Struct Client

pub struct Client(/* private fields */);

An instance of a Client is a connection to a single [Server], whether locally in-memory or remote over some transport like a WebSocket.

Client and Perspective objects derived from it have synchronous APIs, suitable for use in a repl or script context where this is the only Client connected to its [Server]. If you want to integrate with a Web framework or otherwise connect multiple clients, use [AsyncClient].

Implementations

impl Client

pub fn new( handle_request: Py<PyAny>, close_cb: Option<Py<PyAny>>, name: Option<String>, ) -> PyResult<Self>

pub fn from_server(py: Python<'_>, server: Py<Server>) -> PyResult<Self>

Create a new Client instance bound to a specific in-process [Server] (e.g. generally not the global [Server]).

pub fn handle_response( &self, py: Python<'_>, response: Py<PyBytes>, ) -> PyResult<bool>

Handle a message from the external message queue. Client::handle_response is part of the low-level message-handling API necessary to implement new transports for a Client connection to a local-or-remote [Server], and doesn’t generally need to be called directly by “users” of a Client once connected.

pub fn table( &self, py: Python<'_>, input: Py<PyAny>, limit: Option<u32>, index: Option<Py<PyString>>, name: Option<Py<PyString>>, format: Option<Py<PyString>>, ) -> PyResult<Table>

Creates a new Table from either a schema or data.

The Client::table factory function can be initialized with either a schema (see Table::schema), or data in one of these formats:

• Apache Arrow
• CSV
• JSON row-oriented
• JSON column-oriented
• NDJSON

When instantiated with data, the schema is inferred from this data. While this is convenient, inferrence is sometimes imperfect e.g. when the input is empty, null or ambiguous. For these cases, Client::table can first be instantiated with a explicit schema.

When instantiated with a schema, the resulting Table is empty but with known column names and column types. When subsqeuently populated with Table::update, these columns will be coerced to the schema’s type. This behavior can be useful when Client::table’s column type inferences doesn’t work.

The resulting Table is virtual, and invoking its methods dispatches events to the perspective_server::Server this Client connects to, where the data is stored and all calculation occurs.

Arguments

• arg - Either schema or initialization data.
• options - Optional configuration which provides one of:
  • limit - The max number of rows the resulting Table can store.
  • index - The column name to use as an index column. If this Table is being instantiated by data, this column name must be present in the data.
  • name - The name of the table. This will be generated if it is not provided.
  • format - The explicit format of the input data, can be one of "json", "columns", "csv" or "arrow". This overrides language-specific type dispatch behavior, which allows stringified and byte array alternative inputs.

Python Examples

Load a CSV from a str:

table = client.table("x,y\n1,2\n3,4")

pub fn open_table(&self, py: Python<'_>, name: String) -> PyResult<Table>

Opens a Table that is hosted on the perspective_server::Server that is connected to this Client.

The name property of TableInitOptions is used to identify each Table. Table names can be looked up for each Client via Client::get_hosted_table_names.

Python Examples

table =  client.open_table("table_one");

pub fn get_hosted_table_names(&self, py: Python<'_>) -> PyResult<Vec<String>>

Retrieves the names of all tables that this client has access to.

name is a string identifier unique to the Table (per Client), which can be used in conjunction with Client::open_table to get a Table instance without the use of Client::table constructor directly (e.g., one created by another Client).

Python Examples

tables = client.get_hosted_table_names();

pub fn on_hosted_tables_update( &self, py: Python<'_>, callback: Py<PyAny>, ) -> PyResult<u32>

Register a callback which is invoked whenever Client::table (on this Client) or Table::delete (on a Table belinging to this Client) are called.

pub fn remove_hosted_tables_update( &self, py: Python<'_>, callback_id: u32, ) -> PyResult<()>

Remove a callback previously registered via Client::on_hosted_tables_update.

pub fn terminate(&self, py: Python<'_>) -> PyResult<()>

Terminates this Client, cleaning up any View handles the Client has open as well as its callbacks.

Trait Implementations

impl<'py> IntoPyObject<'py> for Client

type Target = Client

The Python output type

type Output = Bound<'py, <Client as IntoPyObject<'py>>::Target>

The smart pointer type to use.

type Error = PyErr

The type returned in the event of a conversion error.

fn into_pyobject( self, py: Python<'py>, ) -> Result<<Self as IntoPyObject<'_>>::Output, <Self as IntoPyObject<'_>>::Error>

Performs the conversion.

impl PyClass for Client

type Frozen = False

Whether the pyclass is frozen.

impl PyClassBaseType for Client

type LayoutAsBase = PyClassObject<Client>

type BaseNativeType = <Client as PyClassImpl>::BaseNativeType

type Initializer = PyClassInitializer<Client>

type PyClassMutability = <Client as PyClassImpl>::PyClassMutability

impl PyClassImpl for Client

const IS_BASETYPE: bool = true

#[pyclass(subclass)]

const IS_SUBCLASS: bool = false

#[pyclass(extends=…)]

const IS_MAPPING: bool = false

#[pyclass(mapping)]

const IS_SEQUENCE: bool = false

#[pyclass(sequence)]

const IS_IMMUTABLE_TYPE: bool = false

#[pyclass(immutable_type)]

type BaseType = PyAny

Base class

type ThreadChecker = SendablePyClass<Client>

This handles following two situations:

type PyClassMutability = <<PyAny as PyClassBaseType>::PyClassMutability as PyClassMutability>::MutableChild

Immutable or mutable

type Dict = PyClassDummySlot

Specify this class has #[pyclass(dict)] or not.

type WeakRef = PyClassDummySlot

Specify this class has #[pyclass(weakref)] or not.

type BaseNativeType = PyAny

The closest native ancestor. This is PyAny by default, and when you declare #[pyclass(extends=PyDict)], it’s PyDict.

fn items_iter() -> PyClassItemsIter

fn doc(py: Python<'_>) -> PyResult<&'static CStr>

Rendered class doc

fn lazy_type_object() -> &'static LazyTypeObject<Self>

fn dict_offset() -> Option<isize>

fn weaklist_offset() -> Option<isize>

impl PyClassNewTextSignature<Client> for PyClassImplCollector<Client>

fn new_text_signature(self) -> Option<&'static str>

impl<'a, 'py> PyFunctionArgument<'a, 'py, false> for &'a Client

type Holder = Option<PyRef<'py, Client>>

fn extract( obj: &'a Bound<'py, PyAny>, holder: &'a mut Self::Holder, ) -> PyResult<Self>

impl<'a, 'py> PyFunctionArgument<'a, 'py, false> for &'a mut Client

type Holder = Option<PyRefMut<'py, Client>>

fn extract( obj: &'a Bound<'py, PyAny>, holder: &'a mut Self::Holder, ) -> PyResult<Self>

impl PyMethods<Client> for PyClassImplCollector<Client>

fn py_methods(self) -> &'static PyClassItems

impl PyTypeInfo for Client

const NAME: &'static str = "Client"

Class name.

const MODULE: Option<&'static str>

Module name, if any.

fn type_object_raw(py: Python<'_>) -> *mut PyTypeObject

Returns the PyTypeObject instance for this type.

fn type_object(py: Python<'_>) -> Bound<'_, PyType>

Returns the safe abstraction over the type object.

fn is_type_of(object: &Bound<'_, PyAny>) -> bool

Checks if object is an instance of this type or a subclass of this type.

fn is_exact_type_of(object: &Bound<'_, PyAny>) -> bool

Checks if object is an instance of this type.

impl DerefToPyAny for Client