Json design

We use dummy text because from a design perspective the focus is usually on the visual UI rather than the content, but if we see the UI from an user perspective, actually is the content the most important element, being the interface just the context to show it. So, how can we improve our workflow to guarantee the quality of the content we are using for designing?

Regarding the organization of data, we need to learn more from Developing and seed datawhich is used in the product as a replacement of real data the users are going to generate later. This seed data usually is generated inside a.

However, we can use JSON files. The user flow is a simple access to a database, which includes a confirmation when the user tries to delete an entry. The flow looks like this:. Now, translating this user flow to UI, those 3 environment look like this. This is the structure in this case:. The first step is to identify the nature and function of each value we are using in the interface.

From a high level, there are 2 type of values: Reusable and Contextual data. Why do we need to have this information in a repository? Because this give us the opportunity to work collaboratively in case this information requires to be reviewed and improved by other people. This is how the structure looks in GitHub the files are empty yet :.

Now we can work in each JSON file. Here we are going to include the information we need per each user, considering our table in the database environment: Username, role, location and joined date. We enter this information creating an ID per each user. Then the context. Craft has a functionality that can allows us to pull data from a JSON file, so we paste the URL there and we can see our structure in Sketch, ready to be used:.

Once we got our data in Sketch, we can go to the table symbol — where we are going to use this data — and select the symbol we want to use. When we select a value from the JSON file, Sketch will ask us what is the value we want to connect with.

json design

This is the reason why we need to use placeholders describing the function of the value, otherwise in bigger designs will be really confusing to connect the information. I did the same with all the elements of the design. Once the process has been completed, the environments look like this.Author: Kent Graziano. With the rise of mobile devices and applications, as well as the Internet of Things, the number and variety of data sources has grown exponentially over the past decade.

IDC recently estimated that zettabytes of data will have been created by In order for businesses to be able to use all this data to drive growth, they must first be able to understand it. Effective data modeling is critical to making these massive new data streams and formats usable. Data modeling helps define the structure and semantics of the data, so business users and data scientists can be properly query, manipulate, and analyze it.

Businesses that employ Schema-on-Write methodology know the importance of data modeling. With the more recent advent of the Schema-on-Read methodology, in which the goal is to load data into the system as quickly as possible and without upfront design and modeling, the role of data modeling has taken a backseat. Still, it remains no less important. Schema-on-Read first rose to popularity among software developers, because it shortened the delivery time for working applications.

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Schema-on-Read allows applications to store data in semi-structured formats such as JavaScript Object Notation JSON and to rapidly iterate on it without breaking the database behind the applications.

This was a boon to software developers, but it posed a challenge for the data scientists and data warehouse users who wanted to create reports from the data or analyze it. As flexible and fast as Schema-on-Read is, it also requires that data be transformed into an understandable relational model of some kind in order to allow business users to make sense of it.

As it turns out, semi-structured data can be transformed into a relational model by applying data modeling best practices. With JSON documents, it is relatively easy to identify the elements needed to create a relational database within them, including key:value pairs, nested keys, and arrays.

A data warehouse architect need only be familiar with the notation of these document types in order to discern their structure and develop a model that can be queried within a data warehouse. Using the same principles of data design, semi-structured data such as JSON can be transformed into any model: third normal form 3NFa star schema, or Data Vault.

By examining the content and forms within these semi-structured documents, a data modeler can transform them into actionable, useful data sets that businesses can leverage to generate value. Doing so is worth the effort: Getting a handle on how to treat semi-structured data will greatly increase the amount and types of data available to the business, such as mobile application data or consumer sentiment data, because social media data such as tweets and hashtags are typically semi-structured.

Businesses can use this data to inform business decisions, optimize processes, and create a competitive advantage. Regardless of the data model the business chooses and the tools it employs to implement the model, the goal remains the same: an actionable model that can be queried, understood, and used to derive business value from an ever-increasing stream of data.

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Skip to content. Like what you read? Show your appreciation through likes and shares! Facebook Twitter LinkedIn. Main Blog.If you want to view a beautify version of your JSON stringyou can use thi tool. I'll expand a little on each one, below.

Site design JSON schema

However, crucially, it makes a big difference as to how the JSON is structured. The simpler the JSON structures are, the easier it is to write correct code to deal with them. This is part of why it is so important to prototype some code to work with a structure you are considering, as it gives you a much better sense of how easy it is to work with a given JSON structure. For example, let's say that you want to represent a date in your JSON. You decide that you will call it "arrivalDate" and that you will make this a number which means it is easy to do date arithmetic, for example :.

Later, however, you realize that you need to indicate in which timezone this date occurs. Later, you realize that there are multiple kinds of headline. Your old XML documents with a single headline are still valid, according to your new schema.

One technique I've used when having to switch from single instances to array properties is to name my properties carefully. When a property is an array, I make it a plural.

This leaves open the possibility of having a singular property - such as "headline" - and then later adding an array property with the plural name - "headlines". Flatter is better In XML, it is natural to have multi-level structures.

When XML is pretty-printed, the indentation of enclosing elements helps to make the document structure easier to grasp. It is tempting to do the same when designing your JSON representation. In particular, it is difficult to query JSON using complex criteria.

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In part, this is due to a lack of standards for how to specify JSON queries. So, the less structure the better. Most of the JSON formats I've worked on are designed to be used by multiple systems whether internally to AP or as a standard to be used by many publishers. To help ensure that multiple implementations wind up using your JSON in compatible ways, you want to restrict the degrees of freedom to interpret the format in different ways.Most modern web applications expose APIs that clients can use to interact with the application.

