body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
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def __init__(self, ignore_validation: bool) -> None:
'Initialize Class properties.'
super().__init__()
self.ignore_validation = ignore_validation
self._app_packages = []
self._install_json_schema = None
self._layout_json_schema = None
self.config = {}
self.ij = InstallJson()
self.inv... | 2,886,200,466,622,236,700 | Initialize Class properties. | tcex/bin/validate.py | __init__ | benjaminPurdy/tcex | python | def __init__(self, ignore_validation: bool) -> None:
super().__init__()
self.ignore_validation = ignore_validation
self._app_packages = []
self._install_json_schema = None
self._layout_json_schema = None
self.config = {}
self.ij = InstallJson()
self.invalid_json_files = []
self.... |
@property
def _validation_data(self) -> Dict[(str, list)]:
'Return structure for validation data.'
return {'errors': [], 'fileSyntax': [], 'layouts': [], 'moduleImports': [], 'schema': [], 'feeds': []} | 5,958,275,173,923,295,000 | Return structure for validation data. | tcex/bin/validate.py | _validation_data | benjaminPurdy/tcex | python | @property
def _validation_data(self) -> Dict[(str, list)]:
return {'errors': [], 'fileSyntax': [], 'layouts': [], 'moduleImports': [], 'schema': [], 'feeds': []} |
def _check_node_import(self, node: Union[(ast.Import, ast.ImportFrom)], filename: str) -> None:
'.'
if isinstance(node, ast.Import):
for n in node.names:
m = n.name.split('.')[0]
if (not self.check_import_stdlib(m)):
m_status = self.check_imported(m)
... | -3,932,265,064,709,798,000 | . | tcex/bin/validate.py | _check_node_import | benjaminPurdy/tcex | python | def _check_node_import(self, node: Union[(astImport, astImportFrom)], filename: str) -> None:
if isinstance(node, astImport):
for n in nodenames:
m = nnamesplit()[0]
if (not selfcheck_import_stdlib(m)):
m_status = selfcheck_imported(m)
if (not m_s... |
def check_imports(self) -> None:
'Check the projects top level directory for missing imports.\n\n This method will check only files ending in **.py** and does not handle imports validation\n for sub-directories.\n '
for filename in sorted(os.listdir(self.app_path)):
if (not filename... | 8,037,250,862,082,015,000 | Check the projects top level directory for missing imports.
This method will check only files ending in **.py** and does not handle imports validation
for sub-directories. | tcex/bin/validate.py | check_imports | benjaminPurdy/tcex | python | def check_imports(self) -> None:
'Check the projects top level directory for missing imports.\n\n This method will check only files ending in **.py** and does not handle imports validation\n for sub-directories.\n '
for filename in sorted(os.listdir(self.app_path)):
if (not filename... |
@staticmethod
def check_import_stdlib(module: str) -> bool:
'Check if module is in Python stdlib.\n\n Args:\n module: The name of the module to check.\n\n Returns:\n bool: Returns True if the module is in the stdlib or template.\n '
if ((module in stdlib_list('3.6')) o... | 574,623,895,274,065,000 | Check if module is in Python stdlib.
Args:
module: The name of the module to check.
Returns:
bool: Returns True if the module is in the stdlib or template. | tcex/bin/validate.py | check_import_stdlib | benjaminPurdy/tcex | python | @staticmethod
def check_import_stdlib(module: str) -> bool:
'Check if module is in Python stdlib.\n\n Args:\n module: The name of the module to check.\n\n Returns:\n bool: Returns True if the module is in the stdlib or template.\n '
if ((module in stdlib_list('3.6')) o... |
@staticmethod
def check_imported(module: str) -> bool:
'Check whether the provide module can be imported (package installed).\n\n Args:\n module: The name of the module to check availability.\n\n Returns:\n bool: True if the module can be imported, False otherwise.\n '
... | 556,081,726,153,656,300 | Check whether the provide module can be imported (package installed).
Args:
module: The name of the module to check availability.
Returns:
bool: True if the module can be imported, False otherwise. | tcex/bin/validate.py | check_imported | benjaminPurdy/tcex | python | @staticmethod
def check_imported(module: str) -> bool:
'Check whether the provide module can be imported (package installed).\n\n Args:\n module: The name of the module to check availability.\n\n Returns:\n bool: True if the module can be imported, False otherwise.\n '
... |
def check_install_json(self) -> None:
'Check all install.json files for valid schema.'
if ('install.json' in self.invalid_json_files):
return
status = True
try:
self.ij.model
except ValidationError as ex:
self.invalid_json_files.append(self.ij.fqfn.name)
status = Fals... | 5,865,411,555,246,264,000 | Check all install.json files for valid schema. | tcex/bin/validate.py | check_install_json | benjaminPurdy/tcex | python | def check_install_json(self) -> None:
if ('install.json' in self.invalid_json_files):
return
status = True
try:
self.ij.model
except ValidationError as ex:
self.invalid_json_files.append(self.ij.fqfn.name)
status = False
for error in json.loads(ex.json()):
... |
def check_job_json(self) -> None:
'Validate feed files for feed job apps.'
if ('install.json' in self.invalid_json_files):
return
app_version = (self.tj.model.package.app_version or self.ij.model.package_version)
program_name = f'{self.tj.model.package.app_name}_{app_version}'.replace('_', ' ')
... | 5,187,031,783,895,453,000 | Validate feed files for feed job apps. | tcex/bin/validate.py | check_job_json | benjaminPurdy/tcex | python | def check_job_json(self) -> None:
if ('install.json' in self.invalid_json_files):
return
app_version = (self.tj.model.package.app_version or self.ij.model.package_version)
program_name = f'{self.tj.model.package.app_name}_{app_version}'.replace('_', ' ')
status = True
for feed in self.i... |
def check_layout_json(self) -> None:
'Check all layout.json files for valid schema.'
if ((not self.lj.has_layout) or ('layout.json' in self.invalid_json_files)):
return
status = True
try:
self.lj.model
except ValidationError as ex:
self.invalid_json_files.append(self.ij.fqfn.... | -9,029,930,225,845,429,000 | Check all layout.json files for valid schema. | tcex/bin/validate.py | check_layout_json | benjaminPurdy/tcex | python | def check_layout_json(self) -> None:
if ((not self.lj.has_layout) or ('layout.json' in self.invalid_json_files)):
return
status = True
try:
self.lj.model
except ValidationError as ex:
self.invalid_json_files.append(self.ij.fqfn.name)
status = False
for error ... |
def check_layout_params(self) -> None:
"Check that the layout.json is consistent with install.json.\n\n The layout.json files references the params.name from the install.json file. The method\n will validate that no reference appear for inputs in install.json that don't exist.\n "
ij_input... | 1,388,452,454,794,460,200 | Check that the layout.json is consistent with install.json.
The layout.json files references the params.name from the install.json file. The method
will validate that no reference appear for inputs in install.json that don't exist. | tcex/bin/validate.py | check_layout_params | benjaminPurdy/tcex | python | def check_layout_params(self) -> None:
"Check that the layout.json is consistent with install.json.\n\n The layout.json files references the params.name from the install.json file. The method\n will validate that no reference appear for inputs in install.json that don't exist.\n "
ij_input... |
def check_syntax(self, app_path=None) -> None:
'Run syntax on each ".py" and ".json" file.\n\n Args:\n app_path (str, optional): The path of Python files.\n '
fqpn = Path((app_path or os.getcwd()))
for fqfn in sorted(fqpn.iterdir()):
error = None
status = True
... | 8,878,062,756,795,646,000 | Run syntax on each ".py" and ".json" file.
Args:
app_path (str, optional): The path of Python files. | tcex/bin/validate.py | check_syntax | benjaminPurdy/tcex | python | def check_syntax(self, app_path=None) -> None:
'Run syntax on each ".py" and ".json" file.\n\n Args:\n app_path (str, optional): The path of Python files.\n '
fqpn = Path((app_path or os.getcwd()))
for fqfn in sorted(fqpn.iterdir()):
error = None
status = True
... |
def interactive(self) -> None:
'[App Builder] Run in interactive mode.'
while True:
line = sys.stdin.readline().strip()
if (line == 'quit'):
sys.exit()
elif (line == 'validate'):
self.check_syntax()
self.check_imports()
self.check_install_j... | -7,308,072,104,282,095,000 | [App Builder] Run in interactive mode. | tcex/bin/validate.py | interactive | benjaminPurdy/tcex | python | def interactive(self) -> None:
while True:
line = sys.stdin.readline().strip()
if (line == 'quit'):
sys.exit()
elif (line == 'validate'):
self.check_syntax()
self.check_imports()
self.check_install_json()
self.check_layout_json... |
def print_json(self) -> None:
'[App Builder] Print JSON output.'
print(json.dumps({'validation_data': self.validation_data})) | -1,345,672,885,728,641,000 | [App Builder] Print JSON output. | tcex/bin/validate.py | print_json | benjaminPurdy/tcex | python | def print_json(self) -> None:
print(json.dumps({'validation_data': self.validation_data})) |
def _print_file_syntax_results(self) -> None:
'Print file syntax results.'
