h >> 13
h = ( h * 0xc2b2ae35 ) & 0xFFFFFFFF
h ^= h >> 16
return h
length = len( ke... | [
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12,138 | optimizely/python-sdk | optimizely/lib/pymmh3.py | hash64 | def hash64( key, seed = 0x0, x64arch = True ):
''' Implements 64bit murmur3 hash. Returns a tuple. '''
hash_128 = hash128( key, seed, x64arch )
unsigned_val1 = hash_128 & 0xFFFFFFFFFFFFFFFF
if unsigned_val1 & 0x8000000000000000 == 0:
signed_val1 = unsigned_val1
else:
signed_val1 = ... | python | def hash64( key, seed = 0x0, x64arch = True ):
''' Implements 64bit murmur3 hash. Returns a tuple. '''
hash_128 = hash128( key, seed, x64arch )
unsigned_val1 = hash_128 & 0xFFFFFFFFFFFFFFFF
if unsigned_val1 & 0x8000000000000000 == 0:
signed_val1 = unsigned_val1
else:
signed_val1 = ... | [
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12,139 | optimizely/python-sdk | optimizely/lib/pymmh3.py | hash_bytes | def hash_bytes( key, seed = 0x0, x64arch = True ):
''' Implements 128bit murmur3 hash. Returns a byte string. '''
hash_128 = hash128( key, seed, x64arch )
bytestring = ''
for i in xrange(0, 16, 1):
lsbyte = hash_128 & 0xFF
bytestring = bytestring + str( chr( lsbyte ) )
hash_12... | python | def hash_bytes( key, seed = 0x0, x64arch = True ):
''' Implements 128bit murmur3 hash. Returns a byte string. '''
hash_128 = hash128( key, seed, x64arch )
bytestring = ''
for i in xrange(0, 16, 1):
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bytestring = bytestring + str( chr( lsbyte ) )
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12,140 | optimizely/python-sdk | optimizely/bucketer.py | Bucketer._generate_bucket_value | def _generate_bucket_value(self, bucketing_id):
""" Helper function to generate bucket value in half-closed interval [0, MAX_TRAFFIC_VALUE).
Args:
bucketing_id: ID for bucketing.
Returns:
Bucket value corresponding to the provided bucketing ID.
"""
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""" Helper function to generate bucket value in half-closed interval [0, MAX_TRAFFIC_VALUE).
Args:
bucketing_id: ID for bucketing.
Returns:
Bucket value corresponding to the provided bucketing ID.
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12,141 | optimizely/python-sdk | optimizely/bucketer.py | Bucketer.find_bucket | def find_bucket(self, bucketing_id, parent_id, traffic_allocations):
""" Determine entity based on bucket value and traffic allocations.
Args:
bucketing_id: ID to be used for bucketing the user.
parent_id: ID representing group or experiment.
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bucketing_id: ID to be used for bucketing the user.
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12,142 | optimizely/python-sdk | optimizely/bucketer.py | Bucketer.bucket | def bucket(self, experiment, user_id, bucketing_id):
""" For a given experiment and bucketing ID determines variation to be shown to user.
Args:
experiment: Object representing the experiment for which user is to be bucketed.
user_id: ID for user.
bucketing_id: ID to be used for bucketing the... | python | def bucket(self, experiment, user_id, bucketing_id):
""" For a given experiment and bucketing ID determines variation to be shown to user.
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experiment: Object representing the experiment for which user is to be bucketed.
user_id: ID for user.
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12,143 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig._generate_key_map | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
Returns... | python | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
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12,144 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig._deserialize_audience | def _deserialize_audience(audience_map):
""" Helper method to de-serialize and populate audience map with the condition list and structure.
Args:
audience_map: Dict mapping audience ID to audience object.
Returns:
Dict additionally consisting of condition list and structure on every audience o... | python | def _deserialize_audience(audience_map):
""" Helper method to de-serialize and populate audience map with the condition list and structure.
Args:
audience_map: Dict mapping audience ID to audience object.
