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The function* declaration creates a binding of a new generator function to a given name. A generator function can be exited and later re-entered, with its context (variable bindings) saved across re-entrances.
A function* declaration creates a GeneratorFunction object. Each time when a generator function is called, it returns a new Generator object, which conforms to the iterator protocol. When the iterator's next() method is called, the generator function's body is executed until the first yield expression, which specifies the value to be returned from the iterator or, with yield*, delegates to another generator function. The next() method returns an object with a value property containing the yielded value and a done property which indicates whether the generator has yielded its last value, as a boolean. Calling the next() method with an argument will resume the generator function execution, replacing the yield expression where an execution was paused with the argument from next().
\n A function* declaration creates a GeneratorFunction object. Each time when a generator function is called, it returns a new Generator object, which conforms to the iterator protocol. When the iterator's next()\n method is called, the generator function's body is executed until the first\n yield expression, which specifies the value to be\n returned from the iterator or, with yield*, delegates\n to another generator function. The next() method returns an object with a\n value property containing the yielded value and a done\n property which indicates whether the generator has yielded its last value, as a boolean.\n Calling the next() method with an argument will resume the generator\n function execution, replacing the yield expression where an execution was\n paused with the argument from next().\n
In fact, there's no JavaScript entity that corresponds to the Generator constructor. There's only a hidden object which is the prototype object shared by all objects created by generator functions. This object is often stylized as Generator.prototype to make it look like a class, but it should be more appropriately called GeneratorFunction.prototype.prototype, because GeneratorFunction is an actual JavaScript entity.
Acts as if a return statement is inserted in the generator's body at the current suspended position, which finishes the generator and allows the generator to perform any cleanup tasks when combined with a try...finally block.
Acts as if a throw statement is inserted in the generator's body at the current suspended position, which informs the generator of an error condition and allows it to handle the error, or perform cleanup and close itself.
Inverters: The best gas-powered generators are inverter generators with carbon monoxide detection and Bluetooth monitoring. They should be manufactured by a company with an established reputation for generators. We also looked at similarly sized battery-powered models, and although their battery drain poses some limitations, these units sidestep the inconveniences of owning a gas engine.
Lastly, as mentioned earlier, inverter generators can pair up to double the available power. Two 2,200-watt generators linked together, for example, behave like a single 4,400-watt generator. Making this connection requires a parallel kit, usually sold separately. The ability to double up like this is a nice option to have, but it does bring the added responsibility of maintaining two engines instead of just one.
Bluetooth: Some generators are now equipped with an app and Bluetooth connectivity, which together allow you to monitor power usage, shut the engine off, and get an estimate of the time remaining until the gas runs out. This kind of information feedback removes a lot of wattage-guessing and lets you maximize the available power.
We also tested sound with a Triplett SoniCheck sound meter at the unit and at distances of 5, 10, and 25 feet. We tested them idling in eco mode with no electrical draw and also at around 1,500 watts. In general, inverters of this size are pretty quiet, especially in eco mode, when the engine ramps up and down depending on the draw. Even with the loudest models, we could have a conversation around the generator without needing to raise our voices too much.
Following those checks, we spent the majority of our testing just using the generators: adding and removing wattage, intentionally overloading the generators, seeing how easily they started with a cold engine. We also looked at the engine setup and how easy it would be to drain the oil and change the spark plug. User friendliness played a big role: Are the gauges simple to read? Are the instructions clear? We also looked at portability, moving the generators from place to place and hoisting them onto a truck tailgate.
More than any other generator we found, the RYi2322VNM emphasizes convenience and user-friendliness. It was the only generator we tested that had a readout of the current load and remaining time on the face of the unit. This information also displays in the Bluetooth app, where you can switch eco mode on and off and reset the generator in case of an overload so it begins producing power again. When other generators overload, you need to shut them off and restart them manually. All of these added features in the Ryobi app have the potential to prevent trips outside to the generator in inclement weather.
The overall look and feel is very similar to that of the gas generators we tested. It has a handle at each end and weighs roughly the same as the Honda EU2200i, about 45 pounds with the two batteries. We would prefer to see a single top handle as on the other models, which would make this unit much easier to carry with one hand.
We did test an inexpensive model, the TackLife 2000-Watt Portable Inverter Generator. Its build quality was disappointing, with none of the finesse of the other generators (and no CO-detection feature). When our test unit arrived, we needed to force open the access panels because the holding clips had been installed in the wrong location. This model simply failed to measure up to the others, and we see it as representative of low-cost models sold on Amazon by brands not typically associated with generators. As a final indicator of its poor quality, the TackLife completely disappeared from Amazon as we were writing this guide.
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A common use case of generators is to work with data streams or large files, like CSV files. These text files separate data into columns by using commas. This format is a common way to share data. Now, what if you want to count the number of rows in a CSV file? The code block below shows one way of counting those rows:
You can also define a generator expression (also called a generator comprehension), which has a very similar syntax to list comprehensions. In this way, you can use the generator without calling a function:
Here, you have a generator called gen, which you manually iterate over by repeatedly calling next(). This works as a great sanity check to make sure your generators are producing the output you expect.
Generator functions look and act just like regular functions, but with one defining characteristic. Generator functions use the Python yield keyword instead of return. Recall the generator function you wrote earlier:
Instead, the state of the function is remembered. That way, when next() is called on a generator object (either explicitly or implicitly within a for loop), the previously yielded variable num is incremented, and then yielded again. Since generator functions look like other functions and act very similarly to them, you can assume that generator expressions are very similar to other comprehensions available in Python.
When you call a generator function or use a generator expression, you return a special iterator called a generator. You can assign this generator to a variable in order to use it. When you call special methods on the generator, such as next(), the code within the function is executed up to yield.
When the Python yield statement is hit, the program suspends function execution and returns the yielded value to the caller. (In contrast, return stops function execution completely.) When a function is suspended, the state of that function is saved. This includes any variable bindings local to the generator, the instruction pointer, the internal stack, and any exception handling.
As of Python 2.5 (the same release that introduced the methods you are learning about now), yield is an expression, rather than a statement. Of course, you can still use it as a statement. But now, you can also use it as you see in the code block above, where i takes the value that is yielded. This allows you to manipulate the yielded value. More importantly, it allows you to .send() a value back to the generator. When execution picks up after yield, i will take the value that is sent.
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