16378074149

Committed 18 Jul 2025 06:48PM UTC coverage: 83.993% (+2.1%) from 81.898%

Build # 16378074149

Build Type

push

github

Committed by

web-flow

Commit Message

Ingestion v2.0.8 (#103)

### Description
Ruff Linting Updates

## Added
- New Ruff Linting Rules

## Updated
- Docstrings to accommodate new Linting Rules
- `return` cleanup & optimizations

## Deleted
- None

Run Details

15 of 29 new or added lines in 5 files covered. (51.72%)

1 existing line in 1 file now uncovered.

467 of 556 relevant lines covered (83.99%)

1.68 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

66.67

/src/database.py

import logging

import pandas as pd


def write_to_sql(con, table_name: str, df: pd.DataFrame, table_type: str) -> None:
    """Simple Wrapper Function to write a Pandas DataFrame to SQL

    Args:
        con (SQL Connection): The connection to the SQL DB.

        table_name (str): The Table name to write to SQL as.

        df (DataFrame): The Pandas DataFrame to store in SQL

        table_type (str): Whether the table should replace or append to an
            existing SQL Table under that name

    Returns:
        Writes the Pandas DataFrame to a Table in the Schema we connected to.

    """
    try:
        if len(df) == 0:
            logging.info(f"{table_name} is empty, not writing to SQL")
        else:
            df.to_sql(
                con=con,
                name=table_name,
                index=False,
                if_exists=table_type,
            )
            logging.info(
                f"Writing {len(df)} {table_name} rows to aws_{table_name}_source to SQL"
            )

        return
    except Exception as error:
        logging.error(f"SQL Write Script Failed, {error}")
        return

1	import logging	2✔
2
3	import pandas as pd	2✔
4
5
6	def write_to_sql(con, table_name: str, df: pd.DataFrame, table_type: str) -> None:	2✔
7	"""Simple Wrapper Function to write a Pandas DataFrame to SQL
8
9	Args:
10	con (SQL Connection): The connection to the SQL DB.
11
12	table_name (str): The Table name to write to SQL as.
13
14	df (DataFrame): The Pandas DataFrame to store in SQL
15
16	table_type (str): Whether the table should replace or append to an
17	existing SQL Table under that name
18
19	Returns:
20	Writes the Pandas DataFrame to a Table in the Schema we connected to.
21
22	"""
23	try:	2✔
24	if len(df) == 0:	2✔
25	logging.info(f"{table_name} is empty, not writing to SQL")	×
26	else:
27	df.to_sql(	2✔
28	con=con,
29	name=table_name,
30	index=False,
31	if_exists=table_type,
32	)
33	logging.info(	2✔
34	f"Writing {len(df)} {table_name} rows to aws_{table_name}_source to SQL"
35	)
36
37	return	2✔
38	except Exception as error:	×
39	logging.error(f"SQL Write Script Failed, {error}")	×
NEW 40	return	×

jyablonski / python_docker / 16378074149

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous