def delete_column(self, identifier: str, column_id: int,
datastore: Datastore) -> VizualApiResult:
"""Delete a column in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown.
Parameters
----------
identifier: string
Unique dataset identifier
column_id: int
Unique column identifier
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Confirm that the column actually exists and convert the column_identifier to
# a position in the schema (usually ==, but not guaranteed)
col_index = get_index_for_column(dataset, column_id)
command = {"id": "deleteColumn", "column": col_index}
response = mimir.vizualScript(dataset.identifier, command)
return VizualApiResult.from_mimir(response, identifier)
def update_cell(self, identifier, column_id, row_id, value, datastore):
"""Update a cell in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified cell is outside of the current dataset ranges.
Parameters
----------
identifier : string
Unique dataset identifier
column_id: int
Unique column identifier for updated cell
row_id: int
Unique row identifier
value: string
New cell value
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the index of the specified cell column
col_index = get_index_for_column(dataset, column_id)
# Raise exception if row id is not valid
# Create a view for the modified dataset
col_list = []
for i in range(len(dataset.columns)):
col = dataset.columns[i]
if i == col_index:
try:
val_stmt = col.to_sql_value(value)
col_sql = val_stmt + ' ELSE ' + col.name_in_rdb + ' END '
except ValueError:
col_sql = '\'' + str(
value
) + '\' ELSE CAST({{input}}.' + col.name_in_rdb + ' AS varchar) END '
rid_sql = MIMIR_ROWID_COL.to_sql_value(row_id)
stmt = 'CASE WHEN ' + ROW_ID + ' = ' + rid_sql + ' THEN '
stmt += col_sql
stmt += 'AS ' + col.name_in_rdb
col_list.append(stmt)
else:
col_list.append(col.name_in_rdb)
sql = 'SELECT ' + ','.join(
col_list) + ' FROM ' + dataset.table_name + ';'
view_name, dependencies = mimir.createView(dataset.table_name, sql)
# Store updated dataset information with new identifier
ds = datastore.register_dataset(table_name=view_name,
columns=dataset.columns,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return VizualApiResult(ds)
def filter_columns(self, identifier, columns, names):
"""Dataset projection operator. Returns a copy of the dataset with the
given identifier that contains only those columns listed in columns.
The list of names contains optional new names for the filtered columns.
A value of None in names indicates that the name of the corresponding
column is not changed.
Returns the number of rows in the dataset and the identifier of the
projected dataset.
Raises ValueError if no dataset with given identifier exists or if any
of the filter columns are unknown.
Parameters
----------
identifier: string
Unique dataset identifier
columns: list(int)
List of column identifier for columns in the result.
names: list(string)
Optional new names for filtered columns.
Returns
-------
int, string
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# The schema of the new dataset only contains the columns in the given
# list. Keep track of their index positions to filter values.
schema = list()
val_filter = list()
for i in range(len(columns)):
col_idx = get_index_for_column(dataset, columns[i])
col = dataset.columns[col_idx]
if not names[i] is None:
schema.append(
DatasetColumn(identifier=col.identifier, name=names[i]))
else:
schema.append(col)
val_filter.append(col_idx)
# Create a list of projected rows
rows = list()
for row in dataset.fetch_rows():
values = list()
for v_idx in val_filter:
values.append(row.values[v_idx])
rows.append(DatasetRow(identifier=row.identifier, values=values))
# Store updated dataset to get new identifier
ds = self.datastore.create_dataset(
columns=schema,
rows=rows,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations.filter_columns(columns))
return len(rows), ds.identifier
def filter_columns(self, identifier: str, columns: List[int],
names: List[str],
datastore: Datastore) -> VizualApiResult:
"""Dataset projection operator. Returns a copy of the dataset with the
given identifier that contains only those columns listed in columns.
The list of names contains optional new names for the filtered columns.
A value of None in names indicates that the name of the corresponding
column is not changed.
Raises ValueError if no dataset with given identifier exists or if any
of the filter columns are unknown.
Parameters
----------
identifier: string
Unique dataset identifier
columns: list(int)
List of column identifier for columns in the result.
names: list(string)
Optional new names for filtered columns.
