# -*- coding: utf-8 -*-
import os
import numpy as np
import pandas as pd
from config import config


def load_repo_github_user_info(config, ctx):
    schema = config["schema"]
    df = pd.read_excel(
        schema["repo_github_user_info"]["file"],
        sheet_name=schema["repo_github_user_info"]["sheet_name"])
    df.fillna(value=0, inplace=True)
    ctx["repo_github_user_info"] = df


def load_repo_github_info(config, ctx):
    schema = config["schema"]
    df = pd.read_excel(
        schema["repo_github_info"]["file"],
        sheet_name=schema["repo_github_info"]["sheet_name"])
    df.fillna(value=0, inplace=True)
    ctx["repo_github_info"] = df


def load_repo_csdn_trends(config, ctx):
    schema = config["schema"]
    df = pd.read_excel(
        schema["repo_csdn_trends"]["file"],
        sheet_name=schema["repo_csdn_trends"]["sheet_name"])
    df.fillna(value=0, inplace=True)
    ctx["repo_csdn_trends"] = df


def load_repo_commit_rank(config, ctx):
    schema = config["schema"]
    df = pd.read_csv(schema["repo_commit_rank"]["file"])
    df.fillna(value=0, inplace=True)
    ctx["repo_commit_rank"] = df


def load_repo_github_active_trends(config, ctx):
    schema = config["schema"]
    df = pd.read_csv(schema["repo_github_active_trends"]["file"])
    df.fillna(value=0, inplace=True)
    ctx["repo_github_active_trends"] = df


def load_repo_github_popular_trends(config, ctx):
    schema = config["schema"]
    df = pd.read_csv(schema["repo_github_popular_trends"]["file"])
    df.fillna(value=0, inplace=True)
    ctx["repo_github_popular_trends"] = df


def rank_repo_top_n(config, ctx):
    repo_rank = []
    repo_dict = {}

    # 合并项目的总数据 repo_github_info 主键 FullName
    df = ctx["repo_github_info"]
    df.fillna(value=0)
    for index, row in df.iterrows():
        repo_item = {}
        repo_key = row["FullName"].lower()
        repo_item["region"] = row["Region"]
        repo_item["star"] = int(row["Star"])
        repo_item["fork"] = int(row["Fork"])
        repo_item["contributors"] = int(row["Contributors"])

        repo_dict[repo_key] = repo_item
        repo_rank.append(repo_item)

    # 合并项目的CSDN指数数据 repo_csdn_trends 主键 repo_name
    df = ctx["repo_csdn_trends"]
    for index, row in df.iterrows():
        repo_name = row['repo_name']
        repo_key = repo_name.lower()
        repo_item = repo_dict.get(repo_key)
        repo_item["csdn_index_month_avg"] = row[1:].mean()

    # 合并项目的活跃变动数据 repo_github_active_trends 主键 repo_name
    df = ctx["repo_github_active_trends"]
    df.fillna(value=0)
    df = df.groupby(["repo_name"]).agg(np.mean)
    # print(df.loc['TheAlgorithms/Python'])
    for index, row in df.iterrows():
        repo_name = index
        repo_key = repo_name.lower()
        repo_item = repo_dict.get(repo_key)
        repo_item["push_count_month_avg"] = row["push_count"]
        repo_item["pr_count_month_avg"] = row["pr_count"]
        repo_item["issue_count_month_avg"] = row["issue_count"]
        repo_item["creator_count_month_avg"] = row["creator_count"]

    # 合并项目的激活变动数据 repo_github_popular_trends 主键 repo_name
    df = ctx["repo_github_popular_trends"]
    df = df.groupby(["repo_name"]).agg(np.mean)
    for index, row in df.iterrows():
        repo_name = index
        repo_key = repo_name.lower()
        repo_item = repo_dict.get(repo_key)
        repo_item["watch_count_month_avg"] = row["watch_count"]
        repo_item["fork_count_month_avg"] = row["fork_count"]

    # 合并表
    df = pd.DataFrame.from_dict(repo_dict, orient='index')
    df.fillna(value=0, inplace=True)
    df.reset_index()

    # 计算榜单得分
    weights = {
        "star": 1,
        "fork": 1,
        "contributors": 1,
        "csdn_index_month_avg": 1,
        "push_count_month_avg": 1,
        "pr_count_month_avg": 1,
        "issue_count_month_avg": 1,
        "creator_count_month_avg": 1,
        "watch_count_month_avg": 1,
        "fork_count_month_avg": 1
    }
    total_weight_value = 0
    for key in weights:
        total_weight_value += weights[key]

    for key in weights:
        weights[key] = weights[key]/total_weight_value

    df["score"] = 0
    for key in weights:
        df["score"] += df[key].apply(lambda x: x*weights[key])

    print(df.head())
    df = df.sort_values(by="score", ascending=False)
    df.to_csv(config["ranks"]["repo"]["top_n"])


def rank_personal_top_n(config, ctx):
    pass


def rank_company_top_n(config, ctx):
    pass


def calc_ranks(config, options):
    ctx = {}

    # print("@load_repo_github_user_info..")
    # load_repo_github_user_info(config, ctx)

    # print("@load_repo_commit_rank..")
    # load_repo_commit_rank(config, ctx)

    print("@load_repo_github_info..")
    load_repo_github_info(config, ctx)

    print("@load_repo_csdn_trends..")
    load_repo_csdn_trends(config, ctx)

    print("@load_repo_github_active_trends..")
    load_repo_github_active_trends(config, ctx)

    print("@load_repo_github_popular_trends..")
    load_repo_github_popular_trends(config, ctx)

    print("@rank_repo_top_n..")
    rank_repo_top_n(config, ctx)

    # print("@rank_personal_top_n..")
    # rank_personal_top_n(config, ctx)

    # print("@rank_company_top_n..")
    # rank_company_top_n(config, ctx)