perspective-dev.github.io/python/index.html at main · perspective-dev/perspective-dev.github.io

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<!doctype html>

<head>

<title>perspective API documentation</title>

<body>

<div>

<input type="search" placeholder="Search..." role="searchbox" aria-label="search"

pattern=".+" required>

<h2>Contents</h2>

<ul>

<li><a href="#installation">Installation</a></li>

<li><a href="#quick-start">Quick Start</a></li>

</ul>

<h2>API Documentation</h2>

<li>

<a class="class" href="#Server">Server</a>

<li>

<a class="function" href="#Server.new_local_client">new_local_client</a>

</li>

<li>

<a class="function" href="#Server.new_session">new_session</a>

</li>

<li>

</li>

</ul>

</li>

<li>

<a class="class" href="#Client">Client</a>

<li>

<a class="function" href="#Client.from_server">from_server</a>

</li>

<li>

<a class="function" href="#Client.handle_response">handle_response</a>

</li>

<li>

<a class="function" href="#Client.table">table</a>

</li>

<li>

<a class="function" href="#Client.open_table">open_table</a>

</li>

<li>

<a class="function" href="#Client.get_hosted_table_names">get_hosted_table_names</a>

</li>

<li>

<a class="function" href="#Client.on_hosted_tables_update">on_hosted_tables_update</a>

</li>

<li>

<a class="function" href="#Client.remove_hosted_tables_update">remove_hosted_tables_update</a>

</li>

<li>

<a class="function" href="#Client.system_info">system_info</a>

</li>

<li>

<a class="function" href="#Client.terminate">terminate</a>

</li>

</ul>

</li>

<li>

<a class="class" href="#Table">Table</a>

<li>

<a class="function" href="#Table.get_index">get_index</a>

</li>

<li>

<a class="function" href="#Table.get_client">get_client</a>

</li>

<li>

<a class="function" href="#Table.get_limit">get_limit</a>

</li>

<li>

</li>

<li>

<a class="function" href="#Table.clear">clear</a>

</li>

<li>

<a class="function" href="#Table.columns">columns</a>

</li>

<li>

<a class="function" href="#Table.delete">delete</a>

</li>

<li>

</li>

<li>

<a class="function" href="#Table.on_delete">on_delete</a>

</li>

<li>

<a class="function" href="#Table.remove">remove</a>

</li>

<li>

<a class="function" href="#Table.remove_delete">remove_delete</a>

</li>

<li>

<a class="function" href="#Table.schema">schema</a>

</li>

<li>

<a class="function" href="#Table.validate_expressions">validate_expressions</a>

</li>

<li>

</li>

<li>

</li>

<li>

<a class="function" href="#Table.replace">replace</a>

</li>

<li>

<a class="function" href="#Table.update">update</a>

</li>

</ul>

</li>

<li>

<li>

<a class="function" href="#View.column_paths">column_paths</a>

</li>

<li>

<a class="function" href="#View.to_columns_string">to_columns_string</a>

</li>

<li>

<a class="function" href="#View.to_json_string">to_json_string</a>

</li>

<li>

<a class="function" href="#View.to_ndjson">to_ndjson</a>

</li>

<li>

<a class="function" href="#View.to_records">to_records</a>

</li>

<li>

</li>

<li>

<a class="function" href="#View.to_columns">to_columns</a>

</li>

<li>

</li>

<li>

<a class="function" href="#View.to_dataframe">to_dataframe</a>

</li>

<li>

<a class="function" href="#View.to_pandas">to_pandas</a>

</li>

<li>

<a class="function" href="#View.to_polars">to_polars</a>

</li>

<li>

<a class="function" href="#View.to_arrow">to_arrow</a>

</li>

<li>

<a class="function" href="#View.delete">delete</a>

</li>

<li>

<a class="function" href="#View.expand">expand</a>

</li>

<li>

<a class="function" href="#View.collapse">collapse</a>

</li>

<li>

<a class="function" href="#View.dimensions">dimensions</a>

</li>

<li>

<a class="function" href="#View.expression_schema">expression_schema</a>

</li>

<li>

<a class="function" href="#View.get_config">get_config</a>

</li>

<li>

</li>

<li>

</li>

<li>

<a class="function" href="#View.schema">schema</a>

</li>

<li>

<a class="function" href="#View.on_delete">on_delete</a>

</li>

<li>

<a class="function" href="#View.remove_delete">remove_delete</a>

</li>

<li>

<a class="function" href="#View.on_update">on_update</a>

</li>

<li>

<a class="function" href="#View.remove_update">remove_update</a>

</li>

</ul>

</li>

<li>

<a class="variable" href="#PerspectiveError">PerspectiveError</a>

</li>

<li>

<a class="class" href="#ProxySession">ProxySession</a>

<li>

<a class="function" href="#ProxySession.handle_request">handle_request</a>

</li>

<li>

<a class="function" href="#ProxySession.handle_request_async">handle_request_async</a>

</li>

<li>

<a class="function" href="#ProxySession.close">close</a>

</li>

</ul>

</li>

<li>

<a class="class" href="#GenericSQLVirtualServerModel">GenericSQLVirtualServerModel</a>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.get_hosted_tables">get_hosted_tables</a>

