Claude Skill

deploy-to-connect

Deploy or publish Python and R content to a Posit Connect server using rsconnect-python or the R rsconnect package. Handles interactive apps and dashboards, web APIs, rendered documents, and prepared bundles/manifests. Use whenever the user asks to deploy, publish, or redeploy co

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Part of posit-dev/skills — 23 skills

Install

skills CLI npx skills add https://github.com/posit-dev/skills/tree/main/connect/deploy-to-connect
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install posit-dev-skills@llmmart
Git git clone https://github.com/posit-dev/skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole posit-dev/skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Deploying to Posit Connect

This guide covers Python and R content on a Posit Connect server. Work through the stages in order.

Two toolchains do the work:

  • Python — rsconnect-python, which provides the rsconnect CLI and is published on PyPI.
  • R — the R rsconnect package, pointed at a Connect server.

If the user asks a question ("how do I…", "what is the command…") rather than asking for a deploy, answer from this guide and stop.

At the end, report which server you deployed to, which content type you picked, any tool you installed, and any assumption you made.


Stage 1 — Detect the content

Infer the language and framework from the files in the project directory. Common signals:

Signal in project dir Likely content
app.py Python web app — Shiny for Python, Streamlit, Dash, Gradio, Panel, or Bokeh
app.R, or ui.R + server.R Shiny for R
plumber.R / entrypoint.R containing plumb() Plumber API (R)
*.qmd Quarto document
*.Rmd R Markdown
*.ipynb Jupyter notebook / Voila
manifest.json Prebuilt bundle — deploy it directly, no framework guess needed
A bare .py or .R — no framework import, no ui.R/server.R/plumber.R/entrypoint.R alongside Script — a batch/ETL job that Quarto renders and Connect can schedule

Confirm the guess

The imports in app.py name the framework:

grep -Eo 'import (shiny|streamlit|dash|gradio|panel|bokeh)|from (shiny|streamlit|dash|gradio|panel|bokeh)' app.py

A bare ASGI or WSGI object means fastapi or flask.

Dependency files confirm the language: requirements.txt and pyproject.toml for Python, DESCRIPTION and renv.lock for R.

Quarto renders a script only if it opens with a front-matter comment: # %% [markdown] around a --- block in Python, #' --- in R. Most scripts lack one — add it before the deploy (Stage 5).

If the content is ambiguous (both Python and R files, or an app.py with no recognizable import), use your discretion, and report the assumption you made.


Stage 2 — Inventory your tools

Probe the environment and build a capability set:

command -v rsconnect                                 # rsconnect-python on PATH
command -v uv                                        # uv (installs and runs Python tools)
uv tool list 2>/dev/null | grep rsconnect            # rsconnect-python installed via uv
command -v Rscript                                   # R present
Rscript -e 'cat(requireNamespace("rsconnect", quietly=TRUE))' 2>/dev/null   # R rsconnect package
command -v quarto                                     # quarto CLI
command -v git                                        # git

With uv present, Python content needs no install step. uv tool run --from rsconnect-python rsconnect ... fetches and runs the CLI on demand.


Stage 3 — Pick a route

Cross the detected content (Stage 1) with your capabilities (Stage 2).

Python content

Use rsconnect-python. With rsconnect on PATH:

rsconnect deploy <framework> ./my-app

Off PATH but with uv present:

uv tool run --from rsconnect-python rsconnect deploy <framework> ./my-app

Both forms take identical arguments. The rest of this guide writes the bare rsconnect ... form. Prefix it with uv tool run --from rsconnect-python when you use the second route.

<framework> is one of api, bokeh, bundle, dash, fastapi, flask, git, gradio, html, manifest, nodejs, notebook, panel, pyproject, quarto, shiny, streamlit, tensorflow, voila. For anything outside that list, rsconnect deploy other-content prints guidance.

The frameworks and flags depend on the installed version, so confirm against rsconnect deploy --help rather than this list. If uv tool run resolves a stale cached version, pin it: uv tool run --from 'rsconnect-python==1.30.0' rsconnect ....

R content

Use the R rsconnect package, through Rscript -e '...' or an R session:

  • Shiny for R, Plumber API, or any app directory → deployApp()
  • A single R Markdown or Quarto document → deployDoc()
  • A full R Markdown or Quarto site → deploySite()

If Rscript is absent, deploy the R content through rsconnect-python with a manifest.json:

  • A manifest.json already exists — deploy it directly:
    rsconnect deploy manifest ./manifest.json
    
  • No manifest, but R is available elsewhere — generate one first with rsconnect::writeManifest() (see Stage 5).
  • Neither R nor a manifest — a valid R bundle is not possible. Surface this as a blocker: ask the user or report it clearly.

