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Further analysis
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@Raei-MH
Raei-MH committed Oct 3, 2023
1 parent 45176b7 commit cca8830
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Showing 9 changed files with 236 additions and 133 deletions.
3 changes: 1 addition & 2 deletions phase3 Dashboard/app.py
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Original file line number Diff line number Diff line change
@@ -1,12 +1,11 @@
import streamlit as st
from streamlit_extras.let_it_rain import rain
from PIL import Image
import matplotlib.pyplot as plt

image = Image.open('attrs/logo.png')
st.image(image)
rain(
emoji="📙",
emoji="📗",
font_size=30,
falling_speed=9,
animation_length="infinite",
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170 changes: 118 additions & 52 deletions phase3 Dashboard/model/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -168,57 +168,66 @@ def get_best_books_by_budget(mysql: MySQLConnection, budget) -> pd.DataFrame:
select book_detail.book_id,\
book_detail.Persian_title,\
book_detail.English_title,\
publisher_id,\
max(price_history.date) as last_update,\
score,\
(price * (100 - price_history.discount) / 100) as after_discount,\
sum((price * (100 - price_history.discount) / 100)) over (order by score\
desc, price) as sumofprice\
publisher_id,score,\
(prices_tbl.price * (100 - prices_tbl.discount) / 100) as after_discount,\
prices_tbl.date\
from book_detail\
inner join price_history\
on book_detail.book_id = price_history.book_id\
inner join (SELECT book_id, date, price, discount\
FROM price_history\
WHERE (book_id, date) IN (SELECT book_id, MAX(date)\
FROM price_history\
GROUP BY book_id)) as prices_tbl\
on prices_tbl.book_id = book_detail.book_id\
where book_detail.stock_status = ' موجود '\
and (price * (100 - price_history.discount) / 100)<={budget}\
group by book_detail.book_id\
order by score desc, price) as t where sumofprice<={budget}"
and (prices_tbl.price * (100 - prices_tbl.discount) / 100) <= {budget}\
order by score desc, after_discount) as inner_tbl) as outer_tbl\
where sumofprice <= {budget}"
return pandas_sql(mysql, query)

def get_most_profitable_books_by_budget(mysql:MySQLConnection,budget) ->pd.DataFrame:
query=f"select * from (\

def get_most_profitable_books_by_budget(mysql: MySQLConnection, budget) -> pd.DataFrame:
query = f"select * from (\
select book_detail.book_id,\
book_detail.Persian_title,\
book_detail.English_title,\
max(price_history.date) as last_update,\
edition,\
publisher_id,\
(price * (100 - price_history.discount) / 100) as after_discount,\
sum((price * (100 - price_history.discount) / 100)) over (order by edition\
desc, price) as sumofprice\
publisher_id,edition,\
(prices_tbl.price * (100 - prices_tbl.discount) / 100) as after_discount,\
prices_tbl.date\
from book_detail\
inner join price_history\
on book_detail.book_id = price_history.book_id\
inner join (SELECT book_id, date, price, discount\
FROM price_history\
WHERE (book_id, date) IN (SELECT book_id, MAX(date)\
FROM price_history\
GROUP BY book_id)) as prices_tbl\
on prices_tbl.book_id = book_detail.book_id\
where book_detail.stock_status = ' موجود '\
and (price * (100 - price_history.discount) / 100)<={budget}\
group by book_detail.book_id\
order by edition desc, price) as t where sumofprice<={budget}"
return pandas_sql(mysql,query)
and (prices_tbl.price * (100 - prices_tbl.discount) / 100) <= {budget}\
order by edition desc, after_discount) as inner_tbl) as outer_tbl\
where sumofprice <= {budget}"
return pandas_sql(mysql, query)


