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ANApy is a universal data manipulation tool for handling all major forms of data on the fly

What is Anapy?

Anapy is a compact data serialization and manipulation tool. It is still WIP though the intention is to have a lightweight tool that can read and write to multiple data formats, as well as perform base data manipulation tasks for Data specialists who need a quick solution for a simple problem.

Reading Data

ANApy has a basic reader that currently supports csv, json, yaml and sql-inserts.

from anapy import data_reader as dr
data = dr.DataReader(data='data.csv', format='csv').read(delim=',')
data = dr.DataReader(data='data.json', format='json')
data = dr.DataReader(data='data.yaml', format='yaml')
data = dr.DataReader(data='data.sql', format='sql').read(sql_create=False)

Writing Data

Once data has been consumed, it can be written in various formats:

import anapy.data_writer as dw
dw.write_csv(file='data.csv', data=data, quoting='minimal', header=True)
dw.write_yaml(file='data.yaml', data=data)
dw.write_json(file='data.json', data=data, allow_nan=True, sort_keys=False)

Stashing Data

ANApy is currently having a stashing process developed designed to temporarily store and work with data on a columnar level. This means general querying of data to new subsets should be pretty quick and efficient. Calculations are still a wip.

Multiple tables can be created within the ANApy columnar data structure system.

import anapy.data_reader as dr
import anapy.data_writer as dw
from anapy.stash import StashTable


def main():
    data = dr.DataReader(data='data.csv', format='csv').read()

    # stashing datasets to ANApy tables
    table = StashTable(data=data, table='basic_csv')
    table.save()

    # useful features for querying data
    col_names = table.col_names()
    first_row = table.row(index=0)
    first_col = table.col(key='email')

    # writing subsets of data to file
    females = table.get(key='gender', value='Female', operator='==')
    dw.write_csv(data=females, file='female_subset.csv')

    # removing tables once complete
    table.un_stash()


if __name__ == '__main__':
    main()