Quarto content

rsconnect deploy quarto ./report

R-flavored Quarto (a .qmd with R code chunks) needs R to render. If R is absent, treat the document as R content and use the manifest route, or surface the gap.

Script content

Use the quarto framework. Add the front matter first (Stage 5).

rsconnect deploy quarto script.py    # Python, rsconnect-python 1.23.0 or later
rsconnect::deployApp()               # R, rsconnect 1.2.2 or later, from the directory of the script

Both commands include every file in the directory. Push-button publishing does not cover R scripts, so deployApp() is the only R route.

A script deploys like a Quarto document but is a different content type: a .qmd is a page to read, a script is a job that writes output.


Stage 4 — Find the target and check its credentials

Now that the tool is known, find out which server to deploy to and whether the tool can already reach it. This is a check, not a login.

Do not search the environment for API keys. Do not read CONNECT_API_KEY, CONNECT_SERVER, a .env file, a keychain entry, or any other stored secret to pick a target or to register a server. Do this only when the user explicitly asks for it. An environment variable is not a request to use it.

List the accounts the tool already has. This is the only credential check you need.

rsconnect list                                   # Python: saved servers, stored tokens, and the default server on 1.30.0+
Rscript -e 'print(rsconnect::accounts())'        # R: registered accounts

If the tool is not installed yet, close that gap in Stage 5 first. Then run the check.

Compare the result with the target the user named. Three outcomes:

  • An account matches the named target. The credential path is live. Run no login and no rsconnect add. Continue to Stage 6 once the other gaps are closed.
  • The user named no target. Ask them. List the servers the check found, and ask which one to deploy to, or whether they want a new target instead. Do not pick one for them, and do not deploy to the only saved server because it is the only one.
  • The target is new, or no account matches it. This is a gap for Stage 5. Register it with a browser login.

A browser login is the way to register a new target:

rsconnect login https://connect.example.com      # Python
rsconnect::addServer(url = "https://connect.example.com", name = "myserver")   # R
rsconnect::connectUser(server = "myserver")

Both forms open a browser flow, so the user approves the login and no key passes through the conversation. The credentials reference has the details and the pitfalls.


Stage 5 — Resolve gaps

When Stages 3 and 4 find a gap, close it, then include the action in your report.

rsconnect not on PATH. With uv present, no install is needed:

uv tool run --from rsconnect-python rsconnect deploy <framework> ./my-app

If the user wants it installed persistently, or uv tool run is not viable:

uv tool install rsconnect-python     # or: pip install rsconnect-python

The package name and the command name differ: the PyPI package is rsconnect-python, and the command it provides is rsconnect. That is why uv tool run needs --from rsconnect-python. To update later, run uv tool upgrade rsconnect-python.

R rsconnect package missing, Rscript present. Install it from Posit Package Manager (P3M), which serves precompiled Linux binaries. A binary install is much faster than a source build and needs no -dev system libraries. Binaries need two things: the __linux__/<codename> repo URL and a platform-identifying HTTPUserAgent. Without the user agent, P3M serves source.

export P3M="https://packagemanager.posit.co/cran/__linux__/$(. /etc/os-release && echo "$VERSION_CODENAME")/latest"
Rscript -e '
  options(HTTPUserAgent = sprintf("R/%s R (%s)", getRversion(),
    paste(getRversion(), R.version["platform"], R.version["arch"], R.version["os"])))
  install.packages("rsconnect", repos = Sys.getenv("P3M"))
'

P3M binaries exist for x86_64 on common distros. On arm64 or an unsupported distro, P3M falls back to source. That result is still correct, only slower, and it needs the usual -dev libraries and a compiler. Use https://cloud.r-project.org (CRAN source) only when P3M is unreachable.

manifest.json missing for R content, R present. Generate it:

Rscript -e 'rsconnect::writeManifest()'

rsconnect-python writes one for Python content:

rsconnect write-manifest <framework> ./my-app

Then deploy the manifest with rsconnect-python if R cannot deploy directly.

Script front matter missing. Add the minimal block at the top of the file. Connect takes the content title from title, so write a descriptive one.

Python:

# %% [markdown]
# ---
# title: "Data processing script"
# ---

R:

#' ---
#' title: "Data processing script"
#' ---

No account for the target. Register it now with a browser login: rsconnect login for Python, or rsconnect::addServer() and rsconnect::connectUser() for R. The credentials reference has the details and the pitfalls. Do not fall back to an API key from the environment. If the browser flow is not available, report that and stop.

