def main():
"""Create DataFrame from markdown files, split dataframes
by habit name, create plots, and add plots to PDF
"""
config = configparser.ConfigParser()
config.read('config.ini')
# Directories need to exist
habit_dir = config.get('Directories', 'md_dir')
save_dir = config.get('Directories', 'pdf_save_dir')
color_heatmap_border = config.get('Plots', 'color_heatmap_border')
color_low = config.get('Plots', 'color_low')
color_high = config.get('Plots', 'color_high')
color = config.get('Plots', 'color')
font = config.get('Plots', 'font')
habitlist = md_file_list(habit_dir)
df_list = get_df_list(habitlist, habit_dir)
plotslist = get_plot_list(df_list, color, color_low, color_high,
color_heatmap_border, font, save_dir)
pdf.create_pdf(plotslist, save_dir, get_date())
delete_lists = [x[2] for x in plotslist]
for delete_list in delete_lists:
delete_files(delete_list)
def create_wishlist_pdf():
"""Creates and downloads pdf of user wishlist"""
if g.user:
html = request.form['wished-html']
create_pdf(html, g.user.username)
path = f"wishlists\\{g.user.username}.pdf"
return send_file(path, as_attachment=True)
else:
return "no logged in user"
def get_reports():
"""Route for reports."""
if 'Content-Type' in request.headers and request.headers[
'Content-Type'] in app.config['SUPPORTED_CONTENT_TYPE']:
if request.headers['Content-Type'] == 'application/pdf':
ext = 'pdf'
elif request.headers['Content-Type'] == 'text/xml':
ext = 'xml'
elif request.headers['Content-Type'] == 'application/json':
ext = 'json'
elif 'format' in request.args and request.args['format'] in app.config[
'SUPPORTED_FORMAT']:
ext = request.args['format']
else:
ext = 'json'
cmd = "SELECT * FROM reports;"
# execut the cmd for fetch the correct data.
cursor.execute(cmd)
# fetch the data from the Database.
data = cursor.fetchall()
if not data:
return not_found()
# clean the data
jdata = list(map(decode_data, data))
if ext == 'pdf':
# Generate the pdf
pdf, filename = create_pdf('all', jdata)
# Set the pdf data as responce
resp = make_response(pdf)
# Set the header as pdf
resp.headers["Content-Type"] = 'application/pdf'
return resp
if ext == 'xml':
print('jData: ', jdata)
# Create the xml
xml = dicttoxml(jdata, custom_root='Reports', attr_type=False)
# Set the xml data as responce
resp = make_response(xml)
# Set the header as xml
resp.headers["Content-Type"] = 'text/xml'
return resp
if ext == 'json':
# Create the json
resp = make_response(json.dumps(jdata))
# Set the header as json
resp.headers["Content-Type"] = 'application/json'
return resp
return "Nay!", 202
def main(cat_list,basic,etf,div):
#generate portfolio on preferences
portfolio = create_portfolio(cat_list=cat_list,basic=basic,etf=etf,div=div)
#yields of portfolio
yields = portfolio.iloc[:,3:8].sum().round(2)
#plot history of this portfolio
perf=plot_port_history(yields)
perf = round(perf,4) * 100
#plot Pie Chart of portfolio allocation by Stocks
weight = portfolio.loc[:,['Wertpapier','Weight']]
create_pie(weight)
#plot pie chart of portfolio allocation by cat
cat_alloc= portfolio.loc[:,['Wertpapier','Weight','Kategorie']]
create_pie_cat(cat_alloc)
# sets up the parsing of arguments to the create pdf function
stocks= portfolio['Wertpapier'].tolist()
weights = portfolio['Weight'].tolist()
yd=yields.values.reshape(-1, 1)
yr =[2015,2016,2017,2018,2019]
#create pdf
create_pdf(stocks,weights,yd,yr,perf)
def create(albumData):
pdf = create_pdf(html_doc(albumData))
return pdf
def create(albumData): pdf = create_pdf(html_doc(albumData)) return pdf
line_thickness=8,
min_score_thresh=0.60)
c += 1
if c >= 10:
if (np.squeeze(scores)[0] > 0.5) & (np.squeeze(classes)[0] == 1):
cv2.putText(frame, "Pass!", (100, 100), cv2.FONT_HERSHEY_SIMPLEX,
2, (0, 128, 0))
if flagjer == False:
#cv2.imwrite('C:/Tensorflow/models/research/object_detection/zresult/image%d.jpg' % count, frame)
cv2.imwrite(
'C:/Tensorflow/models/research/object_detection/zresult/image.jpg',
frame)
#count += 1
flagjer = True
pdf.create_pdf()
mailpdf.send_mail()
elif np.squeeze(scores)[0] < 0.5:
flagjer = False
c = 0
#print(np.squeeze(classes)[0])
#print(np.squeeze(scores)[0])
#print(f"Classes: {classes}"+"is Found")
#print(f"cate: {category_index}"+"is Found")
# All the results have been drawn on the frame, so it's time to display it.
cv2.imshow('Object detector', frame)
# Press 'q' to quit
from spider import Spider
from pdf import create_pdf
url = sys.argv[1]
spider = Spider(url)
print('书名：', spider.book.name)
print('作者：', spider.book.author)
print('类型：', spider.book.bookType)
print('简介：', spider.book.description)
isExist = os.path.exists(spider.book.name)
if not isExist:
print('{0}文件夹不存在，自动创建...'.format(spider.book.name))
os.makedirs(spider.book.name)
print('{0}文件夹创建成功！'.format(spider.book.name))
for p in spider.book.content:
story = p['part'] + '\n' + '---------------' + '\n'
print(story)
for charpter in p['charpters']:
story += charpter['title'] + '\n' + \
charpter['content'] + '\n' + '---------------' + '\n'
filePath = '{0}/{1}.pdf'.format(spider.book.name.strip(),
p['part'].strip())
create_pdf(story, filePath)
print('pdf导出完成')