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data-lineage-tracker

Track data origin, transformations, and flow through construction systems. Essential for audit trails, compliance, and debugging data issues.

datadrivenconstruction0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install datadrivenconstruction/data-lineage-tracker

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

Data Lineage Tracker for Construction

Overview

Track the origin, transformations, and flow of construction data through systems. Provides audit trails for compliance, helps debug data issues, and ensures data governance.

Business Case

Construction projects require data accountability:

  • Audit Compliance: Know where every number came from
  • Issue Resolution: Trace data problems to their source
  • Change Impact: Understand what downstream systems are affected
  • Regulatory Requirements: Maintain data provenance for legal/insurance

Technical Implementation

from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional, Set
from datetime import datetime
from enum import Enum
import json
import hashlib
import uuid

class TransformationType(Enum):
    EXTRACT = "extract"
    TRANSFORM = "transform"
    LOAD = "load"
    AGGREGATE = "aggregate"
    JOIN = "join"
    FILTER = "filter"
    CALCULATE = "calculate"
    MANUAL_EDIT = "manual_edit"
    IMPORT = "import"
    EXPORT = "export"

@dataclass
class DataSource:
    id: str
    name: str
    system: str
    location: str
    owner: str
    created_at: datetime

@dataclass
class TransformationStep:
    id: str
    transformation_type: TransformationType
    description: str
    input_entities: List[str]
    output_entities: List[str]
    logic: str  # SQL, Python, or description
    performed_by: str  # user or system
    performed_at: datetime
    parameters: Dict[str, Any] = field(default_factory=dict)

@dataclass
class DataEntity:
    id: str
    name: str
    source_id: str
    entity_type: str  # table, file, field, record
    created_at: datetime
    version: int = 1
    checksum: Optional[str] = None
    parent_entities: List[str] = field(default_factory=list)
    metadata: Dict[str, Any] = field(default_factory=dict)

@dataclass
class LineageRecord:
    id: str
    entity_id: st...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/datadrivenconstruction/data-lineage-tracker
Version
—
Commit
05be094ea838303958fbf0b7828498760067ad5d
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# Data Lineage Tracker for Construction

## Overview

Track the origin, transformations, and flow of construction data through systems. Provides audit trails for compliance, helps debug data issues, and ensures data governance.

## Business Case

Construction projects require data accountability:
- **Audit Compliance**: Know where every number came from
- **Issue Resolution**: Trace data problems to their source
- **Change Impact**: Understand what downstream systems are affected
- **Regulatory Requirements**: Maintain data provenance for legal/insurance

## Technical Implementation

```python
from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional, Set
from datetime import datetime
from enum import Enum
import json
import hashlib
import uuid

class TransformationType(Enum):
    EXTRACT = "extract"
    TRANSFORM = "transform"
    LOAD = "load"
    AGGREGATE = "aggregate"
    JOIN = "join"
    FILTER = "filter"
    CALCULATE = "calculate"
    MANUAL_EDIT = "manual_edit"
    IMPORT = "import"
    EXPORT = "export"

@dataclass
class DataSource:
    id: str
    name: str
    system: str
    location: str
    owner: str
    created_at: datetime

@dataclass
class TransformationStep:
    id: str
    transformation_type: TransformationType
    description: str
    input_entities: List[str]
    output_entities: List[str]
    logic: str  # SQL, Python, or description
    performed_by: str  # user or system
    performed_at: datetime
    parameters: Dict[str, Any] = field(default_factory=dict)

@dataclass
class DataEntity:
    id: str
    name: str
    source_id: str
    entity_type: str  # table, file, field, record
    created_at: datetime
    version: int = 1
    checksum: Optional[str] = None
    parent_entities: List[str] = field(default_factory=list)
    metadata: Dict[str, Any] = field(default_factory=dict)

@dataclass
class LineageRecord:
    id: str
    entity_id: st...

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