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Install

pip install meshive

Docs: SDK & CLI reference · Quickstart · Serverless API · GPU pricing

Authentication

The SDK and CLI authenticate with a Meshive API Key. Issue one from the console (workspace Settings → Secret). A Read only key can view everything; a Read & write key is needed to create, change or delete resources, and it always expires (30 days by default, 90 at most).

The easiest way is meshive login — it verifies the key and stores it (file mode 0600) under ~/.meshive/credentials.json, so later commands need no flags or env vars:

meshive login                 # prompts for the key (hidden input)
meshive me                    # now works with no --api-key
meshive logout                # removes the saved credentials

Alternatively, provide the key explicitly. Resolution order is --api-key flag › MESHIVE_API_KEY env › meshive login file:

export MESHIVE_API_KEY=meshive_xxxxxxxx
# or per-command: meshive me --api-key meshive_xxxxxxxx

Requests go to the production API. If you have been given a different API address, override it with --base-url or MESHIVE_BASE_URL (same precedence: flag › env › login file › default); meshive login --base-url <url> remembers it. The config directory can be relocated via MESHIVE_CONFIG_DIR.

CLI

meshive --help lists the commands; meshive <command> --help shows their options. Commands that spend credit or delete something show an estimate and ask for confirmation (--yes to skip, --estimate to only see the price).

meshive --version
meshive me                     # current API key's owner
meshive api-keys               # your API keys (prefixes only — the secret is never shown)
meshive credit                 # credit balance, paid vs bonus, auto-recharge
meshive credit-history         # top-ups and refunds (--since/--until YYYY-MM-DD)

meshive workspaces             # list workspaces
meshive workspace <workspace>  # cost & resource summary of one workspace
meshive members <workspace>    # members and roles

meshive pods <workspace>       # list pods in a workspace
meshive pods --all             # list pods across every workspace (adds a WORKSPACE column)
meshive pod <workspace> <pod>  # show a single pod
meshive pod-metrics <workspace> <pod>   # live CPU/RAM/GPU/disk usage

meshive storages <workspace>   # storages (volumes) in a workspace
meshive storage <workspace> <storage>   # show a single storage

meshive gpus                   # GPUs available to rent right now, with prices
meshive templates              # official templates (--workspace <id> adds its custom ones)
meshive template <id>          # show a template

meshive assets <workspace>     # assets in a workspace (datasets, models, outputs, ...); --page/--page-size
meshive asset <id>             # show an asset with its versions
meshive asset-storage <workspace>   # managed asset storage, monthly cost, credit status

meshive servings <workspace>   # serverless serving deployments
meshive serving <id>           # show a serving deployment
meshive tasks <workspace>      # serverless tasks (newest first; --limit/--offset paging)
meshive task <id>              # show a task

meshive machines               # list your machines (as a host)
meshive machine <id>           # show a single machine
meshive machine-metrics <id>   # live CPU/RAM/GPU/disk/network of a machine
meshive earnings               # host earnings (--since/--until, --days N for the daily table)

# wait for a pod to reach a status (polls every 5s, gives up early if it errors out)
meshive pod <workspace> <pod> --wait running
meshive pod <workspace> <pod> --wait running --wait-timeout 120

# filter pods (client-side; the API itself returns the full list)
meshive pods <workspace-id> --status running
meshive pods <workspace-id> --status running,error   # comma-separated or repeatable
meshive pods <workspace-id> --rental spot
meshive pods <workspace-id> --name llama              # match the display name (alias)

# same style of filters elsewhere
meshive storages <workspace-id> --type nfs --status running --name datasets
meshive machines --status online --type gpu --name node-a
meshive gpus --rental spot --vram 40 --model h100     # --vram/--rental go to the server, --model is client-side
meshive templates --workspace <workspace-id> --type ide --name jupyter
meshive servings <workspace-id> --status active --name llama
meshive tasks <workspace-id> --status running,failed --limit 20 --offset 20
meshive assets <workspace-id> --type dataset --status active --page 2   # --type/--status/--page go to the server

# output format: table (default) | json (raw payload) | name (IDs only, one per line)
meshive pods <workspace-id> -o json          # --json is a shorthand for this
meshive pods <workspace-id> -o name          # pipe-friendly: one ID per line
meshive credit -o name                       # single-value commands print just the number

# every command also takes --api-key / --base-url / --timeout overrides
meshive machines --timeout 60

Exit codes: 0 success, 1 API or network error, 2 usage error (unknown status, bad date, out-of-range --limit, …), 130 interrupted.

