11 liens privés
1 ls
2 cd crypto1_bs/
3 ls
4 cat txttobin.py
5 cat README.md
6 ls
7 patch -p1 < ../crypto1_bs.diff
8 ls
9 make get_craptev1
10 make
11 l
12 ls
13 mkdir crapto1-v3.3
14 craptev1-v1.1
15 mkdir craptev1-v1.1
16 ls
17 cd .;
18 cd ..
19 ls
20 sudo ./miLazyCrackerFreshInstall.sh
21 ls
22 cd crypto1_bs/
23 ls
24 mkdir crapto1-v3.3
25 mkdir craptev1-v1.1
26 ls
27 make
28 sudo make
29 ls
30 ./libnfc_crypto1_crack
31 miLazyCracker
32 nfc-list
33 modprobe -r pn533_usb
34 nfc-list
35 miLazyCracker
36 ./libnfc_crypto1_crack a0a1a2a3a4a5 32 A 32 B
37 cd
38 ls
39 mfoc -O badge_a_copier.dmp
40 mfoc -O badge_a_copier.dmp -k 415a54454b4d
41 ls
42 ls -lha
43 scp badge_a_copier.dmp pi@192.168.1.4:/home/pi
44 ls
45 mfoc -P 500 -O carte-vierge.dmp
46 nfc-mfclassic W a badge_a_copier.dmp carte-vierge.dmp
47 history
livetvru
rojadirect
streammonsport
https://www.lacasadeltikitakatv.net
df = pd.read_csv(r"C:\Users\micault.DOMPHILYO1\Downloads\nat2017_txt\nat2017.txt", sep='\t')
df2 = df[df.annais != 'XXXX']
df2.annais = df2.annais.astype('int64')
df3 = df2[df2.sexe == 2].groupby(['sexe', 'preusuel'], as_index = False).sum().sort_values(by='nombre', ascending=False).iloc[0:600,]
import sqlite3, random
con = sqlite3.connect("/home/pi/django/prenoms/prenoms/db.sqlite3")
d= con.execute('SELECT * from main_prenoms WHERE voted = 0 AND id = ' + str(random.randrange(6,605)))
res= d.fetchone()
con.execute("UPDATE main_prenoms SET voted = 1 WHERE prenom = '" + res[1] + "'")
string_html = 'http://127.0.0.1:8000/main/?prenom=' + res[1] + '&user=caro&token=petitpepin'
echo $'Vote pour http://127.0.0.1:8000/main/?prenom=HELENA=&user=caro&token=petitpepin \n balala' | mail -s "test" micaultanthony@gmail.com
pour installer ubuntu :
enable uefi
et ppour booter sur la clé USB NE PAS FAIRE F2 mais F7 pour sélectionner la clé
SPEDIFEN
import pandas as pd
df = pd.read_csv(r"C:\Users\micault.DOMPHILYO1\Documents\Perso\temp.csv", header= None, index_col =1)
df.drop(0, axis=1, inplace=True)
df.columns = ['temp', 'temp_dehors', 'conso_maison']
df.index = pd.to_datetime(df.index)
import numpy as np
df.replace('\N',np.nan, inplace = True)
df.temp.astype('float64')
df.temp = df.temp.astype('float64')
df.temp_dehors = df.temp_dehors.astype('float64')
df.conso_maison = df.conso_maison.astype('float64')
from matplotlib import pyplot as plt
df2 = df.resample("M").mean()
plt.plot_date(df2.index, df2.temp_dehors)
plt.plot_date(df2.index, df2.conso_maison)
plt.show()
data table html