| EXEC = $(shell basename $(CURDIR)) | |
| CFILES = $(wildcard *.c) | |
| HFILES = $(wildcard *.h) | |
| #OFILES = $(patsubst %.c, %.o, $(filter-out $(CFILES), $(wildcard *.c))) | |
| CC = gcc | |
| CFLAGS = -g -std=c99 -Wall -Werror | |
| CFLAGS += -Wconversion -Wno-sign-conversion -Wbad-function-cast -Wshadow | |
| CFLAGS += -Wno-unused-function #Solo para comodidad en pruebas locales | |
| CFLAGS += -Wtype-limits -pedantic |
| import requests, zipfile | |
| from bs4 import BeautifulSoup | |
| soup = BeautifulSoup(requests.get("http://limbero.org/jl8").content, "lxml") | |
| latest_issue = int(soup.title.string.split(' ')[0][1:]) | |
| FIRST = 0 | |
| LAST = latest_issue | |
| COVER = 'http://static.tvtropes.org/pmwiki/pub/images/rsz_tumblr_or2whrxrgs1r7ni1io1_1280.jpg' |
| from termcolor import colored #pip install termcolor | |
| import random, re | |
| COLORS = ["green", "blue", "red", "yellow", "magenta", "cyan"] | |
| ANSI_ESCAPE = re.compile(r'\x1b[^m]*m') | |
| """Utilizacion: | |
| Desde la terminal de Python: from CountingSort import counting_sort | |
| counting_sort([1,2,3]) | |
| Procede a colorear la lista de enteros y luego ordenarla. El color sirve para mostrar la estabilidad del ordenamiento. |
| #include "fake_malloc.h" | |
| bool trucho = false; | |
| int MALLOC_TRUCHO(void) { return trucho; } | |
| void *malloc(size_t size) { | |
| if (MALLOC_TRUCHO()) return NULL; | |
| static void * (*func)(); | |
| if(!func) func = (void *(*)()) dlsym(RTLD_NEXT, "malloc"); | |
| return(func(size)); |
| #include <stdio.h> | |
| #include <stdlib.h> | |
| /* | |
| Compilacion: | |
| gcc -g errores_tipicos.c -o errores | |
| * g: Compila con información de debugging, para que programas como Valgrind y GDB vean bien donde estan los errores, entre otras cosas. | |
| Corrida: | |
| ./errores | |
| Chequeo de perdida de memoria: |
| #!/usr/bin/env python | |
| # 1. Download TMDB's database with @galli-leo's script | |
| # https://gist.github.com/galli-leo/6398f9128ffc20af70c6c7eedfeb0a65 | |
| # 2. Run python3 tmdbdump_to_csv.py | |
| import pandas as pd | |
| import numpy as np | |
| import json | |
| import os |
python imdbtocsv.py actresses.list actors.list o cada uno por separadoEn imdbtocsv.py se puede leer un pequeño paso a paso de como se parsea el archivo