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Peter Diamandis and Dan Sullivan discuss how exponential technologies are creating massive opportunities for entrepreneurs all over the world and the impact of hyperconnectivity on global innovation.

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December 4, 2017

Pe ter and Dan give an update on the latest research in technologies extending the healthy human lifespan. Peter and Dan agree that “retirement” is one of the leading causes of death, and that mindset is a major factor in the game of human longevity.

In this episode:

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November 17, 2017

Peter and Dan discuss the latest technologies in the transportation industry. Electric autonomous cars, Virgin Hyperloop One, flying vehicles like Airbus and Uber Elevate, and Elon Musk’s Boring Company and SpaceX rockets.

November 3, 2017

Peter and Dan delve into a number of dangerous ideas, including changing government, healthcare, and education, and discuss how these opinions are less than a decade away.

October 19, 2017

Peter and Dan revisit Peter’s 6 D’s of exponentials framework and discuss a new thinking tool created to help entrepreneurs measure how they are using technology in their companies and their lives.

October 9, 2017

Peter and Dan discuss a common conversation theme in Silicon Valley — namely, that most people have no idea how quickly things are changing — and how technology has caused the world to move at an accelerated pace.

September 24, 2017

Peter and Dan discuss a conversation they had in 2013 that led to the creation of the Abundance 360 executive summit and the 25-year framework behind the idea.

September 8, 2017

Peter and Dan discuss entrepreneurial commercial space. Why is this happening now? Which companies are the most exciting to watch?

August 16, 2017

In Episode 27: Evidence of Abundance , Peter and Dan discussed the 6 D’s framework and how this model is a road map to contextualize exponential technologies. In this episode, they dig deeper into the first step, Digitization, and why spending energy early on will ultimately lead to an enormous amount of time saved.

July 24, 2017

P eter and Dan discuss setting boundaries for kids and their gadgets. They explore the potential benefits and pitfalls of kids using technology and growing up in a world where every toy contains exponential technology.

Continuing the example, note that calling dir() on the module also imports the remaining plugins:

dir() usually lists all available attributes on an object. Normally, using dir() on a module results in something like this:

While this might be useful information, we are more interested in exposing the available plugins. In Python 3.7, you can customize the result of calling dir() on a module by adding a __dir__() special function. For plugins/__init__.py , this function first makes sure all plugins have been imported and then lists their names:

Before leaving this example, please note that we also used another cool new feature of Python 3.7. To import all modules inside the plugins directory, we used the new importlib.resources module. This module gives access to files and resources inside modules and packages without the need for __file__ hacks (which do not always work) or pkg_resources (which is slow). Other features of importlib.resources will be highlighted later .

Type hinting and annotations have been in constant development throughout the Python 3 series of releases. Python’s Ganni Jerome Lace Dress Black 4Cjizib
is now quite stable. Still, Python 3.7 brings some enhancements to the table: better performance, core support, and forward references.

Python does not do any type checking at runtime (unless you are explicitly using packages like New Balance Sneakers Military Green TG3jw
). Therefore, adding type hints to your code should not affect its performance.

Unfortunately, this is not completely true as most type hints need the typing module. The typing module is one of the slowest modules in the standard library. SelfPortrait Floral Crepe Midi Dress Red Vinz6Fkq0H
adds some core support for typing in Python 3.7, which significantly speeds up the typing module. The details of this are in general not necessary to know about. Simply lean back and enjoy the increased performance.

While Python’s type system is reasonably expressive, one issue that causes some pain is forward references. Type hints—or more generally annotations—are evaluated while the module is imported. Therefore, all names must already be defined before they are used. The following is not possible:

Running the code raises a NameError because the class Tree is not yet (completely) defined in the definition of the .__init__() method:

To overcome this, you would have needed to write "Tree" as a string literal instead:

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for the original discussion.

In a future Python 4.0 , such so called forward references will be allowed. This will be handled by not evaluating annotations until that is explicitly asked for. LArtiste L Artiste Womens Natalia Boot Black Leather QuNDgWJ9VE
describes the details of this proposal. In Python 3.7, forward references are already available as a __future__ import . You can now write the following:

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