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"""Illustrate some strategies to cache potentially expensive results.

Sometimes results are obtained via code which has side effects and/or is
potentially expensive so you don't want to run it more often than
necessary. This script demonstrates a few different ways of caching
those results at the use site, so they only need to be generated once
and can be read from whatever is used as a cache afterwards.
"""

# First we need a function having an observable side effect, so we can

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#! /usr/bin/env python

from pathlib import Path
import csv
import json

from shapely.geometry import Point, shape
from shapely.prepared import prep

from egon.data import subprocess

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from functools import partial
import json

from geocube.api.core import make_geocube
from geocube.rasterize import rasterize_image
from rasterio.enums import MergeAlg
from shapely.wkt import loads
from shapely.geometry import box, mapping, MultiPoint
import pandas as pd
import geopandas as gpd

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import os
import zipfile

with zipfile.ZipFile(PATH_TO_ZIPFILE) as zf:
    for filename in zf.namelist():
        zf.extract(filename)
        # Do stuff with `filename`.
        os.remove(filename)

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Topic Partitioning Votes

These are the most significant polling results:

Partitioning	Votes
2, 3	5
7, 9	5
5, 6	4
10	4

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Math

Here's a math block. Let's see how it's rendered.

$$\sum_{n=1}^{\infty}$$

Apparently not at all. So what about the same thing inlined:

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spec Sorting =
  TotalOrder and List
then {
  preds is_ordered : List;
        permutation : List * List
  vars x,y:Elem; L,L1,L2:List
  . is_ordered([])
  . is_ordered(x::[])
  . is_ordered(x::y::L) <=> x<=y /\ is_ordered(y::L)
  . permutation(L1,L2) <=> (forall x:Elem . count(x,L1) = count(x,L2))

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from oemof.network import Source


class Investment:
    """ Components (Nodes?) grouped under `Investment` objects are optimized
        for investment.
    """

    def __init__(self, maximum=float('+inf')):
        self.maximum = maximum