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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Gleam’s singleflight package coalesces overlapping requests that use the same key: one worker performs the work and waiting callers share its result. It is useful when multiple requests arrive for the same expensive operation at once, but it is not a cache and does not promise reuse by later requests. This guide uses the package’s documented v1.1.0 API and explains how it fits Gleam’s typed process and OTP model.
What single flight does—and what it does not
Single flight deduplicates concurrent work by key. If several callers request the same key while a worker is already handling it, the package lets them share the result rather than starting equivalent work independently. Requests for different keys are distinct work.
This applies to overlapping requests, not persistent storage. Once the work has finished, a later independent request is not guaranteed to receive a saved result; use a cache or other storage layer when you need that behavior. Single flight also does not make the underlying work infallible: callers need to handle worker or actor crashes and timeouts.
Use the Gleam singleflight package
The documented package version is 1.1.0. Its example follows three steps: create a process name, configure and start the singleflight actor, then call fetch with a key and work function. Consult the singleflight v1.1.0 documentation for the exact module imports, configuration fields, and function types for your project.
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The outcome of fetch is a result: handle a successful value, Crashed, and TimedOut. For example, the control flow should have this shape:
case singleflight.fetch(name, key, work) {
Ok(value) -> use_value(value)
Error(singleflight.Crashed) -> handle_crash()
Error(singleflight.TimedOut) -> handle_timeout()
}This is illustrative control flow, not a complete compiling program: the actual module paths, types, and configuration depend on the package API. A worker that exits before producing a value can lead to Crashed; a fetch that receives no reply within its configured timeout can lead to TimedOut. Decide what your caller should do in each case—for example, report an error, retry under a bounded policy, or serve a fallback—rather than treating either result as success.
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How Gleam processes and actors fit
BEAM processes are the underlying concurrency primitive. Gleam’s process APIs use typed subjects: a subject identifies the kind of messages a process can receive, so sending through it is checked against that message type. A request-reply call sends a request containing a reply subject and waits for a response up to a timeout.
An actor is the higher-level pattern for a long-lived process that repeatedly handles messages while retaining state. The actor interface is designed to keep message handling type-safe. The Gleam OTP project describes its actor as the common process type and notes that it handles OTP system messages used for debugging and tracing.
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Single flight is a higher-level use of this process model: callers ask an actor to fetch work by key, while the package manages request coalescing. You can think of raw message handling as the lower-level choice when you need custom behavior, an actor as a stateful message-handling abstraction, and single flight as a specialized abstraction for deduplicating concurrent same-key work.
Supervision, ownership, and restart behavior
OTP supervisors start and monitor child processes, and can restart a child that crashes. Supervisors can themselves be children, creating a supervision tree. This makes ownership and restart boundaries explicit: for example, a top-level supervisor might own database, monitoring, and HTTP-handling workers.
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A restart restores the process structure, not the crashed process’s in-memory state. Any state the worker held must be reconstructed by its startup logic or recovered from an external source. When integrating a long-lived service such as single flight, decide which supervisor owns it and what callers should do while it is restarting; do not assume that a restart preserves work already in progress.
Gleam OTP provides typed APIs for core OTP concepts and interoperability with Erlang’s OTP framework, not every Erlang/OTP feature. The project identifies type safety, OTP compatibility, fault tolerance, and supervisor-based self-healing among its goals, while noting that some supervision strategies remain in development. Check the current project documentation before depending on a particular OTP feature.
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Process names and message-ordering cautions
Create names during startup
Some process-name APIs create an Erlang atom for each generated name. Because excessive atom creation can exhaust the VM’s atom table, avoid generating names in loops or repeatedly along worker-restart paths. Create names during application startup and pass them to the processes that need them.
Do not assume global message ordering
Message ordering is guaranteed for messages sent by one process to another. It is not a global ordering guarantee across different senders; if your logic depends on ordering, make the sender and synchronization assumptions explicit.
Choose the right call and learning path
Typed failure results versus lower-level calls
Do not assume every process-call API reports failures the same way. The documented gleam_erlang process call can panic if the callee exits, fails to reply in time, or a named subject is unregistered. By contrast, singleflight.fetch documents typed Result errors for its crash and timeout cases. See the gleam_erlang v1.3.0 process documentation alongside the singleflight docs when choosing between these levels.
Study OTP concepts as well as Gleam APIs
Gleam OTP’s own project documentation says its OTP documentation is limited and advises learning the framework itself. The official Gleam introduction to processes and channels is useful for the underlying concepts, but older examples may need updating for current package APIs. The published sources establish no current benchmark for single flight or a supported performance figure, so choose it for its concurrency semantics rather than an assumed throughput claim.
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