Download Job Lifecycle¶

When you submit a download over the REST API, the server does not block the request until the file is written. Instead it creates a job, hands it back to you with an ID, and works through it in the background. Everything you do afterwards (watching progress, cancelling, retrying, reading the result) is done by referring to that job ID.

This page explains the states a job moves through, how live progress is reported, how to cancel or retry, and, in clearly marked developer sections, how the worker and manager behind the queue actually run the download.

Who this page is for

The first half is for anyone driving the API: the states, the fields you can read, and the calls that move a job around. The Under the hood sections near the end describe the internal worker/manager model and are aimed at contributors and people debugging the server. You do not need them to use the API.

For the full request and response shape of each endpoint, see Endpoints. For how errors are reported, see Error Responses.

The five states¶

A job is always in exactly one of five states, exposed as the status field:

Status	Meaning
`queued`	Created and waiting for a free worker. No download has started yet.
`downloading`	A worker has picked the job up and the download is in progress.
`completed`	The download finished successfully; `output_files` lists the results.
`failed`	The download stopped with an error; `error_message` and `error_code` explain why.
`cancelled`	The job was cancelled before it could finish, from either the queued or downloading state.

The last three (completed, failed, and cancelled) are terminal: once a job reaches one of them it never changes state again. Terminal jobs can be removed, retried, or read from history, but they will not resume.

How a job moves between states¶

stateDiagram-v2
    [*] --> queued: POST /api/download
    queued --> downloading: a worker picks it up
    queued --> cancelled: DELETE (while queued)
    downloading --> completed: download succeeds
    downloading --> failed: download errors
    downloading --> cancelled: DELETE (while downloading)
    completed --> [*]
    failed --> [*]
    cancelled --> [*]

    completed --> queued: POST .../retry (as a NEW job)
    failed --> queued: POST .../retry (as a NEW job)
    cancelled --> queued: POST .../retry (as a NEW job)

The transitions in prose:

queued → downloading happens automatically. As soon as one of the server's workers is free, it takes the next job off the queue and starts it. You do not trigger this; you only observe it.
downloading → completed is the happy path: the download engine wrote all the requested files and reported success.
downloading → failed is any error during the download: a service failure, a network problem, a DRM error, and so on. The job records what went wrong.
queued/downloading → cancelled happens when you send a DELETE for a job that has not finished (see Cancelling a job).
Retry does not move a terminal job back to queued. Instead it creates a brand-new job that reuses the old job's service, title, and parameters. The original job stays in its terminal state (see Retrying a job).

Priority does not change status

Moving a job to the front of the queue with the priority endpoint reorders when it will start, but it stays queued until a worker actually picks it up. It is not a state change.

Creating a job¶

A download is queued with POST /api/download. The request needs at least a service and a title_id, plus any download options you want to set. On success the server replies with 202 Accepted and the new job's identity:

Queue a download

curl -X POST http://127.0.0.1:8786/api/download \
  -H "X-Secret-Key: your-api-secret" \
  -H "Content-Type: application/json" \
  -d '{
        "service": "EXAMPLE",
        "title_id": "81234567",
        "quality": ["1080"],
        "range": ["HDR10"]
      }'

202 Accepted

{
  "job_id": "b1e6c7de-6d0a-4f2f-9d1e-3a2b4c5d6e7f",
  "status": "queued",
  "created_time": "2026-07-03T12:00:00.000000"
}

The job starts in queued. Workers auto-start on the first job submitted, so there is nothing else to switch on. Keep the job_id; every later call is addressed to it.

The full parameter set

POST /api/download accepts the same download options as the dl command (quality, codecs, language selection, wanted episode ranges, and many more), with server-side defaults filling in anything you omit. The complete list, their defaults, and validation rules are documented on the Endpoints page.

Reading a job's status and progress¶

There are two ways to look at jobs.

One job in fullAll jobs (summaries)

GET /api/download/jobs/{job_id} returns the complete detail for a single job, including parameters (with secrets redacted), timing, output files, and error information if it failed.

curl http://127.0.0.1:8786/api/download/jobs/b1e6c7de-6d0a-4f2f-9d1e-3a2b4c5d6e7f \
  -H "X-Secret-Key: your-api-secret"

GET /api/download/jobs lists every job the manager currently holds. By default each entry is a summary. Pass full=true to get the same full detail as the single-job endpoint for every job.

curl "http://127.0.0.1:8786/api/download/jobs?status=downloading&sort_by=progress&sort_order=desc" \
  -H "X-Secret-Key: your-api-secret"

The list can be filtered by status and service, and ordered with sort_by (created_time, started_time, completed_time, progress, status, or service) and sort_order (asc / desc). See Endpoints for the query-parameter reference.

