In a previous article (Python tools for developing secure and quality code) I covered tools that make it easier to comply with Python's PEP8, improve code security and format it; in that case circle-ci was used for the evaluations.

In this article the evaluation will be done before pushing code to a git repository. The article is based on the following articles:

The tools explained in the previous article will be covered again.

The code that will be evaluated is the following (it does not pass the checks):


import numpy as np
from scipy import signal as sp
import matplotlib.pylab as plt
import scipy.signal as signal
import scipy.stats as stats
import streamlit as st


def u(amplitud, t):
    """Función escalón unitario

    Args:
        amplitud (int): Amplitud del escalon
        t (list): Lista de tiempo

    Returns:
        list: Lista de valores
    """
    return amplitud*np.piecewise(t, [t < 0.0, t >= 0.0], [0, 1])


def OndaCuadrada(amplitud, t, fs=1):
    """Función  de Onda Cuadrada

    Args:
        amplitud (int): Amplitud de la segnal
        t (list): Lista de valores de tiempo
        fs (int, optional): Frecuencia.. Defaults to 1.

    Returns:
        list: Lista de valores
    """
    return ((sp.square(2 * fs*t)) * (amplitud / 2.0)) + (amplitud / 2.0)


def segnal_triangular(amplitud, simetria, t, fs=1):
    """Señal triangular 

    Args:
        amplitud (int): Amplitud de la señal
        simetria (float): simetria de la señal
        t (list): Lista de valores que definen el tiempo.
        fs (int, optional): Frecuencia de la señal. Defaults to 1.

    Returns:
        list: Lista de valores de la señal
    """
    return amplitud*(signal.sawtooth(2 * np.pi * fs * t, simetria))


def seno(amplitud, t, fs=1):
    """ Onda Seno

    Args:
        amplitud (int): Amplitud de la señal
        t (list): Lista de valores de tiempo
        fs (int, optional): Frecuencia de la señal. Defaults to 1.

    Returns:
        list: Lista de valores de la señal de seno
    """
    return amplitud*np.sin(fs*t)


def coseno(amplitud, t, fs=1):
    """Señal de coseno

    Args:
        amplitud (int): Amplitud de la señal
        t (list): lista de valores para generar la señal
        fs (int, optional): Frecuencia de la señal. Defaults to 1.

    Returns:
        list: Lista de valores de la señal
    """
    return amplitud*np.cos(fs*t)


def tiempo(lim_inf, lim_sup, n):
    """Lista de valores que definen el tiempo de la señal

    Args:
        lim_inf (int): Límite inferior del tiempo 
        lim_sup (int): Límite superior del tiempo
        n (int): Cantidad de valores a generar del tiempo

    Returns:
        list: Lista de valores del tiemmpo
    """
    return np.linspace(lim_inf, lim_sup, n)


def plot_signal(xi, xf, yi, yf, t, titulo, etiqueta, values):
    """Generación de la gráfica de la señal.

    Args:
        xi (int): x inicial
        xf (int): x final
        yi (int): y inicial
        yf (int): y final
        t (list): lista de valores de tiempo
        titulo (str): Título de la gráfica
        etiqueta (str): Etiqueta de la señal.
        values (list): Valores de la señal 
    """
    plot(t, values, 'k', label=etiqueta, lw=2)
    xlim(xi, xf)


def main():
    # Definir título
    st.title("Generación de gráficas de señales")
    st.sidebar.header("Entradas:")
    segnales = ["Escalon Unitario", "Onda Cuadrada",
                "Onda triangular", "Seno", "Coseno"]

    resp = st.sidebar.selectbox("Tipo de señal", segnales)

    st.sidebar.header("Definición del tiempo:")
    st.sidebar.subheader("Rango")
    # SelectBox
    t0 = int(st.sidebar.selectbox(
        "", range(0, 10)
    ))
    ti = 0
    tf = t0
    n = 10000
    t = tiempo(ti, tf, n)
    st.sidebar.subheader("Amplitud de la señal")
    amplitud = int(st.sidebar.selectbox(
        "", range(1, 10)
    ))

    # numpy.ndarray
    if resp == "Escalon Unitario":
        ti = -tf
        resultado = u(amplitud, t)
    elif resp == "Onda Cuadrada":
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox(
            "", range(1, 11)
        ))
        resultado = OndaCuadrada(amplitud, t, fs)
    elif resp == "Onda triangular":
        simetria = 0.5
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox(
            "", range(1, 11)
        ))
        resultado = segnal_triangular(amplitud, simetria, t, fs)
    elif resp == "Seno":
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox(
            "", range(1, 11)
        ))
        resultado = seno(amplitud, t, fs)
    elif resp == "Coseno":
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox(
            "", range(1, 11)
        ))
        resultado = coseno(amplitud, t, fs)
    else:
        resultado = 0
        st.error("Error")

    fig = plt.figure()
    ax = fig.add_subplot(111)
    st.header(f"Gráfica de {resp}")
    ax.plot(t, resultado)
    ax.set_xlim(ti, tf)
    ax.set_xlabel("Tiempo")
    ax.set_ylabel("f(t)")
    ax.set_ylim(2*amplitud*-1, 2*amplitud)
    st.pyplot(fig)


if __name__ == "__main__":
    main()

Its requirements file is the following:

streamlit==0.70.0
scipy==1.5.4
numpy==1.19.3
matplotlib==3.3.3

Its initial file structure is the following (including hidden files):

signals_fft_streamlit
├── .git
│   ├── branches
│   ├── config
│   ├── description
│   ├── HEAD
│   ├── hooks
│   │   ├── applypatch-msg.sample
│   │   ├── commit-msg.sample
│   │   ├── fsmonitor-watchman.sample
│   │   ├── post-update.sample
│   │   ├── pre-applypatch.sample
│   │   ├── pre-commit.sample
│   │   ├── pre-merge-commit.sample
│   │   ├── prepare-commit-msg.sample
│   │   ├── pre-push.sample
│   │   ├── pre-rebase.sample
│   │   ├── pre-receive.sample
│   │   └── update.sample
│   ├── index
│   ├── info
│   │   └── exclude
│   ├── logs
│   │   ├── HEAD
│   │   └── refs
│   │       ├── heads
│   │       │   └── main
│   │       └── remotes
│   │           └── origin
│   │               └── HEAD
│   ├── objects
│   │   ├── info
│   │   └── pack
│   │       ├── pack-a6d9863d11286fbea66f5aafa93a9dbafaf3f4fc.idx
│   │       └── pack-a6d9863d11286fbea66f5aafa93a9dbafaf3f4fc.pack
│   ├── packed-refs
│   └── refs
│       ├── heads
│       │   └── main
│       ├── remotes
│       │   └── origin
│       │       └── HEAD
│       └── tags
├── .gitignore
├── LICENSE
├── README.md
├── requirements.txt
└── src
    └── app.py

In the hooks you can define what runs before a commit using pre-commit, which will be covered later.

Code validation

Linters

Linters are programming tools that check code in any programming language.

Flake8

A tool that checks that the code complies with Python's PEP-8.

It can be installed via pip:

pip install flake8

Run flake8 on the app.py file:

python -m flake8 src/app.py
src/app.py:5:1: F401 'scipy.stats' imported but unused
src/app.py:22:6: N802 function name 'OndaCuadrada' should be lowercase
src/app.py:37:20: W291 trailing whitespace
src/app.py:83:50: W291 trailing whitespace
src/app.py:104:43: W291 trailing whitespace
src/app.py:106:5: F821 undefined name 'plot'
src/app.py:107:5: F821 undefined name 'xlim'

The command output shows the lines of code where there are errors, the type of error and a description of it.

pep8-naming

In addition to flake you can use pep8-naming to comply with PEP8's naming rules.