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# The schema of the new dataset only contains the columns in the given
# list. A column might need to be renamed.
schema = list()
column_mapping = list()
col_list = []
for i in range(len(columns)):
col_idx = get_index_for_column(dataset, columns[i])
col = dataset.columns[col_idx]
if not names[i] is None:
if not is_valid_name(names[i]):
raise ValueError('invalid column name \'' + str(names[i]) +
'\'')
schema.append(
MimirDatasetColumn(identifier=col.identifier,
name_in_dataset=names[i],
name_in_rdb=names[i]))
else:
schema.append(col)
column_mapping.append({
"columns_column": col_idx,
"columns_name": schema[-1].name
})
col_list.append(col.name_in_rdb)
command = {"id": "projection", "columns": column_mapping}
response = mimir.vizualScript(dataset.identifier, command)
return VizualApiResult.from_mimir(response)
def filter_columns(self, identifier, columns, names):
"""Dataset projection operator. Returns a copy of the dataset with the
given identifier that contains only those columns listed in columns.
The list of names contains optional new names for the filtered columns.
A value of None in names indicates that the name of the corresponding
column is not changed.
Returns the number of rows in the dataset and the identifier of the
projected dataset.
Raises ValueError if no dataset with given identifier exists or if any
of the filter columns are unknown.
Parameters
----------
identifier: string
Unique dataset identifier
columns: list(int)
List of column identifier for columns in the result.
names: list(string)
Optional new names for filtered columns.
Returns
-------
int, string
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# The schema of the new dataset only contains the columns in the given
# list. A column might need to be renamed.
schema = list()
col_list = [ROW_ID]
for i in range(len(columns)):
col_idx = get_index_for_column(dataset, columns[i])
col = dataset.columns[col_idx]
if not names[i] is None:
schema.append(
MimirDatasetColumn(identifier=col.identifier,
name_in_dataset=names[i],
name_in_rdb=col.name_in_rdb))
else:
schema.append(col)
col_list.append(col.name_in_rdb)
sql = 'SELECT ' + ','.join(col_list) + ' FROM ' + dataset.table_name
view_name = mimir._mimir.createView(dataset.table_name, sql)
# Store updated dataset information with new identifier
ds = self.datastore.register_dataset(
table_name=view_name,
columns=schema,
row_ids=dataset.row_ids,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations.filter_columns(columns))
return len(dataset.row_ids), ds.identifier
def sort_dataset(self, identifier, columns, reversed):
"""Sort the dataset with the given identifier according to the order by
statement. The order by statement is a pair of lists. The first list
contains the identifier of columns to sort on. The second list contains
boolean flags, one for each entry in columns, indicating whether sort
order is revered for the corresponding column or not.
Returns the number of rows in the database and the identifier of the
sorted dataset.
Raises ValueError if no dataset with given identifier exists or if any
of the columns in the order by clause are unknown.
Parameters
----------
identifier: string
Unique dataset identifier
columns: list(int)
List of column identifier for sort columns.
reversed: list(bool)
Flags indicating whether the sort order of the corresponding column
is reveresed.
Returns
-------
int, string
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Fetch the full set of rows
rows = dataset.fetch_rows()
# Sort multiple times, ones for each of the sort columns (in reverse
# order of appearance in the order by clause)
for i in range(len(columns)):
l_idx = len(columns) - (i + 1)
col_id = columns[l_idx]
col_idx = get_index_for_column(dataset, col_id)
reverse = reversed[l_idx]
rows.sort(key=lambda row: row.values[col_idx], reverse=reverse)
# Store updated dataset to get new identifier
ds = self.datastore.create_dataset(
columns=dataset.columns,
rows=rows,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return len(rows), ds.identifier
def move_column(self, identifier, column, position):
"""Move a column within a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown or the target position invalid.
Parameters
----------
identifier: string
Unique dataset identifier
column: int
Unique column identifier
position: int
Target position for the column
Returns
-------
int, string
Number of moved columns (i.e., 1) and identifier of resulting
dataset
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Make sure that position is a valid column index in the new dataset
if position < 0 or position > len(dataset.columns):
raise ValueError('invalid target position \'' + str(position) +
'\'')
# Get index position of column that is being moved
source_idx = get_index_for_column(dataset, column)
# No need to do anything if source position equals target position
if source_idx != position:
columns = list(dataset.columns)
columns.insert(position, columns.pop(source_idx))
rows = dataset.fetch_rows()
for row in rows:
row.values.insert(position, row.values.pop(source_idx))
# Store updated dataset to get new identifier
ds = self.datastore.create_dataset(
columns=columns,
rows=rows,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
else:
return 0, identifier
def move_column(self, identifier, column, position):
"""Move a column within a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown or the target position invalid.