The progress fields¶

While a job is downloading, the following fields update roughly twice a second so a client can poll and render live progress. They are present on both the summary and the full detail:

Field	Type	Meaning
`progress`	number `0` to `100`	Overall percent complete.
`phase`	string	Human-readable phase, e.g. `downloading video 1080p HDR10, audio en 5.1`.
`title`	string	Title being processed.
`current_title`	string	The specific episode/movie in progress (for a batch).
`completed_tracks`	int	Number of tracks finished so far.
`total_tracks`	int	Total tracks selected for the download.
`active_tracks`	list of strings	Labels of the tracks downloading right now.
`track_progress`	list	Per-active-track `{label, progress, speed}` entries.
`segments_done`	number	Segments downloaded for the track in progress.
`segments_total`	number	Total segments for the track in progress.
`speed`	string	Transfer speed of the track in progress, e.g. `4.20 MB/s`.
`skipped_subtitles`	list	Subtitles that were skipped as non-fatal failures (when `skip_subtitle_errors` is set).

The full detail adds started_time, completed_time, output_files, the redacted parameters, and, for failed jobs, error_message, error_details, error_code, error_traceback, and worker_stderr.

A typical polling loop

JOB=b1e6c7de-6d0a-4f2f-9d1e-3a2b4c5d6e7f
while true; do
  curl -s "http://127.0.0.1:8786/api/download/jobs/$JOB" \
    -H "X-Secret-Key: your-api-secret" \
    | python -c 'import sys,json; d=json.load(sys.stdin); print(d["status"], d["progress"], d.get("phase"))'
  sleep 1
done

What the percentage means

progress climbs from 0 toward 90 while tracks download, then the final stretch to 100 covers post-download work such as decryption cleanup, repackaging, and muxing. A job that has finished downloading but is still muxing can sit near 90 for a moment before completing. On success the manager sets it to exactly 100.

For a batch, progress is per-episode, not whole-batch

A multi-episode request (a wanted range) is a single job that processes its episodes sequentially. As each new episode begins, progress and the track counts (completed_tracks / total_tracks) reset to zero and count up again for that episode alone. The top-level bar therefore tracks the current episode, not the batch as a whole. To derive true overall completion, compare the growing output_files array against parameters.wanted rather than trusting progress.

Terminal states in detail¶

Completed¶

A completed job has its output_files populated with the paths of the muxed results, and progress is 100. This is the state you are waiting for.

Failed¶

A failed job carries the error. error_message is the short human message, error_code is one of the API's structured error codes (for example NETWORK_ERROR, DRM_ERROR, AUTH_FAILED, or DOWNLOAD_ERROR), and error_details gives more context. When the server was started with --debug-api, error_traceback and worker_stderr are also filled in for diagnosis.

Secrets are scrubbed from error text

A service can echo a credential or a proxy URL into its output. The server masks any known secret values out of error_message, error_details, error_traceback, and worker_stderr before returning them, so it is safe to log these fields.

The error-code catalogue and how each maps to an HTTP status is on the Error Responses page.

Cancelled¶

A cancelled job was stopped on request before finishing. It may have partial output, but it is not considered complete. See below.

Cancelling a job¶

Send DELETE /api/download/jobs/{job_id}. The behaviour depends on the job's current state, and this is important because the response differs:

Job state when you DELETE	What happens	Response
`queued` or `downloading`	The job is cancelled. A running download's worker process is terminated.	`200` with `{"status": "success", "message": "Job cancelled"}`
`completed`, `failed`, or `cancelled` (terminal)	The job is removed from the manager entirely.	`204 No Content`, empty body
Not found	-	`404` with error code `JOB_NOT_FOUND`

In other words, DELETE on a live job cancels it, while DELETE on an already finished job deletes it from the list. This dual meaning is deliberate: one verb both stops in-flight work and tidies up afterwards.

Do not parse the body of a 204

Removing a terminal job returns 204 No Content with an empty body. A client must not try to decode JSON from it; check the status code first.

Cancel a running job

curl -X DELETE http://127.0.0.1:8786/api/download/jobs/b1e6c7de-6d0a-4f2f-9d1e-3a2b4c5d6e7f \
  -H "X-Secret-Key: your-api-secret"

To remove all terminal jobs at once, use POST /api/download/jobs/clear-finished, which returns {"removed": <count>}.

Retrying a job¶

POST /api/download/jobs/{job_id}/retry re-runs a finished job by creating a new job with the same service, title, and parameters. The original job is untouched and stays in its terminal state; the response gives you the new job's ID with 202.

Only terminal jobs can be retried. Retrying a queued or downloading job returns 409 with error code CONFLICT.
A missing job returns 404 (JOB_NOT_FOUND).
The service allowlist and any download gates are re-checked for the new job, exactly as they were for the original submission, so a retry can be rejected with INVALID_SERVICE or FORBIDDEN if permissions changed.

202 Accepted, a fresh job

{
  "job_id": "c2f7d8ef-7e1b-5a3a-ae2f-4b3c5d6e7f80",
  "status": "queued",
  "created_time": "2026-07-03T12:30:00.000000"
}

Prioritising a job¶

POST /api/download/jobs/{job_id}/priority moves a queued job to the front of the line, so it will be the next one a free worker picks up.

The job must be queued. Prioritising a job in any other state returns 409 (CONFLICT); a missing job returns 404.
On success the response is {"job_id": "<id>", "position": "front"}.

This only reorders the queue; the job's status stays queued until a worker starts it.

History and retention¶

Every job that reaches a terminal state is also written once to a persistent history log, so it survives even after the job is removed from the live list.

Read it with GET /api/history (newest first; supports limit and service filters).
Delete a single entry with DELETE /api/history/{job_id} (returns 204).

The live in-memory jobs are separate from this on-disk history. A background cleanup task periodically drops old terminal jobs from the live list based on a retention period; the history file keeps them for later reference. See Endpoints for the history response shape.

Why the history file lives under the cache directory

api_history.jsonl is placed under the cache directory on purpose, so it stays out of the config/data tree. It is disposable runtime state, not user configuration or curated data, which is exactly why clearing the cache is a safe operation against it.

Under the hood: the worker/manager model¶

Developer section

Everything below describes server internals. It is useful for contributors and for anyone debugging the server, but it is not needed to use the API.

The manager and its queue¶

A single process-wide download queue manager owns all jobs. It holds them in memory keyed by ID, backs the wait list with a FIFO queue, and keeps a separate priority deque for jobs that have been bumped to the front. On the first job, it starts a fixed pool of worker tasks plus one cleanup task; starting is idempotent, so later jobs reuse the same pool.

Concurrency is capped by max_concurrent_downloads (default 2). That many jobs can be in downloading at once; the rest wait in queued.
Retention is governed by job_retention_hours (default 24). An hourly cleanup task removes terminal jobs whose completion time (or, if never started, creation time) is older than the retention window.

Two concurrency knobs that are easy to conflate

max_concurrent_downloads caps how many separate download jobs run at once. The separate serve.downloads setting controls how many tracks download in parallel within a single job. They are independent, and raising one does not affect the other.

Concurrency and retention config keys

The manager reads these as top-level config attributes (config.max_concurrent_downloads and config.download_job_retention_hours). Those keys are not part of the standard config schema, so in practice the built-in defaults of 2 and 24 apply. The live values are surfaced by GET /api/config. The related serve.history_limit (default 100) instead controls how many entries the on-disk history file keeps.

Each worker loop drains the priority deque first, then the FIFO queue. A job that was promoted has its stale FIFO copy skipped so it does not run twice. When a worker takes a job it flips it to downloading, stamps started_time, runs it, and on finish stamps completed_time and records history.

Each job runs in its own subprocess¶

The manager does not run the download in the server's event loop or even in the server process. For each job it spawns a separate Python subprocess:

python -m unshackle.core.api.download_worker <payload.json> <result.json> <progress.json>

Three temporary files bridge the parent and the worker:

payload.json: written by the manager before launch; contains the job ID, service, title ID, and merged parameters.
progress.json: written continuously by the worker as the download proceeds.
result.json: written by the worker at the end.

Running each download out-of-process isolates the server from crashes, memory growth, and blocking work inside the download engine, and makes hard cancellation (killing the process) reliable.

The worker's exit codes are 0 for success, 1 for a download error, and 2 for bad arguments. Its result.json is either {"status": "success", "output_files": [...]} or {"status": "error", "message", "error_details", "error_code", "traceback"}. If the process exits non-zero, or the result is missing or not a success, the parent marks the job failed and adopts the worker's error_code (or derives one by categorising the exception).

How progress reaches the API¶

While the worker runs, the manager polls progress.json every 0.5 s and copies the fields it finds onto the live DownloadJob. That is what the GET endpoints return.

Inside the worker, progress is aggregated across all selected tracks. Each track's completion fraction is weighted by its bitrate, so video and audio dominate the bar and subtitles barely move it (subtitles get a small fixed weight). Track fractions are kept monotonic: the percentage only ever climbs. The download portion is scaled to fill 0 to 90; the remaining 90 to 100 is driven by the download engine as it repackages and muxes. A track counts as done when it reaches a terminal state such as Downloaded, Decrypted, or a skipped subtitle.

How cancellation actually works¶

Each job carries a cancellation event. When you DELETE a live job:

If it is queued, it flips straight to cancelled, its history is recorded immediately (it never reaches a worker), and the worker loop skips it if it later pops it off the queue.
If it is downloading, the manager sets the cancellation event and flips the job to cancelled. The polling loop notices the event, terminate()s the worker subprocess (escalating to kill() if it does not exit within 5 seconds), and raises a cancellation so the task unwinds. The subprocess model is what makes this a clean, immediate stop rather than a cooperative one.

Secret handling in serialized jobs¶

Job parameters may carry secrets: a raw user:pass credential, or a proxy URL with embedded userinfo. Whenever the manager serializes a job (for an API response or the history file), it masks the sensitive keys (credential, credentials, password, token, api_key) and strips userinfo from proxy URLs. Free-text fields that a service might have leaked a secret into (error_message, error_details, error_traceback, worker_stderr, and worker stdout/stderr in the logs) are scrubbed of the job's known secret values, longest-match first, before they are ever returned or logged.