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driftx/Telephus | telephus/protocol.py | ManagedCassandraClientFactory.login | def login(self, credentials):
""" authenticate all connections """
dfrds = []
for p in self._protos:
dfrds.append(p.submitRequest(ManagedThriftRequest('login',
ttypes.AuthenticationRequest(credentials=credentials))))
return defer.gatherResults(dfrds) | python | def login(self, credentials):
""" authenticate all connections """
dfrds = []
for p in self._protos:
dfrds.append(p.submitRequest(ManagedThriftRequest('login',
ttypes.AuthenticationRequest(credentials=credentials))))
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ttinoco/OPTALG | optalg/opt_solver/iqp.py | OptSolverIQP.solve | def solve(self,problem):
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problem : Object
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"""
Solves optimization problem.
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----------
problem : Object
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ttinoco/OPTALG | optalg/lin_solver/umfpack.py | LinSolverUMFPACK.factorize | def factorize(self, A):
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Parameters
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A : matrix
For symmetric systems, should contain only lower diagonal part.
"""
A = csc_matrix(A)
if self.prop == self.SYMMETRIC:
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Factorizes A.
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A : matrix
For symmetric systems, should contain only lower diagonal part.
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driftx/Telephus | telephus/pool.py | CassandraPoolReconnectorFactory.retry | def retry(self):
"""
Retry this factory's connection. It is assumed that a previous
connection was attempted and failed- either before or after a
successful connection.
"""
if self.connector is None:
raise ValueError("No connector to retry")
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Retry this factory's connection. It is assumed that a previous
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driftx/Telephus | telephus/pool.py | CassandraPoolReconnectorFactory.prep_connection | def prep_connection(self, creds=None, keyspace=None, node_auto_discovery=True):
"""
Do login and set_keyspace tasks as necessary, and also check this
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driftx/Telephus | telephus/pool.py | CassandraPoolReconnectorFactory.my_pick_non_system_keyspace | def my_pick_non_system_keyspace(self):
"""
Find a keyspace in the cluster which is not 'system', for the purpose
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"""
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... | python | def my_pick_non_system_keyspace(self):
"""
Find a keyspace in the cluster which is not 'system', for the purpose
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"""
d = self.my_describe_keyspaces()
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driftx/Telephus | telephus/pool.py | CassandraPoolReconnectorFactory.finish_and_die | def finish_and_die(self):
"""
If there is a request pending, let it finish and be handled, then
disconnect and die. If not, cancel any pending queue requests and
just die.
"""
self.logstate('finish_and_die')
self.stop_working_on_queue()
if self.jobphase !=... | python | def finish_and_die(self):
"""
If there is a request pending, let it finish and be handled, then
disconnect and die. If not, cancel any pending queue requests and
just die.
"""
self.logstate('finish_and_die')
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driftx/Telephus | telephus/pool.py | CassandraClusterPool.add_connection_score | def add_connection_score(self, node):
"""
Return a numeric value that determines this node's score for adding
a new connection. A negative value indicates that no connections
should be made to this node for at least that number of seconds.
A value of -inf indicates no connections... | python | def add_connection_score(self, node):
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Return a numeric value that determines this node's score for adding
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driftx/Telephus | telephus/pool.py | CassandraClusterPool.adjustPoolSize | def adjustPoolSize(self, newsize):
"""
Change the target pool size. If we have too many connections already,
ask some to finish what they're doing and die (preferring to kill
connections to the node that already has the most connections). If
we have too few, create more.
... | python | def adjustPoolSize(self, newsize):
"""
Change the target pool size. If we have too many connections already,
ask some to finish what they're doing and die (preferring to kill
connections to the node that already has the most connections). If
we have too few, create more.
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driftx/Telephus | telephus/pool.py | CassandraClusterPool.fill_pool | def fill_pool(self):
"""
Add connections as necessary to meet the target pool size. If there
are no nodes to connect to (because we maxed out connections-per-node
on all active connections and any unconnected nodes have pending
reconnect timers), call the on_insufficient_nodes ca... | python | def fill_pool(self):
"""
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driftx/Telephus | telephus/pool.py | CassandraClusterPool.resubmit | def resubmit(self, req, keyspace, req_d, retries):
"""
Push this request to the front of the line, just to be a jerk.
"""
self.log('resubmitting %s request' % (req.method,))
self.pushRequest_really(req, keyspace, req_d, retries)
try:
self.request_queue.pending... | python | def resubmit(self, req, keyspace, req_d, retries):
"""
Push this request to the front of the line, just to be a jerk.
