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Better clear some space in that trophy case, because it's time for Bleacher Report's midseason awards for the 2018 Major League Baseball season.

Though the actual midway point has already come and gone, the arrival of the All-Star break marks the traditional midway point of the season. And there are candidates aplenty for the five major awards in the American League and National League: Comeback Player of the Year, Manager of the Year, Rookie of the Year, Cy Young Award and Most Valuable Player.

Our picks were informed mostly by statistics. However, there were also opportunities to make a few classic judgment calls.

Let's get to it.

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Following a breakout season in 2015, Matt Duffy's 2016 and 2017 seasons involved disappointing production, a trade from one coast to another and a litany of injuries that limited him to 91 total games.

Now look at him.

Duffy, 27, has compiled a .317/.371/.413 slash line in 80 games for the Tampa Bay Rays this season. He currently holds the fifth-highest batting average among American League qualifiers.

That Duffy is playing at all this season is a feat in its own right. He missed the entire 2017 season due to a difficult recovery from left Achilles surgery that left him with plenty of doubts.

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Martes, 13 de febrero de 2018 18:16


Date un tiempo para ahorrar un poco de dinero y deja que Netflix te envuelva en sus atractivas propuestas...

El título de este artículo tal vez sea demasiado pretencioso y absolutista. Por supuesto, hay honrosas excepciones como Three Billboards Outside Ebbing, Missouri (2017), que ha cautivado a más de un espectador y críticos especializados con su historia llena de dramatismo; The Square (2017), una muestra de que el cine sueco siempre nos depara buenas historias y actuaciones memorables; o rarezas como The Killing of a Sacred Deer (2017), que hacen que la visita al cine no se sienta como un desperdicio. Seguramente tú estarás añadiendo en estos momentos una o dos películas más y tienes razón al hacerlo. Nadie puede decir que tenga la verdad absoluta entre sus manos.

Sin embargo, hemos querido desafiar un poco a lo que actualmente está en el cine y recalcar que en esta época en que las salas se están viendo invadidas por las películas nominadas al Zign Ankle strap ballet pumps white MngV0VkZ
, además de los productos vacíos e insustanciales de toda la vida, en la plataforma de streaming más popular del mundo hay películas que poseen una calidad sobresaliente y a las cuales es necesario echar un ojo para redescubrir su importancia.


Sin más preámbulo, esto es lo que puedes hallar en Netflix para darte cuenta de que, a veces, quedarte en casa es una decisión más que acertada para ver buen cine…

¿Qué hay de sobresaliente en ella?

1.Una memorable actuación de Leonardo DiCaprio, quien muestra su ímpetu por salir de su zona de confort para arriesgarse a hacer papeles más serios y salir de su rol de galán.

2. Es una notable película noir con tintes macabros apta para todo fan del terror y el misterio.


3. Su aterradora ambientación y la dirección del gran Martin Scorsese le dan una calificación de 9.5

¿Qué hay de especial en ella?


1.Es un thriller inteligente y bien llevado por Joel Edgerton en su debut como director.

2. ¿Buscas algo realmente entretenido? No lo pienses más y dale clic.

3. Su trama llena de suspenso y momentos aterradores hará que no quieras despegar la vista hasta legar a la resolución del siniestro conflicto por el que tienen que pasar sus protagonistas. Por ello tiene una calificación de 9.


¿Por qué debes verla?

1.Está basada en la historia verídica del "Zodiac Killer", un asesino en serie que aterrorizó a la ciudad de San Francisco durante la década de 1970.

2. Todo en la cinta es perfecto: actuaciones, historia, ambientación. Además su rigor histórico la hace creíble y un documento perfecto para conocer más acerca de este misterioso asesino.

OfBaumol’s many contributions to economics, themost famous is cost disease ,which explains why high-productivity industries raise costs and therefore prices in low-productivity industries. The insight is particularly relevant now, as economic activity has shifted into low-productivity services like health care and education, where price increases are devouring public and household budgets, and whose continued low productivity has weighed down U.S. productivity growth overall.

But there’s a lesser-known ideaof Baumol’s that is equally relevant today and that may help explain America’s productivity slump. Baumol’s writing raises the possibility that U.S. productivity is low because would-be entrepreneurs are focused on the wrong kind of work.

In a 1990 paper, Naot Womens Fiona Wedge Sandal FsWDk0kIs
Baumol argued that the level of entrepreneurial ambition in a country is essentially fixed over time, and that what determines a nation’s entrepreneurial output is the incentive structure that governs and directs entrepreneurial efforts between “productive” and “unproductive” endeavors.

Most people think of entrepreneurship as beingthe “productive” kind, as Baumol referred to it, where the companies that founders launch commercialize something new or better, benefiting society and themselves in the process. A Philippe modelSneakers Marais L U suede MXN0sc5f
establishes that these “Schumpeterian” entrepreneurs, those that are “creatively destroying” the old in favor of the new, are critical for breakthrough innovations and rapid advances in productivity and standards of living.

Baumol was worried, however, by a very different sort of entrepreneur: the “unproductive” ones, who exploit special relationships with the government to construct regulatory moats, secure public spending for their own benefit, or bend specific rules to their will, in the process stifling competition to create advantage for their firms. Economists call this rent-seeking behavior . As Baumol wrote:

…entrepreneurs are always with us and always play some substantial role. But there are a variety of roles among which the entrepreneur’s efforts can be reallocated, and some of those roles do not follow the constructive and innovative script that is conventionally attributed to that person. Indeed, at times the entrepreneur may even lead a parasitical existence that is actually damaging to the economy. How the entrepreneur acts at a given time and place depends heavily on the rules of the game—the reward structure in the economy—that happen to prevail.

