The above code pretty much defines the way looping works under the hood in Python. We've just reinvented a for loop by using a while loop and iterators. Stop our loop if we got a StopIteration exception while getting the next itemĭef funky_for_loop(iterable, action_to_do):.Execute the body of the for loop if we successfully got the next item.Repeatedly get the next item from the iterator.Get an iterator from the given iterable.We'll do so by attempting to turn this for loop into a while loop: def funky_for_loop(iterable, action_to_do): Now that we've learned about iterators and the iter and next functions, we'll try to manually loop over an iterable without using a for loop. You can take Pez out, but once a Pez is removed it can't be put back, and once the dispenser is empty, it's useless. You can think of iterators as Pez dispensers that cannot be reloaded. And if you pass them to next but they don't have a next item, a StopIteration exception will be raised. The only thing you can do with iterators is ask them for their next item using the next function. So you can get an iterator from every iterable. If you ask for the next item from an iterator and there are no more items, you'll get a StopIteration exception: > next(my_iterator) Iterators are stateful, meaning once you've consumed an item from them, it's gone. Once we have an iterator, the one thing we can do with it is get its next item by passing it to the built-in next function. Passing an iterable to the iter function will always give us back an iterator, no matter what type of iterable we're working with. We can ask each of these iterables for an iterator using Python's built-in iter function. This dictionary has two key-value pairs: > counts = We asked the same question twice and Python gave us two different answers. But if we ask the same question again, Python will tell us that 9 is not in squares. If we ask whether 9 is in our squares generator, Python will tell us that 9 is in squares. Let's take the same list of numbers and the same generator object: > numbers = If we then take the same generator object and pass it to the sum function, we might expect that we'd get the sum of these numbers, which would be 88. We can pass our generator object to the tuple constructor to make a tuple out of it: > tuple(squares) Let's say we have a list of numbers and a generator that will give us the squares of those numbers: > numbers = We're going to start off our journey by taking a look at some "gotchas." After we've learned how looping works in Python, we'll take another look at these gotchas and explain what's going on. In this article we'll dive into Python's for loops to take a look at how they work under the hood and why they work the way they do. Python's for loops don't work the way for loops do in other languages.
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Projected growth, 2020–2030: 22% (much faster than average) Women’s share of employment, 2021: 20% (software developers) and 47% (software quality assurance analysts and testers)Ģ020 annual median pay: $110,140 per year Software quality assurance analysts and testers identify problems with applications or programs and report defects. Software developers design computer applications or programs. Software developers and software quality assurance analysts and testers Occupational openings, 2020–2030 annual average: 16,300 Projected growth, 2020–2030: 33% (much faster than average) Typical entry-level education: Bachelor’s degree Information security analysts plan and carry out security measures to protect an organization’s computer networks and systems.Ģ020 annual median pay: $103,590 per year Here are five STEM occupations that are projected to grow faster than average from 2020–30, and in some cases much faster than average, in which at least 1 in 6 jobs were held by women: Bureau of Labor Statistics, Employment Projections Wage data cover non-farm wage and salary workers and do not cover the self-employed, owners and partners in unincorporated firms, or household workers. Wage data are from the Occupational Employment and Wage Statistics program, U.S. Overall, STEM occupations had a median annual wage of $89,780 in May 2020. These STEM occupations pay more, and sometimes significantly more, than the median annual wage for all occupations of $41,950. This day is an opportune time to look at employment statistics for women working in science, technology, engineering, and mathematics, or STEM.Įmployment statistics from the Current Population Survey show that women’s full-time employment has increased in many STEM occupations over the past decade, reaching a level of 2.3 million in 2021.