gamification/objects.py

from datetime import datetime
from pydantic import model_validator, BaseModel
from typing import List, Optional, Union
from bson import ObjectId

class UserLevel(BaseModel):
    _id: Optional[ObjectId]=None  # Make sure _id can be Optional
    id:Optional[str]=None
    maxPoints: int
    minPoints: int
    levelName: str
    careerPath: str
    levelNumber: int

    # To convert MongoDB ObjectId to string
    class Config:
        json_encoders = {
            ObjectId: str
        }

    # Custom validator to handle the ObjectId conversion if needed
    @model_validator(mode='before')
    def handle_objectid(cls, values):
        if '_id' in values and isinstance(values['_id'], ObjectId):
            values['id'] = str(values['_id'])  # Convert ObjectId to string
        return values
    


class UserPoints(BaseModel):
    pointsId:str
    userId:str
    class Config:
        json_encoders = {
            ObjectId: str
        }
        

class LearningProgress(BaseModel):
        course_completion: Optional[int] = None  # Points for course completion
        module_completion: Optional[int] = None  # Points for module completion
        daily_learning_streak: Optional[int] = None  # Points for daily learning streak
        quiz_assessment_completion: Optional[int] = None# Points for quiz/assessment completion
        passing_score: Optional[int] = None # Points for passing assessments
        class Config:
            json_encoders = {
                ObjectId: str
            }
class SkillDevelopment(BaseModel):
        skill_milestone_achievements: Optional[int] = None # Points for achieving milestones
        cross_discipline_learning: Optional[int] = None # Points for completing courses in different tech categories
        practical_project_submission: Optional[int] = None  # Points for submitting a practical project
        project_peer_review: Optional[int] = None  # Points for reviewing a project
        class Config:
            json_encoders = {
                ObjectId: str
            }
class PlatformEngagement(BaseModel):
        profile_completion: Optional[int] = None  # Points for completing profile
        connecting_learning_accounts: Optional[int] = None  # Points for connecting learning accounts
        daily_check_in: Optional[int] = None  # Points for daily check-in
        community_participation: Optional[int] = None  # Points for community participation
        providing_feedback: Optional[int] = None # Points for providing feedback
        class Config:
            json_encoders = {
                ObjectId: str
            }
            
            
class PointMultipliersWeekendWarrior(BaseModel):
    weekendWarrior: float = 1.5
    class Config:
        json_encoders = {
            ObjectId: str
        }

class PointMultipliersFocusMode(BaseModel):
    focusMode: float = 2
    class Config:
        json_encoders = {
            ObjectId: str
        }

class PointMultipliersSkillGapTargeting(BaseModel):
    skillGapTargeting: float = 2
    class Config:
        json_encoders = {
            ObjectId: str
        }

class PointMultipliersTrendingTech(BaseModel):
    trendingTech: float = 1.5

    class Config:
        json_encoders = {
            ObjectId: str
        }




class Points(BaseModel):
    userId: str
    numOfPoints: Optional[float] = None  # Initially set to None
    learningProgress: Optional[LearningProgress] = None
    skillDevelopment: Optional[SkillDevelopment] = None
    platformEngagement: Optional[PlatformEngagement] = None
    weekendWarrior: Optional[PointMultipliersWeekendWarrior] = None
    trendingTech: Optional[PointMultipliersTrendingTech]=None
    skillGapTargeting:Optional[PointMultipliersSkillGapTargeting]=None
    focusMode:Optional[PointMultipliersFocusMode]=None
    earnedAt:Optional[datetime]=datetime.now()    

    @model_validator(mode='before')
    def calculate_num_of_points(cls, values):
        total_points = 0

        # Add points from LearningProgress
        learning_progress = values.get('learningProgress')
        
        if learning_progress:
            total_points += sum(filter(None, [
                learning_progress.course_completion,
                learning_progress.module_completion,
                learning_progress.daily_learning_streak,
                learning_progress.quiz_assessment_completion,
                learning_progress.passing_score
            ]))

        # Add points from SkillDevelopment
        skill_development = values.get('skillDevelopment')
        if skill_development:
            total_points += sum(filter(None, [
                skill_development.skill_milestone_achievements,
                skill_development.cross_discipline_learning,
                skill_development.practical_project_submission,
                skill_development.project_peer_review
            ]))

        # Add points from PlatformEngagement
        platform_engagement = values.get('platformEngagement')
        if platform_engagement:
            total_points += sum(filter(None, [
                platform_engagement.profile_completion,
                platform_engagement.connecting_learning_accounts,
                platform_engagement.daily_check_in,
                platform_engagement.community_participation,
                platform_engagement.providing_feedback
            ]))

        # Apply multipliers if present
        PointMultipliersWeekendWarrior = values.get('weekendWarrior')
        if PointMultipliersWeekendWarrior:
            total_points *= sum([
                PointMultipliersWeekendWarrior.weekendWarrior
            
            ])   
        
        PointMultipliersTrendingTech = values.get('trendingTech')
        if PointMultipliersTrendingTech:
            total_points *= sum([
                PointMultipliersTrendingTech.trendingTech
            ]) 
            
            
        PointMultipliersSkillGapTargeting = values.get('skillGapTargeting')
        if PointMultipliersSkillGapTargeting:
            total_points *= sum([
                PointMultipliersSkillGapTargeting.skillGapTargeting
            ]) 
        
        
        