Parameters
----------
identifier: string
Unique dataset identifier
column: int
Unique column identifier
position: int
Target position for the column
Returns
-------
int, string
Number of moved columns (i.e., 1) and identifier of resulting
dataset
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Make sure that position is a valid column index in the new dataset
if position < 0 or position > len(dataset.columns):
raise ValueError('invalid target position \'' + str(position) +
'\'')
# Get index position of column that is being moved
source_idx = get_index_for_column(dataset, column)
# No need to do anything if source position equals target position
if source_idx != position:
# There are no changes to the underlying database. We only need to
# change the column information in the dataset schema.
schema = list(dataset.columns)
schema.insert(position, schema.pop(source_idx))
# Store updated dataset to get new identifier
ds = self.datastore.register_dataset(
table_name=dataset.table_name,
columns=schema,
row_ids=dataset.row_ids,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
else:
return 0, identifier
def rename_column(self, identifier, column, name):
"""Rename column in a given dataset.
Raises ValueError if no dataset with given identifier exists, if the
specified column is unknown, or if the given column name is invalid.
Parameters
----------
identifier : string
Unique dataset identifier
column : int
Unique column identifier
name : string
New column name
Returns
-------
int, string
Number of renamed columns (i.e., 1) and identifier of resulting
dataset
"""
# Raise ValueError if given colum name is invalid
if not is_valid_name(name):
raise ValueError('invalid column name \'' + name + '\'')
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the specified column that is to be renamed and set the column name
# to the new name
schema = list(dataset.columns)
col = schema[get_index_for_column(dataset, column)]
# No need to do anything if the name hasn't changed
if col.name.lower() != name.lower():
# There are no changes to the underlying database. We only need to
# change the column information in the dataset schema.
col.name = name
# Store updated dataset to get new identifier
ds = self.datastore.register_dataset(
table_name=dataset.table_name,
columns=schema,
row_ids=dataset.row_ids,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
else:
return 0, identifier
def update_cell(self, identifier, column, row, value):
"""Update a cell in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified cell is outside of the current dataset ranges.
Parameters
----------
identifier : string
Unique dataset identifier
column : int
Unique column identifier
row : int
Row index for updated cell (starting at 0)
value : string
New cell value
Returns
-------
int, string
Number of updated rows (i.e., 1) and identifier of resulting
dataset
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get column index forst in case it raises an exception
col_idx = get_index_for_column(dataset, column)
# Make sure that row refers a valid row in the dataset
rows = dataset.fetch_rows()
if row < 0 or row >= len(rows):
raise ValueError('invalid cell [' + str(column) + ', ' + str(row) +
']')
# Update the specified cell in the given data array
r = rows[row]
values = list(r.values)
values[col_idx] = value
rows[row] = DatasetRow(r.identifier, values)
# Store updated dataset to get new identifier
ds = self.datastore.create_dataset(
columns=dataset.columns,
rows=rows,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
def rename_column(self, identifier, column, name):
"""Rename column in a given dataset.
Raises ValueError if no dataset with given identifier exists, if the
specified column is unknown, or if the given column name is invalid.
Parameters
----------
identifier: string
Unique dataset identifier
column: int
Unique column identifier
name: string
New column name
Returns
-------
int, string
Number of renamed columns (i.e., 1) and identifier of resulting
dataset
"""
# Raise ValueError if given colum name is invalid
if not is_valid_name(name):
raise ValueError('invalid column name \'' + name + '\'')
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the specified column that is to be renamed and set the column name
# to the new name
col_idx = get_index_for_column(dataset, column)
# Nothing needs to be changed if name does not differ from column name
if dataset.columns[col_idx].name.lower() != name.lower():
columns = list(dataset.columns)
columns[col_idx] = DatasetColumn(columns[col_idx].identifier, name)
# Store updated dataset to get new identifier
ds = self.datastore.create_dataset(
columns=columns,
rows=dataset.fetch_rows(),
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
else:
return 0, identifier
def move_column(self, identifier, column_id, position, datastore):
"""Move a column within a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown or the target position invalid.
Parameters
----------
identifier: string
Unique dataset identifier
column_id: int
Unique column identifier
position: int
Target position for the column
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Make sure that position is a valid column index in the new dataset
if position < 0 or position > len(dataset.columns):
raise ValueError('invalid target position \'' + str(position) +
'\'')
# Get index position of column that is being moved
source_idx = get_index_for_column(dataset, column_id)
# No need to do anything if source position equals target position
if source_idx != position:
# There are no changes to the underlying database. We only need to
# change the column information in the dataset schema.
schema = list(dataset.columns)
schema.insert(position, schema.pop(source_idx))
# Store updated dataset to get new identifier
ds = datastore.register_dataset(table_name=dataset.table_name,
columns=schema,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return VizualApiResult(ds)
else:
return VizualApiResult(dataset)
def move_column(self, identifier: str, column_id: int, position: int,
datastore: Datastore) -> VizualApiResult:
"""Move a column within a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown or the target position invalid.