Returns:
Dict additionally consisting of condition list and structure on every audience o... | [
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12,145 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_typecast_value | def get_typecast_value(self, value, type):
""" Helper method to determine actual value based on type of feature variable.
Args:
value: Value in string form as it was parsed from datafile.
type: Type denoting the feature flag type.
Return:
Value type-casted based on type of feature variab... | python | def get_typecast_value(self, value, type):
""" Helper method to determine actual value based on type of feature variable.
Args:
value: Value in string form as it was parsed from datafile.
type: Type denoting the feature flag type.
Return:
Value type-casted based on type of feature variab... | [
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12,146 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_experiment_from_key | def get_experiment_from_key(self, experiment_key):
""" Get experiment for the provided experiment key.
Args:
experiment_key: Experiment key for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment key.
"""
experiment = self.experiment_key_... | python | def get_experiment_from_key(self, experiment_key):
""" Get experiment for the provided experiment key.
Args:
experiment_key: Experiment key for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment key.
"""
experiment = self.experiment_key_... | [
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12,147 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_experiment_from_id | def get_experiment_from_id(self, experiment_id):
""" Get experiment for the provided experiment ID.
Args:
experiment_id: Experiment ID for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment ID.
"""
experiment = self.experiment_id_map.get... | python | def get_experiment_from_id(self, experiment_id):
""" Get experiment for the provided experiment ID.
Args:
experiment_id: Experiment ID for which experiment is to be determined.
Returns:
Experiment corresponding to the provided experiment ID.
"""
experiment = self.experiment_id_map.get... | [
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12,148 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_group | def get_group(self, group_id):
""" Get group for the provided group ID.
Args:
group_id: Group ID for which group is to be determined.
Returns:
Group corresponding to the provided group ID.
"""
group = self.group_id_map.get(group_id)
if group:
return group
self.logger.e... | python | def get_group(self, group_id):
""" Get group for the provided group ID.
Args:
group_id: Group ID for which group is to be determined.
Returns:
Group corresponding to the provided group ID.
"""
group = self.group_id_map.get(group_id)
if group:
return group
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12,149 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_audience | def get_audience(self, audience_id):
""" Get audience object for the provided audience ID.
Args:
audience_id: ID of the audience.
Returns:
Dict representing the audience.
"""
audience = self.audience_id_map.get(audience_id)
if audience:
return audience
self.logger.error... | python | def get_audience(self, audience_id):
""" Get audience object for the provided audience ID.
Args:
audience_id: ID of the audience.
Returns:
Dict representing the audience.
"""
audience = self.audience_id_map.get(audience_id)
if audience:
return audience
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12,150 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variation_from_key | def get_variation_from_key(self, experiment_key, variation_key):
""" Get variation given experiment and variation key.
Args:
experiment: Key representing parent experiment of variation.
variation_key: Key representing the variation.
Returns
Object representing the variation.
"""
... | python | def get_variation_from_key(self, experiment_key, variation_key):
""" Get variation given experiment and variation key.
Args:
experiment: Key representing parent experiment of variation.
variation_key: Key representing the variation.
Returns
Object representing the variation.
"""
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12,151 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variation_from_id | def get_variation_from_id(self, experiment_key, variation_id):
""" Get variation given experiment and variation ID.
Args:
experiment: Key representing parent experiment of variation.
variation_id: ID representing the variation.
Returns
Object representing the variation.
"""
vari... | python | def get_variation_from_id(self, experiment_key, variation_id):
""" Get variation given experiment and variation ID.
Args:
experiment: Key representing parent experiment of variation.
variation_id: ID representing the variation.
Returns
Object representing the variation.
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12,152 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_event | def get_event(self, event_key):
""" Get event for the provided event key.
Args:
event_key: Event key for which event is to be determined.
Returns:
Event corresponding to the provided event key.
"""
event = self.event_key_map.get(event_key)
if event:
return event
self.l... | python | def get_event(self, event_key):
""" Get event for the provided event key.
Args:
event_key: Event key for which event is to be determined.
Returns:
Event corresponding to the provided event key.
