Back to skills
SKILL.md
Data Pipeline Processor
ASecurityProcess data files through transformation pipelines with validation,
- 17 stars
- 0 votes
- 0 copies
- 3 views
- Added September 9, 2026
Security analysis
100/100npx -y skills add vamseeachanta/workspace-hub --skill data-pipeline-processor --agent claude-codeAre you the author of Data Pipeline Processor?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/vamseeachanta-data-pipeline-processor)---
name: data-pipeline-processor
description: Process data files through transformation pipelines with validation,
cleaning, and export. Use for CSV/Excel/JSON data processing, encoding handling,
batch operations, and data transformation workflows.
type: reference
version: 1.1.0
category: development
related_skills:
- yaml-workflow-executor
- engineering-report-generator
- parallel-file-processor
capabilities: []
requires: []
tags: []
freedom: medium
---
# Data Pipeline Processor
## Quick Start
```python
import pandas as pd
from pathlib import Path
# Simple pipeline: Load -> Transform -> Export
df = pd.read_csv("data/raw/source.csv")
# Transform
df = df[df['value'] > 0] # Filter
df['date'] = pd.to_datetime(df['date']) # Convert types
df = df.sort_values('date') # Sort
# Export
Path("data/processed").mkdir(parents=True, exist_ok=True)
df.to_csv("data/processed/cleaned.csv", index=False)
print(f"Processed {len(df)} rows")
```
## When to Use
- Processing CSV/Excel/JSON files with validation
- Data cleaning and transformation workflows
- Batch file processing with aggregation
- Handling encoding issues (UTF-8, Latin-1 fallback)
- ETL (Extract, Transform, Load) operations
- Data quality checks and reporting
## Core Pattern
```
Input (CSV/Excel/JSON) -> Validate -> Transform -> Analyze -> Export
```
## Implementation
### Data Reader with Encoding Detection
```python
import pandas as pd
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
import logging
import chardet
logger = logging.getLogger(__name__)
*See sub-skills for full details.*
### Data Validator
```python
from dataclasses import dataclass, field
from typing import Callable, List, Dict, Any
@dataclass
class ValidationResult:
"""Result of data validation."""
is_valid: bool
errors: List[str] = field(default_factory=list)
*See sub-skills for full details.*
### Data Transformer
```python
class DataTransformer:
"""Apply transformations to data."""
def __init__(self, df: pd.DataFrame):
self.df = df.copy()
def rename_columns(self, mapping: Dict[str, str]) -> 'DataTransformer':
"""Rename columns."""
self.df = self.df.rename(columns=mapping)
*See sub-skills for full details.*
### Data Exporter
```python
class DataExporter:
"""Export data to various formats."""
@staticmethod
def to_csv(df: pd.DataFrame, path: str, **kwargs) -> str:
"""Export to CSV."""
Path(path).parent.mkdir(parents=True, exist_ok=True)
df.to_csv(path, index=False, **kwargs)
return path
*See sub-skills for full details.*
### Pipeline Orchestrator
```python
from dataclasses import dataclass
from typing import List, Dict, Any, Optional
@dataclass
class PipelineConfig:
"""Configuration for data pipeline."""
input_path: str
output_path: str
*See sub-skills for full details.*
## YAML Configuration Format
### Basic Pipeline Config
```yaml
# config/pipelines/data_clean.yaml
input:
path: data/raw/source.csv
options:
delimiter: ","
skiprows: 1
validation:
*See sub-skills for full details.*
### Aggregation Pipeline
```yaml
# config/pipelines/monthly_summary.yaml
input:
path: data/processed/daily_data.csv
validation:
required_columns:
- date
- category
*See sub-skills for full details.*
## Related Skills
- [yaml-workflow-executor](../yaml-workflow-executor/SKILL.md) - Workflow orchestration
- [engineering-report-generator](../engineering-report-generator/SKILL.md) - Report generation
- [parallel-file-processor](../parallel-file-processor/SKILL.md) - Parallel file operations
---
## Version History
- **1.1.0** (2026-01-02): Upgraded to SKILL_TEMPLATE_v2 format with Quick Start, Error Handling, Metrics, Execution Checklist, additional examples
- **1.0.0** (2024-10-15): Initial release with DataReader, DataValidator, DataTransformer, pipeline orchestration
## Sub-Skills
- [Example 1: Simple CSV Processing (+3)](example-1-simple-csv-processing/SKILL.md)
- [Do (+6)](do/SKILL.md)
## Sub-Skills
- [Error Handling](error-handling/SKILL.md)
- [Execution Checklist](execution-checklist/SKILL.md)
- [Metrics](metrics/SKILL.md)
Attribution
Comments
Loading comments…
Newsletter
Get the weekly list of safe new skills, and the ones we pulled.