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# Import libaries
from PIL import Image
import pandas as pd
from PIL import Image, ImageOps, ImageDraw
from PIL import ImageFont
from barcode import EAN13
from barcode.writer import ImageWriter

# Import the file
df = pd.read_excel('label information.xlsx')

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# Bar Plot: split per lines per orders
fig, ax = plt.subplots(figsize=(12, 6))
df_lior.plot.bar(figsize=(10, 6), edgecolor='black', x='WEEK', y=COLS_IN[0], color='tab:blue', legend= True, ax = ax)
df_lior.plot.bar(figsize=(10, 6), edgecolor='black', x='WEEK', y=COLS_IN[1], color='tab:red', legend= True, ax = ax)
df_lior.plot.bar(figsize=(10, 6), edgecolor='black', x='WEEK', y=COLS_IN[2], color='tab:orange', legend= True, ax = ax)
df_lior.plot.bar(figsize=(10, 6), edgecolor='black', x='WEEK', y=COLS_IN[3], color='darkblue', legend= True, ax = ax)
df_lior.plot.bar(figsize=(10, 6), edgecolor='black', x='WEEK', y=COLS_IN[4], color='brown', legend= True, ax = ax)
df_lior.plot.bar(figsize=(10, 6), edgecolor='black', x='WEEK', y=COLS_IN[5], color='grey', legend= True, ax = ax)
plt.xlabel('Week', fontsize = 14)
plt.ylabel('Number of Orders', fontsize = 14)

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# Add Analysis lines
total_orders, LIST_ANALYSIS = plot_split(df_lior)
# Create a slide
slide = prs.slides.add_slide(image_slide_layout)
shapes = slide.shapes
# Create Title
title_shape = shapes.title
title_shape.text = 'Order Profile'
# Add Image

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'''Slides Analysis per Week'''
for WEEK in LIST_WEEKS:
    
    # Create Plot
    avg_ratio, max_ratio, busy_day, max_lines, total_lines = analysis_week(df_day, WEEK)

    # Create a slide
    slide = prs.slides.add_slide(image_slide_layout)
    shapes = slide.shapes
    # Create Title

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# Create the presentation object
prs = Presentation()

# Layout Choice for the introduction slide
image_slide_layout = prs.slide_layouts[5]
page = 1

'''Slide Introduction'''
# Create the slide
title_slide_layout = prs.slide_layouts[0]

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Order Time,Order Date,City,Store,#Shipment,Order Amount,Transmission OnTime,Transmission,Start PickPack,Pickpack,Loading,Expected Loading Date,Loading OnTime,Loading Date,Airport Arrival,Airport OnTime,Airport Arrival Date,Takeoff,Landing,Landing Date,Landing OnTime,Start Clearance,End Clearance,Leaving Airport,Store Arrival,Store Arrival Date,Delivery OnTime,Delivery Time,Extraction Time,Last Status
2021-05-02 17:00:00.000000,2021-05-02,CITY1,CITY1/ST8,2021-05-02/CITY1/ST8/1,9538,False,2021-05-03 17:00:00.000000,2021-05-04 07:00:00.000000,2021-05-04 15:08:01.811817,2021-05-04 19:00:00.000000,2021-05-04,True,2021-05-04,2021-05-04 22:28:26.955442,True,2021-05-04,2021-05-05 06:00:00.000000,2021-05-05 18:45:10.610100,2021-05-05,True,2021-05-06 09:00:00.000000,2021-05-06 11:14:17.533875,2021-05-06 12:07:20.920092,2021-05-06 17:01:17.840106,2021-05-06,False,2021-05-07 16:30:00.000000,2021-05-11 10:00:00,Delivery Time
2021-05-09 12:00:00.000000,2021-05-09,CITY2,CITY2/ST9,2021-05-09/CITY2/ST9/2,5735,True,2021-05-09 

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from gtts import gTTS
import pandas as pd
import xlrd

def do_TTS(hanzi):
    tts = gTTS(text=hanzi, lang='zh-CN')
    # Filename
    filename = hanzi[0:10] + '.mp3'
    # Save
    tts.save(filename)

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import pandas as pd
import jieba, itertools

def to_pinyin(sentence):
    segments = jieba.cut(sentence)
    output = " ".join(segments)
    pinyined = pinyin(output)
    combined = list(itertools.chain.from_iterable(pinyined))
    return ''.join(combined)
# Import

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import PyPDF2

# Open the report
pdfFileObj = open('example.pdf', 'rb')

# Launch pdf reader object
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)

# number of pages in pdf
n_pages = pdfReader.numPages)