"""
event = self.event_key_map.get(event_key)
if event:
return event
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12,153 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_attribute_id | def get_attribute_id(self, attribute_key):
""" Get attribute ID for the provided attribute key.
Args:
attribute_key: Attribute key for which attribute is to be fetched.
Returns:
Attribute ID corresponding to the provided attribute key.
"""
attribute = self.attribute_key_map.get(attrib... | python | def get_attribute_id(self, attribute_key):
""" Get attribute ID for the provided attribute key.
Args:
attribute_key: Attribute key for which attribute is to be fetched.
Returns:
Attribute ID corresponding to the provided attribute key.
"""
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12,154 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_feature_from_key | def get_feature_from_key(self, feature_key):
""" Get feature for the provided feature key.
Args:
feature_key: Feature key for which feature is to be fetched.
Returns:
Feature corresponding to the provided feature key.
"""
feature = self.feature_key_map.get(feature_key)
if feature:... | python | def get_feature_from_key(self, feature_key):
""" Get feature for the provided feature key.
Args:
feature_key: Feature key for which feature is to be fetched.
Returns:
Feature corresponding to the provided feature key.
"""
feature = self.feature_key_map.get(feature_key)
if feature:... | [
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12,155 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_rollout_from_id | def get_rollout_from_id(self, rollout_id):
""" Get rollout for the provided ID.
Args:
rollout_id: ID of the rollout to be fetched.
Returns:
Rollout corresponding to the provided ID.
"""
layer = self.rollout_id_map.get(rollout_id)
if layer:
return layer
self.logger.error... | python | def get_rollout_from_id(self, rollout_id):
""" Get rollout for the provided ID.
Args:
rollout_id: ID of the rollout to be fetched.
Returns:
Rollout corresponding to the provided ID.
"""
layer = self.rollout_id_map.get(rollout_id)
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12,156 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variable_value_for_variation | def get_variable_value_for_variation(self, variable, variation):
""" Get the variable value for the given variation.
Args:
variable: The Variable for which we are getting the value.
variation: The Variation for which we are getting the variable value.
Returns:
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""" Get the variable value for the given variation.
Args:
variable: The Variable for which we are getting the value.
variation: The Variation for which we are getting the variable value.
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The variable value or None ... | [
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12,157 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_variable_for_feature | def get_variable_for_feature(self, feature_key, variable_key):
""" Get the variable with the given variable key for the given feature.
Args:
feature_key: The key of the feature for which we are getting the variable.
variable_key: The key of the variable we are getting.
Returns:
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""" Get the variable with the given variable key for the given feature.
Args:
feature_key: The key of the feature for which we are getting the variable.
variable_key: The key of the variable we are getting.
Returns:
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12,158 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.set_forced_variation | def set_forced_variation(self, experiment_key, user_id, variation_key):
""" Sets users to a map of experiments to forced variations.
Args:
experiment_key: Key for experiment.
user_id: The user ID.
variation_key: Key for variation. If None, then clear the existing experiment-to-variati... | python | def set_forced_variation(self, experiment_key, user_id, variation_key):
""" Sets users to a map of experiments to forced variations.
Args:
experiment_key: Key for experiment.
user_id: The user ID.
variation_key: Key for variation. If None, then clear the existing experiment-to-variati... | [
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12,159 | optimizely/python-sdk | optimizely/project_config.py | ProjectConfig.get_forced_variation | def get_forced_variation(self, experiment_key, user_id):
""" Gets the forced variation key for the given user and experiment.
Args:
experiment_key: Key for experiment.
user_id: The user ID.
Returns:
The variation which the given user and experiment should be forced into.
""... | python | def get_forced_variation(self, experiment_key, user_id):
""" Gets the forced variation key for the given user and experiment.
Args:
experiment_key: Key for experiment.
user_id: The user ID.
Returns:
The variation which the given user and experiment should be forced into.
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12,160 | optimizely/python-sdk | optimizely/event_dispatcher.py | EventDispatcher.dispatch_event | def dispatch_event(event):
""" Dispatch the event being represented by the Event object.