"""
self.log('resubmitting %s request' % (req.method,))
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driftx/Telephus | telephus/pool.py | CassandraClusterPool.set_keyspace | def set_keyspace(self, keyspace):
"""
Change the keyspace which will be used for subsequent requests to this
CassandraClusterPool, and return a Deferred that will fire once it can
be verified that connections can successfully use that keyspace.
If something goes wrong trying to ... | python | def set_keyspace(self, keyspace):
"""
Change the keyspace which will be used for subsequent requests to this
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be verified that connections can successfully use that keyspace.
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driftx/Telephus | telephus/pool.py | CassandraClusterPool.keyspaceConnection | def keyspaceConnection(self, keyspace, consistency=ConsistencyLevel.ONE):
"""
Return a CassandraClient instance which uses this CassandraClusterPool
by way of a CassandraKeyspaceConnection, so that all requests made
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pre-commit/pre-commit-mirror-maker | pre_commit_mirror_maker/main.py | split_by_commas | def split_by_commas(maybe_s: str) -> Tuple[str, ...]:
"""Split a string by commas, but allow escaped commas.
- If maybe_s is falsey, returns an empty tuple
- Ignore backslashed commas
"""
if not maybe_s:
return ()
parts: List[str] = []
split_by_backslash = maybe_s.split(r'\,')
fo... | python | def split_by_commas(maybe_s: str) -> Tuple[str, ...]:
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.login | def login(self, auth_request):
"""
Parameters:
- auth_request
"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.set_keyspace | def set_keyspace(self, keyspace):
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.get | def get(self, key, column_path, consistency_level):
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.get_slice | def get_slice(self, key, column_parent, predicate, consistency_level):
"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.get_count | def get_count(self, key, column_parent, predicate, consistency_level):
"""
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<code>ColumnFamily</code> and optionally <code>SuperColumn</code>.
Parameters:
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... | python | def get_count(self, key, column_parent, predicate, consistency_level):
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.multiget_slice | def multiget_slice(self, keys, column_parent, predicate, consistency_level):
"""
Performs a get_slice for column_parent and predicate for the given keys in parallel.
Parameters:
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- column_parent
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- consistency_level
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self._seqid += 1
d = self._reqs[self._... | python | def multiget_slice(self, keys, column_parent, predicate, consistency_level):
"""
Performs a get_slice for column_parent and predicate for the given keys in parallel.
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- predicate
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.multiget_count | def multiget_count(self, keys, column_parent, predicate, consistency_level):
"""
Perform a get_count in parallel on the given list<binary> keys. The return value maps keys to the count found.
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.get_range_slices | def get_range_slices(self, column_parent, predicate, range, consistency_level):
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Parameters:
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- predicate
- range
- consistency_level
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferr... | python | def get_range_slices(self, column_parent, predicate, range, consistency_level):
"""
returns a subset of columns for a contiguous range of keys.
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- predicate
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- consistency_level
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.get_paged_slice | def get_paged_slice(self, column_family, range, start_column, consistency_level):
"""
returns a range of columns, wrapping to the next rows if necessary to collect max_results.
Parameters:
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- range
- start_column
- consistency_level
"""
self._seqid += 1
d = se... | python | def get_paged_slice(self, column_family, range, start_column, consistency_level):
"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.get_indexed_slices | def get_indexed_slices(self, column_parent, index_clause, column_predicate, consistency_level):
"""
Returns the subset of columns specified in SlicePredicate for the rows matching the IndexClause
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Parameters:
- column_parent
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.insert | def insert(self, key, column_parent, column, consistency_level):
"""
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Parameters:
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- column_parent
- column
- consistency_level
"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.add | def add(self, key, column_parent, column, consistency_level):
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Parameters:
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- column_parent
- column
- consistency_level
"""
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"""
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- column
- consistency_level
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.remove | def remove(self, key, column_path, timestamp, consistency_level):
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.remove_counter | def remove_counter(self, key, path, consistency_level):
"""
Remove a counter at the specified location.
Note that counters have limited support for deletes: if you remove a counter, you must wait to issue any following update
until the delete has reached all the nodes and all of them have been fully com... | python | def remove_counter(self, key, path, consistency_level):
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.batch_mutate | def batch_mutate(self, mutation_map, consistency_level):
"""
Mutate many columns or super columns for many row keys. See also: Mutation.
mutation_map maps key to column family to a list of Mutation objects to take place at that scope.
*
Parameters:
- mutation_map
- consistency_level
... | python | def batch_mutate(self, mutation_map, consistency_level):
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Mutate many columns or super columns for many row keys. See also: Mutation.
