Building an RSS Reader for Android from nothing #2: Searching for feeds using Feedly’s Search API

Previously, I wrote about the component that handles retrieving and parsing raw RSS feeds from the web. This component represents one of NiceFeed’s main data sources, giving us an actual RSS feed, in the form of interrelated model objects that we’ve defined (Feed, Entry, FeedWithEntries), which the app can then display. All we need to do is give it the URL of any particular RSS feed, and it does all the work.

In real life, nobody’s going to want to keep entering URLs manually; sometimes, a user won’t even know what they are. A respectable RSS reader would have to have some way for the user to search for new feeds. Therefore, we need another data source—this data source would accept a keyword and return to the user a list of RSS feeds from the internet based on that keyword. The user would then able to choose any of these RSS feeds to subscribe to.

Feedly’s public Search API exists for this very purpose. It accepts a string search query as input, with some optional parameters such as the number of desired search results and a specific locale; in return, we get an organized collection of data in the form of JSON. This data, basically a collection of RSS feeds, is organized into fields such as “title,” “website,” “feedId,” “description,” and so on.

To get this data into the app, we pick the fields we want and create a new data class containing relevant properties corresponding to those fields. I named this data class SearchResultItem, which represents one item (containing data from one RSS feed) in a list of search results.

data class SearchResultItem(
    val title: String?,
    @SerializedName("feedId") val id: String?,
    val website: String?,
    val description: String?,
    val updated: String?,
    @SerializedName("visualUrl") val imageUrl: String?
): Serializable

To actually accomplish the task of communicating with Feedly API to obtain the needed data, some housekeeping is needed. I used the Retrofit library to do all the heavy lifting with regard to networking and parsing JSON from Feedly, making it very easy to implement the whole thing. All that’s needed is a simple interface which sends the request to the API, with an annotation that defines the request—in this case @GET, which represents the method for fetching data. The method returns a Call, which represents one HTTP request, with the parameter SearchResult—a class defined solely to contain one or more SearchResultItems—representing the type of a successful response.

interface FeedlyApi {
    fun fetchSearchResult(@Url url: String): Call<SearchResult>
class SearchResult {
    lateinit var items: List<SearchResultItem>

And now for the main event. I created a class called FeedSearcher to contain all the methods needed to carry out a Feedly search request. It has one public method: getFeedList, which takes a String query or keyword, and returns a LiveData wrapping a list of SearchResultItems.

/*  Generates a search query and returns a list of results from Feedly */
class FeedSearcher(private val networkMonitor: NetworkMonitor) {

    private val retrofit = Retrofit.Builder()
    private val feedlyApi = retrofit.create(

    fun getFeedList(query: String): LiveData<List<SearchResultItem>> {
        return if (networkMonitor.isOnline) {
            val path = generatePath(query)
            val request: Call<SearchResult> = feedlyApi.fetchSearchResult(path)
        } else {

    private fun generatePath(query: String): String {
        return Uri.Builder()
            .appendQueryParameter("count", RESULTS_COUNT.toString())
            .appendQueryParameter("query", URLEncoder.encode(query, "UTF-8"))

    private fun fetchSearchResult(
        request: Call<SearchResult>
    ): MutableLiveData<List<SearchResultItem>> {
        val searchResultLiveData = MutableLiveData<List<SearchResultItem>>()
        val callback = object : Callback<SearchResult> {
            override fun onFailure(call: Call<SearchResult>, t: Throwable) {} // Do nothing

            override fun onResponse(
                call: Call<SearchResult>,
                response: Response<SearchResult>
            ) {
                val feedSearchResult = response.body()
                searchResultLiveData.value = feedSearchResult?.items ?: emptyList()

        return searchResultLiveData

    companion object {
        private const val RESULTS_COUNT = 100
        private const val BASE_URL = ""

There are several things going on here. First we need a Retrofit object with a base URL of “” to be able to do anything—it accepts the above FeedlyApi interface, and uses it to create a request. To the request itself, we pass a String path to make a complete search URL on top of the base URL; the private method generatePath accepts our String query and returns it in the form (which includes a specified number of search results, in this case 100) that the Feedly search engine expects.

Finally, within the private method fetchSearchResult, the request object is enqueued, which actually executes the HTTP request. The method immediately returns a LiveData to the previous method that called it. We also pass in a callback object that defines what should happen after a request completes successfully or unsuccessfully. In this case, upon a successful request, the aforementioned LiveData is updated with the response—a list of SearchResultItems. And thanks to the attached GsonConverterFactory, Retrofit automatically does the work of parsing the response body from JSON.

Like our first data source, FeedParser, FeedSearcher is also self-contained so that we can completely replace it with something else without affecting anything else in the app, although Feedly’s search engine works perfectly for my purposes. The most important thing it gives us is a collection of usable RSS feed URLS—any of these URLS can then be passed on to FeedParser to attempt to retrieve an actual RSS feed.

Building an RSS reader for Android from nothing: RSS feed retrieval and parsing

I’ve been meaning to write a series of posts about how I built NiceFeed—not a tutorial nor a step-by-step kind of thing, but more like a walkthrough of all the moving parts, how they came to be, and how they all fit together. I present it neither as an example of a great app nor of great programming—and naturally there are dozens of things that can be improved—but as a whole, I’m quite fond of it and use it everyday to get my news on my Android phone. My hope is to clarify some of my thinking about building the app and solving the many problems I encountered, so that it might be applied to future problems and projects. And of course, I hope that anybody who happens to stumble upon these posts may find them somehow instructive if not merely amusing.

RSS has been around for a long time and there are already many other readers and aggregators out there, but I’ve found many of them, particularly the free ones, awkward or difficult to navigate and jam-packed with features I don’t really need. My goal was an attractive and intuitive app, fully functional and with not too many frills.


An RSS feed appears in the wild as XML-formatted plain text, which needs to be parsed and converted to a form usable by an RSS aggregator application. I found that there were several third-party libraries for parsing RSS that already existed, so I didn’t have to write my own parsing code. I chose the aptly named RSS Parser because it seemed to be regularly updated and well documented. In addition, the library not only parses raw XML data, but executes its own HTML requests, making it very easy to get up and running.

To start, I had to decide on what specific data I wanted the app to obtain. RSS Parser, after retrieving and parsing an RSS feed from the web, returns a Channel (or, the feed itself) object, which contains a collection of Articles (the contents of that feed). Both Channel and Article objects contain properties (title, author, URL, image, etc.) we definitely want and some that we don’t need. So, I created my own data classes, Feed and Entry, to contain only those properties that I wanted. Between the two is a many-to-many relationship: a feed is associated with many entries, and a single entry can be associated with more than one feed—we’ll return to this particular detail another time.

Determining which properties to include and exclude involved a lot of hemming and hawing as I became more familiar with the RSS data I was getting. I also added a few of my own: in Feed, category, which defaults to “Uncategorized,” and unreadCount, which simply holds the number of entries associated with that feed that have are not marked as read; and in Entry, the properties isStarred and isRead, both pretty self-explanatory and necessary if we want to be able to keep track of whether entries have been read and/or starred (or marked as favorite).

data class Feed(
    @PrimaryKey val url: String, // Doubles as Feed ID
    var title: String,
    val website: String,
    val description: String? = null,
    val imageUrl: String? = null,
    var category: String = "Uncategorized",
    var unreadCount: Int
): Serializable

data class Entry(
    @PrimaryKey val url: String, // Doubles as Entry ID
    val title: String,
    val website: String,
    val author: String?,
    val date: Date?,
    val content: String?,
    val image: String?,
    var isStarred: Boolean = false,
    var isRead: Boolean = false
) : Serializable {


Now for the real action. I created a class called FeedParser to contain all RSS Parser-related code. This class would contain all the needed methods for interacting with RSS Parser, and act as the authority across the entire app on retrieving and parsing RSS feeds from the internet. Naturally the class evolved over time as the app grew, but its role was always the same. Note: RSS Parser uses Kotlin Coroutines so the methods that use it have to be “suspend” functions.