Dependencies. rsconnect and rsconnect-python scan the code and snapshot the required package versions for you, so hand-listing them is rarely necessary. Python content needs a requirements.txt. For R, the content's own packages must be installed locally for rsconnect to detect them — plumber for a Plumber API, shiny for a Shiny app. Install any that are missing from the same P3M repo shown above.


Stage 6 — Deploy and handle failure

Discover the live command surface (Python)

The frameworks and flags in rsconnect-python change between releases, and the help text is the source of truth:

rsconnect version                  # which version you are actually running
rsconnect deploy --help            # every framework you can deploy
rsconnect deploy <framework> --help  # flags for one framework

Deploy

For Python, run rsconnect deploy <framework> <dir> with the framework Stage 3 picked. The manifest framework takes the manifest file rather than a directory.

Non-obvious flags: -t/--title, -N/--new (force a new deployment instead of updating the recorded one), -a/--app-id <id> (target an existing item explicitly, mutually exclusive with --new), -E NAME=VALUE (set an environment variable, repeatable), --draft (keep serving the previous bundle until published).

For R, call the function Stage 3 selected. Pass appTitle so the content is not named after the directory.

A script deploy sweeps the whole directory. If the directory holds files the script does not need, narrow the selection: name the files in Python (rsconnect deploy quarto script.py helper.py data.csv) or pass appFiles in R (rsconnect::deployApp(appFiles = c("_quarto.yml", "script.R"))). A directory with a _quarto.yml is a Quarto project — deploy it whole with rsconnect deploy quarto ..

If rsconnect is not found at deploy time

It can be installed but off PATH in this shell. IDE-spawned terminals and active virtualenvs both cause this. Fall back to uv tool run as described in Stage 5, with --from rsconnect-python.

Pre-flight check (optional)

To confirm that the target is reachable and the credentials work before you deploy:

rsconnect details -n myserver

When a deploy fails

Python:

  • Auth errors — confirm the target with rsconnect list, then re-run rsconnect login (1.30.0+). Pass -s/-k only when the user told you to use an existing key.
  • -n/--name ... cannot be specified in conjunction with ... -s/--server (from ENVIRONMENT) — CONNECT_SERVER is set and you also passed -n. Run unset CONNECT_SERVER and keep -n. The credentials reference explains why that direction. CONNECT_API_KEY can stay.
  • The requirements file 'requirements.txt' does not exist — Python content needs one. Create it, point at another file with --requirements-file, or generate it with --force-generate. The last option runs a pip freeze, so it can over-pin.
  • Self-signed TLS — use -i/--insecure or -c/--cacert <file>. Set CONNECT_INSECURE or CONNECT_CA_CERTIFICATE to apply it everywhere.
  • Rejected flag or unknown framework — re-check rsconnect version and re-read rsconnect deploy <framework> --help. The installed version is usually older than the flag you used.
  • A deployed script renders empty or broken — the server lacks Quarto 1.4+, Jupyter (Python scripts), or rmarkdown (R scripts). The deploy itself succeeded, so do not retry it. Report the missing server dependency.

R:

  • "No account" or auth errors — run rsconnect::accounts(). If it is empty, re-run rsconnect::addServer(), then connectUser() or connectApiUser(). Make sure that you used a server function and not connectCloudUser().
  • Found multiple accounts. Please disambiguate by setting server and/or account — more than one account is linked. Pass account = and server = explicitly to the deploy call. An interactive R session shows a menu instead, which hangs a headless run.
  • Wrong deploy function — deployApp() for directories and apps, deployDoc() for a single document, deploySite() for a site.
  • Self-signed TLS — pass the CA bundle through the curl options, or add the server with the certificate. For a quick test, set options(rsconnect.check.certificate = FALSE).
  • Absolute-path warnings — files with hard-coded absolute paths do not block the deploy, but they are better made relative to the project directory.

Credentials reference

How to register a target that Stage 4 found no account for. If an account already matches the target, none of this is needed.

A browser login is the route. The API-key routes below it are there for one case only: the user explicitly tells you to use a key that already exists, in an environment variable or a credential store. Do not go looking for a key on your own, and never ask the user to give you one. An API key does not belong in the conversation.