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.atomic_batch_mutate | def atomic_batch_mutate(self, mutation_map, consistency_level):
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mutation_map maps key to column family to a list of Mutation objects to take place at that scope.
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.truncate | def truncate(self, cfname):
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"""
Truncate will mark and entire column family as deleted.
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_schema_versions | def describe_schema_versions(self, ):
"""
for each schema version present in the cluster, returns a list of nodes at that version.
hosts that do not respond will be under the key DatabaseDescriptor.INITIAL_VERSION.
the cluster is all on the same version if the size of the map is 1.
"""
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"""
for each schema version present in the cluster, returns a list of nodes at that version.
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_keyspaces | def describe_keyspaces(self, ):
"""
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"""
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"""
list the defined keyspaces in this cluster
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self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_cluster_name | def describe_cluster_name(self, ):
"""
get the cluster name
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_describe_cluster_name()
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"""
get the cluster name
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self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_version | def describe_version(self, ):
"""
get the thrift api version
"""
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self.send_describe_version()
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get the thrift api version
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_ring | def describe_ring(self, keyspace):
"""
get the token ring: a map of ranges to host addresses,
represented as a set of TokenRange instead of a map from range
to list of endpoints, because you can't use Thrift structs as
map keys:
https://issues.apache.org/jira/browse/THRIFT-162
for the same ... | python | def describe_ring(self, keyspace):
"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_token_map | def describe_token_map(self, ):
"""
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https://issues.apache.org/jira/browse/CASSANDRA-4092
"""
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"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_partitioner | def describe_partitioner(self, ):
"""
returns the partitioner used by this cluster
"""
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return d | python | def describe_partitioner(self, ):
"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_snitch | def describe_snitch(self, ):
"""
returns the snitch used by this cluster
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_describe_snitch()
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_keyspace | def describe_keyspace(self, keyspace):
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describe specified keyspace
Parameters:
- keyspace
"""
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describe specified keyspace
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- keyspace
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_splits | def describe_splits(self, cfName, start_token, end_token, keys_per_split):
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experimental API for hadoop/parallel query support.
may change violently and without warning.
returns list of token strings such that first subrange is (list[0], list[1]],
next is (list[1], list[2]], etc.
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"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.trace_next_query | def trace_next_query(self, ):
"""
Enables tracing for the next query in this connection and returns the UUID for that trace session
The next query will be traced idependently of trace probability and the returned UUID can be used to query the trace keyspace
"""
self._seqid += 1
d = self._reqs[se... | python | def trace_next_query(self, ):
"""
Enables tracing for the next query in this connection and returns the UUID for that trace session
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.describe_splits_ex | def describe_splits_ex(self, cfName, start_token, end_token, keys_per_split):
"""
Parameters:
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- start_token
- end_token
- keys_per_split
"""
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"""
Parameters:
- cfName
- start_token
- end_token
- keys_per_split
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self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.system_add_column_family | def system_add_column_family(self, cf_def):
"""
adds a column family. returns the new schema id.
Parameters:
- cf_def
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_system_add_column_family(cf_def)
return d | python | def system_add_column_family(self, cf_def):
"""
adds a column family. returns the new schema id.
Parameters:
- cf_def
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_system_add_column_family(cf_def)
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.system_drop_column_family | def system_drop_column_family(self, column_family):
"""
drops a column family. returns the new schema id.
Parameters:
- column_family
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_system_drop_column_family(column_family)
return d | python | def system_drop_column_family(self, column_family):
"""
drops a column family. returns the new schema id.
Parameters:
- column_family
"""
self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.system_add_keyspace | def system_add_keyspace(self, ks_def):
"""
adds a keyspace and any column families that are part of it. returns the new schema id.
Parameters:
- ks_def
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_system_add_keyspace(ks_def)
return d | python | def system_add_keyspace(self, ks_def):
"""
adds a keyspace and any column families that are part of it. returns the new schema id.
Parameters:
- ks_def
"""
self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.system_drop_keyspace | def system_drop_keyspace(self, keyspace):
"""
drops a keyspace and any column families that are part of it. returns the new schema id.
Parameters:
- keyspace
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_system_drop_keyspace(keyspace)
return d | python | def system_drop_keyspace(self, keyspace):
"""
drops a keyspace and any column families that are part of it. returns the new schema id.
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self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.system_update_keyspace | def system_update_keyspace(self, ks_def):
"""
updates properties of a keyspace. returns the new schema id.