</li>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.table_schema">table_schema</a>

</li>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.table_size">table_size</a>

</li>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.view_column_size">view_column_size</a>

</li>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.table_validate_expression">table_validate_expression</a>

</li>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.view_delete">view_delete</a>

</li>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.table_make_view">table_make_view</a>

</li>

<li>

</li>

<li>

<a class="function" href="#GenericSQLVirtualServerModel.view_schema">view_schema</a>

</li>

<li>

</li>

</ul>

</li>

<li>

<a class="class" href="#VirtualServer">VirtualServer</a>

<li>

<a class="function" href="#VirtualServer.handle_request">handle_request</a>

</li>

</ul>

</li>

<li>

</li>

<li>

</li>

<li>

<a class="function" href="#system_info">system_info</a>

</li>

</ul>

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</a>

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</nav>

perspective </h1>

<div class="docstring">The Python language bindings for <a href="https://perspective-dev.github.io">Perspective</a>, a

high performance data-visualization and analytics component for the web browser.

A simple example which loads an <a href="https://arrow.apache.org/">Apache Arrow</a> and

computes a "Group By" operation, returning a new Arrow.

<pre><code>from perspective import Server

client = Server().new_local_client()

view = table.view(group_by = ["CounterParty", "Security"])

arrow = view.to_arrow()

</code></pre>

</div>

Perspective for Python uses the exact same C++ data engine used by the

<a href="https://docs.rs/perspective-js/latest/perspective_js/">WebAssembly version</a> and

<a href="https://docs.rs/crate/perspective/latest">Rust version</a>. The library consists

of many of the same abstractions and API as in JavaScript, as well as

Python-specific data loading support for <a href="https://numpy.org/">NumPy</a>,

<a href="https://pandas.pydata.org/">Pandas</a> (and

<a href="https://arrow.apache.org/">Apache Arrow</a>, as in JavaScript).

Additionally, <code>perspective-python</code> provides a session manager suitable for

integration into server systems such as

<a href="https://www.tornadoweb.org/en/stable/websocket.html">Tornado websockets</a>,

<a href="https://docs.aiohttp.org/en/stable/web_quickstart.html#websockets">AIOHTTP</a>, or

<a href="https://www.starlette.io/websockets/">Starlette</a>/<a href="https://fastapi.tiangolo.com/advanced/websockets/">FastAPI</a>,

which allows fully _virtual_ Perspective tables to be interacted with by

multiple <code><perspective-viewer></code> in a web browser. You can also interact with a

Perspective table from python clients, and to that end client libraries are

implemented for both Tornado and AIOHTTP.

As <code><perspective-viewer></code> will only consume the data necessary to render the

current screen, this runtime mode allows _ludicrously-sized_ datasets with

instant-load after they've been manifest on the server (at the expense of

network latency on UI interaction).

The included <code>PerspectiveWidget</code> allows running such a viewer in

<a href="https://jupyterlab.readthedocs.io/en/stable/">JupyterLab</a> in either server or

client (via WebAssembly) mode, and the included <code>PerspectiveTornadoHandler</code>

makes it simple to extend a Tornado server with virtual Perspective support.

The <code><a href="">perspective</a></code> module exports several tools:

<ul>

<li><code><a href="#Server">Server</a></code> the constructor for a new isntance of the Perspective data engine.</li>

<li>The <code><a href="perspective/widget.html">perspective.widget</a></code> module exports <code>PerspectiveWidget</code>, the JupyterLab

widget for interactive visualization in a notebook cell.</li>

<li>The <code>perspective.handlers</code> modules exports web frameworks handlers that

interface with a <code>perspective-client</code> in JavaScript.

<ul>

<li><code><a href="perspective/handlers/tornado.html#PerspectiveTornadoHandler">perspective.handlers.tornado.PerspectiveTornadoHandler</a></code> for

<a href="https://www.tornadoweb.org/">Tornado</a></li>

<li><code><a href="perspective/handlers/starlette.html#PerspectiveStarletteHandler">perspective.handlers.starlette.PerspectiveStarletteHandler</a></code> for

<a href="https://www.starlette.io/">Starlette</a> and

<a href="https://fastapi.tiangolo.com">FastAPI</a></li>

<li><code><a href="perspective/handlers/aiohttp.html#PerspectiveAIOHTTPHandler">perspective.handlers.aiohttp.PerspectiveAIOHTTPHandler</a></code> for

<a href="https://docs.aiohttp.org">AIOHTTP</a>,</li>

</ul></li>

</ul>

This user's guide provides an overview of the most common ways to use

Perspective in Python: the <code><a href="#Table">Table</a></code> API, the JupyterLab widget, and the Tornado

handler.

<a href="https://github.com/perspective-dev/perspective/tree/master/examples">More Examples</a> are

available on GitHub.

<h2 id="installation">Installation</h2>

<code>perspective-python</code> contains full bindings to the Perspective API, a JupyterLab

widget, and a WebSocket handlers for several webserver libraries that allow you

to host Perspective using server-side Python.