def get_most_books_by_budget(mysql:MySQLConnection,budget) ->pd.DataFrame:
query=f"select * from (\
def get_most_books_by_budget(mysql: MySQLConnection, budget) -> pd.DataFrame:
query = f"select * from (\
select book_detail.book_id,\
book_detail.Persian_title,\
book_detail.English_title,\
publisher_id,\
max(price_history.date) as last_update,\
(price * (100 - price_history.discount) / 100) as after_discount,\
sum((price * (100 - price_history.discount) / 100)) over (order by price) as sumofprice\
(prices_tbl.price * (100 - prices_tbl.discount) / 100) as after_discount,\
prices_tbl.date\
from book_detail\
inner join price_history\
on book_detail.book_id = price_history.book_id\
inner join (SELECT book_id, date, price, discount\
FROM price_history\
WHERE (book_id, date) IN (SELECT book_id, MAX(date)\
FROM price_history\
GROUP BY book_id)) as prices_tbl\
on prices_tbl.book_id = book_detail.book_id\
where book_detail.stock_status = ' موجود '\
and (price * (100 - price_history.discount) / 100)<={budget}\
group by book_detail.book_id\
order by price) as t where sumofprice<={budget}"
return pandas_sql(mysql,query)
and (prices_tbl.price * (100 - prices_tbl.discount) / 100) <= {budget}\
order by after_discount) as inner_tbl) as outer_tbl\
where sumofprice <= {budget}"
return pandas_sql(mysql, query)


def get_unique_books(mysql: MySQLConnection, number) -> pd.DataFrame:
query = f"select book_id,Persian_title,English_title,count(distinct rewards.reward) as award\
Expand All @@ -227,42 +236,50 @@ def get_unique_books(mysql: MySQLConnection, number) -> pd.DataFrame:
group by rewards.site_id\
order by award desc\
limit {number}"
return pandas_sql(mysql,query)
def get_most_veneration_book(mysql:MySQLConnection,num) ->pd.DataFrame:
query=f'select book_detail.Persian_title,book_detail.English_title,\
return pandas_sql(mysql, query)


def get_most_veneration_book(mysql: MySQLConnection, num) -> pd.DataFrame:
query = f'select book_detail.Persian_title,book_detail.English_title,\
count(distinct veneration.prise_writer) as count_comment\
from book_detail\
inner join veneration on veneration.site_id = book_detail.site_id\
group by veneration.site_id\
order by count_comment desc\
limit {num}'
return pandas_sql(mysql,query)
def get_all_books_with_tags(mysql:MySQLConnection)->pd.DataFrame:
query='select book_tag.site_id, tags.name\
return pandas_sql(mysql, query)


def get_all_books_with_tags(mysql: MySQLConnection) -> pd.DataFrame:
query = 'select book_tag.site_id, tags.name\
from (select site_id\
from book_tag\
inner join tags on tags.id = book_tag.tag_id) as tbl\
inner join book_tag on tbl.site_id = book_tag.site_id\
inner join tags on book_tag.tag_id = tags.id'
return pandas_sql(mysql,query)
def get_translators_name(mysql:MySQLConnection)->list[str]:
query='select distinct name\
return pandas_sql(mysql, query)


def get_translators_name(mysql: MySQLConnection) -> list[str]:
query = 'select distinct name\
from translator\
inner join translator_page on translator.translator_id = translator_page.translator_id'
return list(pandas_sql(mysql,query).name)
return list(pandas_sql(mysql, query).name)


def get_all_books_translators(mysql:MySQLConnection)->pd.DataFrame:
query="select book_detail.book_id, translator_page.name\
def get_all_books_translators(mysql: MySQLConnection) -> pd.DataFrame:
query = "select book_detail.book_id, translator_page.name\
from (select book_id\
from translator\
inner join translator_page on translator_page.translator_id = translator.translator_id) as tbl\
inner join book_detail on book_detail.book_id = tbl.book_id\
inner join translator on book_detail.book_id = translator.book_id\
inner join translator_page on translator_page.translator_id = translator.translator_id"
return pandas_sql(mysql,query)
return pandas_sql(mysql, query)


