Search is not available for this dataset
identifier stringlengths 1 155 | parameters stringlengths 2 6.09k | docstring stringlengths 11 63.4k | docstring_summary stringlengths 0 63.4k | function stringlengths 29 99.8k | function_tokens list | start_point list | end_point list | language stringclasses 1
value | docstring_language stringlengths 2 7 | docstring_language_predictions stringlengths 18 23 | is_langid_reliable stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|---|---|
feature | (self, node="clickhouse1", mysql_node="mysql1", stress=None, parallel=None) | Check the conversion of extended precision data types.
| Check the conversion of extended precision data types.
| def feature(self, node="clickhouse1", mysql_node="mysql1", stress=None, parallel=None):
"""Check the conversion of extended precision data types.
"""
self.context.node = self.context.cluster.node(node)
self.context.mysql_node = self.context.cluster.node(mysql_node)
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has_flag | (compiler, flagname) | Return a boolean indicating whether a flag name is supported on
the specified compiler.
| Return a boolean indicating whether a flag name is supported on
the specified compiler.
| def has_flag(compiler, flagname):
"""Return a boolean indicating whether a flag name is supported on
the specified compiler.
"""
import tempfile
import os
with tempfile.NamedTemporaryFile("w", suffix=".cpp", delete=False) as f:
f.write("int main (int argc, char **argv) { return 0; }")
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cpp_flag | (compiler) | Return the -std=c++[11/14/17] compiler flag.
The newer version is prefered over c++11 (when it is available).
| Return the -std=c++[11/14/17] compiler flag.
The newer version is prefered over c++11 (when it is available).
| def cpp_flag(compiler):
"""Return the -std=c++[11/14/17] compiler flag.
The newer version is prefered over c++11 (when it is available).
"""
flags = ["-std=c++17", "-std=c++14", "-std=c++11"]
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plain_text | (self) | Check that we can perform LDAP user authentication using `plain text` connection protocol.
| Check that we can perform LDAP user authentication using `plain text` connection protocol.
| def plain_text(self):
"""Check that we can perform LDAP user authentication using `plain text` connection protocol.
"""
servers = {
"openldap1": {
"host": "openldap1",
"enable_tls": "no",
"auth_dn_prefix": "cn=",
"auth_dn_suffix": ",ou=users,dc=company... | [
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plain_text_with_custom_port | (self) | Check that we can perform LDAP user authentication using `plain text` connection protocol
with the server that uses custom port.
| Check that we can perform LDAP user authentication using `plain text` connection protocol
with the server that uses custom port.
| def plain_text_with_custom_port(self):
"""Check that we can perform LDAP user authentication using `plain text` connection protocol
with the server that uses custom port.
"""
servers = {
"openldap3": {
"host": "openldap3",
"port": "3089",
"enable_tls": "no",
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tls_with_custom_port | (self) | Check that we can perform LDAP user authentication using `TLS` connection protocol
with the server that uses custom port.
| Check that we can perform LDAP user authentication using `TLS` connection protocol
with the server that uses custom port.
| def tls_with_custom_port(self):
"""Check that we can perform LDAP user authentication using `TLS` connection protocol
with the server that uses custom port.
"""
servers = {
"openldap4": {
"host": "openldap4",
"port": "6036",
"tls_require_cert": "never",
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starttls_with_custom_port | (self) | Check that we can perform LDAP user authentication using `StartTLS` connection protocol
with the server that uses custom port.
| Check that we can perform LDAP user authentication using `StartTLS` connection protocol
with the server that uses custom port.
| def starttls_with_custom_port(self):
"""Check that we can perform LDAP user authentication using `StartTLS` connection protocol
with the server that uses custom port.
"""
servers = {
"openldap4": {
"host": "openldap4",
"port": "3089",
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tls_connection | (enable_tls, tls_require_cert) | Try to login using LDAP user authentication over a TLS connection. | Try to login using LDAP user authentication over a TLS connection. | def tls_connection(enable_tls, tls_require_cert):
"""Try to login using LDAP user authentication over a TLS connection."""
servers = {
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"host": "openldap2",
"enable_tls": enable_tls,
"tls_require_cert": tls_require_cert,
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tls | (self) | Check that we can perform LDAP user authentication using `TLS` connection protocol.
| Check that we can perform LDAP user authentication using `TLS` connection protocol.
| def tls(self):
"""Check that we can perform LDAP user authentication using `TLS` connection protocol.
"""
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tls_enable_tls_default_yes | (self) | Check that the default value for the `enable_tls` is set to `yes`. | Check that the default value for the `enable_tls` is set to `yes`. | def tls_enable_tls_default_yes(self):
"""Check that the default value for the `enable_tls` is set to `yes`."""
servers = {
"openldap2": {
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"tls_require_cert": "never",
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tls_require_cert_default_demand | (self) | Check that the default value for the `tls_require_cert` is set to `demand`. | Check that the default value for the `tls_require_cert` is set to `demand`. | def tls_require_cert_default_demand(self):
"""Check that the default value for the `tls_require_cert` is set to `demand`."""
servers = {
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starttls | (self) | Check that we can perform LDAP user authentication using legacy `StartTLS` connection protocol.
| Check that we can perform LDAP user authentication using legacy `StartTLS` connection protocol.
| def starttls(self):
"""Check that we can perform LDAP user authentication using legacy `StartTLS` connection protocol.
"""
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tls_cipher_suite | (self) | Check that `tls_cipher_suite` parameter can be used specify allowed cipher suites. | Check that `tls_cipher_suite` parameter can be used specify allowed cipher suites. | def tls_cipher_suite(self):
"""Check that `tls_cipher_suite` parameter can be used specify allowed cipher suites."""
servers = {
"openldap4": {
"host": "openldap4",
"port": "6036",
"tls_require_cert": "never",
"tls_cipher_suite": "SECURE256:+SECURE128:-VER... | [
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tls_minimum_protocol_version | (self, version, exitcode, message) | Check that `tls_minimum_protocol_version` parameter can be used specify
to specify the minimum protocol version of SSL/TLS. | Check that `tls_minimum_protocol_version` parameter can be used specify
to specify the minimum protocol version of SSL/TLS. | def tls_minimum_protocol_version(self, version, exitcode, message):
"""Check that `tls_minimum_protocol_version` parameter can be used specify
to specify the minimum protocol version of SSL/TLS."""
servers = {
"openldap4": {
"host": "openldap4",
"port": "6036",
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createDatasetFile | (destDir, **kwargs) |
This function extends genedataset.dataset.createDatasetFile() by adding more objects to the .h5
file created, as these objects are used by BioPyramid.
Parameters
----------
The same parameters as genedataset.dataset.createDatasetFile() are needed. In addition we need:
sampleGroupsDisplayed: (list) a subset list... |
This function extends genedataset.dataset.createDatasetFile() by adding more objects to the .h5
file created, as these objects are used by BioPyramid. | def createDatasetFile(destDir, **kwargs):
"""
This function extends genedataset.dataset.createDatasetFile() by adding more objects to the .h5
file created, as these objects are used by BioPyramid.