Args:
event: Object holding information about the request to be dispatched to the Optimizely backend.
"""
try:
if event.http_verb == enums.HTTPVerbs.GET:
requests.get(event.url, params=event.pa... | python | def dispatch_event(event):
""" Dispatch the event being represented by the Event object.
Args:
event: Object holding information about the request to be dispatched to the Optimizely backend.
"""
try:
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12,161 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely._validate_instantiation_options | def _validate_instantiation_options(self, datafile, skip_json_validation):
""" Helper method to validate all instantiation parameters.
Args:
datafile: JSON string representing the project.
skip_json_validation: Boolean representing whether JSON schema validation needs to be skipped or not.
Rai... | python | def _validate_instantiation_options(self, datafile, skip_json_validation):
""" Helper method to validate all instantiation parameters.
Args:
datafile: JSON string representing the project.
skip_json_validation: Boolean representing whether JSON schema validation needs to be skipped or not.
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12,162 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely._validate_user_inputs | def _validate_user_inputs(self, attributes=None, event_tags=None):
""" Helper method to validate user inputs.
Args:
attributes: Dict representing user attributes.
event_tags: Dict representing metadata associated with an event.
Returns:
Boolean True if inputs are valid. False otherwise.
... | python | def _validate_user_inputs(self, attributes=None, event_tags=None):
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Args:
attributes: Dict representing user attributes.
event_tags: Dict representing metadata associated with an event.
Returns:
Boolean True if inputs are valid. False otherwise.
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12,163 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely._send_impression_event | def _send_impression_event(self, experiment, variation, user_id, attributes):
""" Helper method to send impression event.
Args:
experiment: Experiment for which impression event is being sent.
variation: Variation picked for user for the given experiment.
user_id: ID for user.
attribute... | python | def _send_impression_event(self, experiment, variation, user_id, attributes):
""" Helper method to send impression event.
Args:
experiment: Experiment for which impression event is being sent.
variation: Variation picked for user for the given experiment.
user_id: ID for user.
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12,164 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely._get_feature_variable_for_type | def _get_feature_variable_for_type(self, feature_key, variable_key, variable_type, user_id, attributes):
""" Helper method to determine value for a certain variable attached to a feature flag based on type of variable.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
... | python | def _get_feature_variable_for_type(self, feature_key, variable_key, variable_type, user_id, attributes):
""" Helper method to determine value for a certain variable attached to a feature flag based on type of variable.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
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12,165 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.activate | def activate(self, experiment_key, user_id, attributes=None):
""" Buckets visitor and sends impression event to Optimizely.
Args:
experiment_key: Experiment which needs to be activated.
user_id: ID for user.
attributes: Dict representing user attributes and values which need to be recorded.
... | python | def activate(self, experiment_key, user_id, attributes=None):
""" Buckets visitor and sends impression event to Optimizely.
Args:
experiment_key: Experiment which needs to be activated.
user_id: ID for user.
attributes: Dict representing user attributes and values which need to be recorded.
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12,166 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.track | def track(self, event_key, user_id, attributes=None, event_tags=None):
""" Send conversion event to Optimizely.
Args:
event_key: Event key representing the event which needs to be recorded.
user_id: ID for user.
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""" Send conversion event to Optimizely.
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event_key: Event key representing the event which needs to be recorded.
user_id: ID for user.
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12,167 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_variation | def get_variation(self, experiment_key, user_id, attributes=None):
""" Gets variation where user will be bucketed.
Args:
experiment_key: Experiment for which user variation needs to be determined.
user_id: ID for user.
attributes: Dict representing user attributes.
Returns:
Variati... | python | def get_variation(self, experiment_key, user_id, attributes=None):
""" Gets variation where user will be bucketed.
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experiment_key: Experiment for which user variation needs to be determined.
user_id: ID for user.
attributes: Dict representing user attributes.
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12,168 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.is_feature_enabled | def is_feature_enabled(self, feature_key, user_id, attributes=None):
""" Returns true if the feature is enabled for the given user.