def get_number_of_books_published_by_pubs(mysql:MySQLConnection)->pd.DataFrame:
query='SELECT p1.name AS publisher1, p2.name AS publisher2,COUNT(*) AS book_count\
def get_number_of_books_published_by_pubs(mysql: MySQLConnection) -> pd.DataFrame:
query = 'SELECT p1.name AS publisher1, p2.name AS publisher2,COUNT(*) AS book_count\
FROM book_detail AS bd1\
INNER JOIN book_detail AS bd2 ON bd1.English_title = bd2.English_title AND bd1.publisher_id < bd2.publisher_id\
INNER JOIN publisher AS p1 ON bd1.publisher_id = p1.id\
Expand All @@ -271,4 +288,53 @@ def get_number_of_books_published_by_pubs(mysql:MySQLConnection)->pd.DataFrame:
HAVING book_count >= 1\
ORDER BY book_count DESC\
limit 40;'
return pandas_sql(mysql,query)
return pandas_sql(mysql, query)


def get_all_books_writers(mysql: MySQLConnection) -> pd.DataFrame:
query = "select book_detail.book_id, writer_page.name\
from (select site_id\
from writer\
inner join writer_page on writer_page.writer_id = writer.writer_id ) as tbl\
inner join book_detail on book_detail.site_id = tbl.site_id\
inner join writer on book_detail.site_id= writer.site_id\
inner join writer_page on writer_page.writer_id = writer.writer_id"
return pandas_sql(mysql, query)


def get_publisher_translator(mysql: MySQLConnection) -> pd.DataFrame:
query = "SELECT p.name AS publisher_name, tp.name AS translator_name, MAX(translation_count) AS book_count\
FROM publisher AS p\
JOIN book_detail AS bd ON p.id = bd.publisher_id\
JOIN translator AS t ON bd.book_id = t.book_id\
JOIN translator_page AS tp ON t.translator_id = tp.translator_id\
JOIN(SELECT p.id AS publisher_id, t.name AS translator_name, COUNT(*) AS translation_count\
FROM publisher AS p\
JOIN book_detail AS bd ON p.id = bd.publisher_id\
JOIN translator AS tr ON bd.book_id = tr.book_id\
JOIN translator_page AS t ON tr.translator_id = t.translator_id\
GROUP BY p.id, t.name) AS translator_counts ON p.id = translator_counts.publisher_id\
AND tp.name = translator_counts.translator_name\
GROUP BY p.name\
ORDER BY book_count desc"
return pandas_sql(mysql, query)


def get_publisher_genres(mysql: MySQLConnection) -> pd.DataFrame:
query = "SELECT t.name AS genre_name,p.name AS best_publisher_name,MAX(book_count) AS max_book_count\
FROM tags AS t\
JOIN book_tag AS bt ON t.id = bt.tag_id\
JOIN book_summary AS bs ON bt.site_id = bs.site_id\
JOIN book_detail AS bd ON bs.site_id = bd.site_id\
JOIN publisher AS p ON bd.publisher_id = p.id\
JOIN(SELECT t.id AS tag_id, p.id AS publisher_id,COUNT(*) AS book_count,ROW_NUMBER() OVER (PARTITION BY t.id ORDER BY COUNT(*) DESC) AS row_num\
FROM tags AS t\
JOIN book_tag AS bt ON t.id = bt.tag_id\
JOIN book_summary AS bs ON bt.site_id = bs.site_id\
JOIN book_detail AS bd ON bs.site_id = bd.site_id\
JOIN publisher AS p ON bd.publisher_id = p.id\
GROUP BY t.id, p.id\
) AS max_counts ON t.id = max_counts.tag_id AND p.id = max_counts.publisher_id\
GROUP BY t.name\
limit 20;"
return pandas_sql(mysql, query)
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