SQLDataModel 0.1.2

A data model based on in-memory sqlite

SQLDataModel

SQLDataModel is a speedy & lightweight data model with no external dependencies for quickly fetching and storing your tabular data

Installation

Use the package manager pip to install SQLDataModel.

python -m pip install SQLDataModel

Usage

from SQLDataModel import SQLDataModel

# create a SQLDataModel object from any valid source:
sdm = SQLDataModel.from_csv('data.csv')

# manipulate it
sdm_sliced = sdm[2:7]

# view it as a table
print(sdm)

	country	region	check	total	report date
1	US	West	Yes	2016	2023-08-23 13:11:43
2	US	West	No	1996	2023-08-23 13:11:43
3	US	West	Yes	1296	2023-08-23 13:11:43
4	US	West	No	2392	2023-08-23 13:11:43
5	US	Northeast	Yes	1233	2023-08-23 13:11:43
6	US	Northeast	No	3177	2023-08-23 13:11:43
7	US	Midwest	Yes	1200	2023-08-23 13:11:43
8	US	Midwest	No	2749	2023-08-23 13:11:43
9	US	Midwest	Yes	1551	2023-08-23 13:11:43

# group by columns:
sdm_group = sdm.group_by('region','check')
print(sdm_group)

idx	region	check	count
1	Midwest	Yes	2
2	West	No	2
3	West	Yes	2
4	Midwest	No	1
5	Northeast	No	1
6	Northeast	Yes	1

# loop through it:
for row in sdm.iter_rows():
    print(row)

# or save it for later as csv:
sdm.to_csv('data.csv')

# or to sqlite database:
sdm.to_sql('data', 'sqlite.db')

# and get it back again as a new model:
sdm_new = SQLDataModel.from_sql('select * from data', 'sqlite.db')

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT