Plot, heating curve fit and libraries needed

fit_heating_curve.py

import csv
import numpy as np
from scipy.optimize import curve_fit
from sys import argv

csvfile = open(argv[1], 'r')

linhas = csv.DictReader(csvfile)

Y, t = [], []
for linha in linhas:
    t.append(float(linha['tempo']))
    Y.append(float(linha['temperatura']))
Y, t = np.array(Y), np.array(t)

temperatura_aquecimento = lambda t, T_0, T_F, alpha : T_0 + (T_F - T_0) * (1 - np.exp(-alpha * t))
T_0, T_F, alpha = curve_fit(temperatura_aquecimento, t, Y)[0]
print(str(round(T_0, 2)) + ' + ' + str(round(T_F - T_0, 2)) + ' * (1 - e^(-' + str(round(alpha,4)) + 't))')

plot.py

import csv
from matplotlib import pyplot as plot
from sys import argv
filename = argv[1]

csvfile = open(filename, 'r')
linhas = csv.DictReader(csvfile)

tempo = []
temperatura = []

for linha in linhas:
    tempo.append(float(linha['tempo']))
    temperatura.append(float(linha['temperatura']))

csvfile.close()
plot.plot(tempo, temperatura)

if len(argv) == 3:
    filename = argv[2]
    csvfile = open(filename, 'r')
    linhas = csv.DictReader(csvfile)

    tempo = []
    temperatura = []
    for linha in linhas:
        tempo.append(float(linha['tempo']))
        temperatura.append(float(linha['temperatura']))
    csvfile.close()
    plot.plot(tempo, temperatura)

requirements.txt

backcall==0.1.0
cycler==0.10.0
decorator==4.4.2
ipython==7.13.0
ipython-genutils==0.2.0
jedi==0.16.0
kiwisolver==1.1.0
matplotlib==3.2.1
numpy==1.18.2
parso==0.6.2
pexpect==4.8.0
pickleshare==0.7.5
prompt-toolkit==3.0.5
ptyprocess==0.6.0
Pygments==2.6.1
pyparsing==2.4.6
pyserial==3.4
python-dateutil==2.8.1
scipy==1.4.1
six==1.14.0
traitlets==4.3.3
wcwidth==0.1.9