use PRIMARY KEY and UNIQUE in CSV
Project description
csvkey
For a very limited situation such that you don't need performance and want to use CSV as database.
Example
from csvkey import Connection
import pandas as pd
import numpy as np
# prepare DataFrame
data = pd.DataFrame()
data['A'] = pd.Series([1,2,3], dtype='int')
data['B'] = pd.Series([4,5,6], dtype='float32')
data['C'] = pd.Series([7,8,9], dtype='float64')
# register database
conn = Connection()
conn.initialize(data, r'C:\TEST\database.csv',
primary=['A', 'B'],
unique=['C'],
notnull=['C'])
# database.csv and the configuration file (default: csv.conf) are generated in C:\TEST\
# set 'A' and 'B' columns as a primary key
# values in 'C' column must be unique and not NaN
# connect to database.csv
conn.connect(r'C:\TEST\database.csv')
conn.df.dtypes # dtypes are preserved
# change values in conn.df
conn.df.loc[0, 'C'] = 8
conn.commit() # raise ValueError because 8 is not unique
conn.df.loc[0, 'C'] = np.nan
conn.commit() # raise ValueError because NaN is not allowed in 'C'
conn.df.loc[0, 'C'] = -1
conn.commit() # OK
conn.df.loc[2, ['A', 'B']] = [1, 4]
conn.commit() # raise ValueError because primary keys are duplicated
Installation
pip install csvkey
Requirements
pandas
pyyaml
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
csvkey-0.0.3.tar.gz
(2.9 kB
view hashes)
Built Distribution
csvkey-0.0.3-py3-none-any.whl
(4.1 kB
view hashes)