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https://github.com/colearendt/rsconnect-python-playground


https://github.com/colearendt/rsconnect-python-playground

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README 

        
# The rsconnect-python CLI and library



This package provides both a CLI (command-line interface) and a library for interacting

with and deploying to RStudio Connect. The library is also used by the

[`rsconnect-jupyter`](https://github.com/rstudio/rsconnect-jupyter) package to deploy

Jupyter notebooks via the Jupyter web console. Many types of content supported by RStudio

Connect may be deployed by this package, including WSGI-style APIs, Dash, Streamlit, and

Bokeh applications.



Content types not directly supported by the CLI may also be deployed if they include a

prepared `manifest.json` file. See ["Deploying R or Other

Content"](#deploying-r-or-other-content) for details.



## Deploying Python Content to RStudio Connect



RStudio Connect supports the deployment of Jupyter notebooks, Python APIs (such as

`flask`-based) and apps (such as Dash, Streamlit, and Bokeh apps). Much like deploying R

content to RStudio Connect, there are some caveats to understand when replicating your

environment on the RStudio Connect server:



RStudio Connect insists on matching `` versions of Python. For example,

a server with only Python 3.8 installed will fail to match content deployed with

Python 3.7. Your administrator may also enable exact Python version matching which

will be stricter and require matching major, minor, and patch versions. For more

information see the [RStudio Connect Admin Guide chapter titled Python Version

Matching](https://docs.rstudio.com/connect/admin/python.html#python-version-matching).



### Installation



To install `rsconnect-python` from PYPI, you may use any python package manager such as

pip:



```bash

pip install rsconnect-python

```



You may also build and install a wheel directly from a repository clone:



```bash

git clone https://github.com/rstudio/rsconnect-python.git

cd rsconnect-python

pip install pipenv

make deps dist

pip install ./dist/rsconnect_python-*.whl

```



### Using the rsconnect CLI



Here's an example command that deploys a Jupyter notebook to RStudio Connect.



```bash

rsconnect deploy notebook \

    --server https://connect.example.org:3939 \

    --api-key my-api-key \

    my-notebook.ipynb

```



> **Note:** The examples here use long command line options, but there are short

> options (`-s`, `-k`, etc.) available also. Run `rsconnect deploy notebook --help`

> for details.



### Setting up `rsconnect` CLI auto-completion



If you would like to use your shell's tab completion support with the `rsconnect`

command, use the command below for the shell you are using.



#### `bash`



If you are using the `bash` shell, use this to enable tab completion.



```bash

#~/.bashrc

eval "$(_RSCONNECT_COMPLETE=source rsconnect)"

```



#### `zsh`



If you are using the `zsh` shell, use this to enable tab completion.



```zsh

#~/.zshrc

eval "$(_RSCONNECT_COMPLETE=source_zsh rsconnect)"

```



If you get `command not found: compdef`, you need to add the following lines to your 

`.zshrc` before the completion setup:



```zsh

#~/.zshrc

autoload -Uz compinit

compinit

```



### Managing Server Information



The information used by the `rsconnect` command to communicate with an RStudio Connect

server can be tedious to repeat on every command. To help, the CLI supports the idea

of saving this information, making it usable by a simple nickname.



> **Important:** One item of information saved is the API key used to authenticate with

> RStudio Connect. Although the file where this information is saved is marked as

> accessible by the owner only, it's important to remember that the key is present

> in the file as plain text so care must be taken to prevent any unauthorized access

> to the server information file.



#### TLS Support and RStudio Connect



Usually, an RStudio Connect server will be set up to be accessed in a secure manner,

using the `https` protocol rather than simple `http`. If RStudio Connect is set up

with a self-signed certificate, you will need to include the `--insecure` flag on

all commands. If RStudio Connect is set up to require a client-side certificate chain,

you will need to include the `--cacert` option that points to your certificate

authority (CA) trusted certificates file. Both of these options can be saved along

with the URL and API Key for a server.