Parameters
----------
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instantiateDatasetFile | (ds, sampleGroupsDisplayed, sampleGroupOrdering, sampleGroupColours, pca) | This function is used to
| This function is used to
| def instantiateDatasetFile(ds, sampleGroupsDisplayed, sampleGroupOrdering, sampleGroupColours, pca):
"""This function is used to
"""
store = ds.hdfStore()
store['/series/sampleGroupsDisplayed'] = pandas.Series(sampleGroupsDisplayed)
store['/series/sampleGroupOrdering'] = pandas.Series(sampleGroupOrdering)
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datasetAttributes | (filepath, includeFilepath=False) |
Return a dictionary of dataset attributes from hdf5 file:
(name, fullname, species, version, description, pubmed_id, parent)
This is the same as attributes() method on the BPDataset instant, but should be
faster since it only extracts the attributes rather than all other values.
If includeFilepath is true, fil... |
Return a dictionary of dataset attributes from hdf5 file:
(name, fullname, species, version, description, pubmed_id, parent)
This is the same as attributes() method on the BPDataset instant, but should be
faster since it only extracts the attributes rather than all other values.
If includeFilepath is true, fil... | def datasetAttributes(filepath, includeFilepath=False):
"""
Return a dictionary of dataset attributes from hdf5 file:
(name, fullname, species, version, description, pubmed_id, parent)
This is the same as attributes() method on the BPDataset instant, but should be
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BPDataset.__init__ | (self, pathToHDF) | Instantiate the object by reading the hdf file given by pathToHDF
| Instantiate the object by reading the hdf file given by pathToHDF
| def __init__(self, pathToHDF):
"""Instantiate the object by reading the hdf file given by pathToHDF
"""
super(BPDataset, self).__init__(pathToHDF)
self._sampleGroupColours = pandas.read_hdf(self.filepath, '/series/sampleGroupColours')
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BPDataset.sampleGroups | (self, returnType=None) |
Return a list of sample group names eg: ["celltype","tissue"]. Override base class method
in order to ensure correct ordering and filtering.
Parameters
----------
returnType: {None, "display"}. If display, it returns only sample groups defined as for display.
This is useful when not all sample groups are ... |
Return a list of sample group names eg: ["celltype","tissue"]. Override base class method
in order to ensure correct ordering and filtering. | def sampleGroups(self, returnType=None):
"""
Return a list of sample group names eg: ["celltype","tissue"]. Override base class method
in order to ensure correct ordering and filtering.
Parameters
----------
returnType: {None, "display"}. If display, it returns only sample groups defined as for display.
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BPDataset.sampleGroupItems | (self, sampleGroup=None, groupBy=None, duplicates=False) |
Return sample group items belonging to sampleGroup, eg: ["B1","B2"]. Override base class method
to enforce correct ordering.
Parameters
----------
sampleGroup: name of sample group, eg: 'celltype'
groupBy: name of another sample group for grouping, eg: 'cell_lineage'
duplicates: boolean to return a li... |
Return sample group items belonging to sampleGroup, eg: ["B1","B2"]. Override base class method
to enforce correct ordering.
Parameters
----------
sampleGroup: name of sample group, eg: 'celltype'
groupBy: name of another sample group for grouping, eg: 'cell_lineage'
duplicates: boolean to return a li... | def sampleGroupItems(self, sampleGroup=None, groupBy=None, duplicates=False):
"""
Return sample group items belonging to sampleGroup, eg: ["B1","B2"]. Override base class method
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Parameters
----------
sampleGroup: name of sample group, eg: 'celltype'
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BPDataset.sampleGroupColours | (self, sampleGroup=None) | Return colour dictionary given sampleGroup, eg: {'Stem Cell':'#cccccc', ...}
If sampleGroup==None, returns the dictionary with enclosing sample groups as keys,
eg: {'cell_lineage': {'Stem Cell':'#cccccc', ...}, ...}
Parameters:
sampleGroup: string, a member of self.sampleGroups()
| Return colour dictionary given sampleGroup, eg: {'Stem Cell':'#cccccc', ...}
If sampleGroup==None, returns the dictionary with enclosing sample groups as keys,
eg: {'cell_lineage': {'Stem Cell':'#cccccc', ...}, ...}
Parameters:
sampleGroup: string, a member of self.sampleGroups()
| def sampleGroupColours(self, sampleGroup=None):
"""Return colour dictionary given sampleGroup, eg: {'Stem Cell':'#cccccc', ...}
If sampleGroup==None, returns the dictionary with enclosing sample groups as keys,
eg: {'cell_lineage': {'Stem Cell':'#cccccc', ...}, ...}
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BPDataset.sampleGroupOrdering | (self, sampleGroup=None) | Return list of ordered sample group items given sampleGroup, eg: ['LSK','MPP', ...]
If sampleGroup==None, returns the dictionary with enclosing sample groups as keys,
eg: {'celltype': ['LSK','MPP', ...], ...}
Parameters:
sampleGroup: string, a member of self.sampleGroups()
| Return list of ordered sample group items given sampleGroup, eg: ['LSK','MPP', ...]
If sampleGroup==None, returns the dictionary with enclosing sample groups as keys,
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Parameters:
sampleGroup: string, a member of self.sampleGroups()
| def sampleGroupOrdering(self, sampleGroup=None):
"""Return list of ordered sample group items given sampleGroup, eg: ['LSK','MPP', ...]
If sampleGroup==None, returns the dictionary with enclosing sample groups as keys,
eg: {'celltype': ['LSK','MPP', ...], ...}
Parameters:
sampleGroup: string, a member of... | [
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BPDataset.sampleTable | (self) | Ensure that 'sampleId' is always the name of the index, just in case it was left out.
| Ensure that 'sampleId' is always the name of the index, just in case it was left out.
| def sampleTable(self):
"""Ensure that 'sampleId' is always the name of the index, just in case it was left out.
"""
df = self.samples
df.index.name = 'sampleId'
return df | [
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dict_setup | (node, table_name, dict_name) | Setup and teardown of table and dictionary needed for the tests.
| Setup and teardown of table and dictionary needed for the tests.
| def dict_setup(node, table_name, dict_name):
"""Setup and teardown of table and dictionary needed for the tests.
"""
try:
with Given("I have a table"):
node.query(f"CREATE TABLE {table_name} (key UInt64, val UInt64) Engine=Memory()")
with And("I have a dictionary"):
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config_privileges_granted_directly | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD CONFIG` if and only if
they have `SYSTEM RELOAD CONFIG` privilege granted directly.
| Check that a user is able to execute `SYSTEM RELOAD CONFIG` if and only if
they have `SYSTEM RELOAD CONFIG` privilege granted directly.
| def config_privileges_granted_directly(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD CONFIG` if and only if
they have `SYSTEM RELOAD CONFIG` privilege granted directly.
"""
user_name = f"user_{getuid()}"
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node = self.context.node
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config_privileges_granted_via_role | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD CONFIG` if and only if
they have `SYSTEM RELOAD CONFIG` privilege granted via role.
| Check that a user is able to execute `SYSTEM RELOAD CONFIG` if and only if
they have `SYSTEM RELOAD CONFIG` privilege granted via role.
| def config_privileges_granted_via_role(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD CONFIG` if and only if
they have `SYSTEM RELOAD CONFIG` privilege granted via role.
