app.py

import pandas as pd
import numpy as np
import streamlit as st

# import glob
# import yaml
from pathlib import Path
from collections import defaultdict

import os, time

#########################################
# Helpers Functions

display_cols = ['image','name', 'color', 'star', 'class', 'speed', 'power', 'attack', 'defense', 'health', 'types', 'source', 'family']

def filter_by_1col_num(df, col_name, query, oper_flag="eq"):
    ok_flag_list = []
    assert col_name in df.columns, "col_name must be valid"

    for i, val in enumerate(df[col_name]):
        if oper_flag == 'ge':
            flag = True if val >= query else False
        elif oper_flag == 'le':
            flag = True if val <= query else False
        else: # default = eq
            flag = True if val == query else False

        ok_flag_list.append(flag)
    
    assert len(ok_flag_list) == len(df)
    return np.array(ok_flag_list)

def filter_by_1col(df, col_name, query, exact_flag=False):

    def check_valid_value(query, string, exact_flag=False):
        if exact_flag:
            if query.lower() == string.lower():
                return True

        elif query.lower() in string.lower():
            return True
        
        return False

    ok_flag_list = []
    assert col_name in df.columns, "col_name must be valid"

    for i, s in enumerate(df[col_name]):

        if isinstance(s, list):
            for s2 in s:
                flag = check_valid_value(query, s2, exact_flag=exact_flag)
                if flag: break
        else:
            flag = check_valid_value(query, s, exact_flag=exact_flag)

        
        ok_flag_list.append(flag)
    
    assert len(ok_flag_list) == len(df)
    return np.array(ok_flag_list)

def display_image(url, scale=0.5, enable_flag = False):
    from urllib.request import urlopen
    from PIL import Image

    enable_flag = False if display_img_flag != 'Yes' else True # adhoc code, should send this variable properly
    
    if enable_flag: # default to False as imgur server seems to refuse our request and cause permanent error
        # image = Image.open(urlopen(url))
        # st.image(image.resize(( int(image.width * scale), int(image.height * scale))))

        
        #The problem occur because imgur remove file extension e.g. 'jpg', 
        #so either url is wrong with urlopen or Image.open does not know image type if use requests/urllib3
        st.image(url)

def display_heroes_from_df(df,display_cols=display_cols, show_df=True):
    vtob = "is" if len(df)<=1 else "are"
    st.write(f'There {vtob} {len(df)} heroes in the filtered list')

    if show_df:
        st.dataframe(df[display_cols],
                 column_config={
                         "image": st.column_config.ImageColumn("Avatar", help="",
                                                              # width="medium", # width alone doesnt matter and there is no height option
                                                              )},
                 use_container_width=True,
                 # height=128, # this is height of the whold df, not on each line
                 hide_index=True)

    for i in range(len(df)):
        st.write(" ")
        st.write(f"#########################################")
        st.write(" ")
        
        url = df['image'].values[i]
        display_image(url)
        st.write(f"***{df['name'].values[i]}*** - {df['speed'].values[i]} - {df['class'].values[i]}")
        st.write(f'Attack:{df["attack"].values[i]} -- Defence:{df["defense"].values[i]} -- Health:{df["health"].values[i]}')
        st.write(f"***{df['skill'].values[i]}***" )
        st.write("\n**Special Skills**")
        st.write(df['effects'].values[i])

        if df['passives'].values[i] != 0 and df['passives'].values[i] != '0':
            st.write("\n**Passives**")
            st.write(df['passives'].values[i])

#########################################
## Helper function for LB/CB stat analysis
def return_costume_list(df0, hero_name):
    assert hero_name in df0.name.values

    if hero_name[-2:] == "C3":
        return ['None', 'CB1', 'CB2', 'CB3']
    if hero_name[-2:] == "C2":
        hero_name2 = hero_name[:-1] + "3"
        if hero_name2 in df0.name.values: # if this hero has C3
            return ['None', 'CB1', 'CB2', 'CB3']
        else:
            return ['None', 'CB1', 'CB2']
    elif hero_name[-2:] == " C":
        hero_name2 = hero_name + "2"
        hero_name3 = hero_name + "3"
        if hero_name3 in df0.name.values: # if this hero has C2
            return ['None', 'CB1', 'CB2', 'CB3']
        elif hero_name2 in df0.name.values: # if this hero has C2
            return ['None', 'CB1', 'CB2']
        else:
            return ['None', 'CB1']
    else:
        hero_name1 = hero_name + " C"
        hero_name2 = hero_name + " C2"
        hero_name3 = hero_name + " C3"
        if hero_name3 in df0.name.values: # if this hero has C2
            return ['None', 'CB1', 'CB2', 'CB3']
        elif hero_name2 in df0.name.values: # if this hero has C2
            return ['None', 'CB1', 'CB2']
        elif hero_name1 in df0.name.values: # if this hero has C2
            return ['None', 'CB1']
        else:
            return ['None']