Args:
feature_key: The key of the feature for which we are determining if it is enabled or not for the given user.
user_id: ID for user.
attributes: Dict represe... | python | def is_feature_enabled(self, feature_key, user_id, attributes=None):
""" Returns true if the feature is enabled for the given user.
Args:
feature_key: The key of the feature for which we are determining if it is enabled or not for the given user.
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12,169 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_enabled_features | def get_enabled_features(self, user_id, attributes=None):
""" Returns the list of features that are enabled for the user.
Args:
user_id: ID for user.
attributes: Dict representing user attributes.
Returns:
A list of the keys of the features that are enabled for the user.
"""
ena... | python | def get_enabled_features(self, user_id, attributes=None):
""" Returns the list of features that are enabled for the user.
Args:
user_id: ID for user.
attributes: Dict representing user attributes.
Returns:
A list of the keys of the features that are enabled for the user.
"""
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12,170 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_feature_variable_boolean | def get_feature_variable_boolean(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain boolean variable attached to a feature flag.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
variable_key: Key of the variable whose value is ... | python | def get_feature_variable_boolean(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain boolean variable attached to a feature flag.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
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12,171 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_feature_variable_double | def get_feature_variable_double(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain double variable attached to a feature flag.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
variable_key: Key of the variable whose value is to... | python | def get_feature_variable_double(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain double variable attached to a feature flag.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
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12,172 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_feature_variable_integer | def get_feature_variable_integer(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain integer variable attached to a feature flag.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
variable_key: Key of the variable whose value is ... | python | def get_feature_variable_integer(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain integer variable attached to a feature flag.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
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12,173 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_feature_variable_string | def get_feature_variable_string(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain string variable attached to a feature.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
variable_key: Key of the variable whose value is to be a... | python | def get_feature_variable_string(self, feature_key, variable_key, user_id, attributes=None):
""" Returns value for a certain string variable attached to a feature.
Args:
feature_key: Key of the feature whose variable's value is being accessed.
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12,174 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.set_forced_variation | def set_forced_variation(self, experiment_key, user_id, variation_key):
""" Force a user into a variation for a given experiment.
Args:
experiment_key: A string key identifying the experiment.
user_id: The user ID.
variation_key: A string variation key that specifies the variation which the user... | python | def set_forced_variation(self, experiment_key, user_id, variation_key):
""" Force a user into a variation for a given experiment.
Args:
experiment_key: A string key identifying the experiment.
user_id: The user ID.
variation_key: A string variation key that specifies the variation which the user... | [
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12,175 | optimizely/python-sdk | optimizely/optimizely.py | Optimizely.get_forced_variation | def get_forced_variation(self, experiment_key, user_id):
""" Gets the forced variation for a given user and experiment.
Args:
experiment_key: A string key identifying the experiment.
user_id: The user ID.
Returns:
The forced variation key. None if no forced variation key.
"""
if... | python | def get_forced_variation(self, experiment_key, user_id):
""" Gets the forced variation for a given user and experiment.
Args:
experiment_key: A string key identifying the experiment.
user_id: The user ID.
Returns:
The forced variation key. None if no forced variation key.
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12,176 | optimizely/python-sdk | optimizely/helpers/audience.py | is_user_in_experiment | def is_user_in_experiment(config, experiment, attributes, logger):
""" Determine for given experiment if user satisfies the audiences for the experiment.
Args:
config: project_config.ProjectConfig object representing the project.
experiment: Object representing the experiment.
attributes: Dict represen... | python | def is_user_in_experiment(config, experiment, attributes, logger):
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Args:
config: project_config.ProjectConfig object representing the project.
experiment: Object representing the experiment.
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12,177 | optimizely/python-sdk | optimizely/event_builder.py | BaseEventBuilder._get_common_params | def _get_common_params(self, user_id, attributes):
""" Get params which are used same in both conversion and impression events.
Args:
user_id: ID for user.
attributes: Dict representing user attributes and values which need to be recorded.