        PointMultipliersFocusMode = values.get('focusMode')
        if PointMultipliersFocusMode:
            total_points *= sum([
                PointMultipliersFocusMode.focusMode,
            ]) 
        

        values['numOfPoints'] = total_points  # Store calculated points

        return values

    class Config:
        json_encoders = {
            ObjectId: str
        }




class UserFeedback(BaseModel):
    userId:str
    feedback:str
    rating:int
    respondedAt:datetime
    
    class Config:
        json_encoders = {
            ObjectId: str
        }
      

  
class Feedback(BaseModel):
    feedback:str
    rating:int
    
    class Config:
        json_encoders = {
            ObjectId: str
        }
        
        
class Customer(BaseModel):
    email:str
    first_name:str
    last_name:str
    date_Joined: datetime 
    class Config:
        json_encoders = {
            ObjectId: str
        }

        
        
        
class CustomerInfo(BaseModel):
    totalCustomers:int
    GrowthRate: float
    GrowthRateType:str
    daysAgo:int
    class Config:
        json_encoders = {
            ObjectId: str
        }
    
    
class individualPoints(BaseModel):
    numOfPoints:float
    earnedAt:datetime
    platformEngagement:Optional[dict]=None
    learningProgress:Optional[dict]=None
    skillDevelopment:Optional[dict]=None
    weekendWarrior:Optional[dict]=None
    trendingTech:Optional[dict]=None
    skillGapTargeting:Optional[dict]=None
    focusMode:Optional[dict]=None
    starUrl:Optional[str]="https://iili.io/37bdMPe.png"
    
    @model_validator(mode='after')
    def change_star_url(cls,values):
        weekendWarriorPM = values.weekendWarrior
        trendingTechPM=values.trendingTech
        skillGapTargetingPM=values.skillGapTargeting
        focusModePM=values.focusMode
        a=0
        if weekendWarriorPM !=None:
            a=a+1 
        if trendingTechPM !=None: 
            a=a+1
        if skillGapTargetingPM !=None:
            a=a+1 
        if focusModePM!=None:
            a=a+1
        if a==1 or a==2:
            values.starUrl='https://iili.io/37b2RWP.png'
        elif a==3 or a==4:
            values.starUrl='https://iili.io/37b3Yj2.png'
        return values
    
    
    class Config:
        json_encoders={
            ObjectId:str
        }
        


        
class IndividualUserLevel(BaseModel):
    totalpoints:float
    levelName:str
    levelNumber:int
    maxPoints:float
    minPoints:float
    individualPoints:List[individualPoints]
    
    
        

    class Config:
        json_encoders = {
            ObjectId: str
        }
    
    
class SimpleIndividualUserLevel(BaseModel):
    totalpoints:float
    levelName:Optional[str]="default"
    maxPoints:Optional[float]=0
    minPoints:Optional[float]=999999999999999999999
    levelNumber:Optional[int]=1
    class Config:
        json_encoders = {
            ObjectId: str
        }
    
    
class Ranker(BaseModel):
    firstName:str
    lastName:str
    rank:int
    totalPoints:Optional[float]=None
    dreamJob:Optional[str]=None
    badgeUrl:Optional[str]=None
    class Config:
        json_encoders = {
            ObjectId:str
        }
    @model_validator(mode='before')
    def changeValueNames(cls,values):
        values['totalPoints']= values.get("totalpoints")
        values['dreamJob']=values.get("careerPath")
        if values.get("totalpoints") >=0 and values.get("totalpoints") <=200:
            values['badgeUrl'] ="https://res.cloudinary.com/dfmzougki/image/upload/v1742757994/Frame_121_LE_upscale_magic_x4_strength_20_similarity_50_1-removebg-preview_qnbmf3.png"
        elif values.get("totalpoints") >=201 and values.get("totalpoints") <=400:
            values['badgeUrl'] ="https://res.cloudinary.com/dfmzougki/image/upload/v1742757797/image-21_LE_upscale_magic_x4_strength_20_similarity_50_tone_enhance_30_color_enhance_30_1-removebg-preview_j6mmhm.png"
        elif values.get("totalpoints") >=401 and values.get("totalpoints") <=600:
            values['badgeUrl'] ="https://res.cloudinary.com/dfmzougki/image/upload/v1742757797/last_level_LE_upscale_magic_x4_strength_20_similarity_50_tone_enhance_30_color_enhance_30_1-removebg-preview_bwmdyt.png"
        elif values.get("totalpoints") >=601 and values.get("totalpoints") <=800:
            values['badgeUrl'] ="https://res.cloudinary.com/dfmzougki/image/upload/v1742757797/image_25_LE_upscale_magic_x4_strength_20_similarity_50_1-removebg-preview_dcamov.png"
        elif values.get("totalpoints") >=801 and values.get("totalpoints") <=1000:
            values['badgeUrl'] ="https://res.cloudinary.com/dfmzougki/image/upload/v1742757797/Frame_118_LE_upscale_magic_x4_strength_20_similarity_50_tone_enhance_30_color_enhance_30_1-removebg-preview_ng6kzp.png"
        else: values['badgeUrl'] ="https://res.cloudinary.com/dfmzougki/image/upload/v1742757798/Frame_117_LE_upscale_magic_x4_strength_20_similarity_50_tone_enhance_30_color_enhance_30_1-removebg-preview_esrny1.png"
            
        return values