uweziegenhagen.de

from jinja2 import Environment, BaseLoader
 
myString = 'öäü{{hello}}'
 
template = Environment(loader=BaseLoader).from_string(myString)
 
with open('render2.tex','wb') as output:
    x = template.render(hello='ÖÜÄ')
    output.write(x.encode('utf-8'))

import toml # handle toml files
import sqlite3
from datetime import datetime
import time
 
 
settings = toml.load('settings.toml')
dbfilename = settings['dbfilename'] 
 
conn = sqlite3.connect(":memory:")
c = conn.cursor()
 
with conn:
    c.execute(
        """
    create table if not exists
        contacts (id integer primary key, 
                  personid integer, 
                  validfrom text, 
                  validto text,
                  firstname text,
                  lastname text,
                  phonenumber text);
    """
    )
 
    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
    c.execute(f"INSERT INTO contacts (personid, validfrom, validto, firstname, lastname, phonenumber) values (1,'{now}','9999-12-31 23:59:59','Mickey','Mouse','0123-456')")
    c.execute(f"INSERT INTO contacts (personid, validfrom, validto, firstname, lastname, phonenumber) values (2,'{now}','9999-12-31 23:59:59','Donald','Duck','0123-123')")
 
    time.sleep(6)
    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
    c.execute(f"UPDATE contacts set validto = '{now}' where id = 1")
 
    time.sleep(6)
    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
    c.execute(f"INSERT INTO contacts (personid, validfrom,validto, firstname, lastname, phonenumber) values (1, '{now}','9999-12-31 23:59:59','Mickey','Mouse','0123-789')")
 
 
    result = c.execute(f"select * from contacts where validto > '2023-12-31';").fetchall()
 
    for row in result:
        print(row)

import pip
 
def install(package):
    if hasattr(pip, 'main'):
        pip.main(['install', package])
    else:
        pip._internal.main(['install', package])
 
 
# Beispiel für spyder ide
if __name__ == '__main__':
    install('spyder')

import re
 
s = 'a     b     c'
 
print(re.sub('\s+',' ',s))

import re
buffer = open('./Report.xml','r').read()
 
results = re.findall(r"(<expression>)(.*)(</expression>)",buffer,re.MULTILINE)
 
for result in results:
    expression = result[1]
    opened = expression.count('(')
    closed = expression.count(')')
 
    if opened != closed:
        print(expression)

import pandas as pd
import Levenshtein
 
df = pd.read_excel('Daten.xlsx')
df = df.sort_values(by=['Name'])
df = df.reset_index(drop=True)
 
dfs= df.shift() # Shift df by one row
dfs = dfs.rename(columns={'Name': 'Nameshifted'})
 
df_combined = pd.concat([df,dfs],axis=1) # combine original and shifted df
df_combined = df_combined.fillna('') # remove NaNs
 
for index, row in df_combined.iterrows():
    df_combined.loc[index,'Ratio'] = (Levenshtein.ratio(row['Name'], row['Nameshifted']))
    df_combined.loc[index,'Distance'] = (Levenshtein.distance(row['Name'], row['Nameshifted']))    
 
print(df_combined)

import os
 
for (root,dirs,files) in os.walk('.'):
 
    for file in files:
        fullpath = os.path.join(root,file)
 
        if fullpath.endswith('.txt'):
            newpath = root+'\\'+root[2:].replace('\\','_')+'_'+file
            print(newpath)
            os.rename(fullpath, newpath)

import matplotlib.pyplot as plt
import numpy as np
 
ax = plt.gca()
plt.gca().set_aspect('equal')
 
ax.set_xticks(range(-6,6,1))
ax.set_yticks(range(-6,6,1))
ax.set_xlim([-5, 5])
ax.set_ylim([-5, 5])
 
ax.spines['top'].set_color('none')
ax.spines['bottom'].set_position('zero')
ax.spines['left'].set_position('zero')
ax.spines['right'].set_color('none')
 
x = np.linspace(-5,5,100)
y = 2*x+1
y2 = -0.5*x-2
 
plt.plot(x, y,  'r', label='2*x+1')
plt.plot(x, y2, 'g', label='-0.5*x-2')
 
plt.title('Linear Plots')
 
plt.legend(loc='upper left')
 
plt.grid()
plt.show()

<?xml version='1.0' encoding='UTF-8'?>
	<table name="Tablename">
	{% for _,row in data.iterrows() %}
	<ROW>
    <COLUMN1>{{row['column1']}}</COLUMN1>
    <COLUMN2>{{row['column2']}}</COLUMN2>
    <COLUMN3>{{row['column3']}}</COLUMN3>
	</ROW>
	{% endfor %}
</table>

import pandas as pd # data wrangling
import jinja2 # template engine
import os # for file-related stuff
 
# create jinja env that can load template from filesystem
jinja_env = jinja2.Environment(loader = jinja2.FileSystemLoader(os.path.abspath('.')))
 
df = pd.read_excel('Daten.xlsx')
template = jinja_env.get_template('template.xml')
 
with open('FertigesXML.xml','w') as output:
    output.write(template.render(data=df))

import sys
import collections
import pandas as pd
from tabulate import tabulate
 
 
file1 = pd.read_csv('file1.csv', sep=';', encoding='UTF-8')
file2 = pd.read_csv('file2.csv', sep=';', encoding='UTF-8')
 
columnnames1 = list(file1)
columnnames2 = list(file2)
 
if collections.Counter(columnnames1) == collections.Counter(columnnames2):
    print ("Number of columns and Names match, Comparison possible...\n\n")
else:
    print ("Number of columns and Names are not matching!!! Please check the input!")
    sys.exit('Error!')
 
# add suffixes to distinguish between actual and expected in the merger
file1 = file1.add_suffix('_e') # expected
file2 = file2.add_suffix('_t') # t
 
 
# merge them using the given key, use outer join
comparison = pd.merge(file1,file2, how='outer',
                      left_on=['Key_e'],
                      right_on=['Key_t'])
 
# create the columnwise comparison
for col in columnnames1:
    comparison[(col + '_c')] = comparison[(col + '_t')] == comparison[(col + '_e')]
 
# reorder the columns
comparison=comparison.reindex(sorted(comparison.columns),axis=1)
 
print(tabulate(comparison, tablefmt="pipe", headers="keys"))
 
 
# save the result as Excel file
comparison.to_excel('result.xlsx')
 
# names of the comparison column
check_colnames= [s + '_c' for s in columnnames1]
 
# initialize an empty dataframe for the log
logdf=pd.DataFrame(index=[True,False])
 
for column in check_colnames:
    t=comparison[column].value_counts() # returns a series
    tt=pd.DataFrame(t) # makes a DF out of the series
    logdf = logdf.join(tt,how='outer') # join the two dfs
 
# transpose for better readability
logdf = logdf.transpose()
 
# Ensure fixed sequence of the columns
logdf=logdf.reindex(sorted(logdf.columns),axis=1)
 
# write to disk
logdf.to_excel('logfile.xlsx')
 
# for better viewing on the screen
logdf.fillna('-',inplace=True)
pd.options.display.float_format = '{:,.0f}'.format
 
print(tabulate(logdf, tablefmt="pipe", headers="keys"))