<code>perspective-python</code> can be installed from <a href="https://pypi.org">PyPI</a> via <code>pip</code>:

<pre><code>pip install perspective-python

</code></pre>

</div>

<h2 id="quick-start">Quick Start</h2>

A <code><a href="#Table">Table</a></code> can be created from a dataset or a schema, the specifics of which are

<a href="#loading-data-with-table">discussed</a> in the JavaScript section of the user's

guide. In Python, however, Perspective supports additional data types that are

commonly used when processing data:

<ul>

<li><code>pandas.DataFrame</code></li>

<li><code>polars.DataFrame</code></li>

<li><code>bytes</code> (encoding an Apache Arrow)</li>

<li><code>objects</code> (either extracting a repr or via reference)</li>

<li><code>str</code> (encoding as a CSV)</li>

</ul>

A <code><a href="#Table">Table</a></code> is created in a similar fashion to its JavaScript equivalent:

<pre><code>from datetime import date, datetime

import numpy as np

import pandas as pd

import perspective

data = pd.DataFrame({

"int": np.arange(100),

"float": [i * 1.5 for i in range(100)],

"bool": [True for i in range(100)],

"date": [date.today() for i in range(100)],

"datetime": [datetime.now() for i in range(100)],

"string": [str(i) for i in range(100)]

})

table = perspective.table(data, index="float")

</code></pre>

</div>

Likewise, a <code><a href="#View">View</a></code> can be created via the <code>view()</code> method:

<pre><code>view = table.view(group_by=["float"], filter=[["bool", "==", True]])

column_data = view.to_columns()

row_data = view.to_json()

</code></pre>

</div>

<h4 id="pandas-and-polars-support">Pandas and Polars Support</h4>

Perspective's <code><a href="#Table">Table</a></code> can be constructed from <code>pandas.DataFrame</code> and

<code>polars.DataFrame</code> objects. Internally, this just uses

<a href="https://arrow.apache.org/docs/python/pandas.html"><code>pyarrow::from_pandas</code></a>,

which dictates behavior of this feature including type support.

If the dataframe does not have an index set, an integer-typed column named

<code>"index"</code> is created. If you want to preserve the indexing behavior of the

dataframe passed into Perspective, simply create the <code><a href="#Table">Table</a></code> with

<code>index="index"</code> as a keyword argument. This tells Perspective to once again

treat the index as a primary key:

<pre><code>data.set_index("datetime")

</code></pre>

</div>

<h4 id="time-zone-handling">Time Zone Handling</h4>

When parsing <code>"datetime"</code> strings, times are assumed _local time_ unless an

explicit timezone offset is parsed. All <code>"datetime"</code> columns (regardless of

input time zone) are _output_ to the user as <code>datetime.datetime</code> objects in

_local time_ according to the Python runtime.

This behavior is consistent with Perspective's behavior in JavaScript. For more

details, see this in-depth

<a href="https://github.com/perspective-dev/perspective/pull/867">explanation</a> of

<code>perspective-python</code> semantics around time zone handling.

<h4 id="callbacks-and-events">Callbacks and Events</h4>

<code><a href="#Table">perspective.Table</a></code> allows for <code>on_update</code> and <code>on_delete</code> callbacks to be

set—simply call <code>on_update</code> or <code>on_delete</code> with a reference to a function or a

lambda without any parameters:

<pre><code>def update_callback():

print("Updated!")

# set the update callback

on_update_id = view.on_update(update_callback)

def delete_callback():

print("Deleted!")

# set the delete callback

on_delete_id = view.on_delete(delete_callback)

# set a lambda as a callback

view.on_delete(lambda: print("Deleted x2!"))

</code></pre>

</div>

If the callback is a named reference to a function, it can be removed with

<code>remove_update</code> or <code>remove_delete</code>:

<pre><code>view.remove_update(on_update_id)

view.remove_delete(on_delete_id)

</code></pre>

</div>

Callbacks defined with a lambda function cannot be removed, as lambda functions

have no identifier.

<h3 id="hosting-table-and-view-instances">Hosting <code><a href="#Table">Table</a></code> and <code><a href="#View">View</a></code> instances</h3>

<code><a href="#Server">Server</a></code> "hosts" all <code><a href="#Table">perspective.Table</a></code> and <code><a href="#View">perspective.View</a></code> instances

created by its connected <code><a href="#Client">Client</a></code>s. Hosted tables/views can have their methods

called from other sources than the Python server, i.e. by a <code>perspective-viewer</code>

running in a JavaScript client over the network, interfacing with

<code>perspective-python</code> through the websocket API.