> **Note:** When certificate information is saved for the server, the specified file

> is read and its _contents_ are saved under the server's nickname. If the CA file's

> contents are ever changed, you will need to add the server information again.



See the [Network Options](#network-options) section for more details about these options.



#### Remembering Server Information



Use the `add` command to store information about an RStudio Connect server:



```bash

rsconnect add \

    --api-key my-api-key \

    --server https://connect.example.org:3939 \

    --name myserver

```



> **Note:** The `rsconnect` CLI will verify that the serve URL and API key

> are valid. If either is found not to be, no information will be saved.



If any of the access information for the server changes, simply rerun the

`add` command with the new information and it will replace the original

information.



Once the server's information is saved, you can refer to it by its nickname:



```bash

rsconnect deploy notebook --name myserver my-notebook.ipynb

```



If there is information for only one server saved, this will work too:



```bash

rsconnect deploy notebook my-notebook.ipynb

```



#### Listing Server Information



You can see the list of saved server information with:



```

rsconnect list

```



#### Removing Server Information



You can remove information about a server with:



```

rsconnect remove --name myserver

```



Removing may be done by its nickname (`--name`) or URL (`--server`).



### Verifying Server Information



You can verify that a URL refers to a running instance of RStudio Connect by using

the `details` command:



```bash

rsconnect details --server https://connect.example.org:3939

```



In this form, `rsconnect` will only tell you whether the URL given does, in fact, refer

to a running RStudio Connect instance. If you include a valid API key:



```bash

rsconnect details --server https://connect.example.org:3939 --api-key my-api-key

```



the tool will provide the version of RStudio Connect (if the server is configured to

divulge that information) and environmental information including versions of Python

that are installed on the server.



You can also use nicknames with the `details` command if you want to verify that the

stored information is still valid.



### Notebook Deployment Options



There are a variety of options available to you when deploying a Jupyter notebook to

RStudio Connect.



#### Including Extra Files



You can include extra files in the deployment bundle to make them available when your

notebook is run by the RStudio Connect server. Just specify them on the command line

after the notebook file:



```bash

rsconnect deploy notebook my-notebook.ipynb data.csv

```



#### Package Dependencies



If a `requirements.txt` file exists in the same directory as the notebook file, it will

be included in the bundle. It must specify the package dependencies needed to execute

the notebook. RStudio Connect will reconstruct the Python environment using the

specified package list.



If there is no `requirements.txt` file or the `--force-generate` option is specified,

the package dependencies will be determined from the current Python environment, or

from an alternative Python executable specified via the `--python` option or via the

`RETICULATE_PYTHON` environment variable:



```bash

rsconnect deploy notebook --python /path/to/python my-notebook.ipynb

```



You can see the packages list that will be included by running `pip list --format=freeze` yourself,

ensuring that you use the same Python that you use to run your Jupyter Notebook:



```bash

/path/to/python -m pip list --format=freeze

```



#### Static (Snapshot) Deployment



By default, `rsconnect` deploys the original notebook with all its source code. This

enables the RStudio Connect server to re-run the notebook upon request or on a schedule.



If you just want to publish an HTML snapshot of the notebook, you can use the `--static`

option. This will cause `rsconnect` to execute your notebook locally to produce the HTML

file, then publish the HTML file to the RStudio Connect server:



```bash

rsconnect deploy notebook --static my-notebook.ipynb

```



### Creating a Manifest for Future Deployment



You can create a `manifest.json` file for a Jupyter Notebook, then use that manifest

in a later deployment. Use the `write-manifest` command to do this.



The `write-manifest` command will also create a `requirements.txt` file, if it does

not already exist or the `--force-generate` option is specified. It will contain the

package dependencies from the current Python environment, or from an alternative

Python executable specified in the `--python` option or via the `RETICULATE_PYTHON`

environment variable.



Here is an example of the `write-manifest` command:



```bash

rsconnect write-manifest notebook my-notebook.ipynb

```



> **Note:** Manifests for static (pre-rendered) notebooks cannot be created.