Python (rsconnect-python)

  1. OAuth login (interactive). The default route. Needs rsconnect-python 1.30.0+, so check rsconnect version first. One browser flow per server. Tokens land in the OS keyring, or a local credential store, and refresh automatically.
    rsconnect login https://connect.example.com
    rsconnect login https://connect.example.com --use-device-code   # headless
    
  2. Saved API-key nickname. Only when the user asked for a key route. Save once, select later with -n/--name.
    rsconnect add -n myserver -s https://connect.example.com -k <api-key>
    rsconnect list                    # confirm what is saved
    
    On 1.30.0+ a server can be the default, used when a command passes neither -n nor -s. add sets the default only with --set-default. login sets it unless you pass --no-set-default. rsconnect server set-default -n <name> changes it later. CONNECT_SERVER still takes precedence over the default.
  3. Environment variables. Only when the user asked you to use them. rsconnect-python reads them directly, which suits a headless or automated run with no state to manage.
    export CONNECT_SERVER=https://connect.example.com
    export CONNECT_API_KEY=...        # honored across the whole `rsconnect` surface
    
  4. Ad hoc flags on the deploy command: -s <url> -k <api-key>. Same condition, and read the key from the variable the user named rather than writing it out.

Shared credential flags: -n/--name (saved server), -s/--server (env CONNECT_SERVER), -k/--api-key (env CONNECT_API_KEY), -i/--insecure (env CONNECT_INSECURE, for self-signed TLS), -c/--cacert <file> (env CONNECT_CA_CERTIFICATE).

-n and CONNECT_SERVER cannot both be in play. rsconnect rejects a command that combines a saved-server name (-n/--name) with a server URL, including a URL that came from the environment: -n/--name (from COMMANDLINE) cannot be specified in conjunction with options -s/--server (from ENVIRONMENT).

Only the server conflicts. CONNECT_API_KEY, CONNECT_INSECURE, and CONNECT_CA_CERTIFICATE sit alongside -n without complaint, because the key is not part of the exclusion. -n dogfood with CONNECT_API_KEY exported is a valid command. It is CONNECT_SERVER that has to go.

Choose by what the request names, not by what happens to be exported:

  • The request names a saved server ("deploy to dogfood") — use -n dogfood and unset CONNECT_SERVER for that command. Resolving the conflict the other way is worse: CONNECT_SERVER can point somewhere else entirely, so dropping -n to keep it would deploy to a server the user did not ask for.
  • The request names no server, the typical headless run — let CONNECT_SERVER and CONNECT_API_KEY supply the target, and deploy with rsconnect deploy <framework> <dir>.

CONNECT_SERVER is not secret. Print it if you are unsure which server it points at, and name the server you deployed to in your report.

R (rsconnect)

Register the server under a local nickname, then register your user against it:

library(rsconnect)

# 1. The server (once per server; the name is a local nickname)
rsconnect::addServer(url = "https://connect.example.com", name = "myserver")

# 2a. Interactive — approve in a browser, no key to handle
rsconnect::connectUser(server = "myserver")

# 2b. Or non-interactively (CI), only when the user asked for a key route
rsconnect::connectApiUser(
  server  = "myserver",
  account = "your-username",
  apiKey  = Sys.getenv("CONNECT_API_KEY")
)

connectCloudUser() authenticates against Connect Cloud, a different service, so it does not work for a Connect server. Use connectUser() or connectApiUser() here.

If the login route is not available

Report it and stop. Name the server you tried to register and say which login command failed. Do not search the environment, a .env file, or a credential store for a key to fill the gap, and do not ask the user for a key. The next step is theirs to choose.

Files (skills)
  • SKILL.md 19.4 KB
    ---
    name: deploy-to-connect
    description: >-
      Deploy or publish Python and R content to a Posit Connect server using
      rsconnect-python or the R rsconnect package. Handles interactive apps and
      dashboards, web APIs, rendered documents, and prepared bundles/manifests. Use
      whenever the user asks to deploy, publish, or redeploy content to Posit
      Connect, or mentions rsconnect. Consult this skill instead of guessing flags
      or commands.
    metadata:
      author: posit-pbc
      version: "4.0"
    ---
    
    <!--
    Maintainer note: edit this skill in posit-dev/connect only.
    Downstream copies are overwritten by the sync workflow.
    -->
    
    # Deploying to Posit Connect
    
    This guide covers Python and R content on a Posit Connect server. Work through the stages in order.
    
    Two toolchains do the work:
    
    - Python — [rsconnect-python](https://github.com/posit-dev/rsconnect-python), which provides the `rsconnect` CLI and is published on PyPI.
    - R — the R [`rsconnect`](https://rstudio.github.io/rsconnect/) package, pointed at a Connect server.
    
    If the user asks a question ("how do I…", "what is the command…") rather than asking for a deploy, answer from this guide and stop.
    
    At the end, report which server you deployed to, which content type you picked, any tool you installed, and any assumption you made.
    