A well-designed web API should aim to support:. Platform independence. This requires using standard protocols, and having a mechanism whereby the client and the web service can agree on the format of the data to exchange. Service evolution. The web API should be able to evolve and add functionality independently from client applications. As the API evolves, existing client applications should continue to function without modification. All functionality should be discoverable so that client applications can fully use it.

REST is an architectural style for building distributed systems based on hypermedia. REST APIs are designed around resourceswhich are any kind of object, data, or service that can be accessed by the client. A resource has an identifierwhich is a URI that uniquely identifies that resource. For example, the URI for a particular customer order might be:.

Clients interact with a service by exchanging representations of resources. HTTP requests should be independent and may occur in any order, so keeping transient state information between requests is not feasible. The only place where information is stored is in the resources themselves, and each request should be an atomic operation. This constraint enables web services to be highly scalable, because there is no need to retain any affinity between clients and specific servers.

Any server can handle any request from any client. That said, other factors can limit scalability. For example, many web services write to a backend data store, which may be hard to scale out. For more information about strategies to scale out a data store, see Horizontal, vertical, and functional data partitioning. For example, the following shows a JSON representation of an order. It contains links to get or update the customer associated with the order.

In practice, many published web APIs fall somewhere around level 2. Focus on the business entities that the web API exposes. For example, in an e-commerce system, the primary entities might be customers and orders. The HTTP response indicates whether the order was placed successfully or not.

When possible, resource URIs should be based on nouns the resource and not verbs the operations on the resource.But what exactly is JSON? What can it do, and how do you use it? JSON is a simple, text-based way to store and transmit structured data. By using a simple syntax, you can easily store anything from a single number through to strings, arrays, and objects using nothing but a string of plain text.

You can also nest arrays and objects, allowing you to create complex data structures. JSON is most commonly used in web applications to send data from the server to the browser.

Typically you transfer JSON data using Ajaxwhich lets your web application exchange data and messages between the browser and the server without having to reload the page. This approach is less common, since the data sent in Ajax requests tend to be fairly simple for example, a product ID.

To put double quotes inside strings, use the backslash character to escape the double quotes: ". You can also put control characters and hexadecimal-encoded characters in strings using the backslash, like you do in most programming languages. See the JSON website for details. As you can see, this XML version is a fair bit longer. The XML version is also harder to read.

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Fortunately, most programming languages give you tools that can easily turn variables into JSON strings, and vice-versa. The basic idea is as follows:. Notice that JSON. These let you do things like encode certain special characters using hex notation to make the string more portable, and force empty and indexed arrays to be encoded as objects associative arrays. Find out more. These are generic PHP objects of the stdClass class. For example:. Although simple to understand and use, JSON is a very useful and flexible way to transfer data between applications and computers, particularly when sending Ajax data from server to browser.

As you can see, the problem is on line 17 of your JSON.The site design is a list of actions. For more complex actions, such as creating a list, there are also subactions.

JSON Basics: What You Need to Know

Each action is specified by a "verb" value. Verb actions are run in the order they appear in the JSON script. Only the verb actions listed here can be used; otherwise, an "unable to handle action" error will be thrown when trying to upload a site script.

json design

More actions will be added over time. Actions can be run more than once on a site.

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Rerunning actions on the same site with the same parameters will result in an update to the existing schema and not duplication of schema. Once createSPList is applied on a site, runnning the createSPList with the same list name will act as an update to the existing list. Typically you would use value The full list of template type values is documented in SPListTemplateType enumeration - but the ones we currently support include:.

If you use or and reference the default names "Documents" or "Site Pages"you can modify the library created with the template. See example below. The subactions array provides additional actions to specify how to construct the list. Subactions are also specified using a verb value.

json design

For reference, see Field element Field. Providing the ID attribute in the field schemaXml is important in order to prevent the field from being created multiple times if the script is run more than once.

Currently these field constructs can't be designated as site columns nor added to content types. Subaction to add a previously defined site column directly to a list existing or created through the site script.

Defines and adds a view to the list. Use this action to specify the desired columns and how you want the list items displayed using a CAML query. Action properties allow you to specify row limits, and whether the view is paged and recurses over items in nested folders. You can also designate your constructed view as the default. Removes a view from a list. This action can also be used to remove a view applied by the site template. Adds a content type to the list.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again. There are myriads of JSON libraries out there, and each may even have its reason to exist. Our class had these design goals:. Intuitive syntax. Check out the examples below and you'll know what I mean. Trivial integration. Our whole code consists of a single header file json.

That's it. No library, no subproject, no dependencies, no complex build system. All in all, everything should require no adjustment of your compiler flags or project settings.

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Serious testing. Furthermore, we checked with Valgrind and the Clang Sanitizers that there are no memory leaks.

JSON Basics: What You Need to Know

Memory efficiency. Each JSON object has an overhead of one pointer the maximal size of a union and one enumeration element 1 byte. There are certainly faster JSON libraries out there.

However, if your goal is to speed up your development by adding JSON support with a single header, then this library is the way to go. If you know how to use a std::vector or std::mapyou are already set. See the contribution guidelines for more information. You can sponsor this library at GitHub Sponsors. You need to add. To allow your project to support either an externally supplied or an embedded JSON library, you can use a pattern akin to the following:.

If you want the bleeding edge rather than the latest release, use brew install nlohmann-json --HEAD. If you are using the Meson Build Systemadd this source tree as a meson subproject.

You may also use the include. Please see the meson project for any issues regarding the packaging. The provided meson. In Meson, it is preferred to use the dependency object with a subproject fallback, rather than using the subproject directly.

Working with JSON

Please file issues here if you experience problems with the packages. If you are using Spack to manage your dependencies, you can use the nlohmann-json package. Please see the spack project for any issues regarding the packaging. Please see the hunter project for any issues regarding the packaging. If you are using Buckarooyou can install this library's module with buckaroo add github. Please file issues here.


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