"""
user_name = f"user_{getuid()}"
role_name = f"role_{getuid()}"
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node = s... | [
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config | (self, privilege, grant_target_name, user_name, node=None) | Run checks for `SYSTEM RELOAD CONFIG` privilege.
| Run checks for `SYSTEM RELOAD CONFIG` privilege.
| def config(self, privilege, grant_target_name, user_name, node=None):
"""Run checks for `SYSTEM RELOAD CONFIG` privilege.
"""
exitcode, message = errors.not_enough_privileges(name=user_name)
if node is None:
node = self.context.node
with Scenario("SYSTEM RELOAD CONFIG without privilege"):
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dictionary_privileges_granted_directly | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD DICTIONARY` if and only if
they have `SYSTEM RELOAD DICTIONARY` privilege granted directly.
| Check that a user is able to execute `SYSTEM RELOAD DICTIONARY` if and only if
they have `SYSTEM RELOAD DICTIONARY` privilege granted directly.
| def dictionary_privileges_granted_directly(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD DICTIONARY` if and only if
they have `SYSTEM RELOAD DICTIONARY` privilege granted directly.
"""
user_name = f"user_{getuid()}"
if node is None:
node = self.context.node
w... | [
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dictionary_privileges_granted_via_role | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD DICTIONARY` if and only if
they have `SYSTEM RELOAD DICTIONARY` privilege granted via role.
| Check that a user is able to execute `SYSTEM RELOAD DICTIONARY` if and only if
they have `SYSTEM RELOAD DICTIONARY` privilege granted via role.
| def dictionary_privileges_granted_via_role(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD DICTIONARY` if and only if
they have `SYSTEM RELOAD DICTIONARY` privilege granted via role.
"""
user_name = f"user_{getuid()}"
role_name = f"role_{getuid()}"
if node is None:
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dictionary | (self, privilege, grant_target_name, user_name, node=None) | Run checks for `SYSTEM RELOAD DICTIONARY` privilege.
| Run checks for `SYSTEM RELOAD DICTIONARY` privilege.
| def dictionary(self, privilege, grant_target_name, user_name, node=None):
"""Run checks for `SYSTEM RELOAD DICTIONARY` privilege.
"""
exitcode, message = errors.not_enough_privileges(name=user_name)
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dictionaries_privileges_granted_directly | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD DICTIONARIES` if and only if
they have `SYSTEM RELOAD DICTIONARIES` privilege granted directly.
| Check that a user is able to execute `SYSTEM RELOAD DICTIONARIES` if and only if
they have `SYSTEM RELOAD DICTIONARIES` privilege granted directly.
| def dictionaries_privileges_granted_directly(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD DICTIONARIES` if and only if
they have `SYSTEM RELOAD DICTIONARIES` privilege granted directly.
"""
user_name = f"user_{getuid()}"
if node is None:
node = self.context.node
... | [
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dictionaries_privileges_granted_via_role | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD DICTIONARIES` if and only if
they have `SYSTEM RELOAD DICTIONARIES` privilege granted via role.
| Check that a user is able to execute `SYSTEM RELOAD DICTIONARIES` if and only if
they have `SYSTEM RELOAD DICTIONARIES` privilege granted via role.
| def dictionaries_privileges_granted_via_role(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD DICTIONARIES` if and only if
they have `SYSTEM RELOAD DICTIONARIES` privilege granted via role.
"""
user_name = f"user_{getuid()}"
role_name = f"role_{getuid()}"
if node is None... | [
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dictionaries | (self, privilege, grant_target_name, user_name, node=None) | Run checks for `SYSTEM RELOAD DICTIONARIES` privilege.
| Run checks for `SYSTEM RELOAD DICTIONARIES` privilege.
| def dictionaries(self, privilege, grant_target_name, user_name, node=None):
"""Run checks for `SYSTEM RELOAD DICTIONARIES` privilege.
"""
exitcode, message = errors.not_enough_privileges(name=user_name)
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node = self.context.node
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embedded_dictionaries_privileges_granted_directly | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD EMBEDDED DICTIONARIES` if and only if
they have `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege granted directly.
| Check that a user is able to execute `SYSTEM RELOAD EMBEDDED DICTIONARIES` if and only if
they have `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege granted directly.
| def embedded_dictionaries_privileges_granted_directly(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD EMBEDDED DICTIONARIES` if and only if
they have `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege granted directly.
"""
user_name = f"user_{getuid()}"
if node is None:
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embedded_dictionaries_privileges_granted_via_role | (self, node=None) | Check that a user is able to execute `SYSTEM RELOAD EMBEDDED DICTIONARIES` if and only if
they have `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege granted via role.
| Check that a user is able to execute `SYSTEM RELOAD EMBEDDED DICTIONARIES` if and only if
they have `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege granted via role.
| def embedded_dictionaries_privileges_granted_via_role(self, node=None):
"""Check that a user is able to execute `SYSTEM RELOAD EMBEDDED DICTIONARIES` if and only if
they have `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege granted via role.
"""
user_name = f"user_{getuid()}"
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embedded_dictionaries | (self, privilege, grant_target_name, user_name, node=None) | Run checks for `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege.
| Run checks for `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege.
| def embedded_dictionaries(self, privilege, grant_target_name, user_name, node=None):
"""Run checks for `SYSTEM RELOAD EMBEDDED DICTIONARIES` privilege.
"""
exitcode, message = errors.not_enough_privileges(name=user_name)
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node = self.context.node
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feature | (self, node="clickhouse1") | Check the RBAC functionality of SYSTEM RELOAD.
| Check the RBAC functionality of SYSTEM RELOAD.
| def feature(self, node="clickhouse1"):
"""Check the RBAC functionality of SYSTEM RELOAD.
"""
self.context.node = self.context.cluster.node(node)
Suite(run=config_privileges_granted_directly, setup=instrument_clickhouse_server_log)
Suite(run=config_privileges_granted_via_role, setup=instrument_click... | [
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feature | (self, node="clickhouse1") | Check encryption functions usage compatibility with MySQL.
| Check encryption functions usage compatibility with MySQL.
| def feature(self, node="clickhouse1"):
"""Check encryption functions usage compatibility with MySQL.
"""
self.context.node = self.context.cluster.node(node)
Feature(run=load("aes_encryption.tests.compatibility.mysql.table_engine", "feature"), flags=TE)
Feature(run=load("aes_encryption.tests.compati... | [
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alter_user_granted_directly | (self, node=None) | Check that a user is able to execute `ALTER USER` with privileges are granted directly.
| Check that a user is able to execute `ALTER USER` with privileges are granted directly.
| def alter_user_granted_directly(self, node=None):
"""Check that a user is able to execute `ALTER USER` with privileges are granted directly.
"""
user_name = f"user_{getuid()}"
if node is None:
node = self.context.node
with user(node, f"{user_name}"):
Suite(run=alter_user,
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alter_user_granted_via_role | (self, node=None) | Check that a user is able to execute `ALTER USER` with privileges are granted through a role.
| Check that a user is able to execute `ALTER USER` with privileges are granted through a role.
| def alter_user_granted_via_role(self, node=None):
"""Check that a user is able to execute `ALTER USER` with privileges are granted through a role.
"""
user_name = f"user_{getuid()}"
role_name = f"role_{getuid()}"
if node is None:
node = self.context.node
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alter_user | (self, privilege, grant_target_name, user_name, node=None) | Check that user is only able to execute `ALTER USER` when they have the necessary privilege.
| Check that user is only able to execute `ALTER USER` when they have the necessary privilege.
| def alter_user(self, privilege, grant_target_name, user_name, node=None):
"""Check that user is only able to execute `ALTER USER` when they have the necessary privilege.