The server has full control of all hosted <code><a href="#Table">Table</a></code> and <code><a href="#View">View</a></code> instances, and can

call any public API method on hosted instances. This makes it extremely easy to

stream data to a hosted <code><a href="#Table">Table</a></code> using <code>.update()</code>:

<pre><code>server = <a href="#Server">perspective.Server</a>()

client = server.new_local_client()

table = client.table(data, name="data_source")

for i in range(10):

# updates continue to propagate automatically

table.update(new_data)

</code></pre>

</div>

The <code>name</code> provided is important, as it enables Perspective in JavaScript to

look up a <code><a href="#Table">Table</a></code> and get a handle to it over the network. Otherwise, <code>name</code>

will be assigned randomlu and the <code><a href="#Client">Client</a></code> must look this up with

<code>CLient.get_hosted_table_names()</code>

<h3 id="clientserver-replicated-mode">Client/Server Replicated Mode</h3>

Using Tornado and

<a href="python.md#perspectivetornadohandler"><code>PerspectiveTornadoHandler</code></a>, as well as

<code>Perspective</code>'s JavaScript library, we can set up "distributed" Perspective

instances that allows multiple browser <code>perspective-viewer</code> clients to read from

a common <code>perspective-python</code> server, as in the

<a href="https://github.com/perspective-dev/perspective/tree/master/examples/python-tornado">Tornado Example Project</a>.

This architecture works by maintaining two <code>Tables</code>—one on the server, and one

on the client that mirrors the server's <code><a href="#Table">Table</a></code> automatically using <code>on_update</code>.

All updates to the table on the server are automatically applied to each client,

which makes this architecture a natural fit for streaming dashboards and other

distributed use-cases. In conjunction with <a href="#multi-threading">multithreading</a>,

distributed Perspective offers consistently high performance over large numbers

of clients and large datasets.

_*server.py*_

<pre><code>from perspective import Server

from perspective.hadnlers.tornado import PerspectiveTornadoHandler

# Create an instance of Server, and host a Table

SERVER = Server()

CLIENT = SERVER.new_local_client()

# The Table is exposed at `localhost:8888/websocket` with the name `data_source`

client.table(data, name = "data_source")

app = tornado.web.Application([

# create a websocket endpoint that the client JavaScript can access

(r"/websocket", PerspectiveTornadoHandler, {"perspective_server": SERVER})

])

# Start the Tornado server

app.listen(8888)

loop = tornado.ioloop.IOLoop.current()

loop.start()

</code></pre>

</div>

Instead of calling <code>load(server_table)</code>, create a <code><a href="#View">View</a></code> using <code>server_table</code>

and pass that into <code>viewer.load()</code>. This will automatically register an

<code>on_update</code> callback that synchronizes state between the server and the client.

_*index.html*_

// Create a client that expects a Perspective server

// to accept connections at the specified URL.

const websocket = await perspective.websocket(

"ws://localhost:8888/websocket"

);

// Get a handle to the Table on the server

const server_table = await websocket.open_table("data_source_one");

// Create a new view

const server_view = await table.view();

// Create a Table on the client using `perspective.worker()`

const worker = await perspective.worker();

const client_table = await worker.table(view);

// Load the client table in the `<perspective-viewer>`.

document.getElementById("viewer").load(client_table);

</script>

</code></pre>

</div>

For a more complex example that offers distributed editing of the server

dataset, see

<a href="https://github.com/perspective-dev/perspective/blob/master/examples/python-tornado/client_server_editing.html">client_server_editing.html</a>.

We also provide examples for Starlette/FastAPI and AIOHTTP:

<ul>

<li><a href="https://github.com/perspective-dev/perspective/tree/master/examples/python-starlette">Starlette Example Project</a>.</li>

<li><a href="https://github.com/perspective-dev/perspective/tree/master/examples/python-aiohttp">AIOHTTP Example Project</a>.</li>

</ul>

<h3 id="server-only-mode">Server-only Mode</h3>

The server setup is identical to <a href="#distributed-mode">Distributed Mode</a> above,

but instead of creating a view, the client calls <code>load(server_table)</code>: In

Python, use <code><a href="#Server">Server</a></code> and <code>PerspectiveTornadoHandler</code> to create a websocket

server that exposes a <code><a href="#Table">Table</a></code>. In this example, <code>table</code> is a proxy for the

<code><a href="#Table">Table</a></code> we created on the server. All API methods are available on _proxies_,

the.g.us calling <code>view()</code>, <code>schema()</code>, <code>update()</code> on <code>table</code> will pass those

operations to the Python <code><a href="#Table">Table</a></code>, execute the commands, and return the result

back to Javascript.

</code></pre>

</div>

<pre><code>const websocket = perspective.websocket("ws://localhost:8888/websocket");

const table = websocket.open_table("data_source");

document.getElementById("viewer").load(table);

</code></pre>

</div>

<label class="view-source-button" for="mod-perspective-view-source">View Source</label>

<div class="pdoc-code codehilite"><pre><a href="#L-1"> 1</a># ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓

<a href="#L-2"> 2</a># ┃ ██████ ██████ ██████ █ █ █ █ █ █▄ ▀███ █ ┃

<a href="#L-3"> 3</a># ┃ ▄▄▄▄▄█ █▄▄▄▄▄ ▄▄▄▄▄█ ▀▀▀▀▀█▀▀▀▀▀ █ ▀▀▀▀▀█ ████████▌▐███ ███▄ ▀█ █ ▀▀▀▀▀ ┃

<a href="#L-4"> 4</a># ┃ █▀▀▀▀▀ █▀▀▀▀▀ █▀██▀▀ ▄▄▄▄▄ █ ▄▄▄▄▄█ ▄▄▄▄▄█ ████████▌▐███ █████▄ █ ▄▄▄▄▄ ┃

