leontrolski

import os
from typing import TypeVar
import pydantic

T = TypeVar("T")


class _Missing:
    ...

leontrolski

<style>
.red {
    color: red;
}
</style>

<div id="root"></div>

<script>

leontrolski

# pip install sqlalchemy testing.postgresql
# see also: https://blog.crunchydata.com/blog/message-queuing-using-native-postgresql
import threading
from contextlib import contextmanager

from sqlalchemy import Column, Integer, String, create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import  sessionmaker
import testing.postgresql

leontrolski

# This is a version of https://gist.github.com/natekupp/1763661 without
# using mutation and with some other simplifications. Hopefully it's slightly
# easier to follow. Performance wise - from some small benchmarking - it has
# the same O(N) characteristics/memory usage, but is about twice as slow.
#
# Use it like:
#
#    b = Node([], [])
#    b = add(b, n)
#    print(pp(b))

leontrolski

//   ___________________________
// _| generic constraint solver |__________________________________________________

type Assignments<V> = {[K: string]: V}
type Constraint<V> = (assignments: Assignments<V>) => boolean
type KProperties<V> = {
    domain: V[]
    constraints: Constraint<V>[]
}
type Problem<V> = {

leontrolski

// 80 line parser and interpreter for a small language with
// integers, assignments, lexical scope, first class functions
const source = `
(block
    (assign x 5)
    (assign f
        (function
            (a b)
            (block
                (assign c (+ a b))

leontrolski

# 105 line parser and interpreter for a small language with
# integers, assignments, lexical scope, first class functions
from __future__ import annotations
from dataclasses import dataclass, replace
from typing import Callable, Union

source = """
(#{
    (#= x 5)
    (#= f

leontrolski

import base64
from functools import lru_cache
import logging
from time import sleep, time
from typing import Dict, TypedDict, Tuple, List, TypeVar

import requests
from google.auth.transport.requests import AuthorizedSession
import google.auth

leontrolski

"""This isn't the most efficient, but is the most "natural" to me.

match(i, j) => do letters `s[:i]` match chars `p[:j]`

- If i == -1, return False
- Set letter to the last of letters and char to last of chars
- If chars is empty, the only match is if letters is empty
- If char is *, did s[:i-1] match p[:j] or did s[:i] match p[:j-1]?
- Else does char match letter and did s[:i-1] match p[:j-1]?

leontrolski

from StringIO import StringIO
from itertools import islice, izip_longest, tee

import pandas as pd
from pandas.util.testing import assert_frame_equal

def read_data_frame_str(s, first_col_index=False):
    """Read a markdown-style description of a table into a DataFrame.
    :param str s:
    :param bool first_col_index: if `True`, use the first column as an index.