In Baumol’s theoretical framework, depressed rates of entrepreneurship aren’t the culprit for periods of slow economic growth; rather, a change in the mix of entrepreneurial effort between the two kinds of entrepreneurship is to blame — specifically, a decline in productive entrepreneurship and a coincident rise in unproductive entrepreneurship. But is this what’s actually happening in the U.S.?

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Just some guy. On Twitter

I recently asked a coworker why a certain check was being done, and he answered with a shrug and said, “Just to be safe.” Over my career, I’ve seen a lot of code written just to be safe. I’ve written a lot of that code myself! If I wasn’t sure if I could rely on something, I’d add a safety check to prevent it from throwing an exception.

To give some examples, I mean idioms like providing unnecessary default values.

Or checking that each key exists in deeply nested data.

And many other idioms. Idioms like these prevent exceptions from being thrown. Used without care, suppressing an exception is like hanging art over a hole in the wall.

At a glance, there doesn’t appear to be a problem. But you haven’t patched the hole and you haven’t fixed the bug. Instead of an easy-to-trace exception, you have unusable values — bad data — infiltrating your program. What if there’s a bad deployment on the backend and it begins returning an empty response? Your default value gets used, your chain of checks returns , and the string ‘undefined’ gets put on your page. In React code, it won’t render anything at all.

There’s an adage in computing, “be liberal in what you accept and conservative in what you send.” Some might argue that these are examples of this principle in action, but I disagree. I think these patterns, when used to excess, show a lack of understanding of what guarantees your libraries and services provide.

Data or arguments from thirdparties

What your code expects from somebody else’s code is a contract. Often, this contract is only implied, but care should be taken to identify what form the data take and to document it. Without a well understood, clearly documented response format from an API, how can you tell whose code is in error when something breaks? Having a clear definition builds trust.

When you request data from an external HTTP API, you don’t need to inspect the object to see if it has . You already know that it exists because of the contract you have with your request library. For a specific example, the axios documentation defines a schema for the format the response comes back with. Further, you should know the shape of the data in the response. Unless the request is stateful or encounters an error, you’ll get the same response every time — this is the contract you have with the backend.

Data passed within the application

The functions you write and the classes you create are also contracts, but it’s up to you as a developer to enforce them. Trust in your data, and your code will be more predictable and your failure cases more obvious. Data errors are simpler to debug if an error is thrown close to the source of the bad data.

Unnecessary safety means that functions will continue to silently pass bad data until it gets to a function that overly safe. This causes errors to manifest in a strange behavior somewhere in the middle of your application, which can be hard to track with automated tools. Debugging it means tracking the error back to find where the bad data was introduced.

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with an example of overly safe and unsafe accesses.

The “safe” component guards against exceptions being thrown.

And the unsafe one gets the values without any checks.

This approximates what could happen if an external API starts returning unusable data. Which of these failure modes would you rather diagnose?

Performance and development speed

Beyond that, conditionals aren’t free. Individually, they have little impact on performance, but codebase that makes a widespread habit of doing unnecessary checks will begin to use an observable amount of time. The impact can be significant: React’s production mode removes prop types checks for a significant performance increase. Some benchmarks show production mode in React 15 getting a 2–4x boost over development mode.

Conditional logic adds mental overhead as well, which affects all code that relies on the module. Being overly cautious with external data means that the next person to consume it doesn’t know if it’s trustworthy, either. Without digging into the source to see how trustworthy the data is, the safest choice is to treat it as unsafe. Thus the behavior of this code forces other developers to treat it as an unknown, infecting all new code that’s written.

Fixing theproblem

When writing code, take a minute to think through the edge cases.

Many of the fixes to patterns like this are to handle the errors you can and to throw the errors you can’t. It makes sense to verify that data from an external API comes back in the shape you’re expecting, but if it doesn’t, can your app realistically continue? Lean on your error handling to show an appropriate response to the user, and your error logging to notify you that there’s an issue.

Learning what to expect from your tools is a large part of writing code you can trust. Many times this is documented explicitly, but sometimes it’s only implied. The format of data with a backend API is up to whoever’s writing that backend. If you’re full-stack, great news! You control both ends, and you can trust yourself (right?). If a separate team controls the backend API, then you’ll need to establish what is correct behavior and hold each other to it. A third party API can be harder to trust, but you’ll also have minimal influence over what it returns.

When writing React components, you have an even more powerful tool: PropTypes. Instead of scattering checks like , you can add a type definition as a static property.

This might look a little ugly, but now the component will log an error during development if your data is wrong. The missing data will likely cause its own error to throw afterward, and which of these messages is more helpful?

External data thatchanges

Of course, sometimes you will have data that you’re not sure about. It might have keys or , or the key might be . These are good times to add checks, but consider defining them as functions that communicate their intent.

Well named functions will tell your coworkers down the road why these checks are present. Particularly good names will enable them to make the checks more accurate in the future.

Excessively safe idioms — and even well-considered checks — amount to stopgaps to guard against type errors. PropTypes are easy to add to an existing React codebase but aren’t the only option available. TypeScript and Flow are much more advanced tools to verify your data types. PropTypes will save you at runtime, but either TypeScript or Flow will allow you to verify that your code works at build time. Types give you an ironclad contract in your code: if you’re not using your data correctly, it won’t even build!

Types aren’t everyone’s jam, but they’ve grown on me for widely shared, highly complex, or difficult-to-change parts of the code. For the rest of the code, in React at least, PropTypes will help you catch errors more quickly and have more confidence in your codebase.

When a developer does something “just to be safe,” it’s a hint that there’s an unrecognized unknown. Ignoring these hints can cause small problems to accumulate into large problems. Know what errors you want when you’re making changes, how to guard against those you don’t, and learn to trust your code.

Thanks to Mae Capozzi .
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