Skip to main content

Python library for extract property from data.

Project description

Summary

A Python library for extract property from data.

PyPI package version https://img.shields.io/pypi/pyversions/DataProperty.svg Linux/macOS CI status Windows CI status Test coverage

Installation

pip install DataProperty

Usage

Extract property of data

e.g. Extract a float value property

>>> from dataproperty import DataProperty
>>> DataProperty(-1.1)
data=-1.1, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=1, extra_len=1

e.g. Extract a int value property

>>> from dataproperty import DataProperty
>>> DataProperty(123456789)
data=123456789, type=INTEGER, align=right, ascii_width=9, int_digits=9, decimal_places=0, extra_len=0

e.g. Extract a str (ascii) value property

>>> from dataproperty import DataProperty
>>> DataProperty("sample string")
data=sample string, type=STRING, align=left, length=13, ascii_width=13, extra_len=0

e.g. Extract a str (multi-byte) value property

>>> import six
>>> from dataproperty import DataProperty
>>> six.text_type(DataProperty("吾輩は猫である"))
data=吾輩は猫である, type=STRING, align=left, length=7, ascii_width=14, extra_len=0

e.g. Extract a time (datetime) value property

>>> import datetime
>>> from dataproperty import DataProperty
>>> DataProperty(datetime.datetime(2017, 1, 1, 0, 0, 0))
data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0

e.g. Extract a bool value property

>>> from dataproperty import DataProperty
>>> DataProperty(True)
data=True, type=BOOL, align=left, ascii_width=4, extra_len=0

Extract data property for each element from a matrix

DataPropertyExtractor.to_dp_matrix method returns a matrix of DataProperty instances from a data matrix. An example data set and the result are as follows:

Sample Code:
import datetime
from dataproperty import DataPropertyExtractor

dp_extractor = DataPropertyExtractor()
dt = datetime.datetime(2017, 1, 1, 0, 0, 0)
inf = float("inf")
nan = float("nan")

dp_matrix = dp_extractor.to_dp_matrix([
    [1, 1.1, "aa", 1, 1, True, inf, nan, dt],
    [2, 2.2, "bbb", 2.2, 2.2, False, "inf", "nan", dt],
    [3, 3.33, "cccc", -3, "ccc", "true", inf, "NAN", "2017-01-01T01:23:45+0900"],
])

for row, dp_list in enumerate(dp_matrix):
    for col, dp in enumerate(dp_list):
        print("row={:d}, col={:d}, {}".format(row, col, str(dp)))
Output:
row=0, col=0, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=0, col=1, data=1.1, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=0, col=2, data=aa, type=STRING, align=left, ascii_width=2, length=2, extra_len=0
row=0, col=3, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=0, col=4, data=1, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=0, col=5, data=True, type=BOOL, align=left, ascii_width=4, extra_len=0
row=0, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
row=0, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
row=0, col=8, data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0
row=1, col=0, data=2, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=1, col=1, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=1, col=2, data=bbb, type=STRING, align=left, ascii_width=3, length=3, extra_len=0
row=1, col=3, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=1, col=4, data=2.2, type=REAL_NUMBER, align=right, ascii_width=3, int_digits=1, decimal_places=1, extra_len=0
row=1, col=5, data=False, type=BOOL, align=left, ascii_width=5, extra_len=0
row=1, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
row=1, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
row=1, col=8, data=2017-01-01 00:00:00, type=DATETIME, align=left, ascii_width=19, extra_len=0
row=2, col=0, data=3, type=INTEGER, align=right, ascii_width=1, int_digits=1, decimal_places=0, extra_len=0
row=2, col=1, data=3.33, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=2, extra_len=0
row=2, col=2, data=cccc, type=STRING, align=left, ascii_width=4, length=4, extra_len=0
row=2, col=3, data=-3, type=INTEGER, align=right, ascii_width=2, int_digits=1, decimal_places=0, extra_len=1
row=2, col=4, data=ccc, type=STRING, align=left, ascii_width=3, length=3, extra_len=0
row=2, col=5, data=True, type=BOOL, align=left, ascii_width=4, extra_len=0
row=2, col=6, data=Infinity, type=INFINITY, align=left, ascii_width=8, extra_len=0
row=2, col=7, data=NaN, type=NAN, align=left, ascii_width=3, extra_len=0
row=2, col=8, data=2017-01-01T01:23:45+0900, type=STRING, align=left, ascii_width=24, length=24, extra_len=0

Full example source code can be found at examples/py/to_dp_matrix.py

Extract property for each column from a matrix

DataPropertyExtractor.to_column_dp_list method returns a list of DataProperty instances from a data matrix. The list represents the properties for each column. An example data set and the result are as follows:

Example data set and result are as follows:

Sample Code:
import datetime
from dataproperty import DataPropertyExtractor

dp_extractor = DataPropertyExtractor()
dt = datetime.datetime(2017, 1, 1, 0, 0, 0)
inf = float("inf")
nan = float("nan")

data_matrix = [
    [1, 1.1,  "aa",   1,   1,     True,   inf,   nan,   dt],
    [2, 2.2,  "bbb",  2.2, 2.2,   False,  "inf", "nan", dt],
    [3, 3.33, "cccc", -3,  "ccc", "true", inf,   "NAN", "2017-01-01T01:23:45+0900"],
]

dp_extractor.headers = ["int", "float", "str", "num", "mix", "bool", "inf", "nan", "time"]
col_dp_list = dp_extractor.to_column_dp_list(dp_extractor.to_dp_matrix(dp_matrix))

for col_idx, col_dp in enumerate(col_dp_list):
    print(str(col_dp))
Output:
column=0, type=INTEGER, align=right, ascii_width=3, bit_len=2, int_digits=1, decimal_places=0
column=1, type=REAL_NUMBER, align=right, ascii_width=5, int_digits=1, decimal_places=(min=1, max=2)
column=2, type=STRING, align=left, ascii_width=4
column=3, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=(min=0, max=1), extra_len=(min=0, max=1)
column=4, type=STRING, align=left, ascii_width=3, int_digits=1, decimal_places=(min=0, max=1)
column=5, type=BOOL, align=left, ascii_width=5
column=6, type=INFINITY, align=left, ascii_width=8
column=7, type=NAN, align=left, ascii_width=3
column=8, type=STRING, align=left, ascii_width=24

Full example source code can be found at examples/py/to_column_dp_list.py

Dependencies

Python 2.7+ or 3.4+

Optional dependencies

  • logbook
    • Logging using logbook if the package installed

Test dependencies

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

DataProperty-0.42.3.tar.gz (30.5 kB view hashes)

Uploaded Source

Built Distribution

DataProperty-0.42.3-py2.py3-none-any.whl (24.5 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page