IDs vs names

List output shows two columns:

  • ID — the canonical identifier (namespace_name for workspaces, pod_name for pods, the volume name for storages, numeric IDs for templates/servings, task_… for tasks, asset_… for assets). This is what you pass to the singular commands. It is unique and stable.
  • NAME — the display alias you set (workspace_name / user_alias / model name). It is a label, not a key: it is not guaranteed unique and can change. Use --name to filter by it, but address resources by their ID.

Sizes and rates

RAM, storage and VRAM are shown in GB (the same conversion the console uses); usage rates in percent, with n/a when a measurement is unavailable; network throughput in Mbps.

Write commands (Read & write key)

meshive pod-create <workspace> my-pod --template 457 --gpu "RTX 3060" --estimate   # price only
meshive pod-create <workspace> my-pod --template 457 --gpu "RTX 3060" --max-price 0.10 --wait running
meshive pod-stop <workspace> <pod>          # billing stops (storage still billed)
meshive pod-start <workspace> <pod>         # --any-node to move to another machine
meshive pod-delete <workspace> <pod> --yes
meshive logs <workspace> <pod> --tail 100

meshive storage-create <workspace> data --size 50 --type nfs
meshive storage-delete <workspace> <pv>

meshive task-submit <workspace> train --script train.py --image python:3.12-slim --gpu "RTX 3060"
meshive task-logs <task>; meshive task-stop <task>
meshive serving-deploy <workspace> <model_id> --price-cap 1.5 --max-replicas 2

SDK

from meshive import Meshive

with Meshive() as client:               # reads MESHIVE_API_KEY / MESHIVE_BASE_URL
    me = client.me()
    print(me.email, me.user_role)

    for ws in client.list_workspaces():
        print(ws.namespace_name, ws.status)
    detail = client.get_workspace("my-workspace")
    print(detail.price_per_hour, detail.gpus, [r.type for r in detail.resources])

    pods = client.list_pods("my-workspace")
    pod = client.get_pod(pods[0].pod_name, "my-workspace")
    print(pod.status, pod.raw)           # .raw holds the full payload (machine, template, ...)

    # block until a pod is up (polls every `interval` seconds)
    pod = client.wait_for_pod(pod.pod_name, "my-workspace", until="running", timeout=600)

    usage = client.get_pod_metrics(pod.pod_name, "my-workspace")
    print(usage.cpu_usage_rate, [g.vram_usage_rate for g in usage.gpus])

    for storage in client.list_storages("my-workspace"):
        print(storage.pv_name, storage.storage_type, storage.usage_rate)

    page = client.list_assets("my-workspace", asset_type="dataset")   # one page (20 by default)
    for asset in page:
        print(asset.asset_id, asset.name, asset.size_bytes, asset.storage_provider)
    print(page.total, page.pages)
    print(client.get_asset_storage("my-workspace").estimated_monthly_cost)

    # what can I rent right now?
    for gpu in client.list_gpus(rental_type="demand", min_vram=40):
        print(gpu.gpu_model, gpu.vram, gpu.price_per_hour, gpu.available_gpus)

    # account
    credit = client.get_credit()
    print(credit.paid_balance, credit.bonus_balance)
    for key in client.list_api_keys():
        print(key.prefix, key.last_used_at)   # prefixes only; the secret is never returned

    # host view: the machines you contribute to the network
    machines = client.list_machines()
    for m in machines:
        print(m.machine_id, m.status, m.gpu_count, m.gpu_model)
    machine = client.get_machine(machines[0].machine_id)
    print(machine.earning_hourly, machine.raw)   # .raw holds specs, state, podUses, ...
    print(client.get_earnings().accumulated_until_payout)

All methods (identical on AsyncMeshive, awaited):

Method Returns
me() WhoAmI
list_api_keys() list[ApiKey]
get_credit() / list_credit_history(start_date=, end_date=) Credit / list[CreditHistoryEntry]
list_workspaces() / get_workspace(workspace) list[Workspace] / WorkspaceDetail
list_members(workspace) list[Member]
list_pods(workspace) / get_pod(pod_name, workspace) / wait_for_pod(...) list[Pod] / Pod
get_pod_metrics(pod_name, workspace) PodMetrics
list_storages(workspace) / get_storage(storage_name, workspace) list[Storage] / Storage
list_gpus(rental_type=, min_vram=) list[GpuAvailability]
list_templates(workspace=None, app_type=) / get_template(template_id, workspace=None) list[Template] / Template
list_servings(workspace) / get_serving(serving_id) list[Serving] / Serving
list_tasks(workspace, status=, limit=, offset=) / get_task(task_id) list[Task] / Task
list_assets(workspace, asset_type=, status=, page=, page_size=) / get_asset(asset_id) AssetPage (iterable, .total, .pages) / Asset
get_asset_storage(workspace) AssetStorage
list_machines() / get_machine(machine_id) list[Machine] / Machine
get_machine_metrics(machine_id) MachineMetrics
get_earnings(start_date=, end_date=) Earnings