Parameters
----------
identifier: string
Unique dataset identifier
column_id: int
Unique column identifier
position: int
Target position for the column
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Make sure that position is a valid column index in the new dataset
if position < 0 or position > len(dataset.columns):
raise ValueError('invalid target position \'' + str(position) +
'\'')
# Get index position of column that is being moved
source_idx = get_index_for_column(dataset, column_id)
# No need to do anything if source position equals target position
if source_idx != position:
# Keep the mimir-side schema aligned with the vizier-side schema
command = {
"id": "moveColumn",
"column": source_idx,
"position": position
}
response = mimir.vizualScript(dataset.identifier, command)
return VizualApiResult.from_mimir(response)
else:
return VizualApiResult(dataset)
def delete_column(self, identifier, column):
"""Delete a column in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown.
Parameters
----------
identifier: string
Unique dataset identifier
column: int
Unique column identifier
Returns
-------
int, string
Number of deleted columns (i.e., 1) and identifier of resulting
dataset
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the index of the specified column that is to be deleted.
col_index = get_index_for_column(dataset, column)
# Delete column from schema
schema = list(dataset.columns)
del schema[col_index]
# Create a view for the modified schema
col_list = [ROW_ID]
for col in schema:
col_list.append(col.name_in_rdb)
sql = 'SELECT ' + ','.join(col_list) + ' FROM ' + dataset.table_name
view_name = mimir._mimir.createView(dataset.table_name, sql)
# Store updated dataset information with new identifier
ds = self.datastore.register_dataset(
table_name=view_name,
columns=schema,
row_ids=dataset.row_ids,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
def delete_column(self, identifier, column_id, datastore):
"""Delete a column in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown.
Parameters
----------
identifier: string
Unique dataset identifier
column_id: int
Unique column identifier
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the index of the specified column that is to be deleted.
col_index = get_index_for_column(dataset, column_id)
# Delete column from schema
schema = list(dataset.columns)
del schema[col_index]
# Create a view for the modified schema
col_list = []
for col in schema:
col_list.append(col.name_in_rdb)
sql = 'SELECT ' + ','.join(
col_list) + ' FROM ' + dataset.table_name + ';'
view_name, dependencies = mimir.createView(dataset.table_name, sql)
# Store updated dataset information with new identifier
ds = datastore.register_dataset(table_name=view_name,
columns=schema,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return VizualApiResult(ds)
def delete_column(self, identifier, column):
"""Delete a column in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified column is unknown.
Parameters
----------
identifier: string
Unique dataset identifier
column: int
Unique column identifier
Returns
-------
int, string
Number of deleted columns (i.e., 1) and identifier of resulting
dataset
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the index of the specified column that is to be deleted.
col_index = get_index_for_column(dataset, column)
# Delete column from schema
columns = list(dataset.columns)
del columns[col_index]
# Delete all value for the deleted column
rows = dataset.fetch_rows()
for row in rows:
del row.values[col_index]
# Store updated dataset to get new identifier
ds = self.datastore.create_dataset(
columns=columns,
rows=rows,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
def update_cell(self, identifier: str, column_id: int, row_id: str,
value: str, datastore: Datastore) -> VizualApiResult:
"""Update a cell in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified cell is outside of the current dataset ranges.
Parameters
----------
identifier : string
Unique dataset identifier
column_id: int
Unique column identifier for updated cell
row_id: int
Unique row identifier
value: string
New cell value
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the index of the specified cell column
col_index = get_index_for_column(dataset, column_id)
# Raise exception if row id is not valid
command = {
"id": "updateCell",
"column": col_index,
"row": row_id,
"value": str(value) if value is not None else None
}
response = mimir.vizualScript(dataset.identifier, command)
return VizualApiResult.from_mimir(response)
def rename_column(self, identifier: str, column_id: int, name: str,
datastore: Datastore) -> VizualApiResult:
"""Rename column in a given dataset.
Raises ValueError if no dataset with given identifier exists, if the
specified column is unknown, or if the given column name is invalid.
Parameters
----------
identifier: string
Unique dataset identifier
column_id: int
Unique column identifier
name: string
New column name
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Raise ValueError if given colum name is invalid
if not is_valid_name(name):
raise ValueError('invalid column name \'' + str(name) + '\'')
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the specified column that is to be renamed and set the column name
# to the new name
target_col_index = get_index_for_column(dataset, column_id)
command = {
"id": "renameColumn",
"column": target_col_index,
"name": name
}
response = mimir.vizualScript(dataset.identifier, command)
return VizualApiResult.from_mimir(response)
def update_cell(self, identifier, column, row, value):
"""Update a cell in a given dataset.
