from elasticsearch import Elasticsearch
from elasticsearch.helpers import bulk 
from models.data_thread import Threads
from interfaces.db_testing_interface import DB_Testing
import json

INDEX = "threads" 

class Elastic_Testing(DB_Testing):
    driver_name = "ES"
    def __init__(self, shards = 1) -> None:
        super().__init__()
        self.shards = shards
        self.driver_name += f" ({shards} Shards)"
        self.singles_data = []
        for t in Threads:
            x = t.__dict__.copy()
            self.singles_data.append(x)
        
        self.bulk_data = []
        for t in Threads:
            y = "{\"index\":{}}\n"
            y +=  json.dumps(t.__dict__.copy())
            self.bulk_data.append(y)
    
    def delete_table(self, driver: Elasticsearch):
        if driver.indices.exists(index=INDEX):
            driver.indices.delete(index=INDEX)

    def create_table(self, driver: Elasticsearch):
        self.delete_table(driver)
        driver.indices.create(index=INDEX, body={
            'settings': {
                'index': {
                    'number_of_replicas': 0,
                    'number_of_shards': self.shards
                }
            }
        })
    
    def delete_data(self, driver: Elasticsearch):
        if driver.indices.exists(index=INDEX):
            driver.indices.delete(index=INDEX)

    def add_bulk(self, driver: Elasticsearch):
        self.create_table(driver)
        for i in range(0, len(self.bulk_data), 1000):
            driver.bulk(index=INDEX, operations = '\n'.join(self.bulk_data[i:i+1000]), refresh=True)

    def add_singles(self, driver: Elasticsearch):
        for t in self.singles_data:
            driver.index(index=INDEX, document=t)

    def attach5_mr_mrs(self, driver: Elasticsearch):
        query = {
            "query": {
                "bool": {
                    "must": [
                        {
                            "range": {
                                "attachment_count": {
                                    "gt": 5
                                }
                            }
                        },
                        {
                            "terms": {
                                "subject.keyword": ["Mr", "Mrs"]
                            }
                        }
                    ]
                }
            }
        }
        return f"Got {driver.count(index=INDEX, body=query).body['count']}"

    def search_mails_ends_microsoftcom(self, driver: Elasticsearch):
        query = {
            "query": {
                "wildcard": {
                    "cc_recipients.keyword": "*@microsoft.com"
                }
            }
        }
        return f"Got {driver.count(index=INDEX, body=query).body['count']}"
        
    def search_lorem(self, driver: Elasticsearch):
        query = {
            "query": {
                "match_phrase": {
                    "body": "Nullam sit amet turpis elementum ligula vehicula consequat. Morbi a ipsum. Integer a nibh."
                }
            }
        }
        return f"Got {driver.count(index=INDEX, body=query).body['count']}"
        
    def get_sum_attachment_less_5(self, driver: Elasticsearch):
        query = {
            "size": 0,
            "query": {
                "bool": {
                    "must": [
                        {
                            "range": {
                                "attachment_count": {
                                    "lt": 5
                                }
                            }
                        }
                    ]
                }
            }, 
            "aggs": {
                "attachment_count": {
                    "sum": {
                        "field": "attachment_count"
                    }
                }
            }
        }
        return f"Got {driver.search(index=INDEX, body=query).body['aggregations']['attachment_count']['value']}"
    
    def update_add_replies_per_last_name(self, driver: Elasticsearch) -> str:
        agg_query = {
            "size": 0,
            "aggs": {
                "reply_count_by_last_name": {
                "terms": {
                    "script": {
                    "source": "String name = doc['sender_name.keyword'].value; String[] parts = /\\s+/.split(name); return parts[parts.length - 1]",
                    "lang": "painless"
                    },
                    "size": 1000
                },
                "aggs": {
                    "last_name_replies": {
                    "sum": {
                        "field": "reply_count"
                    }
                    }
                }
                }
            }
        }
        
        agg_results = driver.search(index=INDEX, body=agg_query)
        
        buckets = agg_results['aggregations']['reply_count_by_last_name']['buckets']
        reply_counts = {bucket['key']: bucket['last_name_replies']['value'] for bucket in buckets}
        
        update_query = {
            "script": {
                "source": """
                String name = ctx._source.sender_name;
                String[] parts = /\\s+/.split(name);
                String lastName = parts[parts.length - 1];
                if (params.replyCounts.containsKey(lastName)) {
                    ctx._source.last_name_replies = params.replyCounts.get(lastName);
                }
                """,
                "lang": "painless",
                "params": {
                "replyCounts": reply_counts
                }
            },
            "query": {
                "match_all": {}
            }
        }
            
        driver.update_by_query(index=INDEX, body=update_query, conflicts="proceed", slices=len(Threads)//250, request_timeout=120)
            
            
    def update_add_replies_per_subject(self, driver: Elasticsearch) -> str:
        agg_query = {
            "size": 0,
            "aggs": {
                "reply_count_by_subject": {
                "terms": {
                    "script": {
                    "source": "String name = doc['sender_name.keyword'].value; String[] parts = /\\s+/.split(name); return parts[parts.length - 1]",
                    "lang": "painless"
                    },
                    "size": 1000
                },
                "aggs": {
                    "subject_replies": {
                    "sum": {
                        "field": "reply_count"
                    }
                    }
                }
                }
            }
        }
        
        agg_results = driver.search(index=INDEX, body=agg_query)
        
        buckets = agg_results['aggregations']['reply_count_by_subject']['buckets']
        reply_counts = {bucket['key']: bucket['subject_replies']['value'] for bucket in buckets}
        
        update_query = {
            "script": {
                "source": """
                    ctx._source.subject_replies = params.replyCounts.get(ctx.subject);
                """,
                "lang": "painless",
                "params": {
                "replyCounts": reply_counts
                }
            },
            "query": {
                "match_all": {}
            }
        }
            
        driver.update_by_query(index=INDEX, body=update_query, conflicts="proceed", slices=len(Threads)//250, request_timeout=120)