Parameters:
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"""
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.system_update_column_family | def system_update_column_family(self, cf_def):
"""
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Parameters:
- cf_def
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
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return d | python | def system_update_column_family(self, cf_def):
"""
updates properties of a column family. returns the new schema id.
Parameters:
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self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.execute_cql_query | def execute_cql_query(self, query, compression):
"""
Executes a CQL (Cassandra Query Language) statement and returns a
CqlResult containing the results.
Parameters:
- query
- compression
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_execute_cql_... | python | def execute_cql_query(self, query, compression):
"""
Executes a CQL (Cassandra Query Language) statement and returns a
CqlResult containing the results.
Parameters:
- query
- compression
"""
self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.execute_cql3_query | def execute_cql3_query(self, query, compression, consistency):
"""
Parameters:
- query
- compression
- consistency
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
self.send_execute_cql3_query(query, compression, consistency)
return d | python | def execute_cql3_query(self, query, compression, consistency):
"""
Parameters:
- query
- compression
- consistency
"""
self._seqid += 1
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self.send_execute_cql3_query(query, compression, consistency)
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.prepare_cql_query | def prepare_cql_query(self, query, compression):
"""
Prepare a CQL (Cassandra Query Language) statement by compiling and returning
- the type of CQL statement
- an id token of the compiled CQL stored on the server side.
- a count of the discovered bound markers in the statement
Parameters:
... | python | def prepare_cql_query(self, query, compression):
"""
Prepare a CQL (Cassandra Query Language) statement by compiling and returning
- the type of CQL statement
- an id token of the compiled CQL stored on the server side.
- a count of the discovered bound markers in the statement
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.prepare_cql3_query | def prepare_cql3_query(self, query, compression):
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.execute_prepared_cql_query | def execute_prepared_cql_query(self, itemId, values):
"""
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Parameters:
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- values
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self._seqid += 1
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.execute_prepared_cql3_query | def execute_prepared_cql3_query(self, itemId, values, consistency):
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driftx/Telephus | telephus/cassandra/Cassandra.py | Client.set_cql_version | def set_cql_version(self, version):
"""
@deprecated This is now a no-op. Please use the CQL3 specific methods instead.
Parameters:
- version
"""
self._seqid += 1
d = self._reqs[self._seqid] = defer.Deferred()
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"""
@deprecated This is now a no-op. Please use the CQL3 specific methods instead.
Parameters:
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"""
self._seqid += 1
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ttinoco/OPTALG | optalg/lin_solver/__init__.py | new_linsolver | def new_linsolver(name,prop):
"""
Creates a linear solver.
Parameters
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name : string
prop : string
Returns
-------
solver : :class:`LinSolver <optalg.lin_solver.LinSolver>`
"""
if name == 'mumps':
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elif name == 'supe... | python | def new_linsolver(name,prop):
"""
Creates a linear solver.
Parameters
----------
name : string
prop : string
Returns
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solver : :class:`LinSolver <optalg.lin_solver.LinSolver>`
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ttinoco/OPTALG | optalg/opt_solver/problem.py | cast_problem | def cast_problem(problem):
"""
Casts problem object with known interface as OptProblem.
Parameters
----------
problem : Object
"""
# Optproblem
if isinstance(problem,OptProblem):
return problem
# Other
else:
# Type Base
if (not hasattr(... | python | def cast_problem(problem):
"""
Casts problem object with known interface as OptProblem.
Parameters
----------
problem : Object
"""
# Optproblem
if isinstance(problem,OptProblem):
return problem
# Other
else:
# Type Base
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ttinoco/OPTALG | optalg/opt_solver/problem.py | create_problem_from_type_base | def create_problem_from_type_base(problem):
"""
Creates OptProblem from type-base problem.
Parameters
----------
problem : Object
"""
p = OptProblem()
# Init attributes
p.phi = problem.phi
p.gphi = problem.gphi
p.Hphi = problem.Hphi
p.A = problem.A
p.b = problem.... | python | def create_problem_from_type_base(problem):
"""
Creates OptProblem from type-base problem.
Parameters
----------
problem : Object
"""
p = OptProblem()
# Init attributes
p.phi = problem.phi
p.gphi = problem.gphi
p.Hphi = problem.Hphi
p.A = problem.A
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ttinoco/OPTALG | optalg/opt_solver/problem.py | create_problem_from_type_A | def create_problem_from_type_A(problem):
"""
Creates OptProblem from type-A problem.
Parameters
----------
problem : Object
"""
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"""
Creates OptProblem from type-A problem.
Parameters
----------
problem : Object
"""
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ttinoco/OPTALG | optalg/opt_solver/problem.py | OptProblem.recover_dual_variables | def recover_dual_variables(self,lam,nu,mu,pi):
"""
Recovers dual variables for original problem.
Parameters
----------
lam : ndarray
nu : ndarray
mu : ndarray
pi : ndarray
"""
return lam,nu,mu,pi | python | def recover_dual_variables(self,lam,nu,mu,pi):
"""
Recovers dual variables for original problem.
Parameters
----------
lam : ndarray
nu : ndarray
mu : ndarray
pi : ndarray
"""
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ttinoco/OPTALG | optalg/opt_solver/problem.py | OptProblem.get_num_primal_variables | def get_num_primal_variables(self):
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-------
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"""
Gets number of primal variables.
Returns
-------
num : int
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if self.x is not None:
return self.x.size
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ttinoco/OPTALG | optalg/opt_solver/opt_solver.py | OptSolver.get_dual_variables | def get_dual_variables(self):
"""
Gets dual variables.
Returns
-------
lam : vector
nu : vector
mu : vector
pi : vector
"""
if self.problem:
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... | python | def get_dual_variables(self):
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Gets dual variables.
Returns
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lam : vector
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pi : vector
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ttinoco/OPTALG | optalg/opt_solver/opt_solver.py | OptSolver.get_results | def get_results(self):
"""
Gets results.
Returns
-------
results : dictionary
"""
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"""
Gets results.
Returns
-------
results : dictionary
"""
return {'status': self.status,
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'k': self.k,
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ttinoco/OPTALG | optalg/opt_solver/opt_solver.py | OptSolver.line_search | def line_search(self,x,p,F,GradF,func,smax=np.inf,maxiter=40):
"""
Finds steplength along search direction p that
satisfies the strong Wolfe conditions.
Parameters
----------
x : current point (ndarray)
p : search direction (ndarray)
F : function... | python | def line_search(self,x,p,F,GradF,func,smax=np.inf,maxiter=40):
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Finds steplength along search direction p that
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ttinoco/OPTALG | optalg/opt_solver/opt_solver.py | OptSolver.reset | def reset(self):
"""
Resets solver data.
"""
self.k = 0.
self.x = np.zeros(0)
self.lam = np.zeros(0)
self.nu = np.zeros(0)
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self.pi = np.zeros(0)
self.status = self.STATUS_UNKNOWN
self.error_msg = ''
... | python | def reset(self):
"""
Resets solver data.
"""
self.k = 0.
self.x = np.zeros(0)
self.lam = np.zeros(0)
self.nu = np.zeros(0)
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ttinoco/OPTALG | optalg/opt_solver/opt_solver.py | OptSolver.set_parameters | def set_parameters(self,parameters):
"""
Sets solver parameters.
Parameters
----------
parameters : dict
"""
for key,value in list(parameters.items()):
if key in self.parameters:
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"""
Sets solver parameters.
Parameters
----------
parameters : dict
"""
for key,value in list(parameters.items()):
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ttinoco/OPTALG | optalg/lin_solver/lin_solver.py | LinSolver.factorize_and_solve | def factorize_and_solve(self, A, b):
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Factorizes A and solves Ax=b.
Returns
-------
x : vector
"""
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x : vector
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ttinoco/OPTALG | optalg/opt_solver/inlp.py | OptSolverINLP.solve | def solve(self,problem):
"""
Solves optimization problem.
Parameters
----------
problem : Object
"""
# Local vars
norm2 = self.norm2
norminf = self.norminf
parameters = self.parameters
# Parameters
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"""
Solves optimization problem.
Parameters
----------
problem : Object
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# Local vars
norm2 = self.norm2
norminf = self.norminf
parameters = self.parameters
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pre-commit/pre-commit-mirror-maker | pre_commit_mirror_maker/make_repo.py | format_files | def format_files(src: str, dest: str, **fmt_vars: str) -> None:
"""Copies all files inside src into dest while formatting the contents
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For example, a file with the following contents:
{foo} bar {baz}
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ttinoco/OPTALG | optalg/lin_solver/mumps.py | LinSolverMUMPS.analyze | def analyze(self,A):
"""
Analyzes structure of A.
Parameters
----------
A : matrix
For symmetric systems, should contain only lower diagonal part.
"""
A = coo_matrix(A)
self.mumps.set_shape(A.shape[0])
self.mumps.set... | python | def analyze(self,A):
"""
Analyzes structure of A.
Parameters
----------
A : matrix
For symmetric systems, should contain only lower diagonal part.