### API/Application Deployment Options



There are a variety of options available to you when deploying a Python WSGI-style API,

Dash, Streamlit, or Bokeh application. All options below apply equally to `api`,

`dash`, `streamlit`, and `bokeh` sub-commands.



#### Including Extra Files



You can include extra files in the deployment bundle to make them available when your

API or application is run by the RStudio Connect server. Just specify them on the

command line after the API or application directory:



```bash

rsconnect deploy api flask-api/ data.csv

```



Since deploying an API or application starts at a directory level, there will be times

when some files under that directory subtree should not be included in the deployment

or manifest. Use the `--exclude` option to specify files to exclude. An exclusion may

be a glob pattern and the `--exclude` option may be repeated.



```bash

rsconnect deploy dash --exclude "workfiles/*" dash-app/ data.csv

```



You should always quote a glob pattern so that it will be passed to `rsconnect` as-is

instead of letting the shell expand it. If a file is specifically listed as an extra

file that also matches an exclusion pattern, the file will still be included in the

deployment (i.e., extra files take precedence).



#### Package Dependencies



If a `requirements.txt` file exists in the API/application directory, it will be

included in the bundle. It must specify the package dependencies needed to execute

the API or application. RStudio Connect will reconstruct the Python environment using

the specified package list.



If there is no `requirements.txt` file or the `--force-generate` option is specified,

the package dependencies will be determined from the current Python environment, or

from an alternative Python executable specified via the `--python` option or via the

`RETICULATE_PYTHON` environment variable:



```bash

rsconnect deploy api --python /path/to/python my-api/

```



You can see the packages list that will be included by running `pip list --format=freeze` yourself,

ensuring that you use the same Python that you use to run your API or application:



```bash

/path/to/python -m pip list --format=freeze

```



### Creating a Manifest for Future Deployment



You can create a `manifest.json` file for an API or application, then use that

manifest in a later deployment. Use the `write-manifest` command to do this.



The `write-manifest` command will also create a `requirements.txt` file, if it does

not already exist or the `--force-generate` option is specified. It will contain

the package dependencies from the current Python environment, or from an alternative

Python executable specified in the `--python` option or via the `RETICULATE_PYTHON`

environment variable.



Here is an example of the `write-manifest` command:



```bash

rsconnect write-manifest api my-api/

```



### Deploying R or Other Content



You can deploy other content that has an existing RStudio Connect `manifest.json`

file. For example, if you download and unpack a source bundle from RStudio Connect,

you can deploy the resulting directory. The options are similar to notebook or

API/application deployment; see `rsconnect deploy manifest --help` for details.



Here is an example of the `deploy manifest` command:



```bash

rsconnect deploy manifest /path/to/manifest.json

```



> **Note:** In this case, the existing content is deployed as-is. Python environment

> inspection and notebook pre-rendering, if needed, are assumed to be done already

> and represented in the manifest.



The argument to `deploy manifest` may also be a directory so long as that directory

contains a `manifest.json` file.



If you have R content but don't have a `manifest.json` file, you can use the RStudio

IDE to create the manifest. See the help for the `rsconnect::writeManifest` R function:



```r

install.packages('rsconnect')

library(rsconnect)

?rsconnect::writeManifest

```



### Options for All Types of Deployments



These options apply to any type of content deployment.



#### Title



The title of the deployed content is, by default, derived from the filename. For

example, if you deploy `my-notebook.ipynb`, the title will be `my-notebook`. To change

this, use the `--title` option:



```

rsconnect deploy notebook --title "My Notebook" my-notebook.ipynb

```



When using `rsconnect deploy api`, `rsconnect deploy dash`, `rsconnect deploy

streamlit`, or `rsconnect deploy bokeh`, the title is derived from the directory

containing the API or application.



When using `rsconnect deploy manifest`, the title is derived from the primary

filename referenced in the manifest.



