mfurquimdev

import uvicorn
from fastapi import FastAPI
from view import router as sample_router

app = FastAPI()

app.include_router(sample_router)


if __name__ == "__main__":

mfurquimdev

This gist holds SVG file of lowlighter/metrics for my github profile.

mfurquimdev

Git LOC

Define the AUTHOR_NAME as an environment variable before calling the script:

$ AUTHOR_NAME="João" ./git_loc.sh

The outputs will be separated into three files:

• João.csv: File containing insertions, deletions, and file path
• commits.list: File containing one commit id per line

mfurquimdev

#!/bin/bash

pipenv run pytest -s -vv --failed-first -x --cov-report term-missing --cov=. tests

mfurquimdev

#!/bin/bash

pushd pangram
stack test --allow-different-user --install-ghc

mfurquimdev

#!/bin/bash

mix test

mfurquimdev

#!/bin/bash
#
# Modified a few lines from:
# https://github.com/neurosnap/lists.sh/discussions/24
#
# Automatically scp files to https://prose.sh
# when $HOME/prose_sh files are changed.
#
# Setup a prose.sh account first (See https://prose.sh)
#

mfurquimdev

from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser
from sklearn.datasets import make_classification
from sklearn.decomposition import PCA
from sklearn.manifold import LocallyLinearEmbedding
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from gooey import Gooey

mfurquimdev

#!/bin/env python

import matplotlib.pyplot as plt
import numpy as np
import os
import torch

from collections import Counter
from os.path import exists as file_exists
from sklearn.model_selection import train_test_split

mfurquimdev

@pytest.mark.asyncio
@pytest.mark.parametrize(
    "request_body",
    [
        {
            "start_date": "2021-02-01 00:00:00",
            "sensors": [],
        },
        {"start_date": "2021-02-01 00:00:00", "end_date": "2021-02-01 00:30:00"},
    ],