if self.validation_data.get('fileSyntax'):
print(f'''
{c.Style.BRIGHT}{c.Fore.BLUE}Validated File Syntax:''')
print(f"{c.Style.BRIGHT}{'File:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('fileSynta... | -7,130,818,483,572,398,000 | Print file syntax results. | tcex/bin/validate.py | _print_file_syntax_results | benjaminPurdy/tcex | python | def _print_file_syntax_results(self) -> None:
if self.validation_data.get('fileSyntax'):
print(f'
{c.Style.BRIGHT}{c.Fore.BLUE}Validated File Syntax:')
print(f"{c.Style.BRIGHT}{'File:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('fileSyntax'):
status_color = ... |
def _print_imports_results(self) -> None:
'Print import results.'
if self.validation_data.get('moduleImports'):
print(f'''
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Imports:''')
print(f"{c.Style.BRIGHT}{'File:'!s:<30}{'Module:'!s:<30}{'Status:'!s:<25}")
for f in self.validation_data.get('mo... | 4,693,549,105,083,687,000 | Print import results. | tcex/bin/validate.py | _print_imports_results | benjaminPurdy/tcex | python | def _print_imports_results(self) -> None:
if self.validation_data.get('moduleImports'):
print(f'
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Imports:')
print(f"{c.Style.BRIGHT}{'File:'!s:<30}{'Module:'!s:<30}{'Status:'!s:<25}")
for f in self.validation_data.get('moduleImports'):
... |
def _print_schema_results(self) -> None:
'Print schema results.'
if self.validation_data.get('schema'):
print(f'''
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Schema:''')
print(f"{c.Style.BRIGHT}{'File:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('schema'):
status... | -5,820,603,044,823,452,000 | Print schema results. | tcex/bin/validate.py | _print_schema_results | benjaminPurdy/tcex | python | def _print_schema_results(self) -> None:
if self.validation_data.get('schema'):
print(f'
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Schema:')
print(f"{c.Style.BRIGHT}{'File:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('schema'):
status_color = self.status_color(... |
def _print_layouts_results(self) -> None:
'Print layout results.'
if self.validation_data.get('layouts'):
print(f'''
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Layouts:''')
print(f"{c.Style.BRIGHT}{'Params:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('layouts'):
... | 1,522,637,771,830,174,000 | Print layout results. | tcex/bin/validate.py | _print_layouts_results | benjaminPurdy/tcex | python | def _print_layouts_results(self) -> None:
if self.validation_data.get('layouts'):
print(f'
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Layouts:')
print(f"{c.Style.BRIGHT}{'Params:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('layouts'):
status_color = self.status_... |
def _print_feed_results(self) -> None:
'Print feed results.'
if self.validation_data.get('feeds'):
print(f'''
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Feed Jobs:''')
print(f"{c.Style.BRIGHT}{'Feeds:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('feeds'):
status_c... | 7,289,236,692,831,736,000 | Print feed results. | tcex/bin/validate.py | _print_feed_results | benjaminPurdy/tcex | python | def _print_feed_results(self) -> None:
if self.validation_data.get('feeds'):
print(f'
{c.Style.BRIGHT}{c.Fore.BLUE}Validated Feed Jobs:')
print(f"{c.Style.BRIGHT}{'Feeds:'!s:<60}{'Status:'!s:<25}")
for f in self.validation_data.get('feeds'):
status_color = self.status_color(... |
def _print_errors(self) -> None:
'Print errors results.'
if self.validation_data.get('errors'):
print('\n')
for error in self.validation_data.get('errors'):
print(f'* {c.Fore.RED}{error}')
if (not self.ignore_validation):
self.exit_code = 1 | 2,625,961,558,882,467,300 | Print errors results. | tcex/bin/validate.py | _print_errors | benjaminPurdy/tcex | python | def _print_errors(self) -> None:
if self.validation_data.get('errors'):
print('\n')
for error in self.validation_data.get('errors'):
print(f'* {c.Fore.RED}{error}')
if (not self.ignore_validation):
self.exit_code = 1 |
def print_results(self) -> None:
'Print results.'
self._print_file_syntax_results()
self._print_imports_results()
self._print_schema_results()
self._print_layouts_results()
self._print_feed_results()
self._print_errors() | 5,307,456,271,778,884,000 | Print results. | tcex/bin/validate.py | print_results | benjaminPurdy/tcex | python | def print_results(self) -> None:
self._print_file_syntax_results()
self._print_imports_results()
self._print_schema_results()
self._print_layouts_results()
self._print_feed_results()
self._print_errors() |
@staticmethod
def status_color(status) -> str:
'Return the appropriate status color.'
return (c.Fore.GREEN if status else c.Fore.RED) | -5,684,548,797,497,374,000 | Return the appropriate status color. | tcex/bin/validate.py | status_color | benjaminPurdy/tcex | python | @staticmethod
def status_color(status) -> str:
return (c.Fore.GREEN if status else c.Fore.RED) |
@staticmethod
def status_value(status) -> str:
'Return the appropriate status color.'
return ('passed' if status else 'failed') | -6,747,285,470,334,901,000 | Return the appropriate status color. | tcex/bin/validate.py | status_value | benjaminPurdy/tcex | python | @staticmethod
def status_value(status) -> str:
return ('passed' if status else 'failed') |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.empty_like)
def empty_like(prototype, dtype=None, order=None, subok=None):
"\n empty_like(prototype, dtype=None, order='K', subok=True)\n\n Return a new array with the same shape and type as a given array.\n\n Parameters\n ----------\n prot... | -1,656,268,581,539,844,600 | empty_like(prototype, dtype=None, order='K', subok=True)
Return a new array with the same shape and type as a given array.
Parameters
----------
prototype : array_like
The shape and data-type of `prototype` define these same attributes
of the returned array.
dtype : data-type, optional
Overrides the data ... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | empty_like | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.empty_like)
def empty_like(prototype, dtype=None, order=None, subok=None):
"\n empty_like(prototype, dtype=None, order='K', subok=True)\n\n Return a new array with the same shape and type as a given array.\n\n Parameters\n ----------\n prot... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.concatenate)
def concatenate(arrays, axis=None, out=None):
'\n concatenate((a1, a2, ...), axis=0, out=None)\n\n Join a sequence of arrays along an existing axis.\n\n Parameters\n ----------\n a1, a2, ... : sequence of array_like\n Th... | -8,880,532,773,887,127,000 | concatenate((a1, a2, ...), axis=0, out=None)
Join a sequence of arrays along an existing axis.
Parameters
----------
a1, a2, ... : sequence of array_like
The arrays must have the same shape, except in the dimension
corresponding to `axis` (the first, by default).
axis : int, optional
The axis along which ... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | concatenate | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.concatenate)
def concatenate(arrays, axis=None, out=None):
'\n concatenate((a1, a2, ...), axis=0, out=None)\n\n Join a sequence of arrays along an existing axis.\n\n Parameters\n ----------\n a1, a2, ... : sequence of array_like\n Th... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.inner)
def inner(a, b):
'\n inner(a, b)\n\n Inner product of two arrays.\n\n Ordinary inner product of vectors for 1-D arrays (without complex\n conjugation), in higher dimensions a sum product over the last axes.\n\n Parameters\n ------... | -7,448,896,873,532,278,000 | inner(a, b)
Inner product of two arrays.
Ordinary inner product of vectors for 1-D arrays (without complex
conjugation), in higher dimensions a sum product over the last axes.
Parameters
----------
a, b : array_like
If `a` and `b` are nonscalar, their last dimensions must match.
Returns
-------
out : ndarray
... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | inner | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.inner)
def inner(a, b):
'\n inner(a, b)\n\n Inner product of two arrays.\n\n Ordinary inner product of vectors for 1-D arrays (without complex\n conjugation), in higher dimensions a sum product over the last axes.\n\n Parameters\n ------... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.where)
def where(condition, x=None, y=None):
'\n where(condition, [x, y])\n\n Return elements chosen from `x` or `y` depending on `condition`.\n\n .. note::\n When only `condition` is provided, this function is a shorthand for\n ``n... | 5,377,605,712,749,175,000 | where(condition, [x, y])
Return elements chosen from `x` or `y` depending on `condition`.
.. note::
When only `condition` is provided, this function is a shorthand for
``np.asarray(condition).nonzero()``. Using `nonzero` directly should be
preferred, as it behaves correctly for subclasses. The rest of thi... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | where | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.where)
def where(condition, x=None, y=None):
'\n where(condition, [x, y])\n\n Return elements chosen from `x` or `y` depending on `condition`.\n\n .. note::\n When only `condition` is provided, this function is a shorthand for\n ``n... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.lexsort)
def lexsort(keys, axis=None):
'\n lexsort(keys, axis=-1)\n\n Perform an indirect stable sort using a sequence of keys.\n\n Given multiple sorting keys, which can be interpreted as columns in a\n spreadsheet, lexsort returns an array o... | 4,072,387,893,560,209,000 | lexsort(keys, axis=-1)
Perform an indirect stable sort using a sequence of keys.
Given multiple sorting keys, which can be interpreted as columns in a
spreadsheet, lexsort returns an array of integer indices that describes
the sort order by multiple columns. The last key in the sequence is used
for the primary sort o... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | lexsort | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.lexsort)
def lexsort(keys, axis=None):
'\n lexsort(keys, axis=-1)\n\n Perform an indirect stable sort using a sequence of keys.\n\n Given multiple sorting keys, which can be interpreted as columns in a\n spreadsheet, lexsort returns an array o... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.can_cast)
def can_cast(from_, to, casting=None):
"\n can_cast(from_, to, casting='safe')\n\n Returns True if cast between data types can occur according to the\n casting rule. If from is a scalar or array scalar, also returns\n True if the sc... | 420,385,678,301,806,100 | can_cast(from_, to, casting='safe')
Returns True if cast between data types can occur according to the
casting rule. If from is a scalar or array scalar, also returns
True if the scalar value can be cast without overflow or truncation
to an integer.
Parameters
----------
from_ : dtype, dtype specifier, scalar, or ar... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | can_cast | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.can_cast)
def can_cast(from_, to, casting=None):
"\n can_cast(from_, to, casting='safe')\n\n Returns True if cast between data types can occur according to the\n casting rule. If from is a scalar or array scalar, also returns\n True if the sc... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.min_scalar_type)
def min_scalar_type(a):
"\n min_scalar_type(a)\n\n For scalar ``a``, returns the data type with the smallest size\n and smallest scalar kind which can hold its value. For non-scalar\n array ``a``, returns the vector's dtype u... | -5,644,159,851,517,568,000 | min_scalar_type(a)
For scalar ``a``, returns the data type with the smallest size
and smallest scalar kind which can hold its value. For non-scalar
array ``a``, returns the vector's dtype unmodified.
Floating point values are not demoted to integers,
and complex values are not demoted to floats.
Parameters
--------... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | min_scalar_type | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.min_scalar_type)
def min_scalar_type(a):
"\n min_scalar_type(a)\n\n For scalar ``a``, returns the data type with the smallest size\n and smallest scalar kind which can hold its value. For non-scalar\n array ``a``, returns the vector's dtype u... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.result_type)
def result_type(*arrays_and_dtypes):
"\n result_type(*arrays_and_dtypes)\n\n Returns the type that results from applying the NumPy\n type promotion rules to the arguments.\n\n Type promotion in NumPy works similarly to the rules i... | 6,623,818,526,093,711,000 | result_type(*arrays_and_dtypes)
Returns the type that results from applying the NumPy
type promotion rules to the arguments.
Type promotion in NumPy works similarly to the rules in languages
like C++, with some slight differences. When both scalars and
arrays are used, the array's type takes precedence and the actua... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | result_type | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.result_type)
def result_type(*arrays_and_dtypes):
"\n result_type(*arrays_and_dtypes)\n\n Returns the type that results from applying the NumPy\n type promotion rules to the arguments.\n\n Type promotion in NumPy works similarly to the rules i... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.dot)
def dot(a, b, out=None):
"\n dot(a, b, out=None)\n\n Dot product of two arrays. Specifically,\n\n - If both `a` and `b` are 1-D arrays, it is inner product of vectors\n (without complex conjugation).\n\n - If both `a` and `b` are 2-D... | -4,682,007,655,391,947,000 | dot(a, b, out=None)
Dot product of two arrays. Specifically,
- If both `a` and `b` are 1-D arrays, it is inner product of vectors
(without complex conjugation).
- If both `a` and `b` are 2-D arrays, it is matrix multiplication,
but using :func:`matmul` or ``a @ b`` is preferred.
- If either `a` or `b` is 0-D (s... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | dot | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.dot)
def dot(a, b, out=None):
"\n dot(a, b, out=None)\n\n Dot product of two arrays. Specifically,\n\n - If both `a` and `b` are 1-D arrays, it is inner product of vectors\n (without complex conjugation).\n\n - If both `a` and `b` are 2-D... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.vdot)
def vdot(a, b):
'\n vdot(a, b)\n\n Return the dot product of two vectors.\n\n The vdot(`a`, `b`) function handles complex numbers differently than\n dot(`a`, `b`). If the first argument is complex the complex conjugate\n of the first... | -7,113,312,379,025,483,000 | vdot(a, b)
Return the dot product of two vectors.
The vdot(`a`, `b`) function handles complex numbers differently than
dot(`a`, `b`). If the first argument is complex the complex conjugate
of the first argument is used for the calculation of the dot product.
Note that `vdot` handles multidimensional arrays differen... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | vdot | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.vdot)
def vdot(a, b):
'\n vdot(a, b)\n\n Return the dot product of two vectors.\n\n The vdot(`a`, `b`) function handles complex numbers differently than\n dot(`a`, `b`). If the first argument is complex the complex conjugate\n of the first... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.bincount)
def bincount(x, weights=None, minlength=None):
'\n bincount(x, weights=None, minlength=0)\n\n Count number of occurrences of each value in array of non-negative ints.\n\n The number of bins (of size 1) is one larger than the largest val... | -8,931,369,888,445,359,000 | bincount(x, weights=None, minlength=0)
Count number of occurrences of each value in array of non-negative ints.
The number of bins (of size 1) is one larger than the largest value in
`x`. If `minlength` is specified, there will be at least this number
of bins in the output array (though it will be longer if necessary... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | bincount | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.bincount)
def bincount(x, weights=None, minlength=None):
'\n bincount(x, weights=None, minlength=0)\n\n Count number of occurrences of each value in array of non-negative ints.\n\n The number of bins (of size 1) is one larger than the largest val... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.ravel_multi_index)
def ravel_multi_index(multi_index, dims, mode=None, order=None):
"\n ravel_multi_index(multi_index, dims, mode='raise', order='C')\n\n Converts a tuple of index arrays into an array of flat\n indices, applying boundary modes to... | 6,791,245,878,041,759,000 | ravel_multi_index(multi_index, dims, mode='raise', order='C')
Converts a tuple of index arrays into an array of flat
indices, applying boundary modes to the multi-index.
Parameters
----------
multi_index : tuple of array_like
A tuple of integer arrays, one array for each dimension.
dims : tuple of ints
The sh... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | ravel_multi_index | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.ravel_multi_index)
def ravel_multi_index(multi_index, dims, mode=None, order=None):
"\n ravel_multi_index(multi_index, dims, mode='raise', order='C')\n\n Converts a tuple of index arrays into an array of flat\n indices, applying boundary modes to... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.unravel_index)
def unravel_index(indices, shape=None, order=None, dims=None):
"\n unravel_index(indices, shape, order='C')\n\n Converts a flat index or array of flat indices into a tuple\n of coordinate arrays.\n\n Parameters\n ----------\n... | -5,508,050,244,993,584,000 | unravel_index(indices, shape, order='C')
Converts a flat index or array of flat indices into a tuple
of coordinate arrays.
Parameters
----------
indices : array_like
An integer array whose elements are indices into the flattened
version of an array of dimensions ``shape``. Before version 1.6.0,
this funct... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | unravel_index | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.unravel_index)
def unravel_index(indices, shape=None, order=None, dims=None):
"\n unravel_index(indices, shape, order='C')\n\n Converts a flat index or array of flat indices into a tuple\n of coordinate arrays.\n\n Parameters\n ----------\n... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.copyto)
def copyto(dst, src, casting=None, where=None):
"\n copyto(dst, src, casting='same_kind', where=True)\n\n Copies values from one array to another, broadcasting as necessary.\n\n Raises a TypeError if the `casting` rule is violated, and if... | 3,615,085,328,127,619,000 | copyto(dst, src, casting='same_kind', where=True)
Copies values from one array to another, broadcasting as necessary.
Raises a TypeError if the `casting` rule is violated, and if
`where` is provided, it selects which elements to copy.
.. versionadded:: 1.7.0
Parameters
----------
dst : ndarray
The array into wh... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | copyto | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.copyto)
def copyto(dst, src, casting=None, where=None):
"\n copyto(dst, src, casting='same_kind', where=True)\n\n Copies values from one array to another, broadcasting as necessary.\n\n Raises a TypeError if the `casting` rule is violated, and if... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.putmask)
def putmask(a, mask, values):
'\n putmask(a, mask, values)\n\n Changes elements of an array based on conditional and input values.\n\n Sets ``a.flat[n] = values[n]`` for each n where ``mask.flat[n]==True``.\n\n If `values` is not the ... | -2,530,559,739,271,771,600 | putmask(a, mask, values)
Changes elements of an array based on conditional and input values.
Sets ``a.flat[n] = values[n]`` for each n where ``mask.flat[n]==True``.
If `values` is not the same size as `a` and `mask` then it will repeat.
This gives behavior different from ``a[mask] = values``.
Parameters
----------
... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | putmask | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.putmask)
def putmask(a, mask, values):
'\n putmask(a, mask, values)\n\n Changes elements of an array based on conditional and input values.\n\n Sets ``a.flat[n] = values[n]`` for each n where ``mask.flat[n]==True``.\n\n If `values` is not the ... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.packbits)
def packbits(myarray, axis=None):
'\n packbits(myarray, axis=None)\n\n Packs the elements of a binary-valued array into bits in a uint8 array.\n\n The result is padded to full bytes by inserting zero bits at the end.\n\n Parameters\n... | -5,699,911,325,572,923,000 | packbits(myarray, axis=None)
Packs the elements of a binary-valued array into bits in a uint8 array.
The result is padded to full bytes by inserting zero bits at the end.
Parameters
----------
myarray : array_like
An array of integers or booleans whose elements should be packed to
bits.
axis : int, optional
... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | packbits | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.packbits)
def packbits(myarray, axis=None):
'\n packbits(myarray, axis=None)\n\n Packs the elements of a binary-valued array into bits in a uint8 array.\n\n The result is padded to full bytes by inserting zero bits at the end.\n\n Parameters\n... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.unpackbits)
def unpackbits(myarray, axis=None):
'\n unpackbits(myarray, axis=None)\n\n Unpacks elements of a uint8 array into a binary-valued output array.\n\n Each element of `myarray` represents a bit-field that should be unpacked\n into a b... | 4,681,147,811,743,044,000 | unpackbits(myarray, axis=None)
Unpacks elements of a uint8 array into a binary-valued output array.
Each element of `myarray` represents a bit-field that should be unpacked
into a binary-valued output array. The shape of the output array is either
1-D (if `axis` is None) or the same shape as the input array with unpa... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | unpackbits | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.unpackbits)
def unpackbits(myarray, axis=None):
'\n unpackbits(myarray, axis=None)\n\n Unpacks elements of a uint8 array into a binary-valued output array.\n\n Each element of `myarray` represents a bit-field that should be unpacked\n into a b... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.shares_memory)
def shares_memory(a, b, max_work=None):
'\n shares_memory(a, b, max_work=None)\n\n Determine if two arrays share memory\n\n Parameters\n ----------\n a, b : ndarray\n Input arrays\n max_work : int, optional\n ... | -2,958,432,600,631,115,000 | shares_memory(a, b, max_work=None)
Determine if two arrays share memory
Parameters
----------
a, b : ndarray
Input arrays
max_work : int, optional
Effort to spend on solving the overlap problem (maximum number
of candidate solutions to consider). The following special
values are recognized:
max_w... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | shares_memory | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.shares_memory)
def shares_memory(a, b, max_work=None):
'\n shares_memory(a, b, max_work=None)\n\n Determine if two arrays share memory\n\n Parameters\n ----------\n a, b : ndarray\n Input arrays\n max_work : int, optional\n ... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.may_share_memory)
def may_share_memory(a, b, max_work=None):
'\n may_share_memory(a, b, max_work=None)\n\n Determine if two arrays might share memory\n\n A return of True does not necessarily mean that the two arrays\n share any element. It j... | 379,643,540,804,239,400 | may_share_memory(a, b, max_work=None)
Determine if two arrays might share memory
A return of True does not necessarily mean that the two arrays
share any element. It just means that they *might*.
Only the memory bounds of a and b are checked by default.
Parameters
----------
a, b : ndarray
Input arrays
max_wor... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | may_share_memory | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.may_share_memory)
def may_share_memory(a, b, max_work=None):
'\n may_share_memory(a, b, max_work=None)\n\n Determine if two arrays might share memory\n\n A return of True does not necessarily mean that the two arrays\n share any element. It j... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.is_busday)
def is_busday(dates, weekmask=None, holidays=None, busdaycal=None, out=None):
'\n is_busday(dates, weekmask=\'1111100\', holidays=None, busdaycal=None, out=None)\n\n Calculates which of the given dates are valid days, and which are not.\n... | -3,946,965,257,007,669,000 | is_busday(dates, weekmask='1111100', holidays=None, busdaycal=None, out=None)
Calculates which of the given dates are valid days, and which are not.
.. versionadded:: 1.7.0
Parameters
----------
dates : array_like of datetime64[D]
The array of dates to process.
weekmask : str or array_like of bool, optional
... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | is_busday | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.is_busday)
def is_busday(dates, weekmask=None, holidays=None, busdaycal=None, out=None):
'\n is_busday(dates, weekmask=\'1111100\', holidays=None, busdaycal=None, out=None)\n\n Calculates which of the given dates are valid days, and which are not.\n... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.busday_offset)
def busday_offset(dates, offsets, roll=None, weekmask=None, holidays=None, busdaycal=None, out=None):
'\n busday_offset(dates, offsets, roll=\'raise\', weekmask=\'1111100\', holidays=None, busdaycal=None, out=None)\n\n First adjusts t... | -7,629,953,265,631,859,000 | busday_offset(dates, offsets, roll='raise', weekmask='1111100', holidays=None, busdaycal=None, out=None)
First adjusts the date to fall on a valid day according to
the ``roll`` rule, then applies offsets to the given dates
counted in valid days.
.. versionadded:: 1.7.0
Parameters
----------
dates : array_like of dat... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | busday_offset | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.busday_offset)
def busday_offset(dates, offsets, roll=None, weekmask=None, holidays=None, busdaycal=None, out=None):
'\n busday_offset(dates, offsets, roll=\'raise\', weekmask=\'1111100\', holidays=None, busdaycal=None, out=None)\n\n First adjusts t... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.busday_count)
def busday_count(begindates, enddates, weekmask=None, holidays=None, busdaycal=None, out=None):
'\n busday_count(begindates, enddates, weekmask=\'1111100\', holidays=[], busdaycal=None, out=None)\n\n Counts the number of valid days bet... | 2,000,849,704,293,497,000 | busday_count(begindates, enddates, weekmask='1111100', holidays=[], busdaycal=None, out=None)
Counts the number of valid days between `begindates` and
`enddates`, not including the day of `enddates`.
If ``enddates`` specifies a date value that is earlier than the
corresponding ``begindates`` date value, the count wil... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | busday_count | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.busday_count)
def busday_count(begindates, enddates, weekmask=None, holidays=None, busdaycal=None, out=None):
'\n busday_count(begindates, enddates, weekmask=\'1111100\', holidays=[], busdaycal=None, out=None)\n\n Counts the number of valid days bet... |
@array_function_from_c_func_and_dispatcher(_multiarray_umath.datetime_as_string)
def datetime_as_string(arr, unit=None, timezone=None, casting=None):
"\n datetime_as_string(arr, unit=None, timezone='naive', casting='same_kind')\n\n Convert an array of datetimes into an array of strings.\n\n Parameters\n ... | 7,093,229,090,673,673,000 | datetime_as_string(arr, unit=None, timezone='naive', casting='same_kind')
Convert an array of datetimes into an array of strings.
Parameters
----------
arr : array_like of datetime64
The array of UTC timestamps to format.
unit : str
One of None, 'auto', or a :ref:`datetime unit <arrays.dtypes.dateunits>`.
tim... | venv/lib/python3.7/site-packages/numpy/core/multiarray.py | datetime_as_string | 180Studios/LoginApp | python | @array_function_from_c_func_and_dispatcher(_multiarray_umath.datetime_as_string)
def datetime_as_string(arr, unit=None, timezone=None, casting=None):
"\n datetime_as_string(arr, unit=None, timezone='naive', casting='same_kind')\n\n Convert an array of datetimes into an array of strings.\n\n Parameters\n ... |
def set_seed(seed):
'Set seed for reproduction.\n '
seed = (seed + dist.get_rank())
random.seed(seed)
np.random.seed(seed)
paddle.seed(seed)
os.environ['PYTHONHASHSEED'] = str(seed) | -1,180,362,922,598,118,700 | Set seed for reproduction. | apps/Graph4KG/utils.py | set_seed | LemonNoel/PGL | python | def set_seed(seed):
'\n '
seed = (seed + dist.get_rank())
random.seed(seed)
np.random.seed(seed)
paddle.seed(seed)
os.environ['PYTHONHASHSEED'] = str(seed) |
def set_logger(args):
'Write logs to console and log file.\n '
log_file = os.path.join(args.save_path, 'train.log')
logging.basicConfig(format='%(asctime)s %(levelname)-8s %(message)s', level=logging.INFO, datefmt='%Y-%m-%d %H:%M:%S', filename=log_file, filemode='a+')
if args.print_on_screen:
... | 1,284,161,568,627,359,000 | Write logs to console and log file. | apps/Graph4KG/utils.py | set_logger | LemonNoel/PGL | python | def set_logger(args):
'\n '
log_file = os.path.join(args.save_path, 'train.log')
logging.basicConfig(format='%(asctime)s %(levelname)-8s %(message)s', level=logging.INFO, datefmt='%Y-%m-%d %H:%M:%S', filename=log_file, filemode='a+')
if args.print_on_screen:
console = logging.StreamHandler()
... |
def print_log(step, interval, log, timer, time_sum):
'Print log to logger.\n '
logging.info(('[GPU %d] step: %d, loss: %.5f, reg: %.4e, speed: %.2f steps/s, time: %.2f s' % (dist.get_rank(), step, (log['loss'] / interval), (log['reg'] / interval), (interval / time_sum), time_sum)))
logging.info(('sample:... | -7,832,974,644,119,050,000 | Print log to logger. | apps/Graph4KG/utils.py | print_log | LemonNoel/PGL | python | def print_log(step, interval, log, timer, time_sum):
'\n '
logging.info(('[GPU %d] step: %d, loss: %.5f, reg: %.4e, speed: %.2f steps/s, time: %.2f s' % (dist.get_rank(), step, (log['loss'] / interval), (log['reg'] / interval), (interval / time_sum), time_sum)))
logging.info(('sample: %f, forward: %f, ba... |
def uniform(low, high, size, dtype=np.float32, seed=0):
'Memory efficient uniform implementation.\n '
rng = np.random.default_rng(seed)
out = (((high - low) * rng.random(size, dtype=dtype)) + low)
return out | 5,091,072,456,343,243,000 | Memory efficient uniform implementation. | apps/Graph4KG/utils.py | uniform | LemonNoel/PGL | python | def uniform(low, high, size, dtype=np.float32, seed=0):
'\n '
rng = np.random.default_rng(seed)
out = (((high - low) * rng.random(size, dtype=dtype)) + low)
return out |
def timer_wrapper(name):
'Time counter wrapper.\n '
def decorate(func):
'decorate func\n '
@functools.wraps(func)
def wrapper(*args, **kwargs):
'wrapper func\n '
logging.info(f'[{name}] start...')