"""
A = coo_matrix(A)
self.mumps.set_shape(A.shape[0])
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ttinoco/OPTALG | optalg/lin_solver/mumps.py | LinSolverMUMPS.factorize | def factorize(self,A):
"""
Factorizes A.
Parameters
----------
A : matrix
For symmetric systems, should contain only lower diagonal part.
"""
A = coo_matrix(A)
self.mumps.set_centralized_assembled_values(A.data)
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"""
Factorizes A.
Parameters
----------
A : matrix
For symmetric systems, should contain only lower diagonal part.
"""
A = coo_matrix(A)
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ttinoco/OPTALG | optalg/lin_solver/mumps.py | LinSolverMUMPS.solve | def solve(self,b):
"""
Solves system Ax=b.
Parameters
----------
b : ndarray
Returns
-------
x : ndarray
"""
x = b.copy()
self.mumps.set_rhs(x)
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return x | python | def solve(self,b):
"""
Solves system Ax=b.
Parameters
----------
b : ndarray
Returns
-------
x : ndarray
"""
x = b.copy()
self.mumps.set_rhs(x)
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ttinoco/OPTALG | optalg/lin_solver/mumps.py | LinSolverMUMPS.factorize_and_solve | def factorize_and_solve(self,A,b):
"""
Factorizes A and sovles Ax=b.
Parameters
----------
A : matrix
b : ndarray
Returns
-------
x : ndarray
"""
A = coo_matrix(A)
x = b.copy()
self.mumps.set_centralized_assemble... | python | def factorize_and_solve(self,A,b):
"""
Factorizes A and sovles Ax=b.
Parameters
----------
A : matrix
b : ndarray
Returns
-------
x : ndarray
"""
A = coo_matrix(A)
x = b.copy()
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | spsolve | def spsolve(A, b, comm=None):
"""Sparse solve A\b."""
assert A.dtype == 'd' and b.dtype == 'd', "Only double precision supported."
with DMumpsContext(par=1, sym=0, comm=comm) as ctx:
if ctx.myid == 0:
# Set the sparse matrix -- only necessary on
ctx.set_centralized_sparse(A.... | python | def spsolve(A, b, comm=None):
"""Sparse solve A\b."""
assert A.dtype == 'd' and b.dtype == 'd', "Only double precision supported."
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_centralized_sparse | def set_centralized_sparse(self, A):
"""Set assembled matrix on processor 0.
Parameters
----------
A : `scipy.sparse.coo_matrix`
Sparse matrices of other formats will be converted to
COOrdinate form.
"""
if self.myid != 0:
return
... | python | def set_centralized_sparse(self, A):
"""Set assembled matrix on processor 0.
Parameters
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A : `scipy.sparse.coo_matrix`
Sparse matrices of other formats will be converted to
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if self.myid != 0:
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_centralized_assembled | def set_centralized_assembled(self, irn, jcn, a):
"""Set assembled matrix on processor 0.
The row and column indices (irn & jcn) should be one based.
"""
self.set_centralized_assembled_rows_cols(irn, jcn)
self.set_centralized_assembled_values(a) | python | def set_centralized_assembled(self, irn, jcn, a):
"""Set assembled matrix on processor 0.
The row and column indices (irn & jcn) should be one based.
"""
self.set_centralized_assembled_rows_cols(irn, jcn)
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_centralized_assembled_rows_cols | def set_centralized_assembled_rows_cols(self, irn, jcn):
"""Set assembled matrix indices on processor 0.
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"""
if self.myid != 0:
return
assert irn.size == jcn.size
self._refs.update(irn=irn, jcn=jcn)
... | python | def set_centralized_assembled_rows_cols(self, irn, jcn):
"""Set assembled matrix indices on processor 0.
The row and column indices (irn & jcn) should be one based.
"""
if self.myid != 0:
return
assert irn.size == jcn.size
self._refs.update(irn=irn, jcn=jcn)
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_centralized_assembled_values | def set_centralized_assembled_values(self, a):
"""Set assembled matrix values on processor 0."""
if self.myid != 0:
return
assert a.size == self.id.nz
self._refs.update(a=a)
self.id.a = self.cast_array(a) | python | def set_centralized_assembled_values(self, a):
"""Set assembled matrix values on processor 0."""
if self.myid != 0:
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assert a.size == self.id.nz
self._refs.update(a=a)
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_distributed_assembled | def set_distributed_assembled(self, irn_loc, jcn_loc, a_loc):
"""Set the distributed assembled matrix.
