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Home/Questions/Python/Coding/Write a Python script to process raw JSON files containing sales data and load them into a relational database.

Write a Python script to process raw JSON files containing sales data and load them into a relational database.

Python/Codingeasy0.3 min read

**Flow:** Read JSON → pd.json_normalize (flatten nested) → DataFrame → to_sql. For multiple files: concat then load. Use chunksize if large. **Schema:** json_normalize with record_path, meta for nested. Validate required keys. Handle missing: fillna or reject. **Production:**...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
179
questions in Python/Coding
Difficulty Split
127E|24M|28H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Adidas
Key Concepts Tested
pythonsql

Why This Question Matters

This easy-level Python/Coding question appears frequently in data engineering interviews at companies like Adidas. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (python, sql) will help you answer variations of this question confidently.

How to Approach This

Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
68 words

Flow: Read JSON → pd.json_normalize (flatten nested) → DataFrame → to_sql. For multiple files: concat then load. Use chunksize if large.

Schema: json_normalize with record_path, meta for nested. Validate required keys. Handle missing: fillna or reject.

Production: Transaction per file (all-or-nothing). Bulk insert (to_sql with method='multi'). Idempotency: upsert by (date, id) or truncate+load. Use SQLAlchemy for connection management.

df = pd.json_normalize(data, record_path='sales', meta=['store_id','date'])
df.to_sql('sales', engine, if_exists='append', index=False, chunksize=5000)

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