ts = time.time()
res... | -1,646,729,750,719,834,600 | Time counter wrapper. | apps/Graph4KG/utils.py | timer_wrapper | LemonNoel/PGL | python | def timer_wrapper(name):
'\n '
def decorate(func):
'decorate func\n '
@functools.wraps(func)
def wrapper(*args, **kwargs):
'wrapper func\n '
logging.info(f'[{name}] start...')
ts = time.time()
result = func(*args, **k... |
def calculate_metrics(scores, corr_idxs, filter_list):
'Calculate metrics according to scores.\n '
logs = []
for i in range(scores.shape[0]):
rank = (scores[i] > scores[i][corr_idxs[i]]).astype('float32')
if (filter_list is not None):
mask = paddle.ones(rank.shape, dtype='floa... | -941,842,204,942,299,900 | Calculate metrics according to scores. | apps/Graph4KG/utils.py | calculate_metrics | LemonNoel/PGL | python | def calculate_metrics(scores, corr_idxs, filter_list):
'\n '
logs = []
for i in range(scores.shape[0]):
rank = (scores[i] > scores[i][corr_idxs[i]]).astype('float32')
if (filter_list is not None):
mask = paddle.ones(rank.shape, dtype='float32')
mask[filter_list[i]]... |
@timer_wrapper('evaluation')
def evaluate(model, loader, evaluate_mode='test', filter_dict=None, save_path='./tmp/', data_mode='hrt'):
'Evaluate given KGE model.\n '
if (data_mode == 'wikikg2'):
evaluate_wikikg2(model, loader, evaluate_mode, save_path)
elif (data_mode == 'wikikg90m'):
eva... | 8,041,928,486,932,966,000 | Evaluate given KGE model. | apps/Graph4KG/utils.py | evaluate | LemonNoel/PGL | python | @timer_wrapper('evaluation')
def evaluate(model, loader, evaluate_mode='test', filter_dict=None, save_path='./tmp/', data_mode='hrt'):
'\n '
if (data_mode == 'wikikg2'):
evaluate_wikikg2(model, loader, evaluate_mode, save_path)
elif (data_mode == 'wikikg90m'):
evaluate_wikikg90m(model, lo... |
def gram_schimidt_process(embeds, num_elem, use_scale):
' Orthogonalize embeddings.\n '
num_embed = embeds.shape[0]
assert (embeds.shape[1] == num_elem)
assert (embeds.shape[2] == (num_elem + int(use_scale)))
if use_scale:
scales = embeds[:, :, (- 1)]
embeds = embeds[:, :, :num_el... | 8,071,425,646,455,714,000 | Orthogonalize embeddings. | apps/Graph4KG/utils.py | gram_schimidt_process | LemonNoel/PGL | python | def gram_schimidt_process(embeds, num_elem, use_scale):
' \n '
num_embed = embeds.shape[0]
assert (embeds.shape[1] == num_elem)
assert (embeds.shape[2] == (num_elem + int(use_scale)))
if use_scale:
scales = embeds[:, :, (- 1)]
embeds = embeds[:, :, :num_elem]
u = [embeds[:, 0]... |
def decorate(func):
'decorate func\n '
@functools.wraps(func)
def wrapper(*args, **kwargs):
'wrapper func\n '
logging.info(f'[{name}] start...')
ts = time.time()
result = func(*args, **kwargs)
te = time.time()
costs = (te - ts)
if (c... | -8,385,293,892,817,383,000 | decorate func | apps/Graph4KG/utils.py | decorate | LemonNoel/PGL | python | def decorate(func):
'\n '
@functools.wraps(func)
def wrapper(*args, **kwargs):
'wrapper func\n '
logging.info(f'[{name}] start...')
ts = time.time()
result = func(*args, **kwargs)
te = time.time()
costs = (te - ts)
if (costs < 0.0001... |
@functools.wraps(func)
def wrapper(*args, **kwargs):
'wrapper func\n '
logging.info(f'[{name}] start...')
ts = time.time()
result = func(*args, **kwargs)
te = time.time()
costs = (te - ts)
if (costs < 0.0001):
cost_str = ('%f sec' % costs)
elif (costs > 3600):
... | 5,612,435,469,472,388,000 | wrapper func | apps/Graph4KG/utils.py | wrapper | LemonNoel/PGL | python | @functools.wraps(func)
def wrapper(*args, **kwargs):
'\n '
logging.info(f'[{name}] start...')
ts = time.time()
result = func(*args, **kwargs)
te = time.time()
costs = (te - ts)
if (costs < 0.0001):
cost_str = ('%f sec' % costs)
elif (costs > 3600):
cost_str = (... |
def test_address(self):
'Tests address makes an address that identifies as the correct AddressSpace'
user_id = addresser.user.unique_id()
user_address = addresser.user.address(user_id)
self.assertIsAddress(user_address)
self.assertEqual(addresser.get_address_type(user_address), addresser.AddressSpac... | -6,768,783,794,536,796,000 | Tests address makes an address that identifies as the correct AddressSpace | tests/rbac/common/addresser/user_test.py | test_address | kthblmfld/sawtooth-next-directory | python | def test_address(self):
user_id = addresser.user.unique_id()
user_address = addresser.user.address(user_id)
self.assertIsAddress(user_address)
self.assertEqual(addresser.get_address_type(user_address), addresser.AddressSpace.USER) |
def test_unique_id(self):
'Tests that unique_id generates a unique identifier and is unique'
id1 = addresser.user.unique_id()
id2 = addresser.user.unique_id()
self.assertIsIdentifier(id1)
self.assertIsIdentifier(id2)
self.assertNotEqual(id1, id2) | -7,196,710,362,681,734,000 | Tests that unique_id generates a unique identifier and is unique | tests/rbac/common/addresser/user_test.py | test_unique_id | kthblmfld/sawtooth-next-directory | python | def test_unique_id(self):
id1 = addresser.user.unique_id()
id2 = addresser.user.unique_id()
self.assertIsIdentifier(id1)
self.assertIsIdentifier(id2)
self.assertNotEqual(id1, id2) |
def test_get_address_type(self):
'Tests that get_address_type returns AddressSpace.USER if it is a user\n address, and None if it is of another address type'
user_address = addresser.user.address(addresser.user.unique_id())
role_address = addresser.role.address(addresser.role.unique_id())
self.as... | -2,365,047,442,419,383,000 | Tests that get_address_type returns AddressSpace.USER if it is a user
address, and None if it is of another address type | tests/rbac/common/addresser/user_test.py | test_get_address_type | kthblmfld/sawtooth-next-directory | python | def test_get_address_type(self):
'Tests that get_address_type returns AddressSpace.USER if it is a user\n address, and None if it is of another address type'
user_address = addresser.user.address(addresser.user.unique_id())
role_address = addresser.role.address(addresser.role.unique_id())
self.as... |
def test_get_addresser(self):
'Test that get_addresser returns the addresser class if it is a\n user address, and None if it is of another address type'
user_address = addresser.user.address(addresser.user.unique_id())
other_address = addresser.role.address(addresser.role.unique_id())
self.assert... | -6,577,220,945,678,064,000 | Test that get_addresser returns the addresser class if it is a
user address, and None if it is of another address type | tests/rbac/common/addresser/user_test.py | test_get_addresser | kthblmfld/sawtooth-next-directory | python | def test_get_addresser(self):
'Test that get_addresser returns the addresser class if it is a\n user address, and None if it is of another address type'
user_address = addresser.user.address(addresser.user.unique_id())
other_address = addresser.role.address(addresser.role.unique_id())
self.assert... |
def test_user_parse(self):
'Test addresser.user.parse returns a parsed address if it is a user address'
user_id = addresser.user.unique_id()
user_address = addresser.user.address(user_id)
parsed = addresser.user.parse(user_address)
self.assertEqual(parsed.object_type, addresser.ObjectType.USER)
... | 433,924,049,134,503,230 | Test addresser.user.parse returns a parsed address if it is a user address | tests/rbac/common/addresser/user_test.py | test_user_parse | kthblmfld/sawtooth-next-directory | python | def test_user_parse(self):
user_id = addresser.user.unique_id()
user_address = addresser.user.address(user_id)
parsed = addresser.user.parse(user_address)
self.assertEqual(parsed.object_type, addresser.ObjectType.USER)
self.assertEqual(parsed.related_type, addresser.ObjectType.NONE)
self.as... |
def test_addresser_parse(self):
'Test addresser.parse returns a parsed address'
user_id = addresser.user.unique_id()
user_address = addresser.user.address(user_id)
parsed = addresser.parse(user_address)
self.assertEqual(parsed.object_type, addresser.ObjectType.USER)
self.assertEqual(parsed.relat... | 7,162,493,697,817,564,000 | Test addresser.parse returns a parsed address | tests/rbac/common/addresser/user_test.py | test_addresser_parse | kthblmfld/sawtooth-next-directory | python | def test_addresser_parse(self):
user_id = addresser.user.unique_id()
user_address = addresser.user.address(user_id)
parsed = addresser.parse(user_address)
self.assertEqual(parsed.object_type, addresser.ObjectType.USER)
self.assertEqual(parsed.related_type, addresser.ObjectType.NONE)
self.as... |
def test_parse_other(self):
'Test that parse returns None if it is not a user address'
other_address = addresser.role.address(addresser.role.unique_id())
self.assertIsNone(addresser.user.parse(other_address)) | -610,400,045,570,985,700 | Test that parse returns None if it is not a user address | tests/rbac/common/addresser/user_test.py | test_parse_other | kthblmfld/sawtooth-next-directory | python | def test_parse_other(self):
other_address = addresser.role.address(addresser.role.unique_id())
self.assertIsNone(addresser.user.parse(other_address)) |
def test_addresses_are(self):
'Test that addresses_are returns True if all addresses are a user\n addresses, and False if any addresses are if a different address type'
user_address1 = addresser.user.address(addresser.user.unique_id())
user_address2 = addresser.user.address(addresser.user.unique_id()... | 779,494,870,157,806,300 | Test that addresses_are returns True if all addresses are a user
addresses, and False if any addresses are if a different address type | tests/rbac/common/addresser/user_test.py | test_addresses_are | kthblmfld/sawtooth-next-directory | python | def test_addresses_are(self):
'Test that addresses_are returns True if all addresses are a user\n addresses, and False if any addresses are if a different address type'
user_address1 = addresser.user.address(addresser.user.unique_id())
user_address2 = addresser.user.address(addresser.user.unique_id()... |
def test_address_deterministic(self):
'Tests address makes an address that identifies as the correct AddressSpace'
user_id1 = addresser.user.unique_id()
user_address1 = addresser.user.address(user_id1)
user_address2 = addresser.user.address(user_id1)
self.assertIsAddress(user_address1)
self.asse... | 507,684,526,630,221,630 | Tests address makes an address that identifies as the correct AddressSpace | tests/rbac/common/addresser/user_test.py | test_address_deterministic | kthblmfld/sawtooth-next-directory | python | def test_address_deterministic(self):
user_id1 = addresser.user.unique_id()
user_address1 = addresser.user.address(user_id1)
user_address2 = addresser.user.address(user_id1)
self.assertIsAddress(user_address1)
self.assertIsAddress(user_address2)
self.assertEqual(user_address1, user_address2... |
def test_address_random(self):
'Tests address makes a unique address given different inputs'
user_id1 = addresser.user.unique_id()
user_id2 = addresser.user.unique_id()
user_address1 = addresser.user.address(user_id1)
user_address2 = addresser.user.address(user_id2)
self.assertIsAddress(user_add... | -283,297,163,203,004,260 | Tests address makes a unique address given different inputs | tests/rbac/common/addresser/user_test.py | test_address_random | kthblmfld/sawtooth-next-directory | python | def test_address_random(self):
user_id1 = addresser.user.unique_id()
user_id2 = addresser.user.unique_id()
user_address1 = addresser.user.address(user_id1)
user_address2 = addresser.user.address(user_id2)
self.assertIsAddress(user_address1)
self.assertIsAddress(user_address2)
self.asser... |
def tile_index(A, B):
'\n Entrywise comparison index of tile index (column) vectors.\n '
(AA, BB) = broadcast_arrays(A, B)
if DEBUGGING:
shape = (max(A.shape[0], B.shape[0]), 1)
_check_shape('AA', AA, shape)
_check_shape('BB', BB, shape)
return (AA, BB) | 1,716,995,872,579,375,000 | Entrywise comparison index of tile index (column) vectors. | neuroswarms/matrix.py | tile_index | jdmonaco/neuroswarms | python | def tile_index(A, B):
'\n \n '
(AA, BB) = broadcast_arrays(A, B)
if DEBUGGING:
shape = (max(A.shape[0], B.shape[0]), 1)
_check_shape('AA', AA, shape)
_check_shape('BB', BB, shape)
return (AA, BB) |
def pairwise_tile_index(A, B):
'\n Pairwise comparison index of tile index (column) vectors.\n '
(AA, BB) = broadcast_arrays(A, B.T)
if DEBUGGING:
shape = (len(A), len(B))
_check_shape('AA', AA, shape)
_check_shape('BB', BB, shape)
return (AA, BB) | -8,375,266,190,173,897,000 | Pairwise comparison index of tile index (column) vectors. | neuroswarms/matrix.py | pairwise_tile_index | jdmonaco/neuroswarms | python | def pairwise_tile_index(A, B):
'\n \n '
(AA, BB) = broadcast_arrays(A, B.T)
if DEBUGGING:
shape = (len(A), len(B))
_check_shape('AA', AA, shape)
_check_shape('BB', BB, shape)
return (AA, BB) |
def pairwise_phasediffs(A, B):
'\n Compute synchronizing phase differences between phase pairs.\n '
N_A = len(A)
N_B = len(B)
DD_shape = (N_A, N_B)
if DEBUGGING:
_check_ndim('A', A, 2)
_check_ndim('B', B, 2)
_check_shape('A', A, 1, axis=1)
_check_shape('B', B, 1... | 3,069,492,397,436,846,000 | Compute synchronizing phase differences between phase pairs. | neuroswarms/matrix.py | pairwise_phasediffs | jdmonaco/neuroswarms | python | def pairwise_phasediffs(A, B):
'\n \n '
N_A = len(A)
N_B = len(B)
DD_shape = (N_A, N_B)
if DEBUGGING:
_check_ndim('A', A, 2)
_check_ndim('B', B, 2)
_check_shape('A', A, 1, axis=1)
_check_shape('B', B, 1, axis=1)
return (B.T - A) |
def distances(A, B):
'\n Compute distances between points in entrywise order.\n '
(AA, BB) = broadcast_arrays(A, B)
shape = AA.shape
if DEBUGGING:
_check_ndim('AA', AA, 2)
_check_ndim('BB', BB, 2)
_check_shape('AA', AA, 2, axis=1)
_check_shape('BB', BB, 2, axis=1)
... | -7,030,238,118,766,872,000 | Compute distances between points in entrywise order. | neuroswarms/matrix.py | distances | jdmonaco/neuroswarms | python | def distances(A, B):
'\n \n '
(AA, BB) = broadcast_arrays(A, B)
shape = AA.shape
if DEBUGGING:
_check_ndim('AA', AA, 2)
_check_ndim('BB', BB, 2)
_check_shape('AA', AA, 2, axis=1)
_check_shape('BB', BB, 2, axis=1)
return hypot((AA[:, 0] - BB[:, 0]), (AA[:, 1] - B... |
def pairwise_unit_diffs(A, B):
'\n Compute attracting unit-vector differences between pairs of points.\n '
DD = pairwise_position_deltas(A, B)
D_norm = hypot(DD[(..., 0)], DD[(..., 1)])
nz = D_norm.nonzero()
DD[nz] /= D_norm[nz][(..., AX)]
return DD | -424,086,748,636,339,500 | Compute attracting unit-vector differences between pairs of points. | neuroswarms/matrix.py | pairwise_unit_diffs | jdmonaco/neuroswarms | python | def pairwise_unit_diffs(A, B):
'\n \n '
DD = pairwise_position_deltas(A, B)
D_norm = hypot(DD[(..., 0)], DD[(..., 1)])
nz = D_norm.nonzero()
DD[nz] /= D_norm[nz][(..., AX)]
return DD |
def pairwise_distances(A, B):
'\n Compute distances between pairs of points.\n '
DD = pairwise_position_deltas(A, B)
return hypot(DD[(..., 0)], DD[(..., 1)]) | 721,351,548,684,608,900 | Compute distances between pairs of points. | neuroswarms/matrix.py | pairwise_distances | jdmonaco/neuroswarms | python | def pairwise_distances(A, B):
'\n \n '
DD = pairwise_position_deltas(A, B)
return hypot(DD[(..., 0)], DD[(..., 1)]) |
def pairwise_position_deltas(A, B):
'\n Compute attracting component deltas between pairs of points.\n '
N_A = len(A)
N_B = len(B)
if DEBUGGING:
_check_ndim('A', A, 2)
_check_ndim('B', B, 2)
_check_shape('A', A, 2, axis=1)
_check_shape('B', B, 2, axis=1)
AA = em... | -5,928,309,153,118,387,000 | Compute attracting component deltas between pairs of points. | neuroswarms/matrix.py | pairwise_position_deltas | jdmonaco/neuroswarms | python | def pairwise_position_deltas(A, B):
'\n \n '
N_A = len(A)
N_B = len(B)
if DEBUGGING:
_check_ndim('A', A, 2)
_check_ndim('B', B, 2)
_check_shape('A', A, 2, axis=1)
_check_shape('B', B, 2, axis=1)
AA = empty((N_A, N_B, 2), DISTANCE_DTYPE)
AA[:] = A[:, AX, :]
... |
def somatic_motion_update(D_up, D_cur, X, V):
"\n Compute updated positions by averaging pairwise difference vectors for\n mutually visible pairs with equal bidirectional adjustments within each\n pair. The updated distance matrix does not need to be symmetric; it\n represents 'desired' updates based on... | 5,209,787,987,385,210,000 | Compute updated positions by averaging pairwise difference vectors for
mutually visible pairs with equal bidirectional adjustments within each
pair. The updated distance matrix does not need to be symmetric; it
represents 'desired' updates based on recurrent learning.