def get_prefix(lb_choice="None", costume_choice="None"):
    prefix_1 = "Max level"

    if lb_choice != 'None':
        prefix_1 = "Limit Break"
    
    prefix_2 = ""
    if costume_choice != "None":
        prefix_2 = f" {costume_choice}" # CB1 or CB2

    prefix_3 = ":"
    if lb_choice == 'LB1':
        prefix_3 = " #1:"
    elif lb_choice == 'LB2':
        prefix_3 = " #2:"

    return prefix_1 + prefix_2 + prefix_3

def return_hero_stat(df0, hero_name, lb_choice="None", costume_choice="None"):
    assert hero_name in df0.name.values
    
    display_cols_0 = ['image', 'name', 'color', 'star', 'class', 'speed',]
    display_cols_1 = [] # ['power', 'attack', 'defense', 'health', ] --> to be select base one LB/Costume choice
    display_cols_2 = ['AetherPower', 'source', 'family', 'types', 'skill', 'effects', 'passives'] # 'AetherPower' name is changed since June2024

    prefix = get_prefix(lb_choice, costume_choice)

    display_cols_1.append(f'{prefix} Power')
    display_cols_1.append(f'{prefix} Attack')
    display_cols_1.append(f'{prefix} Defense')
    display_cols_1.append(f'{prefix} Health')
    
    display_cols_all = display_cols_0 + display_cols_1 + display_cols_2
    df_ret = df0[df0.name == hero_name][display_cols_all]

    df_ret = df_ret.rename(columns={f'{prefix} Power':'power',
                    f'{prefix} Attack':'attack',
                    f'{prefix} Defense':'defense',
                    f'{prefix} Health':'health'})
    return df_ret

    
def return_talent_choice(key="default_key"):
    talent_list = ['None', 'Sword+20', 'Shield+20', 'Health+20', 'Sword+25', 'Shield+25', 'Health+20 Shield+5','Sword+20 Shield+5','Shield+20 Sword+5']
    
    talent_choice = st.selectbox(label='Approx. Talent (stat are all cruded approximated. Visit heroplan.io for exact calculation.) :', 
                                 options=talent_list, 
                                 index=0, 
                                 key=key)
    
    talent_tp, talent_attack, talent_defense, talent_health = 0, 0, 0, 0
    if talent_choice == 'Sword+20':
        talent_tp, talent_attack, talent_defense, talent_health = 100, 150, 50, 100
    elif talent_choice == 'Shield+20':
        talent_tp, talent_attack, talent_defense, talent_health = 100, 50, 150, 100
    elif talent_choice == 'Health+20':
        talent_tp, talent_attack, talent_defense, talent_health = 100, 75, 75, 200
    if talent_choice == 'Sword+25':
        talent_tp, talent_attack, talent_defense, talent_health = 125, 300, 50, 200
    elif talent_choice == 'Shield+25':
        talent_tp, talent_attack, talent_defense, talent_health = 125, 50, 330, 200
    elif talent_choice == 'Health+20 Shield+5': # choose shield-path on 5 master nodes
        talent_tp, talent_attack, talent_defense, talent_health = 125, 75, 255, 300
    elif talent_choice == 'Sword+20 Shield+5':
        talent_tp, talent_attack, talent_defense, talent_health = 125, 150, 230, 200
    elif talent_choice == 'Shield+20 Sword+5':
        talent_tp, talent_attack, talent_defense, talent_health = 125, 200, 150, 200
    return talent_tp, talent_attack, talent_defense, talent_health

#########################################
## Load the main file (TODO: caching)=
st.set_page_config(layout="wide")
st.header(f'HeroPlan Explorer')
st.write('Powered by Heroplan.io : Thanks E&P community for continually update hero data.')

df = pd.read_csv('heroes_ep.csv')
st.write(f'### Updated: {time.ctime(os.path.getmtime("heroes_ep.csv"))} -- Total heroes in HeroPlan database = {len(df)}')

df_extra = pd.read_csv("heroes_ep_extra.csv")
all_name_extra = sorted(list(df_extra['name'].values))

#########################################

class_values = ['None'] + list(df['class'].unique()) 
star_values = ['None'] + list(df['star'].unique())
color_values = ['None'] + list(df['color'].unique())
speed_values = ['None'] + list(df['speed'].unique())
source_values = ['None'] + list(df['source'].unique()) # Contain lot of typo bugs from HeroPlan