Returns:
Dict consisting of parameters common to ... | python | def _get_common_params(self, user_id, attributes):
""" Get params which are used same in both conversion and impression events.
Args:
user_id: ID for user.
attributes: Dict representing user attributes and values which need to be recorded.
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12,178 | optimizely/python-sdk | optimizely/event_builder.py | EventBuilder._get_required_params_for_impression | def _get_required_params_for_impression(self, experiment, variation_id):
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Args:
experiment: Experiment for which impression needs to be recorded.
variation_id: ID for variation which would be presented to user.
Returns:
... | python | def _get_required_params_for_impression(self, experiment, variation_id):
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Args:
experiment: Experiment for which impression needs to be recorded.
variation_id: ID for variation which would be presented to user.
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12,179 | optimizely/python-sdk | optimizely/event_builder.py | EventBuilder._get_required_params_for_conversion | def _get_required_params_for_conversion(self, event_key, event_tags):
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Args:
event_key: Key representing the event which needs to be recorded.
event_tags: Dict representing metadata associated with the event.
Returns:
... | python | def _get_required_params_for_conversion(self, event_key, event_tags):
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Args:
event_key: Key representing the event which needs to be recorded.
event_tags: Dict representing metadata associated with the event.
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12,180 | optimizely/python-sdk | optimizely/event_builder.py | EventBuilder.create_impression_event | def create_impression_event(self, experiment, variation_id, user_id, attributes):
""" Create impression Event to be sent to the logging endpoint.
Args:
experiment: Experiment for which impression needs to be recorded.
variation_id: ID for variation which would be presented to user.
user_id: I... | python | def create_impression_event(self, experiment, variation_id, user_id, attributes):
""" Create impression Event to be sent to the logging endpoint.
Args:
experiment: Experiment for which impression needs to be recorded.
variation_id: ID for variation which would be presented to user.
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12,181 | optimizely/python-sdk | optimizely/event_builder.py | EventBuilder.create_conversion_event | def create_conversion_event(self, event_key, user_id, attributes, event_tags):
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Args:
event_key: Key representing the event which needs to be recorded.
user_id: ID for user.
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event_key: Key representing the event which needs to be recorded.
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12,182 | optimizely/python-sdk | optimizely/helpers/condition.py | _audience_condition_deserializer | def _audience_condition_deserializer(obj_dict):
""" Deserializer defining how dict objects need to be decoded for audience conditions.
Args:
obj_dict: Dict representing one audience condition.
Returns:
List consisting of condition key with corresponding value, type and match.
"""
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obj_di... | python | def _audience_condition_deserializer(obj_dict):
""" Deserializer defining how dict objects need to be decoded for audience conditions.
Args:
obj_dict: Dict representing one audience condition.
Returns:
List consisting of condition key with corresponding value, type and match.
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12,183 | optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator._get_condition_json | def _get_condition_json(self, index):
""" Method to generate json for logging audience condition.
Args:
index: Index of the condition.
Returns:
String: Audience condition JSON.
"""
condition = self.condition_data[index]
condition_log = {
'name': condition[0],
'value': c... | python | def _get_condition_json(self, index):
""" Method to generate json for logging audience condition.
Args:
index: Index of the condition.
Returns:
String: Audience condition JSON.
"""
condition = self.condition_data[index]
condition_log = {
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'value': c... | [
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12,184 | optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.is_value_type_valid_for_exact_conditions | def is_value_type_valid_for_exact_conditions(self, value):
""" Method to validate if the value is valid for exact match type evaluation.
Args:
value: Value to validate.
Returns:
Boolean: True if value is a string, boolean, or number. Otherwise False.
"""
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""" Method to validate if the value is valid for exact match type evaluation.
Args:
value: Value to validate.
Returns:
Boolean: True if value is a string, boolean, or number. Otherwise False.
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12,185 | optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.exists_evaluator | def exists_evaluator(self, index):
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Args:
index: Index of the condition to be evaluated.
Returns:
Boolean: True if the user attributes have a non-null value for the given condition,
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""" Evaluate the given exists match condition for the user attributes.