:D_up: R(N,N)-matrix of updated distances
:D_cur: ... | neuroswarms/matrix.py | somatic_motion_update | jdmonaco/neuroswarms | python | def somatic_motion_update(D_up, D_cur, X, V):
"\n Compute updated positions by averaging pairwise difference vectors for\n mutually visible pairs with equal bidirectional adjustments within each\n pair. The updated distance matrix does not need to be symmetric; it\n represents 'desired' updates based on... |
def reward_motion_update(D_up, D_cur, X, R, V):
"\n Compute updated positions by averaging reward-based unit vectors for\n adjustments of the point only. The updated distance matrix represents\n 'desired' updates based on reward learning.\n\n :D_up: R(N,N_R)-matrix of updated distances between points an... | 7,204,605,029,253,445,000 | Compute updated positions by averaging reward-based unit vectors for
adjustments of the point only. The updated distance matrix represents
'desired' updates based on reward learning.
:D_up: R(N,N_R)-matrix of updated distances between points and rewards
:D_cur: R(N,N_R)-matrix of current distances between points and r... | neuroswarms/matrix.py | reward_motion_update | jdmonaco/neuroswarms | python | def reward_motion_update(D_up, D_cur, X, R, V):
"\n Compute updated positions by averaging reward-based unit vectors for\n adjustments of the point only. The updated distance matrix represents\n 'desired' updates based on reward learning.\n\n :D_up: R(N,N_R)-matrix of updated distances between points an... |
def run_shortcut(name: str):
'Runs a shortcut on macOS'
pass | -6,645,128,257,056,837,000 | Runs a shortcut on macOS | code/platforms/mac/user.py | run_shortcut | palexjo/pokey_talon | python | def run_shortcut(name: str):
pass |
def cleaner(dummy, value, *_):
'Cleans out unsafe HTML tags.\n\n Uses bleach and unescape until it reaches a fix point.\n\n Args:\n dummy: unused, sqalchemy will pass in the model class\n value: html (string) to be cleaned\n Returns:\n Html (string) without unsafe tags.\n '
if (value is None):
... | 6,719,119,775,714,724,000 | Cleans out unsafe HTML tags.
Uses bleach and unescape until it reaches a fix point.
Args:
dummy: unused, sqalchemy will pass in the model class
value: html (string) to be cleaned
Returns:
Html (string) without unsafe tags. | src/ggrc/utils/html_cleaner.py | cleaner | VRolich/ggrc-core | python | def cleaner(dummy, value, *_):
'Cleans out unsafe HTML tags.\n\n Uses bleach and unescape until it reaches a fix point.\n\n Args:\n dummy: unused, sqalchemy will pass in the model class\n value: html (string) to be cleaned\n Returns:\n Html (string) without unsafe tags.\n '
if (value is None):
... |
def predict(self, X):
' Predict the class index of the feature X '
Y_predict = self.clf.predict(self.pca.transform(X))
return Y_predict | 4,818,342,988,168,666,000 | Predict the class index of the feature X | utils/lib_classifier.py | predict | eddylamhw/trAIner24 | python | def predict(self, X):
' '
Y_predict = self.clf.predict(self.pca.transform(X))
return Y_predict |
def predict_and_evaluate(self, te_X, te_Y):
' Test model on test set and obtain accuracy '
te_Y_predict = self.predict(te_X)
N = len(te_Y)
n = sum((te_Y_predict == te_Y))
accu = (n / N)
return (accu, te_Y_predict) | -3,017,998,082,432,039,000 | Test model on test set and obtain accuracy | utils/lib_classifier.py | predict_and_evaluate | eddylamhw/trAIner24 | python | def predict_and_evaluate(self, te_X, te_Y):
' '
te_Y_predict = self.predict(te_X)
N = len(te_Y)
n = sum((te_Y_predict == te_Y))
accu = (n / N)
return (accu, te_Y_predict) |
def train(self, X, Y):
' Train model. The result is saved into self.clf '
n_components = min(NUM_FEATURES_FROM_PCA, X.shape[1])
self.pca = PCA(n_components=n_components, whiten=True)
self.pca.fit(X)
print('Sum eig values:', np.sum(self.pca.explained_variance_ratio_))
X_new = self.pca.transform(X... | -6,929,529,958,043,339,000 | Train model. The result is saved into self.clf | utils/lib_classifier.py | train | eddylamhw/trAIner24 | python | def train(self, X, Y):
' '
n_components = min(NUM_FEATURES_FROM_PCA, X.shape[1])
self.pca = PCA(n_components=n_components, whiten=True)
self.pca.fit(X)
print('Sum eig values:', np.sum(self.pca.explained_variance_ratio_))
X_new = self.pca.transform(X)
print('After PCA, X.shape = ', X_new.sha... |
def _predict_proba(self, X):
' Predict the probability of feature X belonging to each of the class Y[i] '
Y_probs = self.clf.predict_proba(self.pca.transform(X))
return Y_probs | -5,710,001,211,008,620,000 | Predict the probability of feature X belonging to each of the class Y[i] | utils/lib_classifier.py | _predict_proba | eddylamhw/trAIner24 | python | def _predict_proba(self, X):
' '
Y_probs = self.clf.predict_proba(self.pca.transform(X))
return Y_probs |
def predict(self, skeleton):
' Predict the class (string) of the input raw skeleton '
LABEL_UNKNOWN = ''
(is_features_good, features) = self.feature_generator.add_cur_skeleton(skeleton)
if is_features_good:
features = features.reshape((- 1), features.shape[0])
curr_scores = self.model._p... | -2,700,110,827,794,370,600 | Predict the class (string) of the input raw skeleton | utils/lib_classifier.py | predict | eddylamhw/trAIner24 | python | def predict(self, skeleton):
' '
LABEL_UNKNOWN =
(is_features_good, features) = self.feature_generator.add_cur_skeleton(skeleton)
if is_features_good:
features = features.reshape((- 1), features.shape[0])
curr_scores = self.model._predict_proba(features)[0]
self.scores = self.s... |
def smooth_scores(self, curr_scores):
' Smooth the current prediction score\n by taking the average with previous scores\n '
self.scores_hist.append(curr_scores)
DEQUE_MAX_SIZE = 2
if (len(self.scores_hist) > DEQUE_MAX_SIZE):
self.scores_hist.popleft()
if 1:
score_s... | -7,176,214,101,721,385,000 | Smooth the current prediction score
by taking the average with previous scores | utils/lib_classifier.py | smooth_scores | eddylamhw/trAIner24 | python | def smooth_scores(self, curr_scores):
' Smooth the current prediction score\n by taking the average with previous scores\n '
self.scores_hist.append(curr_scores)
DEQUE_MAX_SIZE = 2
if (len(self.scores_hist) > DEQUE_MAX_SIZE):
self.scores_hist.popleft()
if 1:
score_s... |
def args(*types, **ktypes):
'Allow testing of input types:\n argkey=(types) or argkey=type'
def decorator(func):
def modified(*args, **kargs):
position = 1
for (arg, T) in zip(args, types):
if (not isinstance(arg, T)):
raise TypeError(('Po... | 8,286,300,610,226,825,000 | Allow testing of input types:
argkey=(types) or argkey=type | WolfEyes/Utils/TypeChecker.py | args | TBIproject/WolfEye | python | def args(*types, **ktypes):
'Allow testing of input types:\n argkey=(types) or argkey=type'
def decorator(func):
def modified(*args, **kargs):
position = 1
for (arg, T) in zip(args, types):
if (not isinstance(arg, T)):
raise TypeError(('Po... |
def update_sonic_environment(bootloader, binary_image_version):
'Prepare sonic environment variable using incoming image template file. If incoming image template does not exist\n use current image template file.\n '
SONIC_ENV_TEMPLATE_FILE = os.path.join('usr', 'share', 'sonic', 'templates', 'sonic-en... | -8,889,302,718,236,318,000 | Prepare sonic environment variable using incoming image template file. If incoming image template does not exist
use current image template file. | sonic_installer/main.py | update_sonic_environment | Cosmin-Jinga-MS/sonic-utilities | python | def update_sonic_environment(bootloader, binary_image_version):
'Prepare sonic environment variable using incoming image template file. If incoming image template does not exist\n use current image template file.\n '
SONIC_ENV_TEMPLATE_FILE = os.path.join('usr', 'share', 'sonic', 'templates', 'sonic-en... |
def migrate_sonic_packages(bootloader, binary_image_version):
' Migrate SONiC packages to new SONiC image. '
SONIC_PACKAGE_MANAGER = 'sonic-package-manager'
PACKAGE_MANAGER_DIR = '/var/lib/sonic-package-manager/'
DOCKER_CTL_SCRIPT = '/usr/lib/docker/docker.sh'
DOCKERD_SOCK = 'docker.sock'
VAR_RU... | 9,047,976,012,657,931,000 | Migrate SONiC packages to new SONiC image. | sonic_installer/main.py | migrate_sonic_packages | Cosmin-Jinga-MS/sonic-utilities | python | def migrate_sonic_packages(bootloader, binary_image_version):
' '
SONIC_PACKAGE_MANAGER = 'sonic-package-manager'
PACKAGE_MANAGER_DIR = '/var/lib/sonic-package-manager/'
DOCKER_CTL_SCRIPT = '/usr/lib/docker/docker.sh'
DOCKERD_SOCK = 'docker.sock'
VAR_RUN_PATH = '/var/run/'
tmp_dir = 'tmp'
... |
def validate_positive_int(ctx, param, value):
'Callback to validate param passed is a positive integer.'
if (isinstance(value, int) and (value > 0)):
return value
raise click.BadParameter('Must be a positive integer') | -7,279,381,408,099,939,000 | Callback to validate param passed is a positive integer. | sonic_installer/main.py | validate_positive_int | Cosmin-Jinga-MS/sonic-utilities | python | def validate_positive_int(ctx, param, value):
if (isinstance(value, int) and (value > 0)):
return value
raise click.BadParameter('Must be a positive integer') |
@click.group(cls=AliasedGroup)
def sonic_installer():
' SONiC image installation manager '
if (os.geteuid() != 0):
exit('Root privileges required for this operation')
if (os.path.basename(sys.argv[0]) == 'sonic_installer'):
print_deprecation_warning('sonic_installer', 'sonic-installer') | -2,693,594,652,722,779,600 | SONiC image installation manager | sonic_installer/main.py | sonic_installer | Cosmin-Jinga-MS/sonic-utilities | python | @click.group(cls=AliasedGroup)
def sonic_installer():
' '
if (os.geteuid() != 0):
exit('Root privileges required for this operation')
if (os.path.basename(sys.argv[0]) == 'sonic_installer'):
print_deprecation_warning('sonic_installer', 'sonic-installer') |
@sonic_installer.command('install')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='New image will be installed, continue?')
