midjourney-download

Download & Job Management

Download Images

Signature

def download_images(
    self,
    job: Job,
    output_dir: str = "./images",
    size: int = 640,
    indices: list[int] | None = None,
) -> list[Path]

Parameters

Param	Type	Default	Description
job	Job	—	Completed job to download
output_dir	str	"./images"	Output directory (created if needed)
size	int	640	CDN image size (e.g., 640, 1024)
indices	list[int] | None	None	Specific indices to download (None = all)

Usage

with MidjourneyClient() as client:
    job = client.imagine("landscape")

    # Download all 4 grid images
    paths = client.download_images(job, "./output")
    # → ["./output/{job_id}_0.webp", ..., "./output/{job_id}_3.webp"]

    # Download specific indices
    paths = client.download_images(job, "./output", indices=[0, 2])

    # Higher resolution
    paths = client.download_images(job, "./output", size=1024)

    # Upscaled job (1 image)
    upscaled = client.upscale(job.id, index=0)
    paths = client.download_images(upscaled, "./output")
    # → ["./output/{job_id}_0.webp"]

Output Path Format

{output_dir}/{job_id}_{index}.webp

CDN URL Format

https://cdn.midjourney.com/{job_id}/0_{index}_{size}_N.webp?method=shortest

Download Count Logic

• job.image_urls length determines how many to download
• Grid jobs: 4 images (image_urls has 4 entries)
• Upscale jobs: 1 image (image_urls has 1 entry)
• If image_urls is empty, defaults to 4

Download as Bytes (In-Memory)

디스크 I/O 없이 raw bytes로 직접 받아 메모리에서 처리할 때 사용.

Signature

def download_images_bytes(
    self,
    job: Job,
    size: int = 640,
    indices: list[int] | None = None,
) -> list[bytes]

Usage

from io import BytesIO
from PIL import Image

with MidjourneyClient() as client:
    job = client.imagine("landscape")

    # Raw bytes로 받기
    data_list = client.download_images_bytes(job, size=1024)

    # PIL로 직접 디코딩 (임시 파일 불필요)
    images = [Image.open(BytesIO(data)).convert("RGB") for data in data_list]

download_images()와 동일한 CDN URL/인덱스 로직을 사용하지만, 파일을 저장하지 않고 list[bytes]를 반환합니다.

Video Downloads

For full video download details, see the midjourney-animate skill. Quick reference:

# Download video to disk
paths = client.download_video(video_job, "./videos", size=1080)
# -> ["./videos/{job_id}_0_1080.mp4"]

# Download video as bytes
data = client.download_video_bytes(video_job)

List Jobs

jobs = client.list_jobs(limit=50)  # default: 50
for job in jobs:
    print(f"{job.id}: {job.prompt} [{job.status}]")

Signature

def list_jobs(self, limit: int = 50) -> list[Job]

Job Model

Module: midjourney_api.models

@dataclass
class Job:
    id: str                              # job UUID
    prompt: str                          # full prompt with flags
    status: str = "pending"              # pending, running, completed, failed
    progress: int = 0                    # 0–100
    image_urls: list[str] = field(...)   # CDN URLs (populated on completion)
    user_id: str = ""
    enqueue_time: str | None = None
    parent_id: str | None = None         # parent job ID (for vary/upscale/pan)
    event_type: str | None = None        # event type (contains "video" for video jobs)

Properties

Property	Type	Description
job.is_completed	bool	status == "completed"
job.is_failed	bool	status == "failed"
job.is_video	bool	True if event_type contains "video"

Methods

job.cdn_url(index=0, size=640) -> str
# -> "https://cdn.midjourney.com/{id}/0_{index}_{size}_N.webp?method=shortest"

job.video_url(index=0, size=None) -> str
# -> "cdn.midjourney.com/video/{id}/{index}.mp4"

job.gif_url(index=0) -> str
# -> "cdn.midjourney.com/video/{id}/{index}_N.gif"

UserSettings Model

@dataclass
class UserSettings:
    user_id: str
    subscription_type: str = ""           # e.g., "standard", "pro"
    fast_time_remaining: float = 0.0      # remaining fast GPU seconds
    relax_enabled: bool = False
    stealth_enabled: bool = False
    raw_data: dict = field(...)           # full API response

Access

settings = client.get_settings()
print(settings.subscription_type)
print(settings.fast_time_remaining)

Queue Status

queue = client.get_queue()  # raw dict from /api/user-queue