Jupyter
pyprql contains pyprql.magic
, a thin
wrapper of JupySQL
’s SQL IPython magics.
This allows us to run PRQL interactively on Jupyter/IPython.
Check out https://pyprql.readthedocs.io/ for more context.
Installation
pip install pyprql
Usage
When installing pyprql, the duckdb-engine package is also installed with it, so we can start using PRQL immediately to query CSV and Parquet files.
For example, running the example from the JupySQL documentation on IPython:
In [1]: %load_ext pyprql.magic
In [2]: !curl -sL https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv -o penguins.csv
In [3]: %prql duckdb://
In [4]: %prql from `penguins.csv` | take 3
Out[4]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181 3750 MALE
1 Adelie Torgersen 39.5 17.4 186 3800 FEMALE
2 Adelie Torgersen 40.3 18.0 195 3250 FEMALE
In [5]: %%prql
...: from `penguins.csv`
...: filter bill_length_mm > 40
...: take 3
...:
...:
Out[5]:
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 40.3 18.0 195 3250 FEMALE
1 Adelie Torgersen 42.0 20.2 190 4250 None
2 Adelie Torgersen 41.1 17.6 182 3200 FEMALE