"""
exitcode, message = errors.not_enough_privileges(name=user_name)
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feature | (self, node="clickhouse1") | Check the RBAC functionality of ALTER USER.
| Check the RBAC functionality of ALTER USER.
| def feature(self, node="clickhouse1"):
"""Check the RBAC functionality of ALTER USER.
"""
self.context.node = self.context.cluster.node(node)
Suite(run=alter_user_granted_directly, setup=instrument_clickhouse_server_log)
Suite(run=alter_user_granted_via_role, setup=instrument_clickhouse_server_log) | [
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MultiCostDeathGdpControllable.__init__ | (self,
N_region,
N_country,
ratio_death_to_R=0.005,
use_constraints=False,
beta_default=0.5
) |
Multi-objective cost functions with two costs: death toll and gdp recess. It is controllable by three parameters:
the mixing parameter beta, and one constraints of maximum cumulative cost for each of them.
Parameters
----------
N_region: int
Population size of the r... |
Multi-objective cost functions with two costs: death toll and gdp recess. It is controllable by three parameters:
the mixing parameter beta, and one constraints of maximum cumulative cost for each of them. | def __init__(self,
N_region,
N_country,
ratio_death_to_R=0.005,
use_constraints=False,
beta_default=0.5
):
"""
Multi-objective cost functions with two costs: death toll and gdp recess. It is controllabl... | [
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MultiCostDeathGdpControllable.sample_goal_params | (self) |
Sample goal parameters.
Returns
-------
goal: 1D nd.array
Made of three params in [0, 1]: beta is the mixing parameter,
the following are normalized constraints on the maximal values of cumulative costs.
|
Sample goal parameters. | def sample_goal_params(self):
"""
Sample goal parameters.
Returns
-------
goal: 1D nd.array
Made of three params in [0, 1]: beta is the mixing parameter,
the following are normalized constraints on the maximal values of cumulative costs.
"""
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MultiCostDeathGdpControllable.set_goal_params | (self, goal) |
Set a goal.
Parameters
----------
goal: 1D nd.array
Should be of size 3: mixing parameter beta and normalized constraints, all in [0, 1].
|
Set a goal. | def set_goal_params(self, goal):
"""
Set a goal.
Parameters
----------
goal: 1D nd.array
Should be of size 3: mixing parameter beta and normalized constraints, all in [0, 1].
"""
self.beta = goal[0]
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MultiCostDeathGdpControllable.compute_cost | (self, previous_state, state, label_to_id, action, others={}) |
Compute each cost and an aggregated measure of costs as well as constraints.
Parameters
----------
previous_state: 2D nd.array
Previous model states (either 1D or 2D with first dimension # of states).
state: 2D nd.array
Current model states (either 1D or... |
Compute each cost and an aggregated measure of costs as well as constraints. | def compute_cost(self, previous_state, state, label_to_id, action, others={}):
"""
Compute each cost and an aggregated measure of costs as well as constraints.
Parameters
----------
previous_state: 2D nd.array
Previous model states (either 1D or 2D with first dimensi... | [
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MultiCostDeathGdpControllable.compute_deaths | (self, previous_state, state, label_to_id, action, others={}) |
Compute death toll
Parameters
----------
previous_state: 2D nd.array
Previous model states (either 1D or 2D with first dimension # of states).
state: 2D nd.array
Current model states (either 1D or 2D with first dimension # of states).
label_to_id:... |
Compute death toll | def compute_deaths(self, previous_state, state, label_to_id, action, others={}):
"""
Compute death toll
Parameters
----------
previous_state: 2D nd.array
Previous model states (either 1D or 2D with first dimension # of states).
state: 2D nd.array
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MultiCostDeathGdpControllable.compute_aggregated_cost | (self, costs, beta=None, constraints=None) |
Compute aggregated measure of cost with mixing beta and optional constraints.
Parameters
----------
costs: 2D nd.array
Array of costs (n_points, n_costs).
beta: float
Mixing parameters for the two costs.
constraints: nd.array of bools, optional
... |
Compute aggregated measure of cost with mixing beta and optional constraints.
Parameters
----------
costs: 2D nd.array
Array of costs (n_points, n_costs).
beta: float
Mixing parameters for the two costs.
constraints: nd.array of bools, optional
... | def compute_aggregated_cost(self, costs, beta=None, constraints=None):
"""
Compute aggregated measure of cost with mixing beta and optional constraints.
Parameters
----------
costs: 2D nd.array
Array of costs (n_points, n_costs).
beta: float
Mixing... | [
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lovasz_grad | (gt_sorted) |
Computes gradient of the Lovasz extension w.r.t sorted errors
See Alg. 1 in paper
|
Computes gradient of the Lovasz extension w.r.t sorted errors
See Alg. 1 in paper
| def lovasz_grad(gt_sorted):
"""
Computes gradient of the Lovasz extension w.r.t sorted errors
See Alg. 1 in paper
"""
p = len(gt_sorted)
gts = gt_sorted.sum()
intersection = gts - gt_sorted.float().cumsum(0)
union = gts + (1 - gt_sorted).float().cumsum(0)
jaccard = 1. - intersection ... | [
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iou_binary | (preds, labels, EMPTY=1., ignore=None, per_image=True) |
IoU for foreground class
binary: 1 foreground, 0 background
|
IoU for foreground class
binary: 1 foreground, 0 background
| def iou_binary(preds, labels, EMPTY=1., ignore=None, per_image=True):
"""
IoU for foreground class
binary: 1 foreground, 0 background
"""
if not per_image:
preds, labels = (preds,), (labels,)
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iou | (preds, labels, C, EMPTY=1., ignore=None, per_image=False) |
Array of IoU for each (non ignored) class
|
Array of IoU for each (non ignored) class
| def iou(preds, labels, C, EMPTY=1., ignore=None, per_image=False):
"""
Array of IoU for each (non ignored) class
"""
if not per_image:
preds, labels = (preds,), (labels,)
ious = []
for pred, label in zip(preds, labels):
iou = []
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mean | (l, ignore_nan=False, empty=0) |
nanmean compatible with generators.
|
nanmean compatible with generators.
| def mean(l, ignore_nan=False, empty=0):
"""
nanmean compatible with generators.