@click.option('-f', '--force', is_flag=True, help='Force installation of an image of a type which differs from that of the current running image')
... | -8,643,368,970,254,067,000 | Install image from local binary or URL | sonic_installer/main.py | install | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('install')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='New image will be installed, continue?')
@click.option('-f', '--force', is_flag=True, help='Force installation of an image of a type which differs from that of the current running image')
... |
@sonic_installer.command('list')
def list_command():
' Print installed images '
bootloader = get_bootloader()
images = bootloader.get_installed_images()
curimage = bootloader.get_current_image()
nextimage = bootloader.get_next_image()
click.echo(('Current: ' + curimage))
click.echo(('Next: '... | 2,618,359,676,817,890,300 | Print installed images | sonic_installer/main.py | list_command | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('list')
def list_command():
' '
bootloader = get_bootloader()
images = bootloader.get_installed_images()
curimage = bootloader.get_current_image()
nextimage = bootloader.get_next_image()
click.echo(('Current: ' + curimage))
click.echo(('Next: ' + nextimage))
cli... |
@sonic_installer.command('set-default')
@click.argument('image')
def set_default(image):
' Choose image to boot from by default '
if ('set_default' in sys.argv):
print_deprecation_warning('set_default', 'set-default')
bootloader = get_bootloader()
if (image not in bootloader.get_installed_images... | -7,517,770,441,170,818,000 | Choose image to boot from by default | sonic_installer/main.py | set_default | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('set-default')
@click.argument('image')
def set_default(image):
' '
if ('set_default' in sys.argv):
print_deprecation_warning('set_default', 'set-default')
bootloader = get_bootloader()
if (image not in bootloader.get_installed_images()):
echo_and_log('Error: Im... |
@sonic_installer.command('set-next-boot')
@click.argument('image')
def set_next_boot(image):
' Choose image for next reboot (one time action) '
if ('set_next_boot' in sys.argv):
print_deprecation_warning('set_next_boot', 'set-next-boot')
bootloader = get_bootloader()
if (image not in bootloader.... | -6,706,689,704,284,489,000 | Choose image for next reboot (one time action) | sonic_installer/main.py | set_next_boot | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('set-next-boot')
@click.argument('image')
def set_next_boot(image):
' '
if ('set_next_boot' in sys.argv):
print_deprecation_warning('set_next_boot', 'set-next-boot')
bootloader = get_bootloader()
if (image not in bootloader.get_installed_images()):
echo_and_log(... |
@sonic_installer.command('remove')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='Image will be removed, continue?')
@click.argument('image')
def remove(image):
' Uninstall image '
bootloader = get_bootloader()
images = bootloader.get_installed_images()
c... | -1,843,418,837,334,930,400 | Uninstall image | sonic_installer/main.py | remove | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('remove')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='Image will be removed, continue?')
@click.argument('image')
def remove(image):
' '
bootloader = get_bootloader()
images = bootloader.get_installed_images()
current = bootlo... |
@sonic_installer.command('binary-version')
@click.argument('binary_image_path')
def binary_version(binary_image_path):
' Get version from local binary image file '
if ('binary_version' in sys.argv):
print_deprecation_warning('binary_version', 'binary-version')
bootloader = get_bootloader()
versi... | 3,922,998,441,759,064,600 | Get version from local binary image file | sonic_installer/main.py | binary_version | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('binary-version')
@click.argument('binary_image_path')
def binary_version(binary_image_path):
' '
if ('binary_version' in sys.argv):
print_deprecation_warning('binary_version', 'binary-version')
bootloader = get_bootloader()
version = bootloader.get_binary_image_version... |
@sonic_installer.command('cleanup')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='Remove images which are not current and next, continue?')
def cleanup():
' Remove installed images which are not current and next '
bootloader = get_bootloader()
images = bootl... | -158,115,806,792,518,000 | Remove installed images which are not current and next | sonic_installer/main.py | cleanup | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('cleanup')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='Remove images which are not current and next, continue?')
def cleanup():
' '
bootloader = get_bootloader()
images = bootloader.get_installed_images()
curimage = bootloader... |
@sonic_installer.command('upgrade-docker')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='New docker image will be installed, continue?')
@click.option('--cleanup_image', is_flag=True, help='Clean up old docker image')
@click.option('--skip_check', is_flag=True, help='Sk... | -6,863,555,456,993,927,000 | Upgrade docker image from local binary or URL | sonic_installer/main.py | upgrade_docker | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('upgrade-docker')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='New docker image will be installed, continue?')
@click.option('--cleanup_image', is_flag=True, help='Clean up old docker image')
@click.option('--skip_check', is_flag=True, help='Sk... |
@sonic_installer.command('rollback-docker')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='Docker image will be rolled back, continue?')
@click.argument('container_name', metavar='<container_name>', required=True, type=click.Choice(DOCKER_CONTAINER_LIST))
def rollback_do... | 3,255,627,671,178,643,500 | Rollback docker image to previous version | sonic_installer/main.py | rollback_docker | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('rollback-docker')
@click.option('-y', '--yes', is_flag=True, callback=abort_if_false, expose_value=False, prompt='Docker image will be rolled back, continue?')
@click.argument('container_name', metavar='<container_name>', required=True, type=click.Choice(DOCKER_CONTAINER_LIST))
def rollback_do... |
@sonic_installer.command('verify-next-image')
def verify_next_image():
' Verify the next image for reboot'
bootloader = get_bootloader()
if (not bootloader.verify_next_image()):
echo_and_log('Image verification failed', LOG_ERR)
sys.exit(1)
click.echo('Image successfully verified') | -3,142,566,014,996,444,000 | Verify the next image for reboot | sonic_installer/main.py | verify_next_image | Cosmin-Jinga-MS/sonic-utilities | python | @sonic_installer.command('verify-next-image')
def verify_next_image():
' '
bootloader = get_bootloader()
if (not bootloader.verify_next_image()):
echo_and_log('Image verification failed', LOG_ERR)
sys.exit(1)
click.echo('Image successfully verified') |
def __init__(self, allocate, swap_mem_size=None, total_mem_threshold=None, available_mem_threshold=None):
'\n Initialize the SWAP memory allocator.\n The allocator will try to setup SWAP memory only if all the below conditions are met:\n - allocate evaluates to True\n - disk has ... | 5,742,194,480,738,586,000 | Initialize the SWAP memory allocator.
The allocator will try to setup SWAP memory only if all the below conditions are met:
- allocate evaluates to True
- disk has enough space(> DISK_MEM_THRESHOLD)
- either system total memory < total_mem_threshold or system available memory < available_mem_threshold
@par... | sonic_installer/main.py | __init__ | Cosmin-Jinga-MS/sonic-utilities | python | def __init__(self, allocate, swap_mem_size=None, total_mem_threshold=None, available_mem_threshold=None):
'\n Initialize the SWAP memory allocator.\n The allocator will try to setup SWAP memory only if all the below conditions are met:\n - allocate evaluates to True\n - disk has ... |
@staticmethod
def get_disk_freespace(path):
'Return free disk space in bytes.'
fs_stats = os.statvfs(path)
return (fs_stats.f_bsize * fs_stats.f_bavail) | -6,005,371,022,862,676,000 | Return free disk space in bytes. | sonic_installer/main.py | get_disk_freespace | Cosmin-Jinga-MS/sonic-utilities | python | @staticmethod
def get_disk_freespace(path):
fs_stats = os.statvfs(path)
return (fs_stats.f_bsize * fs_stats.f_bavail) |
@staticmethod
def read_from_meminfo():
'Read information from /proc/meminfo.'
meminfo = {}
with open('/proc/meminfo') as fd:
for line in fd.readlines():
if line:
fields = line.split()
if ((len(fields) >= 2) and fields[1].isdigit()):
mem... | 5,057,307,792,526,469,000 | Read information from /proc/meminfo. | sonic_installer/main.py | read_from_meminfo | Cosmin-Jinga-MS/sonic-utilities | python | @staticmethod
def read_from_meminfo():
meminfo = {}
with open('/proc/meminfo') as fd:
for line in fd.readlines():
if line:
fields = line.split()
if ((len(fields) >= 2) and fields[1].isdigit()):
meminfo[fields[0].rstrip(':')] = int(fiel... |
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