<a href="#L-5"> 5</a># ┃ █ ██████ █ ▀█▄ █ ██████ █ ███▌▐███ ███████▄ █ ┃

<a href="#L-6"> 6</a># ┣━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┫

<a href="#L-8"> 8</a># ┃ ╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌ ┃

<a href="#L-9"> 9</a># ┃ This file is part of the Perspective library, distributed under the terms ┃

<a href="#L-10"> 10</a># ┃ of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). ┃

<a href="#L-11"> 11</a># ┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛

<a href="#L-13"> 13</a>__version__ = "4.2.0"

<a href="#L-14"> 14</a>__all__ = [

<a href="#L-15"> 15</a> "_jupyter_labextension_paths",

<a href="#L-16"> 16</a> "Server",

<a href="#L-17"> 17</a> "Client",

<a href="#L-18"> 18</a> "Table",

<a href="#L-19"> 19</a> "View",

<a href="#L-20"> 20</a> "PerspectiveError",

<a href="#L-21"> 21</a> "ProxySession",

<a href="#L-22"> 22</a> "AsyncClient",

<a href="#L-23"> 23</a> "AsyncServer",

<a href="#L-24"> 24</a> "GenericSQLVirtualServerModel",

<a href="#L-25"> 25</a> "VirtualServer",

<a href="#L-26"> 26</a> "num_cpus",

<a href="#L-27"> 27</a> "set_num_cpus",

<a href="#L-28"> 28</a> "system_info",

<a href="#L-29"> 29</a>]

<a href="#L-31"> 31</a>__doc__ = """

<a href="#L-32"> 32</a>The Python language bindings for [Perspective](https://perspective-dev.github.io), a

<a href="#L-33"> 33</a>high performance data-visualization and analytics component for the web browser.

<a href="#L-35"> 35</a>A simple example which loads an [Apache Arrow](https://arrow.apache.org/) and

<a href="#L-36"> 36</a>computes a "Group By" operation, returning a new Arrow.

<a href="#L-38"> 38</a>```python

<a href="#L-39"> 39</a>from perspective import Server

<a href="#L-41"> 41</a>client = Server().new_local_client()

<a href="#L-42"> 42</a>table = client.table(arrow_bytes_data)

<a href="#L-43"> 43</a>view = table.view(group_by = ["CounterParty", "Security"])

<a href="#L-44"> 44</a>arrow = view.to_arrow()

<a href="#L-45"> 45</a>```

<a href="#L-47"> 47</a>Perspective for Python uses the exact same C++ data engine used by the

<a href="#L-48"> 48</a>[WebAssembly version](https://docs.rs/perspective-js/latest/perspective_js/) and

<a href="#L-49"> 49</a>[Rust version](https://docs.rs/crate/perspective/latest). The library consists

<a href="#L-50"> 50</a>of many of the same abstractions and API as in JavaScript, as well as

<a href="#L-51"> 51</a>Python-specific data loading support for [NumPy](https://numpy.org/),

<a href="#L-52"> 52</a>[Pandas](https://pandas.pydata.org/) (and

<a href="#L-53"> 53</a>[Apache Arrow](https://arrow.apache.org/), as in JavaScript).

<a href="#L-55"> 55</a>Additionally, `perspective-python` provides a session manager suitable for

<a href="#L-56"> 56</a>integration into server systems such as

<a href="#L-57"> 57</a>[Tornado websockets](https://www.tornadoweb.org/en/stable/websocket.html),

<a href="#L-58"> 58</a>[AIOHTTP](https://docs.aiohttp.org/en/stable/web_quickstart.html#websockets), or

<a href="#L-59"> 59</a>[Starlette](https://www.starlette.io/websockets/)/[FastAPI](https://fastapi.tiangolo.com/advanced/websockets/),

<a href="#L-60"> 60</a>which allows fully _virtual_ Perspective tables to be interacted with by

<a href="#L-61"> 61</a>multiple `<perspective-viewer>` in a web browser. You can also interact with a

<a href="#L-62"> 62</a>Perspective table from python clients, and to that end client libraries are

<a href="#L-63"> 63</a>implemented for both Tornado and AIOHTTP.

<a href="#L-65"> 65</a>As `<perspective-viewer>` will only consume the data necessary to render the

<a href="#L-66"> 66</a>current screen, this runtime mode allows _ludicrously-sized_ datasets with

<a href="#L-67"> 67</a>instant-load after they've been manifest on the server (at the expense of

<a href="#L-68"> 68</a>network latency on UI interaction).

<a href="#L-70"> 70</a>The included `PerspectiveWidget` allows running such a viewer in

<a href="#L-71"> 71</a>[JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) in either server or

<a href="#L-72"> 72</a>client (via WebAssembly) mode, and the included `PerspectiveTornadoHandler`

<a href="#L-73"> 73</a>makes it simple to extend a Tornado server with virtual Perspective support.

<a href="#L-75"> 75</a>The `perspective` module exports several tools:

<a href="#L-77"> 77</a>- `Server` the constructor for a new isntance of the Perspective data engine.