To install it, use pip:

pip install pep8-naming

Run the same flake8 command; the error message is:

src/app.py:22:6: N802 function name 'OndaCuadrada' should be lowercase

Which already appeared in the previous run.

pycodestyle

It is another PEP-8 validation tool. png

Install it:

pip install pycodestyle

Run it:

pycodestyle src/app.py

In this case, since the flake8 error messages were already fixed, it returns no messages.

pylint

Install it:

pip install pylint

Run it:

pylint src/app.py

Code formatter

It lets you reformat the code so that it complies with a set of standards.

isort

It reorders the imports as follows:

Standard library
Third-party libraries
Local libraries

Install it:

pip install isort

It is used as follows:

isort src/app.py 
Fixing /home/ernesto/proyectos/signals_fft_streamlit/src/app.py

Before, the imports looked like this:


import numpy as np
from scipy import signal as sp
import matplotlib.pylab as plt
import scipy.signal as signal
import scipy.stats as stats
import streamlit as st

Now:


import matplotlib.pylab as plt
import numpy as np
import scipy.signal as signal
import streamlit as st
from scipy import signal as sp

To only check the import order without making the change you can run:

python -m isort src/app.py --check-only

To see the changes without applying them you can use:

python -m isort src/app.py --diff

Black

A code formatter used to reformat code based on the Black code style (broken link), which is very close to PEP-8.

To install it:

pip install black

To check the code without modifying it:

python -m black src/app.py --check  
would reformat src/app.py
Oh no! 💥 💔 💥
1 file would be reformatted.

To see the differences without modifying it (only part of the code is shown):

--- src/app.py	2020-11-15 01:20:29.525556 +0000
+++ src/app.py	2020-11-15 01:29:54.278851 +0000
@@ -13,11 +13,11 @@
         t (list): Lista de tiempo

     Returns:
         list: Lista de valores
     """
-    return amplitud*np.piecewise(t, [t < 0.0, t >= 0.0], [0, 1])
+    return amplitud * np.piecewise(t, [t < 0.0, t >= 0.0], [0, 1])

To make the modifications:

python -m black src/app.py       
reformatted src/app.py
All done! ✨ 🍰 ✨
1 file reformatted.

The code changed to (only part of the code is shown):

def u(amplitud, t):
    """Función escalón unitario

    Args:
        amplitud (int): Amplitud del escalon
        t (list): Lista de tiempo

    Returns:
        list: Lista de valores
    """
    return amplitud * np.piecewise(t, [t < 0.0, t >= 0.0], [0, 1])

Other similar tools are YAPF and autopep8

Security vulnerability scanning

There are tools that evaluate the security vulnerabilities of the code and its dependencies.

Bandit

Bandit is a tool designed to find security issues in Python code.

Install it:

pip install bandit

Run it as follows:

bandit -r src/app.py 
[main]	INFO	profile include tests: None
[main]	INFO	profile exclude tests: None
[main]	INFO	cli include tests: None
[main]	INFO	cli exclude tests: None
[main]	INFO	running on Python 3.8.3
Run started:2020-11-15 01:44:06.048642

Test results:
	No issues identified.

Code scanned:
	Total lines of code: 119
	Total lines skipped (#nosec): 0

Run metrics:
	Total issues (by severity):
		Undefined: 0.0
		Low: 0.0
		Medium: 0.0
		High: 0.0
	Total issues (by confidence):
		Undefined: 0.0
		Low: 0.0
		Medium: 0.0
		High: 0.0
Files skipped (0):

As you can see, the code has no security problems.

Safety

Safety is a tool that checks the application's dependencies for security issues.

Install it:

pip install safety

Run it as follows:

safety check
+==============================================================================+
|                                                                              |
|                               /$$$$$$            /$$                         |
|                              /$$__  $$          | $$                         |
|           /$$$$$$$  /$$$$$$ | $$  \__//$$$$$$  /$$$$$$   /$$   /$$           |
|          /$$_____/ |____  $$| $$$$   /$$__  $$|_  $$_/  | $$  | $$           |
|         |  $$$$$$   /$$$$$$$| $$_/  | $$$$$$$$  | $$    | $$  | $$           |
|          \____  $$ /$$__  $$| $$    | $$_____/  | $$ /$$| $$  | $$           |
|          /$$$$$$$/|  $$$$$$$| $$    |  $$$$$$$  |  $$$$/|  $$$$$$$           |
|         |_______/  \_______/|__/     \_______/   \___/   \____  $$           |
|                                                          /$$  | $$           |
|                                                         |  $$$$$$/           |
|  by pyup.io                                              \______/            |
|                                                                              |
+==============================================================================+
| REPORT                                                                       |
| checked 136 packages, using default DB                                       |
+==============================================================================+
| No known security vulnerabilities found.                                     |
+==============================================================================+

To check only the list of packages in requirements.txt, run:

safety check -r requirements.txt
+==============================================================================+
|                                                                              |
|                               /$$$$$$            /$$                         |
|                              /$$__  $$          | $$                         |
|           /$$$$$$$  /$$$$$$ | $$  \__//$$$$$$  /$$$$$$   /$$   /$$           |
|          /$$_____/ |____  $$| $$$$   /$$__  $$|_  $$_/  | $$  | $$           |
|         |  $$$$$$   /$$$$$$$| $$_/  | $$$$$$$$  | $$    | $$  | $$           |
|          \____  $$ /$$__  $$| $$    | $$_____/  | $$ /$$| $$  | $$           |
|          /$$$$$$$/|  $$$$$$$| $$    |  $$$$$$$  |  $$$$/|  $$$$$$$           |
|         |_______/  \_______/|__/     \_______/   \___/   \____  $$           |
|                                                          /$$  | $$           |
|                                                         |  $$$$$$/           |
|  by pyup.io                                              \______/            |
|                                                                              |
+==============================================================================+
| REPORT                                                                       |
| checked 4 packages, using default DB                                         |
+==============================================================================+
| No known security vulnerabilities found.                                     |
+==============================================================================+

Static typing verification

Since Python 3.7, Python supports, as a form of documentation, the definition of the types of a function's output and its arguments, and there are now tools that verify static typing.

Mypy

Mypy is an optional static type checker for Python that aims to combine the benefits of dynamic (or "duck") typing and static typing.

Install it:

pip install mypy

Use it:

mypy src/app.py 
src/app.py:1: error: No library stub file for module 'matplotlib.pylab'
src/app.py:1: note: (Stub files are from https://github.com/python/typeshed)
src/app.py:1: error: No library stub file for module 'matplotlib'
src/app.py:2: error: No library stub file for module 'numpy'
src/app.py:3: error: No library stub file for module 'scipy.signal'
src/app.py:3: error: No library stub file for module 'scipy'
src/app.py:4: error: Cannot find module named 'streamlit'
src/app.py:4: note: See https://mypy.readthedocs.io/en/latest/running_mypy.html#missing-imports

To ignore these errors use # type: ignore, as shown below:


import matplotlib.pylab as plt  # type: ignore
import numpy as np  # type: ignore
import scipy.signal as signal  # type: ignore
import streamlit as st  # type: ignore
from scipy import signal  # type: ignore

Run it again and those initial errors no longer appear.

An example of static typing is shown below:


def u(amplitud: int, t: np.ndarray) -> np.ndarray:
    """Función escalón unitario

    Args:
        amplitud (int): Amplitud del escalon
        t (np.ndarray): Lista de tiempo

    Returns:
        np.ndarray: Lista de valores
    """
    return amplitud * np.piecewise(t, [t < 0.0, t >= 0.0], [0, 1])

def onda_cuadrada(amplitud: int, t: np.ndarray, fs: int = 1) ->np.ndarray:
    """Función  de Onda Cuadrada

    Args:
        amplitud (int): Amplitud de la segnal
        t (list): Lista de valores de tiempo
        fs (int, optional): Frecuencia.. Defaults to 1.

    Returns:
        list: Lista de valores
    """
    return ((sp.square(2 * fs * t)) * (amplitud / 2.0)) + (amplitud / 2.0)

Another way to ignore all errors is the following:

#!/usr/bin/env python 
#-*- coding: utf-8 -*-
# mypy: ignore-errors

Documentation validation

pydocstyle

pydocstyle is a tool that validates the format of the documentation.

Install it:

pip install pydocstyle

Use it:

pydocstyle src/app.py 
src/app.py:1 at module level:
        D100: Missing docstring in public module
src/app.py:9 in public function `u`:
        D400: First line should end with a period (not 'o')
src/app.py:22 in public function `onda_cuadrada`:
        D400: First line should end with a period (not 'a')
src/app.py:36 in public function `segnal_triangular`:
        D205: 1 blank line required between summary line and description (found 0)
src/app.py:36 in public function `segnal_triangular`:
        D400: First line should end with a period (not 'r')
src/app.py:50 in public function `seno`:
        D400: First line should end with a period (not 'o')
src/app.py:64 in public function `coseno`:
        D400: First line should end with a period (not 'o')
src/app.py:78 in public function `tiempo`:
        D205: 1 blank line required between summary line and description (found 0)
src/app.py:78 in public function `tiempo`:
        D400: First line should end with a period (not 'l')
src/app.py:90 in public function `main`:
        D103: Missing docstring in public function

Cyclomatic Complexity, number of lines of code

There are tools to validate cyclomatic complexity, such as:

In this case wily will be tried

Wily

Wily is an application for tracking the complexity of Python code and applications.

Install it:

pip install wily

You need to index the project by running:

wily build src/
Found 1 revisions from 'git' archiver in '/home/ernesto/proyectos/signals_fft_streamlit'.
Running operators - maintainability,raw,cyclomatic,halstead
Processing |################################| 4/4
Completed building wily history, run `wily report <file>` or `wily index` to see more.

To generate the report for app.py, run:

wily report src/app.py 
Using default metrics ['maintainability.mi', 'raw.loc', 'cyclomatic.complexity', 'halstead.h1']
-----------History for ['maintainability.mi', 'raw.loc', 'cyclomatic.complexity', 'halstead.h1']------------
╒════════════╤════════════════╤════════════╤═════════════════════════╤═════════════════╤═════════════════════════╤═══════════════════╕
│ Revision   │ Author         │ Date       │ Maintainability Index   │ Lines of Code   │ Cyclomatic Complexity   │ Unique Operands   │
╞════════════╪════════════════╪════════════╪═════════════════════════╪═════════════════╪═════════════════════════╪═══════════════════╡
│ f2679c6    │ Ernesto Crespo │ 2020-11-14 │ 68.1377 (0)             │ 153 (0)         │ 12 (0)                  │ 7 (0)             │
╘════════════╧════════════════╧════════════╧═════════════════════════╧═════════════════╧═════════════════════════╧═══════════════════╛

In the report you can pass specific metrics:

wily report src/app.py loc sloc comments --message
-----------History for ('loc', 'sloc', 'comments')------------
╒════════════╤════════════════╤════════════════╤════════════╤═════════════════╤═══════════════════╤═══════════════════════╕
│ Revision   │ Message        │ Author         │ Date       │ Lines of Code   │ S Lines of Code   │ Multi-line comments   │
╞════════════╪════════════════╪════════════════╪════════════╪═════════════════╪═══════════════════╪═══════════════════════╡
│ f2679c6    │ Initial commit │ Ernesto Crespo │ 2020-11-14 │ 153 (0)         │ 71 (0)            │ 8 (0)                 │
╘════════════╧════════════════╧════════════════╧════════════╧═════════════════╧═══════════════════╧═══════════════════════╛

Cyclomatic Complexity

According to the publication by The Software Engineering Institute at Carnegie Mellon defines, which defines the complexity ranges:

1-10: Low risk, simple program.
11-20: Moderate risk, more complex program.
21-50: High risk, very difficult program.
50: Very high risk, unstable program.

Maintainability index

For this case:

<65: Hardly maintainable.
65-85: Moderately maintainable.
85: Easy to maintain.

In the case of app.py it has a moderate risk and is moderately maintainable.

For more information on cyclomatic complexity, you can check Simplify your Python Code: Automating Code Complexity Analysis with Wily or the pdf from The Software Engineering Institute at Carnegie Mellon defines.

Putting it all together with pre-commit

pre-commit

Pre-commit is a framework for managing git hooks.

