All language subtitles for 4. Challenge - Check if it Will Rain in the Next 12 Hours

In order to create my rain alert Python script.
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I want the script to be run every morning at 7:00 AM.
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Let's say that I'm going to head out of the door at 8:00 AM in order to go to
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work, I want my script to run at 7:00 AM,
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check the weather for the next 12 hours,
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so the time when I'm going to be away from home, and then send me a text message
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if it's going to rain today
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so that I can remember to bring an umbrella. That way I'll get notified before I
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leave home and I'll know how to prepare for the day.
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The data that we got back from open weather map contains the hourly
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weather forecast for the next 48 hours.
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So it starts from zero and goes up to 47.
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Now we're only interested in the next 12 hours
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because, if you imagine, this script is run at 7:00 AM
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then plus 12 hours, that's going to be 7:00 PM. By which time,
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hopefully I'm already on the way home
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and I don't need to worry about whether if it rains or not. That's the goal.
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And if we head back into our code,
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what we want to do is firstly modify certain parts.
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Now we know that at the moment,
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the response code that we're getting back from calling this API is 200.
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So it's successful. So we're going to call raise for status
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so that if there is right a problem and we don't get a 200 code that we
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actually raise an exception. Now,
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next we want to save our response.json as the weather data.
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And then we're going to work with this data in order to get the particular
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pieces that we're interested in. So if we look at this JSON that
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we get back, firstly, we don't really care about the current weather or
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the daily weather.
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So when we look at the API documentation
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which is probably the hardest part,
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making sure that you're diligent enough to read the entire documentation,
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there's often some good nuggets in there. For example, in this case,
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we can add another parameter called exclude
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which allows us to exclude some parts of the weather data that comes from the
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API. This should speed up the API fetching process
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and it also means that we're transferring less data across the internet. So we
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can get rid of the current, minutely and daily.
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We're only interested in the hourly and we have to provide this as a comma-
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delimited list. So if we take a look at their example, you can see here,
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they've said exclude and then they've said hourly, daily.
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And notice how it says without spaces. So as I always say,
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this is like going into somebody else's house.
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Everything is different. The way that the washing machine works is different,
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the way that their dryer works is different.
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So you really have to look at the API documentation when you were working
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with a new API just so that you're not caught out
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and you understand exactly what you have to do in order to be a good API user.
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Let's go back into our code and let's provide that extra parameter.
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So that was called exclude.
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And the thing that we want to exclude is going to be provided as a string.
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So we want to get rid of current, minutely and daily.
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So we're going to add that into the string and make sure that we separate each
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with a comma and without spaces.
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okay.
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Now when we hit run
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and when we get back our weather data and we print it out
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and we copy this and put it into our online JSON viewer,
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so let's replace all of the stuff that was there before
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and you can see the JSON we're getting back is now a lot simpler.
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We're only getting back the hourly weather
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forecast.
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So that's step one done.
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The next step is to dig through this hourly forecast and get hold of the thing
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that we're interested in, which is the actual weather condition.
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The way that weather services tend to provide the weather condition is through
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an ID.
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And I know this because I read the API documentation.
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It's not because I'm some sort of weather geek. Although, I mean,
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that's not a bad thing to be
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I guess. If we take a look inside the API key,
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if we scroll down in this documentation past the examples,
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you can see it provides all of the fields in the API response. So these are
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all of the things that we could possibly get back and what they mean.
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And you can see there's some really interesting things like the UV index or you
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can get, um,
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what does the temperature feel like based on the wind chill and actual ground
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temperature.
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But what we're mostly interested in is the hourly data.
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And then inside that the hourly weather data.
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So this hourly.weather.id is a weather condition id.
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And when you click on that link,
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it takes you to this table that shows you all of the weather condition codes
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that we could possibly get back in this particular field.
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Now you can see that all the codes that start off with a two means some sort of
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thunderstorm, and then starting with three
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that means some sort of drizzling starting, with five means rain, starting with
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six means snow. And then afterward we have the seven hundreds
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so these are atmospheric. Thing's like a bit of mist, a bit of smoke,
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a bit of dust or fog. And this is also incidentally,
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the reason why this weather key actually has a value that's in the form of
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a list. You can see that's denoted by the square brackets here.