    ---
    
    ## Stage 1 — Detect the content
    
    Infer the language and framework from the files in the project directory. Common signals:
    
    | Signal in project dir | Likely content |
    | --- | --- |
    | `app.py` | Python web app — Shiny for Python, Streamlit, Dash, Gradio, Panel, or Bokeh |
    | `app.R`, or `ui.R` + `server.R` | Shiny for R |
    | `plumber.R` / `entrypoint.R` containing `plumb()` | Plumber API (R) |
    | `*.qmd` | Quarto document |
    | `*.Rmd` | R Markdown |
    | `*.ipynb` | Jupyter notebook / Voila |
    | `manifest.json` | Prebuilt bundle — deploy it directly, no framework guess needed |
    | A bare `.py` or `.R` — no framework import, no `ui.R`/`server.R`/`plumber.R`/`entrypoint.R` alongside | Script — a batch/ETL job that Quarto renders and Connect can schedule |
    
    ### Confirm the guess
    
    The imports in `app.py` name the framework:
    
    ```console
    grep -Eo 'import (shiny|streamlit|dash|gradio|panel|bokeh)|from (shiny|streamlit|dash|gradio|panel|bokeh)' app.py
    ```
    
    A bare ASGI or WSGI object means `fastapi` or `flask`.
    
    Dependency files confirm the language: `requirements.txt` and `pyproject.toml` for Python, `DESCRIPTION` and `renv.lock` for R.
    
    Quarto renders a script only if it opens with a front-matter comment: `# %% [markdown]` around a `---` block in Python, `#' ---` in R. Most scripts lack one — add it before the deploy (Stage 5).
    
    If the content is ambiguous (both Python and R files, or an `app.py` with no recognizable import), use your discretion, and report the assumption you made.
    
    ---
    
    ## Stage 2 — Inventory your tools
    
    Probe the environment and build a capability set:
    
    ```console
    command -v rsconnect                                 # rsconnect-python on PATH
    command -v uv                                        # uv (installs and runs Python tools)
    uv tool list 2>/dev/null | grep rsconnect            # rsconnect-python installed via uv
    command -v Rscript                                   # R present
    Rscript -e 'cat(requireNamespace("rsconnect", quietly=TRUE))' 2>/dev/null   # R rsconnect package
    command -v quarto                                     # quarto CLI
    command -v git                                        # git
    ```
    
    With `uv` present, Python content needs no install step. `uv tool run --from rsconnect-python rsconnect ...` fetches and runs the CLI on demand.
    
    ---
    
    ## Stage 3 — Pick a route
    
    Cross the detected content (Stage 1) with your capabilities (Stage 2).
    
    ### Python content
    
    Use rsconnect-python. With `rsconnect` on `PATH`:
    
    ```console
    rsconnect deploy <framework> ./my-app
    ```
    
    Off `PATH` but with `uv` present:
    
    ```console
    uv tool run --from rsconnect-python rsconnect deploy <framework> ./my-app
    ```
    
    Both forms take identical arguments. The rest of this guide writes the bare `rsconnect ...` form. Prefix it with `uv tool run --from rsconnect-python` when you use the second route.
    
    `<framework>` is one of `api`, `bokeh`, `bundle`, `dash`, `fastapi`, `flask`, `git`, `gradio`, `html`, `manifest`, `nodejs`, `notebook`, `panel`, `pyproject`, `quarto`, `shiny`, `streamlit`, `tensorflow`, `voila`. For anything outside that list, `rsconnect deploy other-content` prints guidance.
    
    The frameworks and flags depend on the installed version, so confirm against `rsconnect deploy --help` rather than this list. If `uv tool run` resolves a stale cached version, pin it: `uv tool run --from 'rsconnect-python==1.30.0' rsconnect ...`.
    
    ### R content
    
    Use the R `rsconnect` package, through `Rscript -e '...'` or an R session:
    
    - Shiny for R, Plumber API, or any app directory → `deployApp()`
    - A single R Markdown or Quarto document → `deployDoc()`
    - A full R Markdown or Quarto site → `deploySite()`
    
    If `Rscript` is absent, deploy the R content through rsconnect-python with a `manifest.json`:
    
    - A `manifest.json` already exists — deploy it directly:
      ```console
      rsconnect deploy manifest ./manifest.json
      ```
    - No manifest, but R is available elsewhere — generate one first with `rsconnect::writeManifest()` (see Stage 5).
    - Neither R nor a manifest — a valid R bundle is not possible. Surface this as a blocker: ask the user or report it clearly.
    
    ### Quarto content
    
    ```console
    rsconnect deploy quarto ./report
    ```
    
    R-flavored Quarto (a `.qmd` with R code chunks) needs R to render. If R is absent, treat the document as R content and use the manifest route, or surface the gap.
    
    ### Script content
    
    Use the `quarto` framework. Add the front matter first (Stage 5).
    