Īs a group, STEM occupations are projected to grow 10.5% between 20, faster than the average for all occupations (7.7%). Friday, February 11 is International Day of Women and Girls in Science. In the Music Tag Editor tool, you can edit the cover photo of soundtracks as well as the tags.Music Tag Editor is one of the best free MP3 tag editors for Mac that offer the fastest features and help you in changing and editing the metadata of audio files. It allows you to share the MP3 you stream on social media platforms.The files are organized automatically and it removes the duplicate ones.It features waveform recognition technology which lets it detect the acoustic fingerprints of a file and provide you the information.Your search for a software that keeps it organized and clean may end on this tool. It features striking functions along with a friendly and attractive interface. TuneUp, another best MP3 tag editor, helps you in organizing the music collection with ease. You can easily remove the ID3 tags from the audio files.It allows you to write comments to your audio files.In this tool, you can easily copy and paste the data.iD3 tag editor is supported by iTunes, Winamp, Windows Media Player and many other software.It is free to use and is known to be a light software but sometimes, its interface becomes too challenging to comprehend. ID3 editor is one of the best MP3 tag editors for Mac operating system and Windows. In this tool, you can rename the filename, and remove the files easily.Ity enables easy searching for multiple files.Metabliss allows you to edit the song name, artist and many other tags easily.If you are looking for a steadfast editing tool then this one is worth the try. You may want to use MetaBliss, one of the coolest MP3 tag editors with friendly features that is available for MAC OS X for free. It features lookup from CDs allowing to look over the music in one go.It features AcoustID audio fingerprints for audio files to be recognized by actual music.MusicBrainz Picard supports multiple formats such as WMA, WAV, MP3, FLAC, OGG M4A and more.MusicBrainz Picard, introduced by MusicBrainz, counts as one of the best free MP3 Tag Editors for Mac that helps you edit metadata and supports files of several formats alongside the AcoustID feature. You can rename, and generate files in this tool.It supports ID3v1, ID3v2, MP4, Vorbis, APE, and ASF tags from multiple audio formats.It is easy to use and allows you to search the data online.This tool features smooth functionality which allows you to edit/replace the characters and copy tags.Read Also: Best MP3 Duplicate Songs Finder And Remover The best part about this software is that it lets you edit the truckload of audio files as quickly and easily as possible. Metadatics is yet another amazing MP3 tag editor that allows you to edit the information of music on the Mac system.
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It often includes more general information about concentration, interest stimulation, skimming techniques and ways to approach a text. Such a book usually provides speed and comprehension tests as well as techniques to improve reading. However, as this rapid and encouraging improvement is not sufficiently anchored, it often fades with time.Ī book about speed reading is the second possibility. It is quite usual for a slow reader to double and even triple his reading efficiency during a two-day class offering a positive atmosphere, carefully selected texts and comprehension tests. The fastest is probably a speed reading seminar based upon good materials and animated by a dynamic instructor. There are three possible ways to improve reading. On the other hand, human or computer speaking, with an average speed of 150 wpm, will always remain many times slower than a good reader, without any consideration of the skimming and skipping possibilities. The rapid improvement of voice recognition may gradually make typing virtuosity obsolete since a good typist performs well under the speed of speech. Unfortunately, since the age of 12, most readers do not substantially improve their efficiency and never reach their full capacity.Įvery computer-user who is also a slow typist is aware of the benefits he could obtain with a typing course, but nearly no one suspects the much higher profits he could reach by improving his reading comprehension and speed. We can also picture a racing driver never exceeding 30 mph or a pianist playing every day of the week for 20 years and only able to play music like a beginner. We may imagine a sprinter practicing every day for several years on the running track and then just calmly walking for a race. Thus, an efficiency ratio of seven divides these two categories.Ĭompare the results of the average reader to other areas. Reading efficiency is reading speed weighted by comprehension rate and it amounts to 200 x 60% or 120 efficient words per minute (ewpm) for the average reader and to 1000 x 85% or 850 ewpm for top readers. Things are even worse if we consider reading efficiency as well as speed. The average reader is five times slower than the good reader. Unfortunately, this is far from the real situation. With such an intense training everyone should be close to top performances. This seems surprising since most readers, actively reading work documents, newspapers, magazines, books or the contents of a computer display are practicing daily for at least one hour. Average readers are the majority and only reach around 200 wpm with a typical comprehension of 60%. If top readers read at speeds of above 1000 words per minute (wpm) with near 85% comprehension, they only represent 1% of readers. Reading is becoming more and more important in the new knowledge economy and remains the most effective human activity for transforming information into knowledge. |
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