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So there could actually be multiple weather conditions for a particular place
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at a particular hour. And that's because you could maybe have, um,
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snow, but you could also have fog at the same time. Now,
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when I looked through a lot of the examples and the documentation,
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it seems like the first item in that list is the main condition.
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So if it's going to rain, then it's going to be in that first item
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in the list of weather conditions. Inside that list,
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we have a dictionary or many dictionaries.
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Each of those contain a weather condition ID,
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the main condition name and the description.
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So if we look at this ID code 802,
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we can decode it in this table and you can see it means scattered clouds,
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25 to 50% of the sky is covered in clouds basically.
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Based on this list,
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we can say that well anything that has a code less than 700,
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then we probably will need an umbrella.
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I'm not sure how you stand on the umbrella in snow situation
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but I personally do like to hold an umbrella when it's snowing,
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especially because I live in a country where the snow is not crazy.
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It's just sort of,
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it's never sort of the beautiful snow where it's thick and it gets caught on
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your eyelashes. It's is the sort of annoying slush
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that's just sort of snow, but it sort of like somebody spitting at you.
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So in my case, I would prefer to have an umbrella if it was going to snow.
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I'm going to check for the codes that we get back from the open weather map
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API, and if the code is less than 700,
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then I'm going to advise my user to bring an umbrella.
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Here's a challenge for you.
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Can you figure out how to look through the data that we get back,
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which remember looks something like this, get hold of
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the first 12
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items from that hourly list.
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And then look at the weather and the first item in the weather list and also the
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ID. So you are going to go all the way down to this, but remember,
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you're going to do that for all of the items
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and you're going to check for the condition code. Now,
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if any of those ID codes are less than 700 then you want to be able to print
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out, bring an umbrella.
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So that's the goal, and the actual implementation
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I'll leave up to you because there's quite a few ways that you can do this.
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But I'm sure by now you're well prepared with all of your tools in Python to
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figure this out. If you want to make sure that your code is actually working,
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you can switch to a latitude and longitude that is definitely raining.
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So if you go to ventusky.com,
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they actually show you the live weather forecast.
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So we can look at precipitation, which is basically rain.
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And we can find some sort of unfortunate place
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which seems to be really heavily raining. For example,
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this place in Poland, Lodz,
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and if I spell that name correctly,
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right,
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Lodz, and then I'll add the country code Poland.
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And just to make sure in the map
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it's actually found the correct place. Yep that looks pretty much it.
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Then I can switch out my latitude and longitude with this rainy place.
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And that way I know that at least one of the results I get back is definitely
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going to contain some sort of rain
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right.
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Now if we look at their hourly data,
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you can see that the weather is basically just rain, rain, rain.
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So between looking at places which are sunny and places
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which are rainy,
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you should be able to get your code to work so that it tells you in the next 12
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hours
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if any of those condition codes are less than 700,
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which means it's got some form of precipitation.
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Pause the video and give this a go.
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Now.
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All right. So let's narrow down into this
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weather. If we want to get the weather for the next hour,
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then we have to tap into the first item in our hourly list
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and then we get hold of the weather
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and then we get hold of the first item in that list. Under the ID key,
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we'll get the actual value.
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We've talked about this in detail in previous lessons.
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If you've skipped a lot of lessons and you've come here directly,
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then it's going to be a little bit confusing
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and I recommend to review the previous lessons before you continue.
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Instead of printing the weather data, let's drill down.
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Let's get to the first item here, which is hourly.
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If we provide a set of square brackets and then we can access the value inside
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the hourly key like this.
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And now we've got a list with all of the hourly data and it looks pretty much
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like this.
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Now you can confirm this by also pasting this into the JSON viewer,
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replacing the previous text that was there. You can see
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we now have our 48 items in this list of hourly data. To drill further down,
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let's get hold of the first item in that list by providing a square bracket
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and then the index, which is zero.
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Now we're into the first item and this is what the data looks like.
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It's a lot shorter.
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Now we want to tap into the weather condition.
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So that means yet another set of square brackets and then the name of the key,
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which is weather. Now, it's pretty simple.
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It's simply giving us a list with only one item.
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Let's tap into that one item by using, again,
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square brackets, zero.
