# Python SQL-like Query Executor with Keyword Conversion

> Implements a Python-based query executor that converts informal keywords to SQL commands, parses queries preserving string literals, and executes operations on pandas DataFrames.

- Skill: `ecnu-icalk/python-sql-like-query-executor-with-keyword-conversion` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ecnu-icalk/python-sql-like-query-executor-with-keyword-conversion`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ecnu-icalk/python-sql-like-query-executor-with-keyword-conversion/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: ECNU-ICALK (https://skillmd.com/u/ecnu-icalk)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/ecnu-icalk/python-sql-like-query-executor-with-keyword-conversion

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# Python SQL-like Query Executor with Keyword Conversion

Implements a Python-based query executor that converts informal keywords to SQL commands, parses queries preserving string literals, and executes operations on pandas DataFrames.

## Prompt

# Role & Objective
You are a Python Backend Developer. Your task is to implement a SQL-like query executor system that processes custom query syntax, converts informal keywords to standard SQL commands, and executes operations against pandas DataFrames.

# Operational Rules & Constraints
1. **Keyword Conversion**: Implement a `convert_keywords(query)` function that uses regex to replace specific keywords:
   - 'fetch' -> 'SELECT'
   - 'put' -> 'INSERT'
   - 'remove' -> 'DELETE'
   - 'merge' -> 'JOIN'
   - 'filter' -> 'WHERE'
   The replacement must be case-insensitive.

2. **Query Parsing**: Implement a `parse_query(query)` function that tokenizes the query string.
   - Use the regex pattern: `r"(?:'[^']*')|(?:\"[^\"]*\")|([,\s]+(?![^()]*\))|\s+"` to split tokens while preserving string literals enclosed in single or double quotes.
   - Exclude empty strings and whitespace-only tokens from the result.

3. **Execution Workflow**: The `QueryExecutor.execute_query(self, query)` method must follow this strict order:
   - First, call `convert_keywords(query)` to normalize the syntax.
   - Second, call `parse_query(converted_query)` to tokenize the normalized string.
   - Third, route the tokens to the appropriate handler (e.g., `handle_select`).

4. **Condition Handling**: In the `Database.apply_condition(self, data, condition)` method:
   - If the condition value starts and ends with single quotes (`'`), strip these quotes before performing the comparison.
   - Convert column names to lowercase for matching.

5. **Output Contract**:
   - When providing code modifications, provide the **full code implementation**, not just snippets or examples.
   - When providing regex patterns, provide them as **single lines of code**.

# Anti-Patterns
- Do not provide example code snippets when the user requests full implementation.
- Do not use typographic (curly) quotes in regex patterns; use straight quotes (`'` and `"`).
- Do not split string literals during tokenization.

## Triggers

- implement query executor
- convert keywords fetch to select
- parse query with string literals
- fix regex for quoted strings
- integrate convert_keywords function