    ```console
    rsconnect deploy quarto script.py    # Python, rsconnect-python 1.23.0 or later
    ```
    
    ```r
    rsconnect::deployApp()               # R, rsconnect 1.2.2 or later, from the directory of the script
    ```
    
    Both commands include every file in the directory. Push-button publishing does not cover R scripts, so `deployApp()` is the only R route.
    
    A script deploys like a Quarto document but is a different content type: a `.qmd` is a page to read, a script is a job that writes output.
    
    ---
    
    ## Stage 4 — Find the target and check its credentials
    
    Now that the tool is known, find out which server to deploy to and whether the tool can already reach it. This is a check, not a login.
    
    **Do not search the environment for API keys.** Do not read `CONNECT_API_KEY`, `CONNECT_SERVER`, a `.env` file, a keychain entry, or any other stored secret to pick a target or to register a server. Do this only when the user explicitly asks for it. An environment variable is not a request to use it.
    
    List the accounts the tool already has. This is the only credential check you need.
    
    ```console
    rsconnect list                                   # Python: saved servers, stored tokens, and the default server on 1.30.0+
    Rscript -e 'print(rsconnect::accounts())'        # R: registered accounts
    ```
    
    If the tool is not installed yet, close that gap in Stage 5 first. Then run the check.
    
    Compare the result with the target the user named. Three outcomes:
    
    - **An account matches the named target.** The credential path is live. Run no login and no `rsconnect add`. Continue to Stage 6 once the other gaps are closed.
    - **The user named no target.** Ask them. List the servers the check found, and ask which one to deploy to, or whether they want a new target instead. Do not pick one for them, and do not deploy to the only saved server because it is the only one.
    - **The target is new, or no account matches it.** This is a gap for Stage 5. Register it with a browser login.
    
    A browser login is the way to register a new target:
    
    ```console
    rsconnect login https://connect.example.com      # Python
    ```
    
    ```r
    rsconnect::addServer(url = "https://connect.example.com", name = "myserver")   # R
    rsconnect::connectUser(server = "myserver")
    ```
    
    Both forms open a browser flow, so the user approves the login and no key passes through the conversation. The [credentials reference](#credentials-reference) has the details and the pitfalls.
    
    ---
    
    ## Stage 5 — Resolve gaps
    
    When Stages 3 and 4 find a gap, close it, then include the action in your report.
    
    **`rsconnect` not on `PATH`.** With `uv` present, no install is needed:
    
    ```console
    uv tool run --from rsconnect-python rsconnect deploy <framework> ./my-app
    ```
    
    If the user wants it installed persistently, or `uv tool run` is not viable:
    
    ```console
    uv tool install rsconnect-python     # or: pip install rsconnect-python
    ```
    
    The package name and the command name differ: the PyPI package is `rsconnect-python`, and the command it provides is `rsconnect`. That is why `uv tool run` needs `--from rsconnect-python`. To update later, run `uv tool upgrade rsconnect-python`.
    
    **R `rsconnect` package missing, `Rscript` present.** Install it from Posit Package Manager (P3M), which serves precompiled Linux binaries. A binary install is much faster than a source build and needs no `-dev` system libraries. Binaries need two things: the `__linux__/<codename>` repo URL and a platform-identifying `HTTPUserAgent`. Without the user agent, P3M serves source.
    
    ```console
    export P3M="https://packagemanager.posit.co/cran/__linux__/$(. /etc/os-release && echo "$VERSION_CODENAME")/latest"
    Rscript -e '
      options(HTTPUserAgent = sprintf("R/%s R (%s)", getRversion(),
        paste(getRversion(), R.version["platform"], R.version["arch"], R.version["os"])))
      install.packages("rsconnect", repos = Sys.getenv("P3M"))
    '
    ```
    
    P3M binaries exist for x86_64 on common distros. On arm64 or an unsupported distro, P3M falls back to source. That result is still correct, only slower, and it needs the usual `-dev` libraries and a compiler. Use `https://cloud.r-project.org` (CRAN source) only when P3M is unreachable.
    
    **`manifest.json` missing for R content, R present.** Generate it:
    
    ```console
    Rscript -e 'rsconnect::writeManifest()'
    ```
    
    rsconnect-python writes one for Python content:
    
    ```console
    rsconnect write-manifest <framework> ./my-app
    ```
    
    Then deploy the manifest with rsconnect-python if R cannot deploy directly.
    
    **Script front matter missing.** Add the minimal block at the top of the file. Connect takes the content title from `title`, so write a descriptive one.
    