"""
l = iter(l)
if ignore_nan:
l = ifilterfalse(isnan, l)
try:
n = 1
acc = next(l)
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lovasz_hinge | (logits, labels, per_image=True, ignore=None) |
Binary Lovasz hinge loss
logits: [B, H, W] Variable, logits at each pixel (between -\infty and +\infty)
labels: [B, H, W] Tensor, binary ground truth masks (0 or 1)
per_image: compute the loss per image instead of per batch
ignore: void class id
|
Binary Lovasz hinge loss
logits: [B, H, W] Variable, logits at each pixel (between -\infty and +\infty)
labels: [B, H, W] Tensor, binary ground truth masks (0 or 1)
per_image: compute the loss per image instead of per batch
ignore: void class id
| def lovasz_hinge(logits, labels, per_image=True, ignore=None):
"""
Binary Lovasz hinge loss
logits: [B, H, W] Variable, logits at each pixel (between -\infty and +\infty)
labels: [B, H, W] Tensor, binary ground truth masks (0 or 1)
per_image: compute the loss per image instead of per batch
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lovasz_hinge_flat | (logits, labels) |
Binary Lovasz hinge loss
logits: [P] Variable, logits at each prediction (between -\infty and +\infty)
labels: [P] Tensor, binary ground truth labels (0 or 1)
ignore: label to ignore
|
Binary Lovasz hinge loss
logits: [P] Variable, logits at each prediction (between -\infty and +\infty)
labels: [P] Tensor, binary ground truth labels (0 or 1)
ignore: label to ignore
| def lovasz_hinge_flat(logits, labels):
"""
Binary Lovasz hinge loss
logits: [P] Variable, logits at each prediction (between -\infty and +\infty)
labels: [P] Tensor, binary ground truth labels (0 or 1)
ignore: label to ignore
"""
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flatten_binary_scores | (scores, labels, ignore=None) |
Flattens predictions in the batch (binary case)
Remove labels equal to 'ignore'
|
Flattens predictions in the batch (binary case)
Remove labels equal to 'ignore'
| def flatten_binary_scores(scores, labels, ignore=None):
"""
Flattens predictions in the batch (binary case)
Remove labels equal to 'ignore'
"""
scores = scores.view(-1)
labels = labels.view(-1)
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lovasz_softmax | (probas, labels, classes='present', per_image=False, ignore=None) |
Multi-class Lovasz-Softmax loss
probas: [B, C, H, W] Variable, class probabilities at each prediction (between 0 and 1).
Interpreted as binary (sigmoid) output with outputs of size [B, H, W].
labels: [B, H, W] Tensor, ground truth labels (between 0 and C - 1)
classes: 'all' for all,... |
Multi-class Lovasz-Softmax loss
probas: [B, C, H, W] Variable, class probabilities at each prediction (between 0 and 1).
Interpreted as binary (sigmoid) output with outputs of size [B, H, W].
labels: [B, H, W] Tensor, ground truth labels (between 0 and C - 1)
classes: 'all' for all,... | def lovasz_softmax(probas, labels, classes='present', per_image=False, ignore=None):
"""
Multi-class Lovasz-Softmax loss
probas: [B, C, H, W] Variable, class probabilities at each prediction (between 0 and 1).
Interpreted as binary (sigmoid) output with outputs of size [B, H, W].
label... | [
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lovasz_softmax_flat | (probas, labels, classes='present') |
Multi-class Lovasz-Softmax loss
probas: [P, C] Variable, class probabilities at each prediction (between 0 and 1)
labels: [P] Tensor, ground truth labels (between 0 and C - 1)
classes: 'all' for all, 'present' for classes present in labels, or a list of classes to average.
|
Multi-class Lovasz-Softmax loss
probas: [P, C] Variable, class probabilities at each prediction (between 0 and 1)
labels: [P] Tensor, ground truth labels (between 0 and C - 1)
classes: 'all' for all, 'present' for classes present in labels, or a list of classes to average.
| def lovasz_softmax_flat(probas, labels, classes='present'):
"""
Multi-class Lovasz-Softmax loss
probas: [P, C] Variable, class probabilities at each prediction (between 0 and 1)
labels: [P] Tensor, ground truth labels (between 0 and C - 1)
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flatten_probas | (probas, labels, ignore=None) |
Flattens predictions in the batch
|
Flattens predictions in the batch
| def flatten_probas(probas, labels, ignore=None):
"""
Flattens predictions in the batch
"""
if probas.dim() == 3:
# assumes output of a sigmoid layer
B, H, W = probas.size()
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xloss | (logits, labels, ignore=None) |
Cross entropy loss
|
Cross entropy loss
| def xloss(logits, labels, ignore=None):
"""
Cross entropy loss
"""
return F.cross_entropy(logits, Variable(labels), ignore_index=255) | [
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hex | (s) | Convert string to hex.
| Convert string to hex.
| def hex(s):
"""Convert string to hex.
"""
if isinstance(s, str):
return "".join(['%X' % ord(c) for c in s])
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execute_with_scope | (expr, scope, aggcontext=None, clients=None, **kwargs) | Execute an expression `expr`, with data provided in `scope`.
Parameters
----------
expr : ibis.expr.types.Expr
The expression to execute.
scope : collections.Mapping
A dictionary mapping :class:`~ibis.expr.operations.Node` subclass
instances to concrete data such as a pandas Dat... | Execute an expression `expr`, with data provided in `scope`. | def execute_with_scope(expr, scope, aggcontext=None, clients=None, **kwargs):
"""Execute an expression `expr`, with data provided in `scope`.
Parameters
----------
expr : ibis.expr.types.Expr
The expression to execute.
scope : collections.Mapping
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execute_until_in_scope | (
expr, scope, aggcontext=None, clients=None, post_execute_=None, **kwargs
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Parameters
----------
expr : ibis.expr.types.Expr
scope : Mapping
aggcontext : Optional[AggregationContext]
clients : List[ibis.client.Client]
kwargs : Mapping
| Execute until our op is in `scope`. | def execute_until_in_scope(
expr, scope, aggcontext=None, clients=None, post_execute_=None, **kwargs
):
"""Execute until our op is in `scope`.
Parameters
----------
expr : ibis.expr.types.Expr
scope : Mapping
aggcontext : Optional[AggregationContext]
clients : List[ibis.client.Client]
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is_computable_arg | (op, arg) | Is `arg` a valid input to an ``execute_node`` rule?
Parameters
----------
arg : object
Any Python object
Returns
-------
result : bool
| Is `arg` a valid input to an ``execute_node`` rule? | def is_computable_arg(op, arg):
"""Is `arg` a valid input to an ``execute_node`` rule?
Parameters
----------
arg : object
Any Python object
Returns
-------
result : bool
"""
return (
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execute_bottom_up | (
expr, scope, aggcontext=None, post_execute_=None, clients=None, **kwargs
) | Execute `expr` bottom-up.
Parameters
----------
expr : ibis.expr.types.Expr
scope : Mapping[ibis.expr.operations.Node, object]
aggcontext : Optional[ibis.pandas.aggcontext.AggregationContext]
kwargs : Dict[str, object]
Returns
-------
result : Mapping[
ibis.expr.operations.... | Execute `expr` bottom-up. | def execute_bottom_up(
expr, scope, aggcontext=None, post_execute_=None, clients=None, **kwargs
):
"""Execute `expr` bottom-up.
Parameters
----------
expr : ibis.expr.types.Expr
scope : Mapping[ibis.expr.operations.Node, object]
aggcontext : Optional[ibis.pandas.aggcontext.AggregationContex... | [
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main_execute | (expr, params=None, scope=None, aggcontext=None, **kwargs) | Execute an expression against data that are bound to it. If no data
are bound, raise an Exception.
Parameters
----------
expr : ibis.expr.types.Expr
The expression to execute
params : Mapping[ibis.expr.types.Expr, object]
The data that an unbound parameter in `expr` maps to
scop... | Execute an expression against data that are bound to it. If no data
are bound, raise an Exception. | def main_execute(expr, params=None, scope=None, aggcontext=None, **kwargs):
"""Execute an expression against data that are bound to it. If no data
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Parameters
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expr : ibis.expr.types.Expr
The expression to execute
params : Mapping[ibis.expr.types.... | [
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execute_and_reset | (
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) | Execute an expression against data that are bound to it. If no data
are bound, raise an Exception.