#########################################
## Select Main Program

with st.sidebar:
    genre = st.radio(
    "Choose how to explore heroes",
    [":rainbow[Heroes Explorer]", "Team Simulation","***LB/CB Hero Stat*** :movie_camera:"],
    captions = ["Filter only heroes with certain properties", "Co-powered by Elioty33's DataVault"])

    display_img_flag = st.radio(
        "Display Avatar in Description",
        ["Yes", "No"],
        captions = ["Default", "If problem occur, set to 'no'"]
    )
    
#########################################
## Program 1
if genre == ':rainbow[Heroes Explorer]':
    
    col1, col2, col3 = st.columns(3)
    with col1:
        st.header("Standard Filters:")
        st.write("Tips: filter costume by typing ' C' 'C2' or 'C3' in the Name box.")
        with st.expander("Filter Options"):
            name_option = st.text_input(label="Name:", value="")
            star_option = st.selectbox(label='Star:', options=star_values, index=0)
            color_option = st.selectbox(label='Color:', options=color_values, index=0)
            speed_option = st.selectbox(label='Speed:', options=speed_values, index=0)
            class_option = st.selectbox(label='Class:', options=class_values, index=0)
            source_option = st.selectbox(label='Origin:', options=source_values, index=0)
    
            special_type_option = st.text_input(label="SpecialSkill Category", value="Hit 3")
            special_text_option = st.text_input(label="SpecialSkill Text", value="Dispel")
            passive_text_option = st.text_input(label="Passive Text", value="")
    with col2:
        st.header("Stat Filters")
        st.write("Tips: put the **minimum** att/def/hp stat you want to filter heroes")
        with st.expander("Stat Options"):   
            power_option = st.text_input(label="Power:", value="0")
            defense_option = st.text_input(label="Defense:", value="0")
            attack_option = st.text_input(label="Attack:", value="0")
            health_option = st.text_input(label="Health:", value="0")

            max_percent_option = st.text_input(label="Max % in Special Skill:", value="0")
            
            total_dot_option = st.text_input(label="Total DoT Damage:", value="0")
            dot_per_turn_option = st.text_input(label="DoT Damage Per Turn:", value="0")
    with col3:
        st.header("Sorted By")
        st.write("Tips: you can also directly click at the column name to sort")
        sort_option = st.selectbox(label='Sort by', options=display_cols[1:], index=5) # default is power
    
    idx_all = []

    if name_option != '':
        idx_all.append(filter_by_1col(df, 'name', name_option, exact_flag=False)) 

    if star_option != 'None':
        idx_all.append(filter_by_1col_num(df, 'star', star_option, oper_flag="eq"))    

    if speed_option != 'None':
        idx_all.append(filter_by_1col(df, 'speed', speed_option, exact_flag=True))    

    if color_option != 'None':
        idx_all.append(filter_by_1col(df, 'color', color_option, exact_flag=False))    

    if class_option != 'None':
        idx_all.append(filter_by_1col(df, 'class', class_option, exact_flag=False))    

    if source_option != 'None':
        idx_all.append(filter_by_1col(df, 'source', source_option, exact_flag=False))    

    if power_option != "0":
        power_option = int(power_option)
        idx_all.append(filter_by_1col_num(df, 'power', power_option, oper_flag="ge"))
    
    if defense_option != "0":
        defense_option = int(defense_option)
        idx_all.append(filter_by_1col_num(df, 'defense', defense_option, oper_flag="ge"))   

    if attack_option != "0":
        attack_option = int(attack_option)
        idx_all.append(filter_by_1col_num(df, 'attack', attack_option, oper_flag="ge"))   

    if health_option != "0":
        health_option = int(health_option)
        idx_all.append(filter_by_1col_num(df, 'health', health_option, oper_flag="ge"))

    if total_dot_option != "0":
        total_dot_option = int(total_dot_option)
        idx_all.append(filter_by_1col_num(df, 'total_dot_damage', total_dot_option, oper_flag="ge"))

    if dot_per_turn_option != "0":
        dot_per_turn_option = int(dot_per_turn_option)
        idx_all.append(filter_by_1col_num(df, 'dot_damage_per_turn', dot_per_turn_option, oper_flag="ge"))

    if max_percent_option != "0":
        max_percent_option = int(max_percent_option)
        idx_all.append(filter_by_1col_num(df, 'max_special_percent', max_percent_option, oper_flag="ge"))
    
    if special_type_option  != '':
        idx_all.append(filter_by_1col(df, 'types', special_type_option, exact_flag=False))    

    if special_text_option != '':
        idx_all.append(filter_by_1col(df, 'effects', special_text_option, exact_flag=False))    

    if passive_text_option != '':
        idx_all.append(filter_by_1col(df, 'passives', passive_text_option, exact_flag=False))    
    
