samirsaci

import win32com.client
import os
from datetime import datetime, timedelta

# Initiate the Outlook Session
outlook = win32com.client.Dispatch('outlook.application')
mapi = outlook.GetNamespace("MAPI")

# Select the folder 6 to get the emails
inbox = mapi.GetDefaultFolder(6)

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# Message Object
msg = MIMEMultipart()
msg['Subject'] = 'Workload Report for {}'.format(WEEK)
msg['From'] = from_mail
msg['To'] = ', '.join([from_mail, to_mail])
msg.preamble = 'Workload Report for {}'.format(WEEK)

# Attach the HTML code
msg.attach(MIMEText(html_string, 'html', 'utf-8'))

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# Add the insights
html_string = html_string.replace("WEEK", WEEK)
html_string = html_string.replace("total_lines", total_lines)
html_string = html_string.replace("busy_day", busy_day)
html_string = html_string.replace("max_lines", max_lines)
html_string = html_string.replace("avg_ratio", avg_ratio)
html_string = html_string.replace("max_ratio", max_ratio)

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# Open the visual
with open(file_img, 'rb') as fp:
    img = MIMEImage(fp.read())
    img.add_header('Content-Disposition', 'attachment', filename=file_img)
    img.add_header('X-Attachment-Id', '0')
    img.add_header('Content-ID', '<0>')
    fp.close()
    msg.attach(img)

# Open the header

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# save plot
filename = 'visual' + ".png"
path_plot = filename
fig.savefig(path_plot, dpi=fig.dpi)

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# Lines per orders
avg_ratio = '{:.2f} lines/order'.format(df_plot['LINES/ORDER'].mean())
max_ratio = '{:.2f} lines/order'.format(df_plot['LINES/ORDER'].max())

# Maximum Day Lines
busy_day = dict_days[df_plot.set_index('DAY')['LINES'].idxmax()]
max_lines = '{:,} lines'.format(df_plot['LINES'].max())

# Total Workload
total_lines = '{:,} lines'.format(df_plot['LINES'].sum())

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# Bar Plot: Orders/Lines
fig, ax = plt.subplots(figsize=(14, 7))
df_plot.plot.bar(figsize=(8, 6), edgecolor='black', x='DAY', y=['ORDERS', 'LINES'], 
                                           color=['tab:blue', 'tab:red'], legend= True, ax = ax)
plt.xlabel('DAY', fontsize = 12)
plt.title('Workload per day (Lines/day)', fontsize = 12)
plt.show()

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samirsaci

samirsaci

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image, ImageDraw, ImageChops, ImageFont
import io