Notes
-----
The difference between this function and :func:`~ibis.pandas.core.execute`
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-------... | Execute an expression against data that are bound to it. If no data
are bound, raise an Exception. | def execute_and_reset(
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):
"""Execute an expression against data that are bound to it. If no data
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Notes
-----
The difference between this function and :func:`~ibis.pandas.core.execute`
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regression | (self, local, clickhouse_binary_path, stress=None, parallel=None) | ClickHouse integration with LDAP regression module.
| ClickHouse integration with LDAP regression module.
| def regression(self, local, clickhouse_binary_path, stress=None, parallel=None):
"""ClickHouse integration with LDAP regression module.
"""
top().terminating = False
nodes = {
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arguments_from_signature | (signature, *args, **kwargs) | Validate signature against `args` and `kwargs` and return the kwargs
asked for in the signature
Parameters
----------
args : Tuple[object...]
kwargs : Dict[str, object]
Returns
-------
args, kwargs : Tuple[Tuple[object...], Dict[str, object]]
Examples
--------
>>> from ibi... | Validate signature against `args` and `kwargs` and return the kwargs
asked for in the signature | def arguments_from_signature(signature, *args, **kwargs):
"""Validate signature against `args` and `kwargs` and return the kwargs
asked for in the signature
Parameters
----------
args : Tuple[object...]
kwargs : Dict[str, object]
Returns
-------
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nullable | (datatype) | Return the signature of a scalar value that is allowed to be NULL (in
SQL parlance).
Parameters
----------
datatype : ibis.expr.datatypes.DataType
Returns
-------
Tuple[Type]
| Return the signature of a scalar value that is allowed to be NULL (in
SQL parlance). | def nullable(datatype):
"""Return the signature of a scalar value that is allowed to be NULL (in
SQL parlance).
Parameters
----------
datatype : ibis.expr.datatypes.DataType
Returns
-------
Tuple[Type]
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udf_signature | (input_type, klass) | Compute the appropriate signature for an ibis Node from a list of input
types.
Parameters
----------
input_type : List[ibis.expr.datatypes.DataType]
A list of ibis DataType instances
klass : Type
pd.Series or SeriesGroupBy
Returns
-------
Tuple[Type]
A tuple of ... | Compute the appropriate signature for an ibis Node from a list of input
types. | def udf_signature(input_type, klass):
"""Compute the appropriate signature for an ibis Node from a list of input
types.
Parameters
----------
input_type : List[ibis.expr.datatypes.DataType]
A list of ibis DataType instances
klass : Type
pd.Series or SeriesGroupBy
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check_matching_signature | (input_type) | Make sure that the number of arguments declared by the user in
`input_type` matches that of the wrapped function's signature.
Parameters
----------
input_type : List[DataType]
Returns
-------
wrapper : callable
| Make sure that the number of arguments declared by the user in
`input_type` matches that of the wrapped function's signature. | def check_matching_signature(input_type):
"""Make sure that the number of arguments declared by the user in
`input_type` matches that of the wrapped function's signature.
Parameters
----------
input_type : List[DataType]
Returns
-------
wrapper : callable
"""
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udf | (input_type, output_type) | Define a UDF (user-defined function) that operates element wise on a
Pandas Series.
Parameters
----------
input_type : List[ibis.rules]
A rules encoding the abstract type of each argument. These are found in
:mod:`~ibis.expr.rules`. The length of this list must match the number
... | Define a UDF (user-defined function) that operates element wise on a
Pandas Series. | def udf(input_type, output_type):
"""Define a UDF (user-defined function) that operates element wise on a
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Parameters
----------
input_type : List[ibis.rules]
A rules encoding the abstract type of each argument. These are found in
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udaf | (input_type, output_type) | Define a UDAF (user-defined aggregation function) that takes N pandas.
Series or scalar values as inputs.
Parameters
----------
input_type : List[T]
A rules encoding the abstract type of each argument or one of the types
found in :mod:`~ibis.expr.datatypes`. These are found in
:... | Define a UDAF (user-defined aggregation function) that takes N pandas.
Series or scalar values as inputs. | def udaf(input_type, output_type):
"""Define a UDAF (user-defined aggregation function) that takes N pandas.
Series or scalar values as inputs.
Parameters
----------
input_type : List[T]
A rules encoding the abstract type of each argument or one of the types
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pareto_plot | (central, error) |
Plots a Pareto front for a given algorithm. (Ellipses show errors in two dimensions).
Parameters
----------
central: 2D nd.array
Coordinates of solutions from the Pareto front.
error: 2D nd.array
Error measures of solutions from the Pareto front.
|
Plots a Pareto front for a given algorithm. (Ellipses show errors in two dimensions).
Parameters
----------
central: 2D nd.array
Coordinates of solutions from the Pareto front.
error: 2D nd.array
Error measures of solutions from the Pareto front. | def pareto_plot(central, error):
"""
Plots a Pareto front for a given algorithm. (Ellipses show errors in two dimensions).
Parameters
----------
central: 2D nd.array
Coordinates of solutions from the Pareto front.
error: 2D nd.array
Error measures of solutions from the Pareto fro... | [
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extract_res | (folder, algo, max_costs, min_costs) |
This function go through all runs from an algorithm folder, gathers data about their Pareto front and compute the stair-case functions.
Saves information into text file at the algorithm level.
Parameters
----------
folder: str
Directory of the algorithm (full of directories, one for each r... |
This function go through all runs from an algorithm folder, gathers data about their Pareto front and compute the stair-case functions.
Saves information into text file at the algorithm level. | def extract_res(folder, algo, max_costs, min_costs):
"""
This function go through all runs from an algorithm folder, gathers data about their Pareto front and compute the stair-case functions.
Saves information into text file at the algorithm level.
Parameters
----------
folder: str
Dir... | [
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plot_algo_fronts | (folder) |
Plot Pareto fronts of all runs for a given algorithm.
Parameters
----------
folder: str
Directory of the algorithm (full of directories, one for each run).
|
Plot Pareto fronts of all runs for a given algorithm. | def plot_algo_fronts(folder):
"""
Plot Pareto fronts of all runs for a given algorithm.
Parameters
----------
folder: str
Directory of the algorithm (full of directories, one for each run).
"""
print('\n\tPlotting: ', folder.split('/')[-2])
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beta_plot | (folder) |
Custom plotting function to plot the evolution of the two costs as a function of the mixing parameter beta.
Parameters
----------
folder: str
Directory of the algorithm (full of directories, one for each run).
|
Custom plotting function to plot the evolution of the two costs as a function of the mixing parameter beta. | def beta_plot(folder):
"""
Custom plotting function to plot the evolution of the two costs as a function of the mixing parameter beta.
Parameters
----------
folder: str
Directory of the algorithm (full of directories, one for each run).
"""
all_data = dict()
goals = []
lis... | [
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plot_multi_algo | (folder) |
Plot comparison of Pareto fronts.
Parameters
----------
folder: str
Directory that contains folders for each algorithm.
|
Plot comparison of Pareto fronts. | def plot_multi_algo(folder):
"""
Plot comparison of Pareto fronts.
Parameters
----------
folder: str
Directory that contains folders for each algorithm.
"""
list_conds = os.listdir(folder)
data = []
data_std = []
labels = []
areas = []
for cond in list_conds:
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privilege_granted_directly_or_via_role | (self, node=None) | Check that user is only able to execute DETACH VIEW when they have required privilege, either directly or via role.
| Check that user is only able to execute DETACH VIEW when they have required privilege, either directly or via role.
| def privilege_granted_directly_or_via_role(self, node=None):
"""Check that user is only able to execute DETACH VIEW when they have required privilege, either directly or via role.
"""
role_name = f"role_{getuid()}"
user_name = f"user_{getuid()}"
if node is None:
node = self.context.node
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privilege_check | (grant_target_name, user_name, node=None) | Run scenarios to check the user's access with different privileges.
| Run scenarios to check the user's access with different privileges.
| def privilege_check(grant_target_name, user_name, node=None):
"""Run scenarios to check the user's access with different privileges.
"""
exitcode, message = errors.not_enough_privileges(name=f"{user_name}")
with Scenario("user without privilege"):
view_name = f"view_{getuid()}"
try:
... | [
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feature | (self, node="clickhouse1", stress=None, parallel=None) | Check the RBAC functionality of DETACH VIEW.
| Check the RBAC functionality of DETACH VIEW.
| def feature(self, node="clickhouse1", stress=None, parallel=None):
"""Check the RBAC functionality of DETACH VIEW.
"""
self.context.node = self.context.cluster.node(node)
if parallel is not None:
self.context.parallel = parallel
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self.context.stress = stress
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TestPing.test_server_version | (self, connect) |
target: test get the server version
method: call the server_version method after connected
expected: version should be the pymilvus version
|
target: test get the server version
method: call the server_version method after connected
expected: version should be the pymilvus version
| def test_server_version(self, connect):
'''
target: test get the server version
method: call the server_version method after connected
expected: version should be the pymilvus version
'''
status, res = connect.server_version()
assert res == __version__ | [
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TestPing.test_server_status | (self, connect) |
target: test get the server status
method: call the server_status method after connected
expected: status returned should be ok
|
target: test get the server status
method: call the server_status method after connected
expected: status returned should be ok
| def test_server_status(self, connect):
'''
target: test get the server status
method: call the server_status method after connected
expected: status returned should be ok
'''
status, msg = connect.server_status()
assert status.OK() | [
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TestPing.test_server_cmd_with_params_version | (self, connect) |
target: test cmd: version
method: cmd = "version" ...
expected: when cmd = 'version', return version of server;
|
target: test cmd: version
method: cmd = "version" ...
expected: when cmd = 'version', return version of server;
| def test_server_cmd_with_params_version(self, connect):
'''
target: test cmd: version
method: cmd = "version" ...
expected: when cmd = 'version', return version of server;
'''
cmd = "version"
status, msg = connect._cmd(cmd)
logging.getLogger().info(status)... | [
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"\"version\"",
"status",
",",
"msg",
"=",
"connect",
".",
"_cmd",
"(",
"cmd",
")",
"logging",
".",
"getLogger",
"(",
")",
".",
"info",
"(",
"status",
")",
"l... | [
25,
4
] | [
36,
33
] | python | en | ['en', 'error', 'th'] | False |
TestPing.test_server_cmd_with_params_others | (self, connect) |
target: test cmd: lalala
method: cmd = "lalala" ...
expected: when cmd = 'version', return version of server;
|
target: test cmd: lalala
method: cmd = "lalala" ...
expected: when cmd = 'version', return version of server;
| def test_server_cmd_with_params_others(self, connect):
'''
target: test cmd: lalala
method: cmd = "lalala" ...
expected: when cmd = 'version', return version of server;
'''
cmd = "rm -rf test"
status, msg = connect._cmd(cmd)
logging.getLogger().info(status... | [
"def",
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"(",
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")",
... | [
38,
4
] | [
48,
26
] | python | en | ['en', 'error', 'th'] | False |
TestPingDisconnect.test_server_version | (self, dis_connect) |
target: test get the server version, after disconnect
method: call the server_version method after connected
expected: version should not be the pymilvus version
|
target: test get the server version, after disconnect
method: call the server_version method after connected
expected: version should not be the pymilvus version
| def test_server_version(self, dis_connect):
'''
target: test get the server version, after disconnect
method: call the server_version method after connected
expected: version should not be the pymilvus version
'''
res = None
with pytest.raises(Exception) as e:
... | [
"def",
"test_server_version",
"(",
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"dis_connect",
")",
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"server_version",
"(",
")",
"assert",
"res",
... | [
57,
4
] | [
66,
26
] | python | en | ['en', 'error', 'th'] | False |
TestPingDisconnect.test_server_status | (self, dis_connect) |
target: test get the server status, after disconnect
method: call the server_status method after connected
expected: status returned should be not ok
|
target: test get the server status, after disconnect
method: call the server_status method after connected
expected: status returned should be not ok
| def test_server_status(self, dis_connect):
'''
target: test get the server status, after disconnect
method: call the server_status method after connected
expected: status returned should be not ok
'''
status = None
with pytest.raises(Exception) as e:
s... | [
"def",
"test_server_status",
"(",
"self",
",",
"dis_connect",
")",
":",
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",",
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"=",
"connect",
".",
"server_status",
"(",
")",
"assert",
"status... | [
68,
4
] | [
77,
29
] | python | en | ['en', 'error', 'th'] | False |
privilege_granted_directly_or_via_role | (self, node=None) | Check that user is only able to execute DROP DICTIONARY when they have required privilege, either directly or via role.
| Check that user is only able to execute DROP DICTIONARY when they have required privilege, either directly or via role.
| def privilege_granted_directly_or_via_role(self, node=None):
"""Check that user is only able to execute DROP DICTIONARY when they have required privilege, either directly or via role.
"""
role_name = f"role_{getuid()}"
user_name = f"user_{getuid()}"
if node is None:
node = self.context.node... | [
"def",
"privilege_granted_directly_or_via_role",
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":",
"node",
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"self",
".",
"context",
".",
"node... | [
5,
0
] | [
24,
92
] | python | en | ['en', 'en', 'en'] | True |
privilege_check | (grant_target_name, user_name, node=None) | Run scenarios to check the user's access with different privileges.
| Run scenarios to check the user's access with different privileges.
| def privilege_check(grant_target_name, user_name, node=None):
"""Run scenarios to check the user's access with different privileges.
"""
exitcode, message = errors.not_enough_privileges(name=f"{user_name}")
with Scenario("user without privilege"):
dict_name = f"dict_{getuid()}"
try:
... | [
"def",
"privilege_check",
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"f\"{user_name}\"",
")",
"with",
"Scenario",
"(",
"\"user without... | [
26,
0
] | [
103,
68
] | python | en | ['en', 'en', 'en'] | True |
feature | (self, node="clickhouse1", stress=None, parallel=None) | Check the RBAC functionality of DROP DICTIONARY.
| Check the RBAC functionality of DROP DICTIONARY.
| def feature(self, node="clickhouse1", stress=None, parallel=None):
"""Check the RBAC functionality of DROP DICTIONARY.
