File size: 2,332 Bytes
2c3c408 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | # query_condition_string.py
#
# LICENSE
#
# The MIT License
#
# Copyright (c) 2021 TileDB, Inc.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# This example creates an array with one string-typed attribute,
# writes sample data to the array, and then prints out a filtered
# dataframe using the TileDB QueryCondition feature.
import string
import numpy as np
import tiledb
def create_array(path):
dom = tiledb.Domain(tiledb.Dim(name="d", domain=(1, 10), tile=1, dtype=np.uint32))
attrs = [tiledb.Attr(name="ascii_attr", dtype="ascii", var=True)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.SparseArray.create(path, schema, overwrite=True)
# create array of strings from a to a..j
attr_data = np.array([string.ascii_lowercase[0:n] for n in range(1, 11)], dtype="O")
with tiledb.open(path, "w") as arr:
arr[np.arange(1, 11)] = {"ascii_attr": attr_data}
def read_array(path, cond):
with tiledb.open(path) as arr:
print("QueryCondition is: ", cond)
res = arr.query(cond=cond)[:]
return res
uri = "query_condition_string"
create_array(uri)
filtered_df1 = read_array(uri, "ascii_attr == 'abcd'")
print(" result: ", filtered_df1)
filtered_df2 = read_array(uri, "ascii_attr > 'abc'")
print(" result: ", filtered_df2)
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