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And now we've got just a simple dictionary
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essentially. So if you want to get hold of the ID,
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then its the final square brackets and the key
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which is ID. The current weather data ID code is 500 and that, of course, refers to
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light rain.
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The next problem is how do we get hold of the first 12 items that we get back in
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our weather data? In previous lessons, we covered the Python
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slice function
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which could work for this by simply providing a value and slicing a sequence
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like a list or tuple to get hold of a particular section of that list or
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tuple. Now you can also use the Python slice operator
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which is the square bracket and a colon
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and this is probably a more pythonic way of doing things.
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And you'll see more people doing this in the wild than using the slice function.
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So let's do it with this notation. We're going to use this version.
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So we're going to tap into a list and then provide a colon and then where we
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want to stop because we want to go from the beginning of the list through to
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stop-1.
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We know that it's this part of our code that gets us to our list of hourly
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weather forecasts. So we want to create a slice from that data.
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So let's copy that and comment this line out.
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And then I'm going to create my weather slice
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which is going to be generated from the weather data under the key called
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hourly. If I print this,
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you can see it starts off just simply being a list with all of the weather
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forecasts. Now, if I go ahead and slice this,
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I'll use that syntax that you saw earlier on where we have a square bracket,
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a colon, and then where we want our slice to end.
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And we want this slice to go from zero all the way up to hour 11,
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so that's 12 hours in total. So if we want to go up to 11,
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then we have to put 12 in here because it's going to be whatever number here,
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minus one. And now if we print this data that we get back,
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and
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we replaced the existing text inside our JSON viewer,
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then we take a look at it
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you can see we've got the next 12 hours of weather data from 0 to 11.
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Once we've got that slice, the next step is, well,
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how do we get the rest of the stuff, right?
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What if I created a new list that contains the condition codes?
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We know that we've got a list of all of the weather conditions for the next 12
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hours.
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How can we loop through that list to find out the actual ID of the weather
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condition for each of those hours? Well,
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we can create a for loop that looks at each of the data from the hour,
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so for hour_data in weather_slice,
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so this is going to go through each of the 12 hours.
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And then for each of those hours,
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we're going to tap into the hour_data and try to get hold of the item that is in
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the weather key. Like this.
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Now I'm going to print each of these and you can see we've now got a list of all
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of the weather conditions for each of those hours.
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Now let's narrow down that a little bit further.
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Let's get hold of the first item of each of these lists and you can see,
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in fact, there's only one item in all of these lists.
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It's very rare that you have multiple weather conditions for each hour.
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Now, that gives us a Python dictionary for each of those hours
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and we can tap into that final value we're interested in under the key id.
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So now we've looped through the next 12 hours and got hold of the weather
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condition id for each of those hours. Now,
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all we need to do is to save this instead of printing it and we'll call it the
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condition_code.
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Yeah.
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And remember previously we said that if the condition code is less than 700,
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then we're going to print bring an umbrella.
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So we can check if condition_code,
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which remember at this point is still a string
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so we have to turn that into an integer in order to be able to compare it
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against another number.
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If that condition_code as an integer is less than 700,
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then we're going to print bring an umbrella,
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right?
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And you can see that for the next 12 hours
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there's six hours which are going to rain at this particular place
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in Lodz in Poland that I've put into that latitude and longitude.
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Now, if I don't want to call this print statement many times,
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then we can define a variable outside
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the for loop called will_rain and we can set that to false
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to begin with. Now, if during the next 12 hours
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the condition_code is less than 700, then we'll switch that to equal
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true instead. Now,
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after the for loop has completed,
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then we can check to see if it will rain in the next 12 hours. And if so,
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we'll print bring an umbrella. This way
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we'll only get one print statement being called instead of every single time we
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land on a condition code for rain.
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So this involved quite a bit of JSON passing and also understanding how to work
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with parameters in APIs. Now,
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I hope you managed to get this far by yourself.
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But if not, be sure to review what I've written and fix your code as required.
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If any of it was confusing,
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be sure to review previous lessons before you continue
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because we're now building heavily on your previous knowledge that you learnt
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through the course. Now in the next lesson,
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we're going to be looking at how we can, instead of printing
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bring an umbrella, to send a SMS text message that notifies you to bring an
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umbrella instead. So for all of that and more,
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I'll see you on the next lesson.