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توضیحات

Dashborg Python SDK

ویژگی	مقدار
سیستم عامل	-
نام فایل	dashborg-python-sdk-0.4.0.dev5
نام	dashborg-python-sdk
نسخه کتابخانه	0.4.0.dev5
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Michael Sawka
ایمیل نویسنده	mike@dashborg.net
آدرس صفحه اصلی	https://github.com/sawka/dashborg-python-sdk
آدرس اینترنتی	https://pypi.org/project/dashborg-python-sdk/
مجوز	-

# Dashborg Python SDK Dashborg is a SDK that plugs directly into any backend service or script. With a couple lines of code you can register any running function with the Dashborg service and then build secure, modern, interactive tools on top of those functions using a simple, JavaScript free, HTML template language. Dashborg saves you time by handling all of the tedious details of frontend app creation and deployment (hosting, end-to-end security, authentication, transport, UI libraries, JavaScript frameworks, CSS frameworks, etc.). Dashborg works great for debugging, introspecting the running state of servers, viewing/updating configuration values, bite-sized internal tools, status pages, and reports. Dashborg is easy to get started with. You can have your first app deployed in 5-minutes (no account/registration required). Free tier covers most simple use cases. * Doc Site: https://docs.dashborg.net * SDK Reference: https://docs.dashborg.net/reference/python-reference/ * Example Code: https://github.com/sawka/dashborg-examples (python directory) Questions? [Join the Dashborg Slack Channel](https://join.slack.com/t/dashborgworkspace/shared_invite/zt-uphltkhj-r6C62szzoYz7_IIsoJ8WPg) ## Dashborg Hello World ``` pip install dashborg-python-sdk ``` ```Python import dashborg import asyncio counter = 0 def test_fn(): global counter counter += 1 print(f"Calling TestFn counter={counter}") return {"message": "TestFn Output!", "counter": counter} async def main(): config = dashborg.Config(anon_acc=True, auto_keygen=True) client = await dashborg.connect_client(config) app = client.app_client().new_app("hello-world") app.set_html(file_name="hello-world.html", watch=True) app.runtime.handler("test-handler", test_fn, pure_handler=True) await client.app_client().write_app(app, connect=True) await client.wait_for_shutdown() asyncio.run(main()) ``` The HTML template to render your app (save as hello-world.html): ```HTML <app ui="dashborg"> <h1>Hello World</h1> <div class="row xcenter"> <d-button onclickhandler="$.output = /@app:test-handler">Run Test Handler</d-button> <d-stat label="Counter" bind="$.output.counter" defaultvalue="0"/> </div> <hr/> <d-dataview bind="$.output"/> </app> ``` Run your program. A new public/private keypair will be created and used to secure your new Dashborg account. You'll also see a secure link to your new application. Click to view your application! That's it. You've created and deployed, secure, interactive web-app that is directly calling code running on your local machine! ## Adding BLOBs Want to show an image, or add a CSV file your end users to download, here's how to do it: ```Python await client.global_fs_client().set_static_path("/image/myimage.jpg", file_name="./path-to-image.jpg", fileopts=dashborg.FileOpts(mimetype="image/jpeg")) await client.global_fs_client().set_static_path("/mydata.csv", file_name="./path-to-csv.csv", fileopts=dashborg.FileOpts(mimetype="text/csv")) ``` Show the image using a regular <img> tag in your HTML template. Using the path prefix "/@raw/" allows for raw http GET access to your uploaded content: ``` <img src="/@raw/image/myimage.jpg" style="max-width: 500px;"/> ``` Download the CSV using a standard HTML download link: ``` <a href="/@raw/mydata.csv" download>Download CSV</a> ``` Or use a Dashborg download control (defined in the standard Dashborg UI package) to make it look nice: ``` <d-download path="/mydata.csv">Download CSV</d-download> ``` ## Adding Static Data Dashborg uses JSON to transfer data between your app and the Dashborg service. You can send any static JSON-compatible data (bool, str, int, float, dict, list) to Dashborg using set\_json\_path(). Static data is available to apps even when there is no backend connected. For dynamic data, use a runtime handler. Here we'll set favorite color table to the path "/colors.json". We used the app\_fs\_client() instead of the global\_fs\_client(). That makes the data local to the app and is accessible at /@app/colors.json: ```Python colors = [] colors.append({"name": "Mike", "color": "blue", "hex": "#007fff"}) colors.append({"name": "Chris", "color": "red", "hex": "#ee0000"}) colors.append({"name": "Jenny", "color": "purple", "hex": "#a020f0"}) await app.app_fs_client().set_json_path("/colors.json", colors) ``` Load the data into our datamodel using the <d-data> tag. Read from blob "colors", set it into the frontend data model at ```$.colors```: ```html <d-data query="/@app/colors.json" output.bindpath="$.colors"/> ``` Show the first color name as text using ```<d-text>```. Use the hex color to show a small color square using a background-color style (attributes and styles are dynamic when they starts with ```*```): ```html <div> <d-text bind="$.colors[0].name"/>'s favorite color is <d-text bind="$.colors[0].color"/>: <div style="display: inline-block; vertical-align: bottom; width: 18px; height: 18px; background-color: *$.colors[0].hex"/> </div> ``` You can loop using the built-in ```<d-foreach>``` tag (each element is bound to ```.``` inside the loop): ```html <ul class="ui bulleted list"> <d-foreach bind="$.colors"> <li class="item" style="height: 24px"> <div class="row"> <div><d-text bind=".name"/> - Favorite Color is <d-text bind=".color"/></div> <div style="width: 18px; height: 18px; background-color: * .hex"/> </div> </li> </d-foreach> </ul> ``` Or use a Dashborg Table Control (@index is bound to the loop counter): ```html <d-table bind="$.colors"> <d-col label="#" bind="@index+1"/> <d-col label="Name" bind=".name"/> <d-col label="Color" bind=".color"/> <d-col label="Swatch"> <div style="width: 50px; height: 50px; background-color: * .hex"/> </d-col> </d-table> ``` ## Security All communication from your backend to the Dashborg service is done over HTTPS/gRPC. Your account is authenticated with a public/private keypair that can be auto-generated by the Dashborg SDK (AutoKeygen config setting). The frontend is served over HTTPS, and each account is hosted on its own subdomain to prevent inter-account XSS attacks The Dashborg frontend offers pre-built authentication methods, with JWT tokens that are created from your private-key (the default for new anonymous accounts), simple passwords, or user logins. ## Advanced Features * Write your own Dashborg components to reuse among your applications * Create staging/development zones to test your apps without affecting your production site * Assign roles to users (and passwords), set a list of allowed roles per app per zone * Navigate to the '/@fs' path on your Dashborg account to see all of your static data, applications, and handlers.

نیازمندی

مقدار	نام
-	aiofiles
-	cffi
-	cryptography
-	ecdsa
-	grpcio
-	grpcio-tools
-	protobuf
-	pycparser
-	six
-	pyjwt
-	watchdog
-	aiohttp

زبان مورد نیاز

مقدار	نام
>=3.6	Python

نحوه نصب

نصب پکیج whl dashborg-python-sdk-0.4.0.dev5:

pip install dashborg-python-sdk-0.4.0.dev5.whl

نصب پکیج tar.gz dashborg-python-sdk-0.4.0.dev5:

pip install dashborg-python-sdk-0.4.0.dev5.tar.gz