<a href="#L-78"> 78</a>- The `perspective.widget` module exports `PerspectiveWidget`, the JupyterLab

<a href="#L-79"> 79</a> widget for interactive visualization in a notebook cell.

<a href="#L-80"> 80</a>- The `perspective.handlers` modules exports web frameworks handlers that

<a href="#L-81"> 81</a> interface with a `perspective-client` in JavaScript.

<a href="#L-82"> 82</a> - `perspective.handlers.tornado.PerspectiveTornadoHandler` for

<a href="#L-83"> 83</a> [Tornado](https://www.tornadoweb.org/)

<a href="#L-84"> 84</a> - `perspective.handlers.starlette.PerspectiveStarletteHandler` for

<a href="#L-85"> 85</a> [Starlette](https://www.starlette.io/) and

<a href="#L-86"> 86</a> [FastAPI](https://fastapi.tiangolo.com)

<a href="#L-87"> 87</a> - `perspective.handlers.aiohttp.PerspectiveAIOHTTPHandler` for

<a href="#L-88"> 88</a> [AIOHTTP](https://docs.aiohttp.org),

<a href="#L-90"> 90</a>This user's guide provides an overview of the most common ways to use

<a href="#L-91"> 91</a>Perspective in Python: the `Table` API, the JupyterLab widget, and the Tornado

<a href="#L-92"> 92</a>handler.

<a href="#L-94"> 94</a>[More Examples](https://github.com/perspective-dev/perspective/tree/master/examples) are

<a href="#L-95"> 95</a>available on GitHub.

<a href="#L-97"> 97</a>## Installation

<a href="#L-99"> 99</a>`perspective-python` contains full bindings to the Perspective API, a JupyterLab

<a href="#L-100">100</a>widget, and a WebSocket handlers for several webserver libraries that allow you

<a href="#L-101">101</a>to host Perspective using server-side Python.

<a href="#L-103">103</a>`perspective-python` can be installed from [PyPI](https://pypi.org) via `pip`:

<a href="#L-105">105</a>```bash

<a href="#L-106">106</a>pip install perspective-python

<a href="#L-107">107</a>```

<a href="#L-109">109</a>## Quick Start

<a href="#L-111">111</a>A `Table` can be created from a dataset or a schema, the specifics of which are

<a href="#L-112">112</a>[discussed](#loading-data-with-table) in the JavaScript section of the user's

<a href="#L-113">113</a>guide. In Python, however, Perspective supports additional data types that are

<a href="#L-114">114</a>commonly used when processing data:

<a href="#L-116">116</a>- `pandas.DataFrame`

<a href="#L-117">117</a>- `polars.DataFrame`

<a href="#L-118">118</a>- `bytes` (encoding an Apache Arrow)

<a href="#L-119">119</a>- `objects` (either extracting a repr or via reference)

<a href="#L-120">120</a>- `str` (encoding as a CSV)

<a href="#L-122">122</a>A `Table` is created in a similar fashion to its JavaScript equivalent:

<a href="#L-124">124</a>```python

<a href="#L-125">125</a>from datetime import date, datetime

<a href="#L-126">126</a>import numpy as np

<a href="#L-127">127</a>import pandas as pd

<a href="#L-128">128</a>import perspective

<a href="#L-130">130</a>data = pd.DataFrame({

<a href="#L-131">131</a> "int": np.arange(100),

<a href="#L-132">132</a> "float": [i * 1.5 for i in range(100)],

<a href="#L-133">133</a> "bool": [True for i in range(100)],

<a href="#L-134">134</a> "date": [date.today() for i in range(100)],

<a href="#L-135">135</a> "datetime": [datetime.now() for i in range(100)],

<a href="#L-136">136</a> "string": [str(i) for i in range(100)]

<a href="#L-137">137</a>})

<a href="#L-139">139</a>table = perspective.table(data, index="float")

<a href="#L-140">140</a>```

<a href="#L-142">142</a>Likewise, a `View` can be created via the `view()` method:

<a href="#L-144">144</a>```python

<a href="#L-145">145</a>view = table.view(group_by=["float"], filter=[["bool", "==", True]])

<a href="#L-146">146</a>column_data = view.to_columns()

<a href="#L-147">147</a>row_data = view.to_json()

<a href="#L-148">148</a>```

<a href="#L-150">150</a>#### Pandas and Polars Support

<a href="#L-152">152</a>Perspective's `Table` can be constructed from `pandas.DataFrame` and

<a href="#L-153">153</a>`polars.DataFrame` objects. Internally, this just uses

<a href="#L-154">154</a>[`pyarrow::from_pandas`](https://arrow.apache.org/docs/python/pandas.html),

<a href="#L-155">155</a>which dictates behavior of this feature including type support.