Raises ValueError if no dataset with given identifier exists or if the
specified cell is outside of the current dataset ranges.
Parameters
----------
identifier : string
Unique dataset identifier
column : int
Unique column identifier for updated cell (starting at 0)
row : int
Row index for updated cell (starting at 0)
value : string
New cell value
Returns
-------
int, string
Number of updated rows (i.e., 1) and identifier of resulting
dataset
"""
# Get dataset. Raise exception if dataset is unknown
dataset = self.datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the index of the specified cell column
col_index = get_index_for_column(dataset, column)
# Get id of the cell row
row_id = row
# Create a view for the modified dataset
col_list = [ROW_ID]
for i in range(len(dataset.columns)):
col = dataset.columns[i]
if i == col_index:
try:
val_stmt = col.to_sql_value(value)
col_sql = val_stmt + ' ELSE ' + col.name_in_rdb + ' END '
except ValueError:
col_sql = '\'' + str(
value
) + '\' ELSE CAST({{input}}.' + col.name_in_rdb + ' AS varchar) END '
rid_sql = dataset.rowid_column.to_sql_value(row_id)
stmt = 'CASE WHEN ' + ROW_ID + ' = ' + rid_sql + ' THEN '
stmt += col_sql
stmt += 'AS ' + col.name_in_rdb
col_list.append(stmt)
else:
col_list.append(col.name_in_rdb)
sql = 'SELECT ' + ','.join(col_list) + ' FROM ' + dataset.table_name
view_name = mimir._mimir.createView(dataset.table_name, sql)
# Store updated dataset information with new identifier
ds = self.datastore.register_dataset(
table_name=view_name,
columns=dataset.columns,
row_ids=dataset.row_ids,
column_counter=dataset.column_counter,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return 1, ds.identifier
def rename_column(self, identifier, column_id, name, datastore):
"""Rename column in a given dataset.
Raises ValueError if no dataset with given identifier exists, if the
specified column is unknown, or if the given column name is invalid.
Parameters
----------
identifier: string
Unique dataset identifier
column_id: int
Unique column identifier
name: string
New column name
datastore : vizier.datastore.fs.base.FileSystemDatastore
Datastore to retireve and update datasets
Returns
-------
vizier.engine.packages.vizual.api.VizualApiResult
"""
# Raise ValueError if given colum name is invalid
if not is_valid_name(name):
raise ValueError('invalid column name \'' + str(name) + '\'')
# Get dataset. Raise exception if dataset is unknown
dataset = datastore.get_dataset(identifier)
if dataset is None:
raise ValueError('unknown dataset \'' + identifier + '\'')
# Get the specified column that is to be renamed and set the column name
# to the new name
columns = list()
schema = list(dataset.columns)
colIndex = get_index_for_column(dataset, column_id)
col = schema[colIndex]
# No need to do anything if the name hasn't changed
if col.name.lower() != name.lower():
sql = 'SELECT * FROM ' + dataset.table_name
mimirSchema = mimir.getSchema(sql)
# Create list of dataset columns
colSql = ''
idx = 0
for col in mimirSchema:
col_id = len(columns)
name_in_dataset = sanitize_column_name(col['name'].upper())
name_in_rdb = sanitize_column_name(col['name'].upper())
col = MimirDatasetColumn(identifier=col_id,
name_in_dataset=name_in_dataset,
name_in_rdb=name_in_rdb)
if idx == 0:
colSql = name_in_dataset + ' AS ' + name_in_rdb
elif idx == colIndex:
colSql = colSql + ', ' + name_in_dataset + ' AS ' + name
col.name = name
col.name_in_rdb = name
else:
colSql = colSql + ', ' + name_in_dataset + ' AS ' + name_in_rdb
columns.append(col)
idx = idx + 1
# Create view for loaded dataset
sql = 'SELECT ' + colSql + ' FROM {{input}};'
view_name, dependencies = mimir.createView(dataset.table_name, sql)
# There are no changes to the underlying database. We only need to
# change the column information in the dataset schema.
# Store updated dataset to get new identifier
ds = datastore.register_dataset(table_name=view_name,
columns=columns,
row_counter=dataset.row_counter,
annotations=dataset.annotations)
return VizualApiResult(ds)
else:
return VizualApiResult(dataset)