To install it:

pip install pre-commit

To initialize pre-commit, run:

$pre-commit install
pre-commit installed at .git/hooks/pre-commit

Yaml verification

To format yaml you can use the following configuration:

  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v2.4.0
    hooks:
      - id: trailing-whitespace
      - id: end-of-file-fixer
      - id: check-added-large-files
      - id: check-yaml
        exclude: (template|ci).*\.(json|yml|yaml)$

isort

To validate with isort you have the following:

  - repo: https://github.com/asottile/seed-isort-config
    rev: v1.9.3
    hooks:
      - id: seed-isort-config
  - repo: https://github.com/pre-commit/mirrors-isort
    rev: v4.3.21
    hooks:
      - id: isort

For Wily

  - repo: local
    hooks:
      - id: wily
        name: wily
        entry: wily diff
        verbose: true
        language: python
        additional_dependencies: [wily]

Safety

  - repo: git://github.com/Lucas-C/pre-commit-hooks-safety
    rev: v1.1.3
    hooks:
      - id: python-safety-dependencies-check

Black

  - repo: https://github.com/ambv/black
    rev: stable
    hooks:
      - id: black
        language_version: python3.8

Pylint

  - repo: https://github.com/PyCQA/pylint
    rev: "pylint-2.6.0"
    hooks:
      - id: pylint
        args: ["--disable=similarities"]

Mypy


  - repo: https://github.com/pre-commit/mirrors-mypy
    rev: v0.790
    hooks:
      - id: mypy
        exclude: ^testing/resources/

Pyupgrade

  - repo: https://github.com/asottile/pyupgrade
    rev: v2.7.3
    hooks:
      - id: pyupgrade
        args: [--py36-plus]

Flake8

  - repo: https://gitlab.com/pycqa/flake8
    rev: 3.8.4
    hooks:
      - id: flake8
        additional_dependencies: [flake8-typing-imports==1.10.0]

Autopep8


  - repo: https://github.com/pre-commit/mirrors-autopep8
    rev: v1.5.4
    hooks:
      - id: autopep8

Blacken


  - repo: https://github.com/asottile/blacken-docs
    rev: v1.8.0
    hooks:
      - id: blacken-docs
        additional_dependencies: [black==20.8b1]

Bandit

  - repo: git://github.com/Lucas-C/pre-commit-hooks-bandit
    rev: v1.0.4
    hooks:
      - id: python-bandit-vulnerability-check
        exclude: /home/ernesto/proyectos/magnetic_fields/.virtualenvs/*

pydoctstyle

  - repo: local
    hooks:
      - id: pydocstyle
        name: pydocstyle
        entry: pydocstyle
        files: src/app.py
        verbose: true
        language: python
        additional_dependencies: [pydocstyle]

Complete file

The complete .pre-commit-config.yaml file contains the following:

# See https://pre-commit.com for more information
# See https://pre-commit.com/hooks.html for more hooks
repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v2.4.0
    hooks:
      - id: trailing-whitespace
      - id: end-of-file-fixer
      - id: check-added-large-files
      - id: check-yaml
        exclude: (template|ci).*\.(json|yml|yaml)$
  - repo: https://github.com/asottile/seed-isort-config
    rev: v1.9.3
    hooks:
      - id: seed-isort-config
  - repo: https://github.com/pre-commit/mirrors-isort
    rev: v4.3.21
    hooks:
      - id: isort
  - repo: local
    hooks:
      - id: wily
        name: wily
        entry: wily diff
        verbose: true
        language: python
        additional_dependencies: [wily]
  - repo: local
    hooks:
      - id: pydocstyle
        name: pydocstyle
        entry: pydocstyle
        files: src/app.py
        verbose: true
        language: python
        additional_dependencies: [pydocstyle]
  - repo: git://github.com/Lucas-C/pre-commit-hooks-safety
    rev: v1.1.3
    hooks:
      - id: python-safety-dependencies-check
  - repo: https://github.com/ambv/black
    rev: stable
    hooks:
      - id: black
        language_version: python3.8
  - repo: https://github.com/PyCQA/pylint
    rev: "pylint-2.6.0"
    hooks:
      - id: pylint
        args: ["--disable=similarities"]
  - repo: https://github.com/pre-commit/mirrors-mypy
    rev: v0.790
    hooks:
      - id: mypy
        exclude: ^testing/resources/
  - repo: https://github.com/asottile/pyupgrade
    rev: v2.7.3
    hooks:
      - id: pyupgrade
        args: [--py36-plus]
  - repo: https://gitlab.com/pycqa/flake8
    rev: 3.8.4
    hooks:
      - id: flake8
        additional_dependencies: [flake8-typing-imports==1.10.0]
  - repo: https://github.com/pre-commit/mirrors-autopep8
    rev: v1.5.4
    hooks:
      - id: autopep8
  - repo: https://github.com/asottile/blacken-docs
    rev: v1.8.0
    hooks:
      - id: blacken-docs
        additional_dependencies: [black==20.8b1]
  - repo: git://github.com/Lucas-C/pre-commit-hooks-bandit
    rev: v1.0.4
    hooks:
      - id: python-bandit-vulnerability-check
        exclude: /home/ernesto/proyectos/magnetic_fields/.virtualenvs/*