"""
self.context.node = self.context.cluster.node(node)
if parallel is not None:
self.context.parallel = parallel
if stress is not None:
self.context.stress = stres... | [
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"cluster",
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"node",
"(",
"node",
")",
... | [
111,
0
] | [
122,
48
] | python | en | ['en', 'en', 'en'] | True |
drop_user_granted_directly | (self, node=None) | Check that a user is able to execute `DROP USER` with privileges are granted directly.
| Check that a user is able to execute `DROP USER` with privileges are granted directly.
| def drop_user_granted_directly(self, node=None):
"""Check that a user is able to execute `DROP USER` with privileges are granted directly.
"""
user_name = f"user_{getuid()}"
if node is None:
node = self.context.node
with user(node, f"{user_name}"):
Suite(run=drop_user,
... | [
"def",
"drop_user_granted_directly",
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"user",
"(",
"node",
",",
"f\"{user_n... | [
8,
0
] | [
22,
80
] | python | en | ['en', 'en', 'en'] | True |
drop_user_granted_via_role | (self, node=None) | Check that a user is able to execute `DROP USER` with privileges are granted through a role.
| Check that a user is able to execute `DROP USER` with privileges are granted through a role.
| def drop_user_granted_via_role(self, node=None):
"""Check that a user is able to execute `DROP USER` with privileges are granted through a role.
"""
user_name = f"user_{getuid()}"
role_name = f"role_{getuid()}"
if node is None:
node = self.context.node
with user(node, f"{user_name}"),... | [
"def",
"drop_user_granted_via_role",
"(",
"self",
",",
"node",
"=",
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")",
":",
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"if",
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"None",
":",
"node",
"=",
"self",
".",
"context",
".",
"node",
"with",... | [
25,
0
] | [
43,
80
] | python | en | ['en', 'en', 'en'] | True |
drop_user | (self, privilege, grant_target_name, user_name, node=None) | Check that user is only able to execute `DROP USER` when they have the necessary privilege.
| Check that user is only able to execute `DROP USER` when they have the necessary privilege.
| def drop_user(self, privilege, grant_target_name, user_name, node=None):
"""Check that user is only able to execute `DROP USER` when they have the necessary privilege.
"""
exitcode, message = errors.not_enough_privileges(name=user_name)
if node is None:
node = self.context.node
with Scenar... | [
"def",
"drop_user",
"(",
"self",
",",
"privilege",
",",
"grant_target_name",
",",
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"(",
"name",
"=",
"user_name",
")",
"if",
"node",
"i... | [
51,
0
] | [
115,
55
] | python | en | ['en', 'en', 'en'] | True |
feature | (self, node="clickhouse1") | Check the RBAC functionality of DROP USER.
| Check the RBAC functionality of DROP USER.
| def feature(self, node="clickhouse1"):
"""Check the RBAC functionality of DROP USER.
"""
self.context.node = self.context.cluster.node(node)
Suite(run=drop_user_granted_directly, setup=instrument_clickhouse_server_log)
Suite(run=drop_user_granted_via_role, setup=instrument_clickhouse_server_log) | [
"def",
"feature",
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",",
... | [
124,
0
] | [
130,
81
] | python | en | ['en', 'en', 'en'] | True |
TestDistancesPositive.test_l2_pos | (self) |
roundoff errors occur only with the L2 decomposition used
with BLAS, ie. in IndexFlatL2 and with
n > distance_compute_blas_threshold = 20
|
roundoff errors occur only with the L2 decomposition used
with BLAS, ie. in IndexFlatL2 and with
n > distance_compute_blas_threshold = 20
| def test_l2_pos(self):
"""
roundoff errors occur only with the L2 decomposition used
with BLAS, ie. in IndexFlatL2 and with
n > distance_compute_blas_threshold = 20
"""
d = 128
n = 100
rs = np.random.RandomState(1234)
x = rs.rand(n, d).astype('fl... | [
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"(",
"'float32'",
")",
"... | [
511,
4
] | [
529,
29
] | python | en | ['en', 'error', 'th'] | False |
scenario | (self, node="clickhouse1") | Check that multiple LDAP servers can be used to
authenticate users.
| Check that multiple LDAP servers can be used to
authenticate users.
| def scenario(self, node="clickhouse1"):
"""Check that multiple LDAP servers can be used to
authenticate users.
"""
self.context.node = self.context.cluster.node(node)
servers = {
"openldap1": {
"host": "openldap1",
"port": "389",
"enable_tls": "no",
... | [
"def",
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")",
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"=",
"{",
"\"openldap1\"",
":",
"{",
"\"host\"",
... | [
11,
0
] | [
40,
30
] | python | en | ['en', 'en', 'en'] | True |
privileges_granted_directly | (self, node=None) | Check that a user is able to execute `CREATE ROLE` with privileges are granted directly.
| Check that a user is able to execute `CREATE ROLE` with privileges are granted directly.
| def privileges_granted_directly(self, node=None):
"""Check that a user is able to execute `CREATE ROLE` with privileges are granted directly.
"""
user_name = f"user_{getuid()}"
if node is None:
node = self.context.node
with user(node, f"{user_name}"):
Suite(run=create_role,
... | [
"def",
"privileges_granted_directly",
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",",
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"node",
"with",
"user",
"(",
"node",
",",
"f\"{user_... | [
8,
0
] | [
22,
74
] | python | en | ['en', 'en', 'en'] | True |
privileges_granted_via_role | (self, node=None) | Check that a user is able to execute `CREATE ROLE` with privileges are granted through a role.
| Check that a user is able to execute `CREATE ROLE` with privileges are granted through a role.
| def privileges_granted_via_role(self, node=None):
"""Check that a user is able to execute `CREATE ROLE` with privileges are granted through a role.
"""
user_name = f"user_{getuid()}"
role_name = f"role_{getuid()}"
if node is None:
node = self.context.node
with user(node, f"{user_name}... | [
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"node",
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".",
"context",
".",
"node",
"with"... | [
25,
0
] | [
43,
74
] | python | en | ['en', 'en', 'en'] | True |
create_role | (self, privilege, grant_target_name, user_name, node=None) | Check that user is only able to execute `CREATE ROLE` when they have the necessary privilege.
| Check that user is only able to execute `CREATE ROLE` when they have the necessary privilege.
| def create_role(self, privilege, grant_target_name, user_name, node=None):
"""Check that user is only able to execute `CREATE ROLE` when they have the necessary privilege.
"""
exitcode, message = errors.not_enough_privileges(name=user_name)
if node is None:
node = self.context.node
with Sc... | [
"def",
"create_role",
"(",
"self",
",",
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"(",
"name",
"=",
"user_name",
")",
"if",
"node",
... | [
51,
0
] | [
121,
69
] | python | en | ['en', 'en', 'en'] | True |
feature | (self, node="clickhouse1") | Check the RBAC functionality of CREATE ROLE.
| Check the RBAC functionality of CREATE ROLE.
| def feature(self, node="clickhouse1"):
"""Check the RBAC functionality of CREATE ROLE.
"""
self.context.node = self.context.cluster.node(node)
Suite(run=privileges_granted_directly, setup=instrument_clickhouse_server_log)
Suite(run=privileges_granted_via_role, setup=instrument_clickhouse_server_log... | [
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"privileges_granted_directly",
",",
... | [
130,
0
] | [
136,
82
] | python | en | ['en', 'en', 'en'] | True |
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