/*  Responsible for retrieving and parsing RSS feeds */
class FeedParser(private val networkMonitor: NetworkMonitor) {

    private lateinit var rssParser: Parser
    private val _feedRequestLiveData = MutableLiveData<FeedWithEntries>()
    val feedRequestLiveData: LiveData<FeedWithEntries?>
        get() = _feedRequestLiveData

    suspend fun getFeedSynchronously(url: String): FeedWithEntries? {
        rssParser = Parser.Builder().build()
        return if (networkMonitor.isOnline) {
            try {
                val channel = rssParser.getChannel(url)
                ChannelMapper.makeFeedWithEntries(url, channel)
            } catch(e: Exception) {
        } else null

    suspend fun requestFeed(url: String, backup: String? = null) {
        rssParser = Parser.Builder().build()
        if (networkMonitor.isOnline) {
        } else _feedRequestLiveData.postValue(null)

    fun cancelRequest() {

    private suspend fun executeRequest(url: String) {
        // Automatically makes several requests with different possible URLs
        Log.d(TAG, "Requesting $url")

        try {
            val channel = rssParser.getChannel(url)
            val feedWithEntries = ChannelMapper.makeFeedWithEntries(url, channel)
        } catch (e: Exception) {
            // If the initial request fails, try backup URL in different variations
            BackupUrlManager.getNextUrl()?.let { executeRequest(it) }
                ?: let {
                    Log.d(TAG, "Request failed")


    companion object {

        private const val TAG = "FeedParser"
        private const val UNTITLED = "Untitled"
        const val FLAG_EXCERPT = " "

FeedParser takes a NetworkMonitor as an injected dependency. We’ll take a look at that at a later time, but it’s very simple: just an object that monitors the device’s internet connectivity. It contains one public property: isOnline, which at any given time is either true or false. All web requests are first checked against this property before executing.

There are three public methods, the first two of which are very similar, and begin with a new instance of RSS Parser:

First, getFeedSynchronously, which is really only for retrieving a feed as a background task. It takes a String called url (the address of an RSS feed), uses it to make a web request, and returns a FeedWithEntries: an additional data class that combines one Feed with a list of associated Entries. As it is meant to run in a background thread, the function waits for the web request to be completed before proceeding to the next step—hence, it is synchronous.

data class FeedWithEntries(
    @Embedded val feed: Feed,
        parentColumn = "url",
        entityColumn = "url",
        associateBy = Junction(
            value = FeedEntryCrossRef::class,
            parentColumn = "feedUrl",
            entityColumn = "entryUrl"
    val entries: List<Entry>

Second, requestFeed, like the above, takes a String URL, and optionally a “backup” or second URL. Instead of returning anything, the main URL is passed first to a private method, executeRequest, which does the actual requesting via the current instance of RSS Parser. An object called BackupUrlManager notes the backup URL, if any, and hangs on to it until needed. We’ll take a closer look at it at a future time, but for now, all we need to know is that it generates different variations of the backup URL that can be used to retrieve a particular RSS feed.

Regarding the private method executeRequest: if there are any of these aforementioned variations of the backup URL, the method repeats itself via recursion until all variations are exhausted. Upon a successful request, the result is posted asynchronously to the class-level property feedRequestLiveData, which can then be read by whichever part of the app initiated the request.

The third public method is cancelRequest, which simply cancels the current instance of RSS Parser (and with it any pending request), and clears the BackupUrlManager.

You’ll notice also that in all of the above methods except cancelRequest, there is a reference to an object called ChannelMapper. As I said earlier, the RSS Parser object returns a Channel, which contains several properties as well as a collection of Articles. ChannelMapper is nested within FeedParser and contains methods for converting a Channel into a FeedWithEntries (again, a combination of one Feed and multiple Entry objects). This is just my way of organizing the code and keeping these methods in one place.

/*  Maps 'Channel' data into 'Feed' and 'Entry' objects */
private object ChannelMapper {

    private const val MAX_ENTRIES = 300 // Arbitrary
    private const val DATE_PATTERN = "EEE, d MMM yyyy HH:mm:ss Z"

    fun makeFeedWithEntries(url: String, channel: Channel): FeedWithEntries {
        val entries = mapEntries(channel, url)
        val feed = Feed(
            url = url, // The url that successfully completes the request is applied
            website = ?: url,
            title = channel.title ?: ?: url.shortened(),
            description = channel.description,
            imageUrl = channel.image?.url ?: channel.image?.link,
            unreadCount = entries.size

