The client is predefined to access a server at localhost. If you are trying this out on an external host, gome the settings. Login The login command is very basic. We filter a stream based on the User-table by the specified mail and password, and if we get a match, we create a session and return the key. Write login function.
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Then, if there is at least one match, the first match will be mapped using the newSesstion method whereby we get a new session id ofr the user and we return that. However, since findAny returns an Optional we will return false if there are no matches. Self This command is also very easy to implement. When the fof logs into the network or opens the profile page, this command will be called to retrieve a json-encoded string with all the information about the currently logged in user. Since we already have a method for finding the current user remember getLoggedIn we wrote earlier?
The somewhat tricky part is to encode the retrieved entity object into json. Luckily for us, Speedment has a utility class for this called JsonEncoder. The JsonEncoder is available in the json-stream speedment plugin which becomes available by adding an explicit dependency in the project pom. Add the following lines to the list of dependencies near the end of the pom. At the top of the file, we will create two encoders that will be used to json encode users, one without exposing sensitive information, and another to encode all fields of a user object.
Upload In this lab, we use baseencoded strings to store images in the database.
Since the encoding and decoding are done by the client, all we have to think about is making sure the user hoome authorized, and if so, add a row to the correct table. If a user is logged in, we create an ImageBuilder, fill in all the details and persist it in the database. Notice that we get the user id from the user object currently stored in the session map. If the user is not present or if the upload fails for some reason, the Optional will not be present at the end and false will be returned.
Transactions can scial if the database refuses the operation. A common example of this is that a constraint like a unique index or a foreign key prevents us from adding a row with that information. In the onUpload example above, the operation should never fail as long as the logged in user has not been removed manually from the schema. Find The find-command is one of the most interesting tasks to implement.
The purpose is to locate interesting users on the network based on a free ffor search. The users found should also be encoded to a JSON string. Apu method takes a sessionKey as the search result might be customized depending who is asking the question. We will do this in three steps. First off, we write a solution that returns all users and format them correctly, without any filtering. This will be an acceptable solution, even though it is not very good. Write find function.
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If the user is not logged in, the Optional will be empty from the beginning and "false" will be returned. Now we can start with iwki actual logic. First, we only want to see users that match the inputted text in some way. To do this, we create a custom predicate that checks if any field starts with the inputted text. Using the "or" concatenator, we can create nested predicates with many complex criteria to express our query. The solution above should work now if you want to try it out. There are still plenty of room for improvement though. One irritating thing you will notice is that we show up in the list.
Tutorial: Build a Social Network
Following yourself is unnecessary as you will always see your own pictures so this needs to be filtered sociao. We also need to remove all users that we are already following to make room for new, more interesting uploaders. To do this we can reuse the same jsonUserEncoder as we created earlier. This is very similar to the onUpload command.
Write follow function. The medis has two optional parameters for limiting the amount of pictures to load to a certain timespan. Wili response to a common use of sending data to a remote server immediately after a request, OpenSocial 0. Data pipelining allows the developer to specify the social data the application will need and make the data immediately available. OpenSocial Templates were introduced to create data-driven UI with a separation of markup and programmatic logic.
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OpenSocial Markup Language OSML Markup is a new set of standardized tags to accomplish common tasks or safely perform normally unsafe operations within templates. OSML is extensible. Developers can create a library of their own custom tags. The RESTful protocol that was introduced in v0. Existing gadgets continued to use v0. After updating the gadget, it would use v0. Another major announcement came from Apache Shindig. Apache Shindig made gadgets open sourced.