    Python:
    
    ```python
    # %% [markdown]
    # ---
    # title: "Data processing script"
    # ---
    ```
    
    R:
    
    ```r
    #' ---
    #' title: "Data processing script"
    #' ---
    ```
    
    **No account for the target.** Register it now with a browser login: `rsconnect login` for Python, or `rsconnect::addServer()` and `rsconnect::connectUser()` for R. The [credentials reference](#credentials-reference) has the details and the pitfalls. Do not fall back to an API key from the environment. If the browser flow is not available, report that and stop.
    
    **Dependencies.** rsconnect and rsconnect-python scan the code and snapshot the required package versions for you, so hand-listing them is rarely necessary. Python content needs a `requirements.txt`. For R, the content's own packages must be installed locally for rsconnect to detect them — `plumber` for a Plumber API, `shiny` for a Shiny app. Install any that are missing from the same P3M repo shown above.
    
    ---
    
    ## Stage 6 — Deploy and handle failure
    
    ### Discover the live command surface (Python)
    
    The frameworks and flags in rsconnect-python change between releases, and the help text is the source of truth:
    
    ```console
    rsconnect version                  # which version you are actually running
    rsconnect deploy --help            # every framework you can deploy
    rsconnect deploy <framework> --help  # flags for one framework
    ```
    
    ### Deploy
    
    For Python, run `rsconnect deploy <framework> <dir>` with the framework Stage 3 picked. The `manifest` framework takes the manifest file rather than a directory.
    
    Non-obvious flags: `-t/--title`, `-N/--new` (force a new deployment instead of updating the recorded one), `-a/--app-id <id>` (target an existing item explicitly, mutually exclusive with `--new`), `-E NAME=VALUE` (set an environment variable, repeatable), `--draft` (keep serving the previous bundle until published).
    
    For R, call the function Stage 3 selected. Pass `appTitle` so the content is not named after the directory.
    
    A script deploy sweeps the whole directory. If the directory holds files the script does not need, narrow the selection: name the files in Python (`rsconnect deploy quarto script.py helper.py data.csv`) or pass `appFiles` in R (`rsconnect::deployApp(appFiles = c("_quarto.yml", "script.R"))`). A directory with a `_quarto.yml` is a Quarto project — deploy it whole with `rsconnect deploy quarto .`.
    
    ### If `rsconnect` is not found at deploy time
    
    It can be installed but off `PATH` in this shell. IDE-spawned terminals and active virtualenvs both cause this. Fall back to `uv tool run` as described in Stage 5, with `--from rsconnect-python`.
    
    ### Pre-flight check (optional)
    
    To confirm that the target is reachable and the credentials work before you deploy:
    
    ```console
    rsconnect details -n myserver
    ```
    
    ### When a deploy fails
    
    Python:
    
    - Auth errors — confirm the target with `rsconnect list`, then re-run `rsconnect login` (1.30.0+). Pass `-s`/`-k` only when the user told you to use an existing key.
    - `-n/--name ... cannot be specified in conjunction with ... -s/--server (from ENVIRONMENT)` — `CONNECT_SERVER` is set and you also passed `-n`. Run `unset CONNECT_SERVER` and keep `-n`. The credentials reference explains why that direction. `CONNECT_API_KEY` can stay.
    - `The requirements file 'requirements.txt' does not exist` — Python content needs one. Create it, point at another file with `--requirements-file`, or generate it with `--force-generate`. The last option runs a `pip freeze`, so it can over-pin.
    - Self-signed TLS — use `-i/--insecure` or `-c/--cacert <file>`. Set `CONNECT_INSECURE` or `CONNECT_CA_CERTIFICATE` to apply it everywhere.
    - Rejected flag or unknown framework — re-check `rsconnect version` and re-read `rsconnect deploy <framework> --help`. The installed version is usually older than the flag you used.
    - A deployed script renders empty or broken — the server lacks Quarto 1.4+, Jupyter (Python scripts), or `rmarkdown` (R scripts). The deploy itself succeeded, so do not retry it. Report the missing server dependency.
    
    R:
    
    - "No account" or auth errors — run `rsconnect::accounts()`. If it is empty, re-run `rsconnect::addServer()`, then `connectUser()` or `connectApiUser()`. Make sure that you used a server function and not `connectCloudUser()`.
    - `Found multiple accounts. Please disambiguate by setting server and/or account` — more than one account is linked. Pass `account =` and `server =` explicitly to the deploy call. An interactive R session shows a menu instead, which hangs a headless run.
    - Wrong deploy function — `deployApp()` for directories and apps, `deployDoc()` for a single document, `deploySite()` for a site.
    - Self-signed TLS — pass the CA bundle through the `curl` options, or add the server with the certificate. For a quick test, set `options(rsconnect.check.certificate = FALSE)`.
    - Absolute-path warnings — files with hard-coded absolute paths do not block the deploy, but they are better made relative to the project directory.
    