<a href="#L-157">157</a>If the dataframe does not have an index set, an integer-typed column named

<a href="#L-158">158</a>`"index"` is created. If you want to preserve the indexing behavior of the

<a href="#L-159">159</a>dataframe passed into Perspective, simply create the `Table` with

<a href="#L-160">160</a>`index="index"` as a keyword argument. This tells Perspective to once again

<a href="#L-161">161</a>treat the index as a primary key:

<a href="#L-163">163</a>```python

<a href="#L-164">164</a>data.set_index("datetime")

<a href="#L-165">165</a>table = perspective.table(data, index="index")

<a href="#L-166">166</a>```

<a href="#L-168">168</a>#### Time Zone Handling

<a href="#L-170">170</a>When parsing `"datetime"` strings, times are assumed _local time_ unless an

<a href="#L-171">171</a>explicit timezone offset is parsed. All `"datetime"` columns (regardless of

<a href="#L-172">172</a>input time zone) are _output_ to the user as `datetime.datetime` objects in

<a href="#L-173">173</a>_local time_ according to the Python runtime.

<a href="#L-175">175</a>This behavior is consistent with Perspective's behavior in JavaScript. For more

<a href="#L-176">176</a>details, see this in-depth

<a href="#L-177">177</a>[explanation](https://github.com/perspective-dev/perspective/pull/867) of

<a href="#L-178">178</a>`perspective-python` semantics around time zone handling.

<a href="#L-180">180</a>#### Callbacks and Events

<a href="#L-182">182</a>`perspective.Table` allows for `on_update` and `on_delete` callbacks to be

<a href="#L-183">183</a>set—simply call `on_update` or `on_delete` with a reference to a function or a

<a href="#L-184">184</a>lambda without any parameters:

<a href="#L-186">186</a>```python

<a href="#L-187">187</a>def update_callback():

<a href="#L-188">188</a> print("Updated!")

<a href="#L-190">190</a># set the update callback

<a href="#L-191">191</a>on_update_id = view.on_update(update_callback)

<a href="#L-194">194</a>def delete_callback():

<a href="#L-195">195</a> print("Deleted!")

<a href="#L-197">197</a># set the delete callback

<a href="#L-198">198</a>on_delete_id = view.on_delete(delete_callback)

<a href="#L-200">200</a># set a lambda as a callback

<a href="#L-201">201</a>view.on_delete(lambda: print("Deleted x2!"))

<a href="#L-202">202</a>```

<a href="#L-204">204</a>If the callback is a named reference to a function, it can be removed with

<a href="#L-205">205</a>`remove_update` or `remove_delete`:

<a href="#L-207">207</a>```python

<a href="#L-208">208</a>view.remove_update(on_update_id)

<a href="#L-209">209</a>view.remove_delete(on_delete_id)

<a href="#L-210">210</a>```

<a href="#L-212">212</a>Callbacks defined with a lambda function cannot be removed, as lambda functions

<a href="#L-213">213</a>have no identifier.

<a href="#L-215">215</a>### Hosting `Table` and `View` instances

<a href="#L-217">217</a>`Server` "hosts" all `perspective.Table` and `perspective.View` instances

<a href="#L-218">218</a>created by its connected `Client`s. Hosted tables/views can have their methods

<a href="#L-219">219</a>called from other sources than the Python server, i.e. by a `perspective-viewer`

<a href="#L-220">220</a>running in a JavaScript client over the network, interfacing with

<a href="#L-221">221</a>`perspective-python` through the websocket API.

<a href="#L-223">223</a>The server has full control of all hosted `Table` and `View` instances, and can

<a href="#L-224">224</a>call any public API method on hosted instances. This makes it extremely easy to

<a href="#L-225">225</a>stream data to a hosted `Table` using `.update()`:

<a href="#L-227">227</a>```python

<a href="#L-228">228</a>server = perspective.Server()

<a href="#L-229">229</a>client = server.new_local_client()

<a href="#L-230">230</a>table = client.table(data, name="data_source")

<a href="#L-232">232</a>for i in range(10):

<a href="#L-233">233</a> # updates continue to propagate automatically

<a href="#L-234">234</a> table.update(new_data)

<a href="#L-235">235</a>```

<a href="#L-237">237</a>The `name` provided is important, as it enables Perspective in JavaScript to

<a href="#L-238">238</a>look up a `Table` and get a handle to it over the network. Otherwise, `name`

<a href="#L-239">239</a>will be assigned randomlu and the `Client` must look this up with

<a href="#L-240">240</a>`CLient.get_hosted_table_names()`

<a href="#L-242">242</a>### Client/Server Replicated Mode

<a href="#L-244">244</a>Using Tornado and

<a href="#L-245">245</a>[`PerspectiveTornadoHandler`](python.md#perspectivetornadohandler), as well as

<a href="#L-246">246</a>`Perspective`'s JavaScript library, we can set up "distributed" Perspective

<a href="#L-247">247</a>instances that allows multiple browser `perspective-viewer` clients to read from

<a href="#L-248">248</a>a common `perspective-python` server, as in the

<a href="#L-249">249</a>[Tornado Example Project](https://github.com/perspective-dev/perspective/tree/master/examples/python-tornado).

<a href="#L-251">251</a>This architecture works by maintaining two `Tables`—one on the server, and one

<a href="#L-252">252</a>on the client that mirrors the server's `Table` automatically using `on_update`.

<a href="#L-253">253</a>All updates to the table on the server are automatically applied to each client,

<a href="#L-254">254</a>which makes this architecture a natural fit for streaming dashboards and other

<a href="#L-255">255</a>distributed use-cases. In conjunction with [multithreading](#multi-threading),

<a href="#L-256">256</a>distributed Perspective offers consistently high performance over large numbers

<a href="#L-257">257</a>of clients and large datasets.