Args:
index: Index of the condition to be evaluated.
Returns:
Boolean: True if the user attributes have a non-null value for the given condition,
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12,186 | optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.greater_than_evaluator | def greater_than_evaluator(self, index):
""" Evaluate the given greater than match condition for the user attributes.
Args:
index: Index of the condition to be evaluated.
Returns:
Boolean:
- True if the user attribute value is greater than the condition value.
- Fal... | python | def greater_than_evaluator(self, index):
""" Evaluate the given greater than match condition for the user attributes.
Args:
index: Index of the condition to be evaluated.
Returns:
Boolean:
- True if the user attribute value is greater than the condition value.
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12,187 | optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.substring_evaluator | def substring_evaluator(self, index):
""" Evaluate the given substring match condition for the given user attributes.
Args:
index: Index of the condition to be evaluated.
Returns:
Boolean:
- True if the condition value is a substring of the user attribute value.
- False if the ... | python | def substring_evaluator(self, index):
""" Evaluate the given substring match condition for the given user attributes.
Args:
index: Index of the condition to be evaluated.
Returns:
Boolean:
- True if the condition value is a substring of the user attribute value.
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12,188 | optimizely/python-sdk | optimizely/helpers/condition.py | CustomAttributeConditionEvaluator.evaluate | def evaluate(self, index):
""" Given a custom attribute audience condition and user attributes, evaluate the
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Args:
index: Index of the condition to be evaluated.
Returns:
Boolean:
- True if the user attributes match the given condition.
... | python | def evaluate(self, index):
""" Given a custom attribute audience condition and user attributes, evaluate the
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Args:
index: Index of the condition to be evaluated.
Returns:
Boolean:
- True if the user attributes match the given condition.
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12,189 | optimizely/python-sdk | optimizely/helpers/condition.py | ConditionDecoder.object_hook | def object_hook(self, object_dict):
""" Hook which when passed into a json.JSONDecoder will replace each dict
in a json string with its index and convert the dict to an object as defined
by the passed in condition_decoder. The newly created condition object is
appended to the conditions_list.
Args:... | python | def object_hook(self, object_dict):
""" Hook which when passed into a json.JSONDecoder will replace each dict
in a json string with its index and convert the dict to an object as defined
by the passed in condition_decoder. The newly created condition object is
appended to the conditions_list.
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12,190 | optimizely/python-sdk | optimizely/decision_service.py | DecisionService._get_bucketing_id | def _get_bucketing_id(self, user_id, attributes):
""" Helper method to determine bucketing ID for the user.
Args:
user_id: ID for user.
attributes: Dict representing user attributes. May consist of bucketing ID to be used.
Returns:
String representing bucketing ID if it is a String type ... | python | def _get_bucketing_id(self, user_id, attributes):
""" Helper method to determine bucketing ID for the user.
Args:
user_id: ID for user.
attributes: Dict representing user attributes. May consist of bucketing ID to be used.
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String representing bucketing ID if it is a String type ... | [
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12,191 | optimizely/python-sdk | optimizely/decision_service.py | DecisionService.get_forced_variation | def get_forced_variation(self, experiment, user_id):
""" Determine if a user is forced into a variation for the given experiment and return that variation.
Args:
experiment: Object representing the experiment for which user is to be bucketed.
user_id: ID for the user.
Returns:
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""" Determine if a user is forced into a variation for the given experiment and return that variation.
Args:
experiment: Object representing the experiment for which user is to be bucketed.
user_id: ID for the user.
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12,192 | optimizely/python-sdk | optimizely/decision_service.py | DecisionService.get_stored_variation | def get_stored_variation(self, experiment, user_profile):
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Args:
experiment: Object representing the experiment for which user is to be bucketed.
user_profile: UserProfile object representing the use... | python | def get_stored_variation(self, experiment, user_profile):
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experiment: Object representing the experiment for which user is to be bucketed.
