---
title: Backend app
---
# Backend app
This app is in charge of CRUD of data, integrity validation and persistence
into a database and also into a file system for media attachments.
To handle deletions it uses a garbage collector mechanism: no object in the
database is deleted instantly. Instead, a field deleted_at
is set with the
date and time of the deletion, and every query ignores db rows that have this
field set. Then, an async task that runs periodically, locates rows whose
deletion date is older than a given threshold and permanently deletes them.
For this, and other possibly slow tasks, there is an internal async tasks
worker, that may be used to queue tasks to be scheduled and executed when the
backend is idle. Other tasks are email sending, collecting data for telemetry
and detecting unused media attachment, for removing them from the file storage.
## Backend structure
Penpot backend app code resides under backend/src/app
path in the main repository.
@startuml BackendGeneral
!include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml
!define DEVICONS https://raw.githubusercontent.com/tupadr3/plantuml-icon-font-sprites/master/devicons
!include DEVICONS/react.puml
!include DEVICONS/java.puml
!include DEVICONS/clojure.puml
!include DEVICONS/postgresql.puml
!include DEVICONS/redis.puml
!include DEVICONS/chrome.puml
HIDE_STEREOTYPE()
Container(frontend_app, "Frontend app", "React / ClojureScript", "", "react")
System_Boundary(backend, "Backend") {
Container(backend_app, "Backend app", "Clojure / JVM", "", "clojure")
ContainerDb(db, "Database", "PostgreSQL", "", "postgresql")
ContainerDb(redis, "Broker", "Redis", "", "redis")
}
BiRel(frontend_app, backend_app, "Open", "websocket")
Rel(frontend_app, backend_app, "Uses", "RPC API")
Rel(backend_app, db, "Uses", "SQL")
Rel(redis, backend_app, "Subscribes", "pub/sub")
Rel(backend_app, redis, "Notifies", "pub/sub")
@enduml
```
▾ backend/src/app/
▸ cli/
▸ http/
▸ migrations/
▸ rpc/
▸ setup/
▸ srepl/
▸ util/
▸ tasks/
main.clj
config.clj
http.clj
metrics.clj
migrations.clj
notifications.clj
rpc.clj
setup.clj
srepl.clj
worker.clj
...
```
* main.clj
defines the app global settings and the main entry point of the
application, served by a JVM.
* config.clj
defines of the configuration options read from linux
environment.
* http
contains the HTTP server and the backend routes list.
* migrations
contains the SQL scripts that define the database schema, in
the form of a sequence of migrations.
* rpc
is the main module to handle the RPC API calls.
* notifications.clj
is the main module that manages the websocket. It allows
clients to subscribe to open files, intercepts update RPC calls and notify
them to all subscribers of the file.
* setup
initializes the environment (loads config variables, sets up the
database, executes migrations, loads initial data, etc).
* srepl
sets up an interactive REPL shell, with some useful commands to be
used to debug a running instance.
* cli
sets a command-line interface, with some more maintenance commands.
* metrics.clj
has some interceptors that watches RPC calls, calculate
statistics and other metrics, and send them to external systems to store and
analyze.
* worker.clj
and tasks
define some async tasks that are executed in
parallel to the main http server (using java threads), and scheduled in a
cron-like table. They are useful to do some garbage collection, data packing
and similar periodic maintenance tasks.
* db.clj
, emails.clj
, media.clj
, msgbus.clj
, storage.clj
,
rlimits.clj
are general libraries to use I/O resources (SQL database,
send emails, handle multimedia objects, use REDIS messages, external file
storage and semaphores).
* util/
has a collection of generic utility functions.
### RPC calls
The RPC (Remote Procedure Call) subsystem consists of a mechanism that allows
to expose clojure functions as an HTTP endpoint. We take advantage of being
using Clojure at both front and back ends, to avoid needing complex data
conversions.
1. Frontend initiates a "query" or "mutation" call to :xxx
method, and
passes a Clojure object as params.
2. Params are string-encoded using
[transit](https://github.com/cognitect/transit-clj), a format similar to
JSON but more powerful.
3. The call is mapped to /api/rpc/query/xxx
or
/api/rpc/mutation/xxx
.
4. The rpc
module receives the call, decode the parameters and executes the
corresponding method inside src/app/rpc/queries/
or src/app/rpc/mutations/
.
We have created a defmethod
macro to declare an RPC method and its
parameter specs.
5. The result value is also transit-encoded and returned to the frontend.
This way, frontend can execute backend calls like it was calling an async function,
with all the power of Clojure data structures.
### PubSub
To manage subscriptions to a file, to be notified of changes, we use a redis
server as a pub/sub broker. Whenever a user visits a file and opens a
websocket, the backend creates a subscription in redis, with a topic that has
the id of the file. If the user sends any change to the file, backend sends a
notification to this topic, that is received by all subscribers. Then the
notification is retrieved and sent to the user via the websocket.