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labor-allocation

labor-allocation

github.com/datadrivenconstruction生产力375105 次安装1 周前更新
代码仓库

关于 labor-allocation

labor-allocation 是用于建筑项目人员分配与跟踪的技能,支持查询排班、计算人工成本和预测用工需求,帮助管理资源利用与进度。

主要功能

  1. 01按工种和技能添加工人
  2. 02查询每日人员名单
  3. 03计算人工成本
  4. 04预测用工需求

适用场景

  1. 01编制每日人员名单
  2. 02计算某项活动的人工成本
  3. 03估算计划活动的用工需求

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill labor-allocation

安装后在 Claude Code 中输入/labor-allocation确认已加载。

附带文件claw.jsoninstructions.md

详细介绍

劳动力分配管理器

业务案例

问题陈述

劳动力管理面临的挑战:

  • 为各项活动分配工人
  • 平衡工作量
  • 跟踪出勤情况
  • 优化生产力
解决方案

系统化地分配和跟踪劳动力,以优化资源利用并确保项目按计划进行。

技术实现

import pandas as pd
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from datetime import date, timedelta
from enum import Enum
from collections import defaultdict


class Trade(Enum):
    CARPENTER = "carpenter"
    ELECTRICIAN = "electrician"
    PLUMBER = "plumber"
    CONCRETE = "concrete"
    MASON = "mason"
    IRONWORKER = "ironworker"
    HVAC = "hvac"
    PAINTER = "painter"
    LABORER = "laborer"
    OPERATOR = "operator"
    FOREMAN = "foreman"


class WorkerStatus(Enum):
    AVAILABLE = "available"
    ASSIGNED = "assigned"
    ON_LEAVE = "on_leave"
    SICK = "sick"
    TERMINATED = "terminated"


class SkillLevel(Enum):
    APPRENTICE = "apprentice"
    JOURNEYMAN = "journeyman"
    MASTER = "master"


@dataclass
class Worker:
    worker_id: str
    name: str
    trade: Trade
    skill_level: SkillLevel
    hourly_rate: float
    company: str
    status: WorkerStatus = WorkerStatus.AVAILABLE
    certifications: List[str] = field(default_factory=list)


@dataclass
class Assignment:
    assignment_id: str
    worker_id: str
    activity_id: str
    activity_name: str
    start_date: date
    end_date: date
    hours_per_day: float
    location: str


@dataclass
class AttendanceRecord:
    date: date
    worker_id: str
    activity_id: str
    hours_worked: float
    overtime_hours: float
    status: str  # present, absent, late


class LaborAllocation:
    """Manage labor allocation and tracking."""

    def __init__(self, project_name: str):
        self.project_name = project_name
        self.workers: Dict[str, Worker] = {}
        self.assignments: List[Assignment] = []
        self.attendance: List[AttendanceRecord] = []

    def add_worker(self,
                   worker_id: str,
                   name: str,
                   trade: Trade,
                   skill_level: SkillLevel,
                   hourly_rate: float,
                   company: str,
                   certifications: List[str] = None) -> Worker:
        """Add worker to pool."""

        worker = Worker(
            worker_id=worker_id,
            name=name,
            trade=trade,
            skill_level=skill_level,
            hourly_rate=hourly_rate,
            company=company,
            certifications=certifications or []
        )

        self.workers[worker_id] = worker
        return worker

    def assign_worker(self,
                      worker_id: str,
                      activity_id: str,
                      activity_name: str,
                      start_date: date,
                      end_date: date,
                      hours_per_day: float = 8,
                      location: str = "") -> Optional[Assignment]:
        """Assign worker to activity."""

        if worker_id not in self.workers:
            return None

        worker = self.workers[worker_id]

        # Check for conflicts
        conflicts = self.check_conflicts(worker_id, start_date, end_date)
        if conflicts:
            print(f"Warning: Worker has {len(conflicts)} conflicting assignments")

        assignment = Assignment(
            assignment_id=f"ASN-{len(self.assignments)+1:04d}",
            worker_id=worker_id,
            activity_id=activity_id,
            activity_name=activity_name,
            start_date=start_date,
            end_date=end_date,
            hours_per_day=hours_per_day,
            location=location
        )

        self.assignments.append(assignment)
        worker.status = WorkerStatus.ASSIGNED

        return assignment

    def check_conflicts(self,
                        worker_id: str,
                        start_date: date,
                        end_date: date) -> List[Assignment]:
        """Check for scheduling conflicts."""