    ---
    
    ## Credentials reference
    
    How to register a target that Stage 4 found no account for. If an account already matches the target, none of this is needed.
    
    A browser login is the route. The API-key routes below it are there for one case only: the user explicitly tells you to use a key that already exists, in an environment variable or a credential store. Do not go looking for a key on your own, and never ask the user to give you one. An API key does not belong in the conversation.
    
    ### Python (rsconnect-python)
    
    1. **OAuth login (interactive).** The default route. Needs rsconnect-python 1.30.0+, so check `rsconnect version` first. One browser flow per server. Tokens land in the OS keyring, or a local credential store, and refresh automatically.
       ```console
       rsconnect login https://connect.example.com
       rsconnect login https://connect.example.com --use-device-code   # headless
       ```
    2. **Saved API-key nickname.** Only when the user asked for a key route. Save once, select later with `-n/--name`.
       ```console
       rsconnect add -n myserver -s https://connect.example.com -k <api-key>
       rsconnect list                    # confirm what is saved
       ```
       On 1.30.0+ a server can be the default, used when a command passes neither `-n` nor `-s`. `add` sets the default only with `--set-default`. `login` sets it unless you pass `--no-set-default`. `rsconnect server set-default -n <name>` changes it later. `CONNECT_SERVER` still takes precedence over the default.
    3. **Environment variables.** Only when the user asked you to use them. rsconnect-python reads them directly, which suits a headless or automated run with no state to manage.
       ```console
       export CONNECT_SERVER=https://connect.example.com
       export CONNECT_API_KEY=...        # honored across the whole `rsconnect` surface
       ```
    4. **Ad hoc flags** on the deploy command: `-s <url> -k <api-key>`. Same condition, and read the key from the variable the user named rather than writing it out.
    
    Shared credential flags: `-n/--name` (saved server), `-s/--server` (env `CONNECT_SERVER`), `-k/--api-key` (env `CONNECT_API_KEY`), `-i/--insecure` (env `CONNECT_INSECURE`, for self-signed TLS), `-c/--cacert <file>` (env `CONNECT_CA_CERTIFICATE`).
    
    > `-n` and `CONNECT_SERVER` cannot both be in play. rsconnect rejects a command that combines a saved-server name (`-n/--name`) with a server URL, including a URL that came from the environment: `-n/--name (from COMMANDLINE) cannot be specified in conjunction with options -s/--server (from ENVIRONMENT)`.
    >
    > Only the server conflicts. `CONNECT_API_KEY`, `CONNECT_INSECURE`, and `CONNECT_CA_CERTIFICATE` sit alongside `-n` without complaint, because the key is not part of the exclusion. `-n dogfood` with `CONNECT_API_KEY` exported is a valid command. It is `CONNECT_SERVER` that has to go.
    >
    > Choose by what the request names, not by what happens to be exported:
    >
    > - The request names a saved server ("deploy to dogfood") — use `-n dogfood` and `unset CONNECT_SERVER` for that command. Resolving the conflict the other way is worse: `CONNECT_SERVER` can point somewhere else entirely, so dropping `-n` to keep it would deploy to a server the user did not ask for.
    > - The request names no server, the typical headless run — let `CONNECT_SERVER` and `CONNECT_API_KEY` supply the target, and deploy with `rsconnect deploy <framework> <dir>`.
    >
    > `CONNECT_SERVER` is not secret. Print it if you are unsure which server it points at, and name the server you deployed to in your report.
    
    ### R (`rsconnect`)
    
    Register the server under a local nickname, then register your user against it:
    
    ```r
    library(rsconnect)
    
    # 1. The server (once per server; the name is a local nickname)
    rsconnect::addServer(url = "https://connect.example.com", name = "myserver")
    
    # 2a. Interactive — approve in a browser, no key to handle
    rsconnect::connectUser(server = "myserver")
    
    # 2b. Or non-interactively (CI), only when the user asked for a key route
    rsconnect::connectApiUser(
      server  = "myserver",
      account = "your-username",
      apiKey  = Sys.getenv("CONNECT_API_KEY")
    )
    ```
    
    `connectCloudUser()` authenticates against Connect Cloud, a different service, so it does not work for a Connect server. Use `connectUser()` or `connectApiUser()` here.
    
    ### If the login route is not available
    
    Report it and stop. Name the server you tried to register and say which login command failed. Do not search the environment, a `.env` file, or a credential store for a key to fill the gap, and do not ask the user for a key. The next step is theirs to choose.
    

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