You can run the following command for the verification:

pre-commit run --all-files

This returns the messages as shown in the following image: pre-commit

From now on, when you want to make a commit, pre-commit will evaluate the hooks and you have to fix the errors until there are none, and that is when the commit will be made.

Final file structure.

ignals_fft_streamlit
├── .bandit
├── .git
│   ├── branches
│   ├── COMMIT_EDITMSG
│   ├── config
│   ├── description
│   ├── HEAD
│   ├── hooks
│   │   ├── applypatch-msg.sample
│   │   ├── commit-msg.sample
│   │   ├── fsmonitor-watchman.sample
│   │   ├── post-update.sample
│   │   ├── pre-applypatch.sample
│   │   ├── pre-commit
│   │   ├── pre-commit.sample
│   │   ├── pre-merge-commit.sample
│   │   ├── prepare-commit-msg.sample
│   │   ├── pre-push.sample
│   │   ├── pre-rebase.sample
│   │   ├── pre-receive.sample
│   │   └── update.sample
│   ├── index
│   ├── info
│   │   └── exclude
│   ├── logs
│   │   ├── HEAD
│   │   └── refs
│   │       ├── heads
│   │       │   ├── feat
│   │       │   │   └── validado
│   │       │   └── main
│   │       └── remotes
│   │           └── origin
│   │               └── HEAD
│   ├── ORIG_HEAD
│   ├── packed-refs
│   └── refs
│       ├── heads
│       │   ├── feat
│       │   │   └── validado
│       │   └── main
│       ├── remotes
│       │   └── origin
│       │       └── HEAD
│       └── tags
├── .gitignore
├── .isort.cfg
├── LICENSE
├── .pre-commit-config.yaml
├── .pylintrc
├── README.md
├── requirements.txt
└── src
    └── app.py

The final app.py file ended up like this:


"""WebApp with streamlit graph signals."""
import matplotlib.pylab as plt  # type: ignore
import numpy as np  # type: ignore
import streamlit as st  # type: ignore
from scipy import signal  # type: ignore # pylint: disable=import-error


def u(amplitud: int, t: np.ndarray) -> np.ndarray:
    """Función escalón unitario.

    Args:
        amplitud(int): Amplitud del escalon
        t(np.ndarray): Lista de tiempo

    Returns:
        np.ndarray: Lista de valores
    """
    return amplitud * np.piecewise(t, [t < 0.0, t >= 0.0], [0, 1])


def onda_cuadrada(amplitud: int, t: np.ndarray, fs: int = 1) -> np.ndarray:
    """Función  de Onda Cuadrada.

    Args:
        amplitud(int): Amplitud de la segnal
        t(list): Lista de valores de tiempo
        fs(int, optional): Frecuencia.. Defaults to 1.

    Returns:
        list: Lista de valores
    """
    return ((signal.square(2 * fs * t)) * (amplitud / 2.0)) + (amplitud / 2.0)


def segnal_triangular(
    amplitud: int, simetria: float, t: np.ndarray, fs: int = 1
) -> np.ndarray:
    """Señal triangular.

    Args:
        amplitud(int): Amplitud de la señal
        simetria(float): simetria de la señal
        t(np.ndarray): Lista de valores que definen el tiempo.
        fs(int, optional): Frecuencia de la señal. Defaults to 1.

    Returns:
        np.ndarray: Lista de valores de la señal
    """
    return amplitud * (signal.sawtooth(2 * np.pi * fs * t, simetria))


def seno(amplitud: int, t: np.ndarray, fs: int = 1) -> np.ndarray:
    """Onda Seno.

