tinytimmy 0.1.4

A simple and easy to use Data Quality (DQ) tool built with Python.

Tiny Timmy

A dead simple and easy to use Data Quality (DQ) tool built for Dataframes and Files with Python.

Tiny Timmy uses the Python bindings for Polars a Rust based DataFrame tool.

Support includes ...

• polars
• pandas
• pyspark
• csv files
• parquet files

Both dataframe and file support. Simply "point and shoot."

Installation

Install Tiny Timmy with pip

pip install tinytimmy

Usage

Create an instance of Tiny Timmy.

• specify source_type
  • polars
  • pandas
  • pyspark
  • csv
  • parquet
• specify either file_path or dataframe

from tinytimmy.tinytim import TinyTim
tm = TinyTim(source_type="csv", file_path="202306-divvy-tripdata.csv")

Then call either the default checks or a custom check.

results = tm.default_checks()
results = tm.run_custom_check(["{SQL filter}", "{SQL filter}"])

You can pass Tiny Timmy a dataframe while specifying what type it is (pandas, polars, pyspark) and ask for default_checks, also you can simply pass a file uri to a csv or parquet file.

You can also pass custom DQ checks as a list of SQL statements in a normal WHERE clause.

Tiny Timmy returns check results as a Polars dataframe by default, you can request the results as a pandas or pyspark dataframe.

results = tm.default_checks(return_as='pandas')

For example.

┌───────────────────────────────────┬─────────────┐
│ check_type                        ┆ check_value │
│ ---                               ┆ ---         │
│ str                               ┆ i64         │
╞═══════════════════════════════════╪═════════════╡
│ null_check_start_station_name     ┆ 978         │
│ null_check_start_station_id       ┆ 978         │
│ …                                 ┆ …           │
│ started_at_whitespace_count       ┆ 1000        │
│ ended_at_whitespace_count         ┆ 1000        │
│ start_station_name_whitespace_co… ┆ 22          │
│ end_station_name_whitespace_coun… ┆ 22          │

Current functionality ...

• default_checks()
  • check all columns for null values
  • check if dataset is distinct or contains duplicates
  • check if columns have whitespace
  • check for leading or trailing whitespace
• run_custom_check(["{some SQL WHERE clause}"])

Example Usage

CSV support.

from tinytimmy.tinytim import TinyTim
tm = TinyTim(source_type="csv", file_path="202306-divvy-tripdata.csv")
results = tm.default_checks()
>> Column start_station_name has 978 null values
>> Column start_station_id has 978 null values
>> Column end_station_name has 978 null values
>> Column end_station_id has 978 null values
>> Your dataset has 45 duplicates

Pandas support.

from tinytimmy.tinytim import TinyTim
df = pd.read_csv("202306-divvy-tripdata.csv")
tm = TinyTim(source_type="pandas", dataframe=df)
results = tm.default_checks()
>> Column start_station_name has 978 null values
>> Column start_station_id has 978 null values
>> Column end_station_name has 978 null values
>> Column end_station_id has 978 null values
>> Your dataset has no duplicates

Custom Data Quality checks are supported as a list of SQL based formats. They are given as they would appear in a WHERE clause. You can pass one or more checks in the list.

from tinytimmy.tinytim import TinyTim
tm = TinyTim(source_type="csv", file_path="202306-divvy-tripdata.csv")
tm.default_checks()
results = tm.run_custom_check(["start_station_name IS NULL", "end_station_name IS NULL"])
Column start_station_name has 978 null values
Column start_station_id has 978 null values
Column end_station_name has 978 null values
Column end_station_id has 978 null values
Your dataset has no duplicates
Column started_at has 1000 whitespace values
Column ended_at has 1000 whitespace values
Column start_station_name has 22 whitespace values
Column end_station_name has 22 whitespace values
No leading or trailing whitespace values found
shape: (10, 2)
┌───────────────────────────────────┬─────────────┐
│ check_type                        ┆ check_value │
│ ---                               ┆ ---         │
│ str                               ┆ i64         │
╞═══════════════════════════════════╪═════════════╡
│ null_check_start_station_name     ┆ 978         │
│ null_check_start_station_id       ┆ 978         │
│ null_check_end_station_name       ┆ 978         │
│ null_check_end_station_id         ┆ 978         │
│ …                                 ┆ …           │
└───────────────────────────────────┴─────────────┘
Your custom check start_station_name IS NULL found 978 records that match your filter statement
Your custom check end_station_name IS NULL found 978 records that match your filter statement

Tests / Local Setup / Contributions.

To develop and work on TinyTimmy locally, a Docker image and docker-compose is provided.

First, build the image docker build --tag=tinytimmy .

To run the local unit tests run ... docker-compose up test

To simply work inside the Docker container run ... docker run -it tinytimmy /bin/bash