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@gbaman
gbaman / graphql_example.py
Created November 1, 2017 00:18
An example on using the Github GraphQL API with Python 3
# An example to get the remaining rate limit using the Github GraphQL API.
import requests
headers = {"Authorization": "Bearer YOUR API KEY"}
def run_query(query): # A simple function to use requests.post to make the API call. Note the json= section.
request = requests.post('https://api.github.com/graphql', json={'query': query}, headers=headers)
if request.status_code == 200:
@perfecto25
perfecto25 / default.j2
Last active September 25, 2024 15:04
Python function to send email using a Jinja HTML template
<style type="text/css">
@font-face {
font-family: 'Open Sans';
font-style: normal;
font-weight: 300;
src: local('Open Sans Light'), local('OpenSans-Light'), url(http://fonts.gstatic.com/s/opensans/v13/DXI1ORHCpsQm3Vp6mXoaTa-j2U0lmluP9RWlSytm3ho.woff2) format('woff2');
unicode-range: U+0460-052F, U+20B4, U+2DE0-2DFF, U+A640-A69F;
}
.body {
width: 90%;
@akehrer
akehrer / sqlite_to_json.sql
Created January 9, 2018 19:58
SQLite Results as JSON using the SQLite JSON1 extension
-- When SQLite is compiled with the JSON1 extensions it provides builtin tools
-- for manipulating JSON data stored in the database.
-- This is a gist showing SQLite return query data as a JSON object.
-- https://www.sqlite.org/json1.html
-- An example table with some data
CREATE TABLE users (
id INTEGER PRIMARY KEY NOT NULL,
full_name TEXT NOT NULL,
email TEXT NOT NULL,
@emptymonkey
emptymonkey / gist:7d3cb6caef94fa951a65d12e8d3cf3c0
Created May 10, 2018 00:10
Read implies Execute and Linker/Loader suid abuse.
# First, let's demonstrate that read implies execute.
cp /usr/bin/id .
ls -l ./id
./id
chmod a-x ./id
ls -l id
readelf -l ./id | grep "program interpreter"
ls -l /lib64/ld-linux-x86-64.so.2
ls -l /lib/x86_64-linux-gnu/ld-2.23.so
@mvanga
mvanga / ecs-annotated.py
Last active March 30, 2025 02:02
A Python3 implementation of an entity-component-system in under 50 lines code.
import uuid
import json
# Returns a python dictionary given a file containing a JSON-based
# component definition. Every definition *must* contain a 'type'
# and 'schema' field inside a top-level dictionary. Here is an
# example of a simple schema file that defines a 'meta' component
# containing a 'name' field.
#
@danmikita
danmikita / init.vim
Created November 16, 2018 19:16
File preview with FZF, RG, Bat, and Devicons
nnoremap <silent> <leader>e :call Fzf_dev()<CR>
" ripgrep
if executable('rg')
let $FZF_DEFAULT_COMMAND = 'rg --files --hidden --follow --glob "!.git/*"'
set grepprg=rg\ --vimgrep
command! -bang -nargs=* Find call fzf#vim#grep('rg --column --line-number --no-heading --fixed-strings --ignore-case --hidden --follow --glob "!.git/*" --color "always" '.shellescape(<q-args>).'| tr -d "\017"', 1, <bang>0)
endif
" Files + devicons
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@klieret
klieret / random_file_tree.py
Last active June 9, 2020 17:43
Create a random file tree in python, e.g. random subfolders and random files.
#!/usr/bin/env python3
""" AVAILABLE AS A PACKAGE ON github.com/klieret/randomfiletree """
import sys
import os
import random
import string
from pathlib import Path
@zzzeek
zzzeek / sql.py
Last active August 15, 2023 10:00
The SQL is just as easy as an ORM challenge
""" "Writing SQL is just as fast as using an ORM" proof of concept
Below is a simple Python object model, where we represent a database that
stores the names of employees at a company, some of whom are "engineers",
and a list of the jobs they do and the programming languages they use.
We'd like to persist the state represented by this Python object model
in a relational database, using our Python objects as a start. Then we'd
like to write SQL queries for rows in this database, and we get back instances
of Python objects exactly as they were created.
@ktaletsk
ktaletsk / JLab_extensions.md
Last active March 12, 2022 21:28
JupyterLab extensions