Distributed assembled matrices require setting icntl(18) != 0.
"""
self.set_distributed_assembled_rows_cols(irn_loc, jcn_loc)
self.set_distributed_assembled_values(a_loc) | python | def set_distributed_assembled(self, irn_loc, jcn_loc, a_loc):
"""Set the distributed assembled matrix.
Distributed assembled matrices require setting icntl(18) != 0.
"""
self.set_distributed_assembled_rows_cols(irn_loc, jcn_loc)
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_distributed_assembled_rows_cols | def set_distributed_assembled_rows_cols(self, irn_loc, jcn_loc):
"""Set the distributed assembled matrix row & column numbers.
Distributed assembled matrices require setting icntl(18) != 0.
"""
assert irn_loc.size == jcn_loc.size
self._refs.update(irn_loc=irn_loc, jcn_loc=jcn_l... | python | def set_distributed_assembled_rows_cols(self, irn_loc, jcn_loc):
"""Set the distributed assembled matrix row & column numbers.
Distributed assembled matrices require setting icntl(18) != 0.
"""
assert irn_loc.size == jcn_loc.size
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_distributed_assembled_values | def set_distributed_assembled_values(self, a_loc):
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assert a_loc.size == self._refs['irn_loc'].size
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self.id.a_loc = self.cast_... | python | def set_distributed_assembled_values(self, a_loc):
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assert a_loc.size == self._refs['irn_loc'].size
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_rhs | def set_rhs(self, rhs):
"""Set the right hand side. This matrix will be modified in place."""
assert rhs.size == self.id.n
self._refs.update(rhs=rhs)
self.id.rhs = self.cast_array(rhs) | python | def set_rhs(self, rhs):
"""Set the right hand side. This matrix will be modified in place."""
assert rhs.size == self.id.n
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.set_silent | def set_silent(self):
"""Silence most messages."""
self.set_icntl(1, -1) # output stream for error msgs
self.set_icntl(2, -1) # otuput stream for diagnostic msgs
self.set_icntl(3, -1) # output stream for global info
self.set_icntl(4, 0) | python | def set_silent(self):
"""Silence most messages."""
self.set_icntl(1, -1) # output stream for error msgs
self.set_icntl(2, -1) # otuput stream for diagnostic msgs
self.set_icntl(3, -1) # output stream for global info
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.destroy | def destroy(self):
"""Delete the MUMPS context and release all array references."""
if self.id is not None and self._mumps_c is not None:
self.id.job = -2 # JOB_END
self._mumps_c(self.id)
self.id = None
self._refs = None | python | def destroy(self):
"""Delete the MUMPS context and release all array references."""
if self.id is not None and self._mumps_c is not None:
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self._mumps_c(self.id)
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ttinoco/OPTALG | optalg/lin_solver/_mumps/__init__.py | _MumpsBaseContext.mumps | def mumps(self):
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DLR-RM/RAFCON | source/rafcon/core/state_elements/data_flow.py | DataFlow.modify_origin | def modify_origin(self, from_state, from_key):
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DLR-RM/RAFCON | source/rafcon/gui/controllers/utils/editor.py | EditorController.register_actions | def register_actions(self, shortcut_manager):
"""Register callback methods for triggered actions
:param rafcon.gui.shortcut_manager.ShortcutManager shortcut_manager: Shortcut Manager Object holding mappings
between shortcuts and actions.
"""
shortcut_manager.add_callback_for... | python | def register_actions(self, shortcut_manager):
"""Register callback methods for triggered actions
:param rafcon.gui.shortcut_manager.ShortcutManager shortcut_manager: Shortcut Manager Object holding mappings
between shortcuts and actions.
"""
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DLR-RM/RAFCON | source/rafcon/gui/controllers/utils/editor.py | EditorController.code_changed | def code_changed(self, source):
""" Apply checks and adjustments of the TextBuffer and TextView after every change in buffer.
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""" Apply checks and adjustments of the TextBuffer and TextView after every change in buffer.
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DLR-RM/RAFCON | source/rafcon/gui/controllers/utils/editor.py | EditorController.apply_clicked | def apply_clicked(self, button):
"""Triggered when the Apply-Shortcut in the editor is triggered.
"""
if isinstance(self.model.state, LibraryState):
return
self.set_script_text(self.view.get_text()) | python | def apply_clicked(self, button):
"""Triggered when the Apply-Shortcut in the editor is triggered.