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12,193 | optimizely/python-sdk | optimizely/decision_service.py | DecisionService.get_variation | def get_variation(self, experiment, user_id, attributes, ignore_user_profile=False):
""" Top-level function to help determine variation user should be put in.
First, check if experiment is running.
Second, check if user is forced in a variation.
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12,194 | optimizely/python-sdk | optimizely/decision_service.py | DecisionService.get_experiment_in_group | def get_experiment_in_group(self, group, bucketing_id):
""" Determine which experiment in the group the user is bucketed into.
Args:
group: The group to bucket the user into.
bucketing_id: ID to be used for bucketing the user.
Returns:
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""" Determine which experiment in the group the user is bucketed into.
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group: The group to bucket the user into.
bucketing_id: ID to be used for bucketing the user.
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12,195 | optimizely/python-sdk | optimizely/notification_center.py | NotificationCenter.add_notification_listener | def add_notification_listener(self, notification_type, notification_callback):
""" Add a notification callback to the notification center.
Args:
notification_type: A string representing the notification type from .helpers.enums.NotificationTypes
notification_callback: closure of function to call wh... | python | def add_notification_listener(self, notification_type, notification_callback):
""" Add a notification callback to the notification center.
Args:
notification_type: A string representing the notification type from .helpers.enums.NotificationTypes
notification_callback: closure of function to call wh... | [
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12,196 | optimizely/python-sdk | optimizely/notification_center.py | NotificationCenter.remove_notification_listener | def remove_notification_listener(self, notification_id):
""" Remove a previously added notification callback.
Args:
notification_id: The numeric id passed back from add_notification_listener
Returns:
The function returns boolean true if found and removed, false otherwise.
"""
for v in... | python | def remove_notification_listener(self, notification_id):
""" Remove a previously added notification callback.
Args:
notification_id: The numeric id passed back from add_notification_listener
Returns:
The function returns boolean true if found and removed, false otherwise.
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12,197 | optimizely/python-sdk | optimizely/notification_center.py | NotificationCenter.send_notifications | def send_notifications(self, notification_type, *args):
""" Fires off the notification for the specific event. Uses var args to pass in a
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Args:
notification_type: Type of notification to fire (String from .helpers.enums.... | python | def send_notifications(self, notification_type, *args):
""" Fires off the notification for the specific event. Uses var args to pass in a
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Args:
notification_type: Type of notification to fire (String from .helpers.enums.... | [
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] | ec028d9efcf22498c3820f2650fa10f5c30bec90 | https://github.com/optimizely/python-sdk/blob/ec028d9efcf22498c3820f2650fa10f5c30bec90/optimizely/notification_center.py#L87-L101 |
12,198 | optimizely/python-sdk | optimizely/helpers/condition_tree_evaluator.py | and_evaluator | def and_evaluator(conditions, leaf_evaluator):
""" Evaluates a list of conditions as if the evaluator had been applied
to each entry and the results AND-ed together.
Args:
conditions: List of conditions ex: [operand_1, operand_2].
leaf_evaluator: Function which will be called to evaluate leaf condition v... | python | def and_evaluator(conditions, leaf_evaluator):
""" Evaluates a list of conditions as if the evaluator had been applied
to each entry and the results AND-ed together.
Args:
conditions: List of conditions ex: [operand_1, operand_2].
leaf_evaluator: Function which will be called to evaluate leaf condition v... | [
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12,199 | optimizely/python-sdk | optimizely/helpers/condition_tree_evaluator.py | not_evaluator | def not_evaluator(conditions, leaf_evaluator):
""" Evaluates a list of conditions as if the evaluator had been applied
to a single entry and NOT was applied to the result.
Args:
conditions: List of conditions ex: [operand_1, operand_2].
leaf_evaluator: Function which will be called to evaluate leaf condi... | python | def not_evaluator(conditions, leaf_evaluator):
""" Evaluates a list of conditions as if the evaluator had been applied
to a single entry and NOT was applied to the result.
Args:
conditions: List of conditions ex: [operand_1, operand_2].
leaf_evaluator: Function which will be called to evaluate leaf condi... | [
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