<a href="#L-259">259</a>_*server.py*_

<a href="#L-261">261</a>```python

<a href="#L-262">262</a>from perspective import Server

<a href="#L-263">263</a>from perspective.hadnlers.tornado import PerspectiveTornadoHandler

<a href="#L-265">265</a># Create an instance of Server, and host a Table

<a href="#L-266">266</a>SERVER = Server()

<a href="#L-267">267</a>CLIENT = SERVER.new_local_client()

<a href="#L-269">269</a># The Table is exposed at `localhost:8888/websocket` with the name `data_source`

<a href="#L-270">270</a>client.table(data, name = "data_source")

<a href="#L-272">272</a>app = tornado.web.Application([

<a href="#L-273">273</a> # create a websocket endpoint that the client JavaScript can access

<a href="#L-274">274</a> (r"/websocket", PerspectiveTornadoHandler, {"perspective_server": SERVER})

<a href="#L-275">275</a>])

<a href="#L-277">277</a># Start the Tornado server

<a href="#L-278">278</a>app.listen(8888)

<a href="#L-279">279</a>loop = tornado.ioloop.IOLoop.current()

<a href="#L-280">280</a>loop.start()

<a href="#L-281">281</a>```

<a href="#L-283">283</a>Instead of calling `load(server_table)`, create a `View` using `server_table`

<a href="#L-284">284</a>and pass that into `viewer.load()`. This will automatically register an

<a href="#L-285">285</a>`on_update` callback that synchronizes state between the server and the client.

<a href="#L-287">287</a>_*index.html*_

<a href="#L-289">289</a>```html

<a href="#L-293">293</a> // Create a client that expects a Perspective server

<a href="#L-294">294</a> // to accept connections at the specified URL.

<a href="#L-295">295</a> const websocket = await perspective.websocket(

<a href="#L-296">296</a> "ws://localhost:8888/websocket"

<a href="#L-297">297</a> );

<a href="#L-299">299</a> // Get a handle to the Table on the server

<a href="#L-300">300</a> const server_table = await websocket.open_table("data_source_one");

<a href="#L-302">302</a> // Create a new view

<a href="#L-303">303</a> const server_view = await table.view();

<a href="#L-305">305</a> // Create a Table on the client using `perspective.worker()`

<a href="#L-306">306</a> const worker = await perspective.worker();

<a href="#L-307">307</a> const client_table = await worker.table(view);

<a href="#L-309">309</a> // Load the client table in the `<perspective-viewer>`.

<a href="#L-310">310</a> document.getElementById("viewer").load(client_table);

<a href="#L-312">312</a>```

<a href="#L-314">314</a>For a more complex example that offers distributed editing of the server

<a href="#L-315">315</a>dataset, see

<a href="#L-316">316</a>[client_server_editing.html](https://github.com/perspective-dev/perspective/blob/master/examples/python-tornado/client_server_editing.html).

<a href="#L-318">318</a>We also provide examples for Starlette/FastAPI and AIOHTTP:

<a href="#L-320">320</a>- [Starlette Example Project](https://github.com/perspective-dev/perspective/tree/master/examples/python-starlette).

<a href="#L-321">321</a>- [AIOHTTP Example Project](https://github.com/perspective-dev/perspective/tree/master/examples/python-aiohttp).

<a href="#L-323">323</a>### Server-only Mode

<a href="#L-325">325</a>The server setup is identical to [Distributed Mode](#distributed-mode) above,

<a href="#L-326">326</a>but instead of creating a view, the client calls `load(server_table)`: In

<a href="#L-327">327</a>Python, use `Server` and `PerspectiveTornadoHandler` to create a websocket

<a href="#L-328">328</a>server that exposes a `Table`. In this example, `table` is a proxy for the

<a href="#L-329">329</a>`Table` we created on the server. All API methods are available on _proxies_,

<a href="#L-330">330</a>the.g.us calling `view()`, `schema()`, `update()` on `table` will pass those

<a href="#L-331">331</a>operations to the Python `Table`, execute the commands, and return the result

<a href="#L-332">332</a>back to Javascript.

<a href="#L-334">334</a>```html

<a href="#L-336">336</a>```

<a href="#L-338">338</a>```javascript

<a href="#L-339">339</a>const websocket = perspective.websocket("ws://localhost:8888/websocket");

<a href="#L-340">340</a>const table = websocket.open_table("data_source");

<a href="#L-341">341</a>document.getElementById("viewer").load(table);

<a href="#L-342">342</a>```

<a href="#L-344">344</a>"""

<a href="#L-347">347</a>import functools

<a href="#L-349">349</a>from .perspective import (

<a href="#L-350">350</a> Client,

<a href="#L-351">351</a> PerspectiveError,

<a href="#L-352">352</a> ProxySession,

<a href="#L-353">353</a> Server,

<a href="#L-354">354</a> AsyncServer,

<a href="#L-355">355</a> AsyncClient,

<a href="#L-356">356</a> VirtualServer,

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