### Network Options



When specifying information that `rsconnect` needs to be able to interact with RStudio

Connect, you can tailor how transport layer security is performed.



#### TLS/SSL Certificates



RStudio Connect servers can be configured to use TLS/SSL. If your server's certificate

is trusted by your Jupyter Notebook server, API client or user's browser, then you

don't need to do anything special. You can test this out with the `details` command:



```bash

rsconnect details --api-key my-api-key --server https://connect.example.org:3939

```



If this fails with a TLS Certificate Validation error, then you have two options.



* Provide the Root CA certificate that is at the root of the signing chain for your

  RStudio Connect server. This will enable `rsconnect` to securely validate the

  server's TLS certificate.



    ```bash

    rsconnect details \

        --api-key my-api-key \

        --server https://connect.example.org:3939 \

        --cacert /path/to/certificate.pem

    ```



* RStudio Connect is in "insecure mode". This disables TLS certificate verification,

  which results in a less secure connection.



    ```bash

    rsconnect add \

        --api-key my-api-key \

        --server https://connect.example.org:3939 \

        --insecure

    ```



Once you work out the combination of options that allow you to successfully work with

an instance of RStudio Connect, you'll probably want to use the `add` command to have

`rsconnect` remember those options and allow you to just use a nickname.



### Updating a Deployment



If you deploy a file again to the same server, `rsconnect` will update the previous

deployment. This means that you can keep running `rsconnect deploy notebook my-notebook.ipynb`

as you develop new versions of your notebook. The same applies to other Python content

types.



#### Forcing a New Deployment



To bypass this behavior and force a new deployment, use the `--new` option:



```bash

rsconnect deploy dash --new my-app/

```



#### Updating a Different Deployment



If you want to update an existing deployment but don't have the saved deployment data,

you can provide the app's numeric ID or GUID on the command line:



```bash

rsconnect deploy notebook --app-id 123456 my-notebook.ipynb

```



You must be the owner of the target deployment, or a collaborator with permission to

change the content. The type of content (static notebook, notebook with source code,

API, or application) must match the existing deployment.



> **Note:** There is no confirmation required to update a deployment. If you do so

> accidentally, use the "Source Versions" dialog in the RStudio Connect dashboard to

> activate the previous version and remove the erroneous one.



##### Finding the App ID



The App ID associated with a piece of content you have previously deployed from the

`rsconnect` command line interface can be found easily by querying the deployment

information using the `info` command. For more information, see the

[Showing the Deployment Information](#showing-the-deployment-information) section.



If the content was deployed elsewhere or `info` does not return the correct App ID,

but you can open the content on RStudio Connect, find the content and open it in a

browser. The URL in your browser's location bar will contain `#/apps/NNN` where `NNN`

is your App ID. The GUID identifier for the app may be found on the **Info** tab for

the content in the RStudio Connect UI.



#### Showing the Deployment Information



You can see the information that the `rsconnect` command has saved for the most recent

deployment with the `info` command:



```bash

rsconnect info my-notebook.ipynb

```



If you have deployed to multiple servers, the most recent deployment information for

each server will be shown. This command also displays the path to the file where the

deployment data is stored.



## Stored Information Files



Stored information files are stored in a platform-specific directory:



| Platform | Location                                                           |

| -------- | ------------------------------------------------------------------ |

| Mac      | `$HOME/Library/Application Support/rsconnect-python/`              |

| Linux    | `$HOME/.rsconnect-python/` or `$XDG_CONFIG_HOME/rsconnect-python/` |

| Windows  | `$APPDATA/rsconnect-python`                                        |



Remembered server information is stored in the `servers.json` file in that directory.



### Deployment Data



After a deployment is completed, information about the deployment is saved

to enable later redeployment. This data is stored alongside the deployed file,

in an `rsconnect-python` subdirectory, if possible. If that location is not writable

during deployment, then the deployment data will be stored in the global configuration

directory specified above.





Generated from rsconnect-python {{ rsconnect_python.version }}