"""
if isinstance(self.model.state, LibraryState):
return
self.set_script_text(self.view.get_text()) | [
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DLR-RM/RAFCON | source/rafcon/gui/views/utils/editor.py | EditorView.set_text | def set_text(self, text):
""" The method insert text into the text buffer of the text view and preserves the cursor location.
:param str text: which is insert into the text buffer.
:return:
"""
line_number, line_offset = self.get_cursor_position()
self.get_buffer().set_t... | python | def set_text(self, text):
""" The method insert text into the text buffer of the text view and preserves the cursor location.
:param str text: which is insert into the text buffer.
:return:
"""
line_number, line_offset = self.get_cursor_position()
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DLR-RM/RAFCON | source/rafcon/gui/views/utils/editor.py | EditorView.set_enabled | def set_enabled(self, on, text=None):
""" Set the default input or deactivated (disabled) style scheme
The method triggers the signal 'changed' by using set_text. Therefore, the method use the while_in_set_enabled
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""" Set the default input or deactivated (disabled) style scheme
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DLR-RM/RAFCON | share/examples/plugins/templates/hooks.py | pre_init | def pre_init():
"""
The pre_init function of the plugin. Here rafcon-classes can be extended/monkey-patched or completely substituted.
A example is given with the rafcon_execution_hooks_plugin.
:return:
"""
logger.info("Run pre-initiation hook of {} plugin.".format(__file__.split(os.path.sep)[-... | python | def pre_init():
"""
The pre_init function of the plugin. Here rafcon-classes can be extended/monkey-patched or completely substituted.
A example is given with the rafcon_execution_hooks_plugin.
:return:
"""
logger.info("Run pre-initiation hook of {} plugin.".format(__file__.split(os.path.sep)[-... | [
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DLR-RM/RAFCON | share/examples/plugins/templates/hooks.py | post_init | def post_init(setup_config):
"""
The post_init function of the plugin. Here observer can be registered to the observables and other pre-init
functionality of the plugin should be triggered. A simple example is given with the rafcon_execution_hooks_plugin.
A complex example is given with the rafcon_monit... | python | def post_init(setup_config):
"""
The post_init function of the plugin. Here observer can be registered to the observables and other pre-init
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DLR-RM/RAFCON | source/rafcon/gui/models/selection.py | reduce_to_parent_states | def reduce_to_parent_states(models):
"""Remove all models of states that have a state model with parent relation in the list
The function filters the list of models, so that for no model in the list, one of it (grand-)parents is also in
the list. E.g. if the input models consists of a hierarchy state with ... | python | def reduce_to_parent_states(models):
"""Remove all models of states that have a state model with parent relation in the list
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DLR-RM/RAFCON | source/rafcon/gui/models/selection.py | updates_selection | def updates_selection(update_selection):
""" Decorator indicating that the decorated method could change the selection"""
def handle_update(selection, *args, **kwargs):
"""Check for changes in the selection
If the selection is changed by the decorated method, the internal core element lists are... | python | def updates_selection(update_selection):
""" Decorator indicating that the decorated method could change the selection"""
def handle_update(selection, *args, **kwargs):
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DLR-RM/RAFCON | source/rafcon/gui/models/selection.py | extend_selection | def extend_selection():
"""Checks is the selection is to be extended
The selection is to be extended, if a special modifier key (typically <Ctrl>) is being pressed.
:return: If to extend the selection
:rtype: True
"""
from rafcon.gui.singleton import main_window_controller
currently_presse... | python | def extend_selection():
"""Checks is the selection is to be extended
The selection is to be extended, if a special modifier key (typically <Ctrl>) is being pressed.
:return: If to extend the selection
:rtype: True
"""
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DLR-RM/RAFCON | source/rafcon/gui/models/selection.py | Selection._check_model_types | def _check_model_types(self, models):
""" Check types of passed models for correctness and in case raise exception
:rtype: set
:returns: set of models that are valid for the class"""
if not hasattr(models, "__iter__"):
models = {models}
if not all([isinstance(model, ... | python | def _check_model_types(self, models):
""" Check types of passed models for correctness and in case raise exception
:rtype: set
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if not hasattr(models, "__iter__"):
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DLR-RM/RAFCON | source/rafcon/gui/models/selection.py | Selection.add | def add(self, models):
""" Adds the passed model(s) to the selection"""
if models is None:
return
models = self._check_model_types(models)
self._selected.update(models)
self._selected = reduce_to_parent_states(self._selected) | python | def add(self, models):
""" Adds the passed model(s) to the selection"""
if models is None:
return
models = self._check_model_types(models)
self._selected.update(models)
self._selected = reduce_to_parent_states(self._selected) | [
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