        conflicts = []

        for assignment in self.assignments:
            if assignment.worker_id != worker_id:
                continue

            # Check overlap
            if not (end_date < assignment.start_date or start_date > assignment.end_date):
                conflicts.append(assignment)

        return conflicts

    def record_attendance(self,
                          date: date,
                          worker_id: str,
                          activity_id: str,
                          hours_worked: float,
                          overtime_hours: float = 0,
                          status: str = "present"):
        """Record worker attendance."""

        self.attendance.append(AttendanceRecord(
            date=date,
            worker_id=worker_id,
            activity_id=activity_id,
            hours_worked=hours_worked,
            overtime_hours=overtime_hours,
            status=status
        ))

    def get_workers_by_trade(self, trade: Trade) -> List[Worker]:
        """Get available workers by trade."""
        return [
            w for w in self.workers.values()
            if w.trade == trade and w.status in [WorkerStatus.AVAILABLE, WorkerStatus.ASSIGNED]
        ]

    def get_daily_roster(self, target_date: date) -> pd.DataFrame:
        """Get roster for specific date."""

        roster = []

        for assignment in self.assignments:
            if assignment.start_date <= target_date <= assignment.end_date:
                worker = self.workers.get(assignment.worker_id)
                if worker:
                    roster.append({
                        'Worker ID': worker.worker_id,
                        'Name': worker.name,
                        'Trade': worker.trade.value,
                        'Company': worker.company,
                        'Activity': assignment.activity_name,
                        'Location': assignment.location,
                        'Hours': assignment.hours_per_day
                    })

        return pd.DataFrame(roster)

    def get_activity_crew(self, activity_id: str) -> List[Dict[str, Any]]:
        """Get crew assigned to activity."""

        crew = []

        for assignment in self.assignments:
            if assignment.activity_id == activity_id:
                worker = self.workers.get(assignment.worker_id)
                if worker:
                    crew.append({
                        'worker_id': worker.worker_id,
                        'name': worker.name,
                        'trade': worker.trade.value,
                        'skill_level': worker.skill_level.value,
                        'hourly_rate': worker.hourly_rate,
                        'start_date': assignment.start_date,
                        'end_date': assignment.end_date
                    })

        return crew

    def calculate_labor_cost(self,
                              activity_id: str = None,
                              start_date: date = None,
                              end_date: date = None) -> Dict[str, Any]:
        """Calculate labor costs."""

        total_hours = 0
        total_overtime = 0
        total_cost = 0
        by_trade = defaultdict(float)

        for record in self.attendance:
            # Filter by activity
            if activity_id and record.activity_id != activity_id:
                continue

            # Filter by date
            if start_date and record.date < start_date:
                continue
            if end_date and record.date > end_date:
                continue

            worker = self.workers.get(record.worker_id)
            if not worker:
                continue

            regular_cost = record.hours_worked * worker.hourly_rate
            overtime_cost = record.overtime_hours * worker.hourly_rate * 1.5

            total_hours += record.hours_worked
            total_overtime += record.overtime_hours
            total_cost += regular_cost + overtime_cost
            by_trade[worker.trade.value] += regular_cost + overtime_cost

        return {
            'total_hours': round(total_hours, 1),
            'total_overtime': round(total_overtime, 1),
            'total_cost': round(total_cost, 2),
            'by_trade': dict(by_trade)
        }

    def get_utilization_report(self,
                                start_date: date,
                                end_date: date) -> pd.DataFrame:
        """Get worker utilization report."""