    #########################################

    df2 = df[np.all(idx_all,axis=0)]

    display_heroes_from_df(df2.sort_values(sort_option, ascending=False))
#########################################
## Program 2 "Team Simulation"
elif genre == "Team Simulation":
    
    def choose_hero(key="Hero1", default_index=0):
        name_choice = st.selectbox(label='Hero Name:', options=all_name_extra, index=default_index, key=key+"_name")
        costume_list = return_costume_list(df_extra, name_choice)
        costume_choice = st.selectbox(label='Costume:', options=costume_list, index=0, key=key+"_costume")
        lb_list = ['None', 'LB1', 'LB2']
        lb_choice = st.selectbox(label='Limit Break:', options=lb_list, index=0, key=key+"_lb")

        talent_tp, talent_attack, talent_defense, talent_health = return_talent_choice(key=key+"_talent")
        
        df_ret = return_hero_stat(df_extra, name_choice, lb_choice=lb_choice, costume_choice=costume_choice)
        df_ret.power.values[0] += talent_tp
        df_ret.attack.values[0] += talent_attack
        df_ret.defense.values[0] += talent_defense
        df_ret.health.values[0] += talent_health
        
        return df_ret

    def write_short_description(df_hero):
        url = df_hero['image'].values[0]
        display_image(url)
        st.write(f'Power: {df_hero["power"].values[0]}')
        st.write(f'Attack: {df_hero["attack"].values[0]}')
        st.write(f'Defense: {df_hero["defense"].values[0]}')
        st.write(f'Health: {df_hero["health"].values[0]}')
        st.write(f'Speed: {df_hero["speed"].values[0]}')
        st.write(f'Class: {df_hero["class"].values[0]}')
        st.write(f'Types: {df_hero["types"].values[0]}')

    note_flag = st.checkbox("Displayt Notepad", value=False)
    
    nheroes_choice_list = [2,3,4,5]
    nheroes_choice = st.selectbox(label='Number of Heroes:', options=nheroes_choice_list, index=len(nheroes_choice_list)-1)

    additional_col = 0
    if note_flag:
        additional_col = 1
        
    col_list = st.columns(nheroes_choice+additional_col)
    df_hero_list = []
    total_power = 0
    for ii in range(nheroes_choice):
        with col_list[ii]:
            df_hero_list.append(choose_hero(key=f"Hero{ii+1}", default_index=ii)) # 'key' in st.selectbox to differentiate widgets
            write_short_description(df_hero_list[-1])
        total_power += df_hero_list[ii]['power'].values[0]

    if note_flag:
        with col_list[-1]:
            txt = st.text_area("Write your note about team synergy", max_chars=1000, height = 480)

    df_hero_all5 = pd.concat(df_hero_list)
        
    st.write(f'======================')
    st.write(f'### Total power = {total_power}')
    st.write(f'======================')
    
    display_heroes_from_df(df_hero_all5, display_cols=df_hero_all5.columns[:-2], show_df=True) # display all except special-skill text
    
#########################################
## Program 3 "Individual Stat"
else:
    
    
    st.header("Analyze Hero LB/CB Stat (without Emblem)")
    st.write("HeroPlan and DataVault are combined here. Thanks ***@Elioty33*** for his DataVault contribution")
    st.write(f"Currently, there are {len(df_extra)} heroes having both data on HeroPlan and DataVault.")
    st.write(f"We don't have emblem calculator here, you can go heroplan.io to do the job.")
    st.write(f"***Heuristically*** Choose Sword-path can increase att 100-150, def 50-100, hp ~100 (reverse att-def for shield path)")
    st.write(f"Choose HP-path can increase att 50-100, def 50-100, hp ~200")
    

    name_values = sorted(list(df_extra['name'].values))
    name_choice = st.selectbox(label='Hero Name:', options=name_values, index=0)

    costume_list = return_costume_list(df_extra, name_choice)
    costume_choice = st.selectbox(label='Costume:', options=costume_list, index=0)
    
    lb_list = ['None', 'LB1', 'LB2']
    lb_choice = st.selectbox(label='Limit Break:', options=lb_list, index=0)
        
    talent_tp, talent_attack, talent_defense, talent_health = return_talent_choice()
    df_ret = return_hero_stat(df_extra, name_choice, lb_choice=lb_choice, costume_choice=costume_choice)
    
    df_ret.power.values[0] += talent_tp
    df_ret.attack.values[0] += talent_attack
    df_ret.defense.values[0] += talent_defense
    df_ret.health.values[0] += talent_health
    
    display_heroes_from_df(df_ret,display_cols=df_ret.columns[:-2]) # display all except special-skill text