partly-cloudy | seriously lightweight Python wrapper for the littleBits | REST library
kandi X-RAY | partly-cloudy Summary
kandi X-RAY | partly-cloudy Summary
A seriously lightweight Python wrapper for the littleBits cloud API
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Top functions reviewed by kandi - BETA
- Return the next input
- Get the percentage of the device
partly-cloudy Key Features
partly-cloudy Examples and Code Snippets
Community Discussions
Trending Discussions on partly-cloudy
QUESTION
I have an api call from dark skies that returns data as shown:
...ANSWER
Answered 2021-Mar-28 at 22:37You could use the PHP function json_decode (reference)
It would convert your received JSON data into objects or an array. eg.
QUESTION
the mock data in the layout section is showing alright. It is when I run the app no data is flowing into the recycler view. I'd appreciate it if you could take a look at my code below.
activity_hourly_forecast.xml:
...ANSWER
Answered 2020-May-06 at 12:58In your list item layout, you have the text color as white as well as the RecyclerView background is white. Because of that, the text will not be visible and you are getting a blank screen.
QUESTION
I have a CurrentWeatherResponse object that contains the JSON data recovered from a weather API using Retrofit. Here's the JSON response format:
ANSWER
Answered 2020-Apr-16 at 21:01If I correctly understood your problem, I have to say that @Embedded annotation is Room's annotation, not Gson's annotation. So it won't play rule to convert your response to Kotlin data object by Retrofit.
@Embedded annotation only is visible for Room Dao class to convert relational data base to your convenient object model.
So you need to write your own TypeConvertor for Gson.
QUESTION
I'm making a Forecast Request using DarkSky weather API and I do not understand the logic of the time values returned.
The request
...ANSWER
Answered 2020-Feb-27 at 19:18It's returning seconds instead of milliseconds. Multiply by 1000.
QUESTION
I am having issues using the Pad function (Padr) to fill in gaps within a time series. I have some code that downloads hourly data from a server, one day at a time for a specific time period. After each day of data has been downloaded the aim is to use pad to clear up the data and add in the time and date so it can be appropriately combined without an error.
The function downloads the data as a list and looks like the following:
...ANSWER
Answered 2019-Nov-09 at 11:01You can use complete from tidyr and create an hourly sequence between min and max time
QUESTION
I am using Dark Sky API to get weather information and icon parameter gives me cloudy, partly-cloudy, sunny etc. I saved icon images same name with icon names in the folder. I want to write this parameter inside the source path like
...ANSWER
Answered 2019-Aug-02 at 07:37you need to add the image inside the div using the following code:
QUESTION
I'm trying to build a weather app using angular and I'm trying to display icons according to the data received so I made this function that will return the icon according to the data:
...ANSWER
Answered 2019-Jul-22 at 21:39The other answers seem incomplete, so I'll add my own.
[innerHtml]="icon('rain')"
Consider what's happening in the template for the above statement. My guess is that double quotes in your class names are terminating the template string.
What you would end up with is [innerHtml]="'"'
This could evaluate to "'
... additional cases, etc
If you really wanted to clean this up more, you could abstract this switch statment to its own reusable component. That component could have an @Input() iconString, so to show multiple icons you just have multiple instance of the component. A Use-case could be something like:
QUESTION
I'm trying to convert my complicated JSON file with 150.000 observations to a dataframe. Someone generously helped me constructing the code, but I keep running into the same error: Error in 1:nrow(test) : argument of length 0. I've searched the topic on the community but none of the answers provided work in my case. Any tips are welcome!
These two lines give the error:
...ANSWER
Answered 2019-May-30 at 10:29That's because the converted json is a list of lists, which won't work with the nrow() funcition. Can you try this code instead and check if the result is what you expect?
QUESTION
Through an API I accessed weather information in Json format. I want to convert this data to a dataframe. The problem is that not for every date-city combination the api returns weather conditions, so a few rows are empty. Second , not every combination that does return gives the same aspects of the weather. My goal is to convert the Json to a dataframe, where rows that are empty are still showed in the dataframe (which does not happen when I unlist them) and the different aspects of the weather are properly showed under the right variable with NA values if there is no record for that particular variable. I've tried enlisting them and putting it into a dataframe, flattening the table etc (getting the error: arguments imply differing number of rows: 0, 1) . I've searched for this topic but none of them worked for my case (or maybe because I'm not that experienced I applied them wrong), but every tip is welcome!
The input looks like this:
...ANSWER
Answered 2019-May-28 at 15:55There is a problem dealing with the responses that return NULL. To simplify the issue, it is easier to remove these non responses and then parse the remaining JSON response. If desired, one can go back and add the empty rows for the non responses.
QUESTION
I have this following JSON request(only a snippet of it) and I am trying to parse the temperatureHigh in data[{}]. I can't figure out how to parse an array of objects thats inside an object. Im using Qt.
...ANSWER
Answered 2019-Mar-26 at 14:07This is the minimal JSON sample I worked with:
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Install partly-cloudy
You can use partly-cloudy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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