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from dataclasses import dataclass, fields, Field

from typish import SubscriptableType

import yunit


class QuantityMeta(SubscriptableType):
    @property
    def typed_unit(cls):

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%config InteractiveShell.ast_node_interactivity = 'last_expr_or_assign'

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# coding: utf-8
# 
# Montiors the total memory usage of all Chrome processes.
# To be run on a Windows machine.
# Requirements: 
#   - Python 3.6+
#   - Pandas

print('Press Ctrl-C to quit')
print('\n..', end='')

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from pprint import pformat
from tabulate import tabulate

rows = []

for name in dir(obj):
    val = getattr(obj, name)
    if callable(val):
        try:
            content = val()

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-- Export to csv via SQLite Database Browser:
create table promo_post_data as select * from pagepostdata where post_name='Promo-post'

-- Export to csv via SQLite CLI:
sqlite> .header on
sqlite> .output c:/work/dataout.csv
sqlite> .mode csv
sqlite> SELECT * FROM pagepostdata WHERE post_name='Promo-post'
sqlite> .output stdout

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class A:
  def f(self, x): return self.f(x/2) + 1

class B(A):
	def f(self, x=10):
		if x < 0: return self.f(x+200) + 2
		if x > 20: return A.f(self,x-50) + 3
		else: return x

from pylab import *