        data = []
        work_days = (end_date - start_date).days + 1
        available_hours = work_days * 8

        for worker in self.workers.values():
            # Get attendance records
            records = [
                r for r in self.attendance
                if r.worker_id == worker.worker_id
                and start_date <= r.date <= end_date
            ]

            worked_hours = sum(r.hours_worked + r.overtime_hours for r in records)
            utilization = (worked_hours / available_hours * 100) if available_hours > 0 else 0

            data.append({
                'Worker ID': worker.worker_id,
                'Name': worker.name,
                'Trade': worker.trade.value,
                'Available Hours': available_hours,
                'Worked Hours': round(worked_hours, 1),
                'Utilization %': round(utilization, 1)
            })

        return pd.DataFrame(data).sort_values('Utilization %', ascending=False)

    def forecast_labor_needs(self,
                              activities: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Forecast labor needs for activities."""

        needs = defaultdict(lambda: {'hours': 0, 'workers': 0})

        for activity in activities:
            trade = activity.get('trade', 'laborer')
            hours = activity.get('manhours', 0)
            duration = activity.get('duration_days', 1)

            workers_needed = hours / (duration * 8) if duration > 0 else 0

            needs[trade]['hours'] += hours
            needs[trade]['workers'] = max(needs[trade]['workers'], int(workers_needed) + 1)

        # Check availability
        for trade_name, requirement in needs.items():
            try:
                trade = Trade(trade_name)
                available = len(self.get_workers_by_trade(trade))
                requirement['available'] = available
                requirement['shortage'] = max(0, requirement['workers'] - available)
            except ValueError:
                requirement['available'] = 0
                requirement['shortage'] = requirement['workers']

        return dict(needs)

    def export_to_excel(self, output_path: str) -> str:
        """Export labor data to Excel."""

        with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
            # Workers
            workers_df = pd.DataFrame([
                {
                    'ID': w.worker_id,
                    'Name': w.name,
                    'Trade': w.trade.value,
                    'Skill': w.skill_level.value,
                    'Rate': w.hourly_rate,
                    'Company': w.company,
                    'Status': w.status.value
                }
                for w in self.workers.values()
            ])
            workers_df.to_excel(writer, sheet_name='Workers', index=False)

            # Assignments
            assignments_df = pd.DataFrame([
                {
                    'ID': a.assignment_id,
                    'Worker': a.worker_id,
                    'Activity': a.activity_name,
                    'Start': a.start_date,
                    'End': a.end_date,
                    'Hours/Day': a.hours_per_day,
                    'Location': a.location
                }
                for a in self.assignments
            ])
            assignments_df.to_excel(writer, sheet_name='Assignments', index=False)

            # Roster for today
            roster = self.get_daily_roster(date.today())
            roster.to_excel(writer, sheet_name='Today Roster', index=False)

        return output_path

快速入门

from datetime import date, timedelta

# Initialize manager
labor = LaborAllocation("Office Building A")

# Add workers
labor.add_worker("W001", "John Smith", Trade.CONCRETE, SkillLevel.JOURNEYMAN, 45, "ABC Concrete")
labor.add_worker("W002", "Mike Jones", Trade.CONCRETE, SkillLevel.APPRENTICE, 30, "ABC Concrete")
labor.add_worker("W003", "Tom Brown", Trade.CARPENTER, SkillLevel.MASTER, 55, "XYZ Carpentry")

# Assign to activity
labor.assign_worker(
    worker_id="W001",
    activity_id="A-101",
    activity_name="Pour Slab Level 3",
    start_date=date.today(),
    end_date=date.today() + timedelta(days=5),
    hours_per_day=10,
    location="Level 3"
)

# Record attendance
labor.record_attendance(date.today(), "W001", "A-101", hours_worked=10, overtime_hours=2)

常见用例

1. 每日排班
roster = labor.get_daily_roster(date.today())
print(roster)
2. 人工成本
cost = labor.calculate_labor_cost(activity_id="A-101")
print(f"Total Cost: ${cost['total_cost']:,.2f}")
3. 预测需求
activities = [
    {'trade': 'concrete', 'manhours': 400, 'duration_days': 5},
    {'trade': 'carpenter', 'manhours': 200, 'duration_days': 10}
]
needs = labor.forecast_labor_needs(activities)
print(needs)

资源

  • DDC Book:第 3.1 章——劳动力管理

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