        Log.d(TAG, "Retrieved ${entries.size} entries from $url")
        return FeedWithEntries(feed, entries)

    private fun mapEntries(channel: Channel, url: String): List<Entry> {
        val entries = mutableListOf<Entry>()
        for (article in channel.articles) {
            if (entries.size < MAX_ENTRIES) {
                val entry = Entry(
                    url = ?: article.guid ?: "",
                    website = ?: url,
                    title = article.title ?: UNTITLED,
                    author =,
                    content = article.content ?: article.description.flagAsExcerpt(),
                    date = parseDate(article.pubDate),
                    image = article.image
            } else break
        return entries

    private fun parseDate(stringDate: String?): Date? {
        return if (stringDate != null) {
            SimpleDateFormat(DATE_PATTERN, Locale.ENGLISH).parse(stringDate)
        } else null

    private fun String?.flagAsExcerpt() = FLAG_EXCERPT + this

Here, the one public method, makeFeedWithEntries, accepts a String URL and Channel object and initiates the process of assigning all the data we need to properties that we specified earlier in the data classes Feed and Entry, and discarding the rest. The private method mapEntries, which makeFeedWithEntries calls within itself, does the same by looping through each Article contained in the Channel. In the end, we get a FeedWithEntries, ready to be stored or presented by the app.

Side note: at the bottom of ChannelMapper is a method flagAsExcerpt which extends a nullable String. I use it to flag any Entry whose content property is null and the description is not empty—in the wild, it means the entry is probably an excerpt. Many RSS feeds nowadays, especially from subscription sources, do not syndicate full versions of their content, only short excerpts. I have yet to do anything with flagged Entries, but might in the future: for example, the app could be made to open any Entry flagged as an excerpt automatically with the device’s default browser, instead of within the app.

And a final remark: I’ve written all my code with modularity and flexibility in mind, to the extent that I’m able. RSS Parser serves all my current needs but is not a perfect library—notably, it does not support Atom, and in the future I might want to use a different one. Since all the relevant code is contained entirely within the class FeedParser, we could easily create a new class with which to replace it as the final authority on all things related to retrieving and parsing RSS, without affecting much else in the app.

NiceFeed: Updating all subscriptions at once (And, picking up Python)

Per my earlier post, I had a nice break last week from working on NiceFeed while my internet was unusable. However, the plan to stay away from my computer turned out to be a miserable failure, and I decided instead to learn Python. I used Python Projects for Beginners: A Ten-Week Bootcamp Approach to Python Programming by Connor Milliken except instead instead of 10 weeks, I gave myself one. Of course, the real test is what to do with it now—I’d been planning to learn Django and pick up some backend skills, but the chapter on introductory data analytics really got my wheels spinning… We’ll see.

Anyway. A NiceFeed user emailed me about possibly adding an option to update all subscriptions at once. Up to this point, the closest thing I had was a background worker (via WorkManager) that cycles through all existing subscriptions but only updates one subscription every 15 minutes. If it finds any new content, it posts a notification displaying the most recent entry found. Needless to say, if a user has many, many subscriptions, it would take a long time for a full cycle to complete.

We want the app to be able to update all subscriptions in one move. This means quickly looping through every one of them, each time requesting the subscription URL, identifying any new content, and saving it to the database. To do this, I created a new CoroutineWorker class that does the following:

private val repo = NiceFeedRepository.get()
private val feedParser = FeedParser(repo.networkMonitor)

override suspend fun doWork(): Result {
    val feedUrls = repo.getFeedUrlsSynchronously()
    if (feedUrls.isEmpty()) return Result.success()

    for (url in feedUrls) {
        val currentEntryIds: List<String> = repo.getEntryIdsByFeedSynchronously(url)
        val feedWithEntries: FeedWithEntries? = feedParser.getFeedSynchronously(url)

        feedWithEntries?.entries?.let { entries ->
            val newEntries = entries.filterNot { currentEntryIds.contains(it.url) }
            val entryIds = { it.url }
            val oldEntryIds = currentEntryIds.filterNot { entryIds.contains(it) }
            repo.handleBackgroundUpdate(url, newEntries, oldEntryIds)

    return Result.success()

From there, it’s simply a matter of feeding it to WorkManager, which I’ve set to run the worker once a day. I’ve also added the option (via Snackbar message) to run the worker whenever new subscriptions are imported by OPML, since OPML only imports minimal feed data, without any entries. Now we are that much closer to a standard feature of most respectable RSS readers. I find that I enjoy “background” code like this much more than designing and creating the user interface… Hence, I’m still undecided as to whether I should also add a button to allow the option of running the worker whenever the user wants, rather than just on schedule. Thoughts for another day.