Dates accept datetime.date, datetime.datetime, or a "YYYY-MM-DD" string. Every model keeps the exact server payload on .raw, so nested or newly added fields are always reachable. Credit history entries carry the amount, method and date only; Stripe receipt links stay in the console.

Credentials can also be passed explicitly: Meshive(api_key="meshive_..."), and base_url= overrides the API address.

Retries

Rate limits (429), gateway errors (5xx), and dropped connections are retried automatically — twice by default, with exponential backoff, honouring the server's Retry-After header. Other 4xx responses are never retried. Turn it off with Meshive(max_retries=0).

If Retry-After asks for more than 60 seconds, the SDK raises RateLimitError instead of blocking that long — sleeping through it is your call, via .retry_after.

Async

from meshive import AsyncMeshive

async with AsyncMeshive() as client:
    me = await client.me()
    pods = await client.list_pods("my-workspace")
    gpus = await client.list_gpus(min_vram=80)

Errors

All errors subclass meshive.MeshiveError:

  • ConfigurationError — missing API key
  • AuthenticationError (401), PermissionDeniedError (403), NotFoundError (404), RateLimitError (429, exposes .retry_after), and MeshiveAPIError for other HTTP errors (carry .status_code, .title, .message, .raw)
  • WaitTimeoutError — wait_for_pod ran out of time (it is also a built-in TimeoutError). A pod that reaches error/terminated while waiting raises MeshiveError immediately rather than burning the full timeout.

Invalid arguments (a malformed date, limit out of range, an empty ID) raise ValueError before any request is sent. Transport failures (DNS, refused connections) surface as httpx exceptions once retries are exhausted. The package ships a py.typed marker, so mypy/pyright read its annotations.

API compatibility

Version 0.0.7 relies on the extended /v1/sdk read surface (workspace detail, storages, metrics, GPUs, API keys, credit, earnings, members, templates, servings, tasks, assets). Against an older API those calls return NotFoundError; the commands that existed in 0.0.6 keep working.

License

Apache License 2.0

Writing (0.1.0+)

from meshive import Meshive, ConflictError

client = Meshive()  # key with the write scope
est = client.estimate_pod("my-pod", template_id=457, workspace="<workspace>", gpu_model="RTX 3060")
print(est.price_per_hour, est.resources)          # "0.068423" {...}

created = client.create_pod("my-pod", 457, workspace="<workspace>", gpu_model="RTX 3060",
                            max_price_per_hour=0.10)  # refused with ConflictError if pricier
pod = next(p for p in client.list_pods("<workspace>") if p.user_alias == "my-pod")
client.wait_for_pod(pod.pod_name, "<workspace>", until="running")
print(client.get_pod_logs(pod.pod_name, "<workspace>", tail=50).text)
client.stop_pod(pod.pod_name, "<workspace>")
client.delete_pod(pod.pod_name, "<workspace>")

Write safety contract

start_pod(..., placement="any_node") can permanently delete unpreserved workspace files after a node move. Inspect Pod.has_unpreserved_workspace; use allow_data_loss=True only after separate consent for that pod and move. The CLI requires --allow-data-loss in addition to --yes for an unattended move that can lose data. Pod.storage_rate_per_hour is separate from compute pricing.

max_price_per_hour on pods/tasks caps the final compute rate, excluding attached/automatic storage and Asset Hub retention. Over-cap pod placements fail asynchronously. CPU capped requests are refused when a quote is unavailable. Task max_cost may be unknown because fetch time and storage charges exceed the script-runtime estimate.

Keep one idempotency_key for each logical write and reuse it after a timeout. Results expose raw["idempotencyKey"], raw["operationMethod"] and raw["operationPath"]; terminal network/API exceptions expose idempotency_key, operation_method and operation_path. get_operation(key, method="POST", path="/tasks") checks the durable acceptance record without resubmitting work. Pending/unknown records require reconciliation. done records API acceptance, not completion of the asynchronous resource operation.

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