    Args:
        amplitud(int): Amplitud de la señal
        t (np.ndarray): Lista de valores de tiempo
        fs (int, optional): Frecuencia de la señal. Defaults to 1.

    Returns:
        np.ndarray: Lista de valores de la señal de seno
    """
    return amplitud * np.sin(fs * t)


def coseno(amplitud: int, t: np.ndarray, fs: int = 1) -> np.ndarray:
    """Señal de coseno.

    Args:
        amplitud (int): Amplitud de la señal
        t (np.ndarray): lista de valores para generar la señal
        fs (int, optional): Frecuencia de la señal. Defaults to 1.

    Returns:
        np.ndarray: Lista de valores de la señal
    """
    return amplitud * np.cos(fs * t)


def tiempo(lim_inf: int, lim_sup: int, n: int) -> np.ndarray:
    """Lista de valores que definen el tiempo de la señal.

    Args:
        lim_inf (int): Límite inferior del tiempo
        lim_sup (int): Límite superior del tiempo
        n (int): Cantidad de valores a generar del tiempo

    Returns:
        np.ndarray: Lista de valores del tiemmpo
    """
    return np.linspace(lim_inf, lim_sup, n)


def main():
    """Ejecución Streamlit webApp."""
    st.title(  # pylint: disable=no-value-for-parameter
        "Generación de gráficas de señales"
    )  # pylint: disable=no-value-for-parameter
    st.sidebar.header("Entradas:")  # pylint: disable=no-value-for-parameter
    segnales = [
        "Escalon Unitario",
        "Onda Cuadrada",
        "Onda triangular",
        "Seno",
        "Coseno",
    ]

    resp = st.sidebar.selectbox("Tipo de señal", segnales)

    st.sidebar.header("Definición del tiempo:")
    st.sidebar.subheader("Rango")
    # SelectBox
    t0 = int(st.sidebar.selectbox("", range(0, 10)))
    ti = 0
    tf = t0
    n = 10000
    t = tiempo(ti, tf, n)
    st.sidebar.subheader("Amplitud de la señal")
    amplitud = int(st.sidebar.selectbox("", range(1, 10)))

    # numpy.ndarray
    if resp == "Escalon Unitario":
        ti = -tf
        resultado = u(amplitud, t)
    elif resp == "Onda Cuadrada":
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox("", range(1, 11)))
        resultado = onda_cuadrada(amplitud, t, fs)
    elif resp == "Onda triangular":
        simetria = 0.5
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox("", range(1, 11)))
        resultado = segnal_triangular(amplitud, simetria, t, fs)
    elif resp == "Seno":
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox("", range(1, 11)))
        resultado = seno(amplitud, t, fs)
    elif resp == "Coseno":
        st.sidebar.subheader("Frecuencia de la señal")
        fs = int(st.sidebar.selectbox("", range(1, 11)))
        resultado = coseno(amplitud, t, fs)
    else:
        resultado = 0
        st.error("Error")

    fig = plt.figure()
    ax = fig.add_subplot(111)
    st.header(f"Gráfica de {resp}")
    ax.plot(t, resultado)
    ax.set_xlim(ti, tf)
    ax.set_xlabel("Tiempo")
    ax.set_ylabel("f(t)")
    ax.set_ylim(2 * amplitud * -1, 2 * amplitud)
    st.pyplot(fig)


if __name__ == "__main__":
    main()

The repository where you can see the files is on github

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Ernesto Crespo.

Summary

Writing clean Python code

Code validation

Linters

Flake8

pep8-naming

pycodestyle

pylint

Code formatter

isort

Black

Security vulnerability scanning

Bandit

Safety

Static typing verification

Mypy

Documentation validation

pydocstyle

Cyclomatic Complexity, number of lines of code

Wily

Cyclomatic Complexity

Maintainability index

Putting it all together with pre-commit

pre-commit

Yaml verification

isort

For Wily

Safety

Black

Pylint

Mypy

Pyupgrade

Flake8

Autopep8

Blacken

Bandit

pydoctstyle

Complete file

Final file structure.