A data model based on in-memory sqlite
Project description
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 the package when its uploaded.
pip install SQLDataModel
Usage
import SQLDataModel
# create a SQLDataModel object from any valid source:
sdm = SQLDataModel.from_csv('world-cup-2022.csv')
# manipulate it
sdm_sliced = sdm.get_rows_at_index_range(1,4)
# loop through it:
for row in sdm_full.iter_rows():
print(row)
# view it as a table
print(sdm)
| team | rank | federation | |
|---|---|---|---|
| 1 | Argentina | 3 | CONMEBOL |
| 2 | Brazil | 1 | CONMEBOL |
| 3 | Ecuador | 44 | CONMEBOL |
| 4 | Uruguay | 14 | CONMEBOL |
| 5 | Belgium | 2 | UEFA |
| 6 | Croatia | 12 | UEFA |
| 7 | Denmark | 10 | UEFA |
| 8 | England | 5 | UEFA |
| 9 | France | 4 | UEFA |
| 10 | Germany | 11 | UEFA |
| 11 | Netherlands | 8 | UEFA |
| 12 | Poland | 26 | UEFA |
| 13 | Portugal | 9 | UEFA |
| 14 | Serbia | 21 | UEFA |
| 15 | Spain | 7 | UEFA |
| 16 | Switzerland | 15 | UEFA |
| 17 | Wales | 19 | UEFA |
# group by columns:
print(sdm.group_by('federation'))
| federation | count | |
|---|---|---|
| 1 | UEFA | 13 |
| 2 | CONMEBOL | 4 |
# or save it for later as csv:
sdm.to_csv('world_cup_22.csv')
# or to sqlite database:
sdm.to_sql('world_cup_22', 'sqlite.db')
# and get it back again as a new model:
sdm_new = SQLDataModel.from_sql('select * from world_cup_22', '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
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