perspective-client 5.2.0

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// ┃ Copyright (c) 2017, the Perspective Authors.                              ┃
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// ┃ This file is part of the Perspective library, distributed under the terms ┃
// ┃ of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). ┃
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use std::borrow::Cow;

use indexmap::IndexMap;
use serde::{Deserialize, Serialize};
use ts_rs::TS;

use crate::config::{GroupRollupMode, SplitRollupMode};
use crate::proto::get_features_resp::{AggregateArgs, AggregateOptions, ColumnTypeOptions};
use crate::proto::{ColumnType, GetFeaturesResp, WindowAggregateArgs};

/// Describes the capabilities supported by a virtual server handler.
///
/// This struct is returned by
/// [`VirtualServerHandler::get_features`](super::VirtualServerHandler::get_features)
/// to inform clients about which operations are available.
#[derive(Clone, Debug, Default, Deserialize, PartialEq, Serialize, TS)]
pub struct Features<'a> {
    /// Whether group-by aggregation is supported.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub group_by: bool,

    /// Which `group_by_rollup_mode` options are supported
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub group_rollup_mode: Vec<GroupRollupMode>,

    /// Whether split-by (pivot) operations are supported.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub split_by: bool,

    /// Which `split_rollup_mode` options are supported. Empty (the default)
    /// means `["flat"]` - a server must opt in to `"rollup"` explicitly, as
    /// it requires emitting subtotal and grand-total column groups.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub split_rollup_mode: Vec<SplitRollupMode>,

    /// Available filter operators per column type.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub filter_ops: IndexMap<ColumnType, Vec<Cow<'a, str>>>,

    /// Available aggregate functions per column type.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub aggregates: IndexMap<ColumnType, Vec<AggSpec<'a>>>,

    /// Whether sorting is supported.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub sort: bool,

    /// Whether computed expressions are supported.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub expressions: bool,

    /// Available window aggregates per column type.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub window_aggregates: IndexMap<ColumnType, Vec<WindowAggSpec<'a>>>,

    /// Whether update callbacks are supported.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub on_update: bool,

    /// The data store has no reliable natural row order
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub unordered: bool,
}

/// Specification for a window aggregate.
#[derive(Clone, Debug, Deserialize, PartialEq, Serialize, TS)]
pub struct WindowAggSpec<'a> {
    pub name: Cow<'a, str>,

    /// Frame kinds this aggregate accepts (`rows`, `range`, `cumulative`).
    /// Empty means it takes no frame at all.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub frames: Vec<Cow<'a, str>>,

    /// Takes a row offset, as `lag` / `lead` / `diff` do.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub offset: bool,

    /// Takes a smoothing factor, as `ema` does.
    #[serde(default)]
    #[ts(optional, as = "Option<_>")]
    pub alpha: bool,

    /// The output column type. `None` means the source column's type, which
    /// is what `min` / `max` / `lag` do.
    #[serde(default)]
    #[serde(skip_serializing_if = "Option::is_none")]
    #[ts(optional)]
    pub result_type: Option<ColumnType>,
}

impl<'a> From<&'a str> for WindowAggSpec<'a> {
    /// A bare name, taking no frame and no arguments.
    fn from(name: &'a str) -> Self {
        WindowAggSpec {
            name: Cow::Borrowed(name),
            frames: vec![],
            offset: false,
            alpha: false,
            result_type: None,
        }
    }
}

/// Specification for an aggregate function.
///
/// Aggregates can either take no additional arguments ([`AggSpec::Single`])
/// or require column type arguments ([`AggSpec::Multiple`]).
#[derive(Clone, Debug, Deserialize, PartialEq, Serialize, TS)]
#[serde(untagged)]
pub enum AggSpec<'a> {
    /// An aggregate function with no additional arguments.
    Single(Cow<'a, str>),
    /// An aggregate function that requires column type arguments.
    Multiple(Cow<'a, str>, Vec<ColumnType>),
}

impl<'a> From<Features<'a>> for GetFeaturesResp {
    fn from(value: Features<'a>) -> GetFeaturesResp {
        GetFeaturesResp {
            group_by: value.group_by,
            group_rollup_mode: value
                .group_rollup_mode
                .iter()
                .map(|x| crate::proto::GroupRollupMode::from(*x) as i32)
                .collect(),
            split_rollup_mode: value
                .split_rollup_mode
                .iter()
                .map(|x| crate::proto::SplitRollupMode::from(*x) as i32)
                .collect(),
            split_by: value.split_by,
            expressions: value.expressions,
            on_update: value.on_update,
            sort: value.sort,
            unordered: value.unordered,
            window_aggregates: value
                .window_aggregates
                .iter()
                .map(|(ty, aggs)| {
                    (
                        *ty as u32,
                        crate::proto::get_features_resp::WindowAggregateOptions {
                            options: aggs
                                .iter()
                                .map(|x| WindowAggregateArgs {
                                    name: x.name.to_string(),
                                    frames: x.frames.iter().map(|f| f.to_string()).collect(),
                                    offset: x.offset,
                                    alpha: x.alpha,
                                    result_type: x.result_type.map(|t| t as i32),
                                })
                                .collect(),
                        },
                    )
                })
                .collect(),
            aggregates: value
                .aggregates
                .iter()
                .map(|(dtype, aggs)| {
                    (*dtype as u32, AggregateOptions {
                        aggregates: aggs
                            .iter()
                            .map(|agg| match agg {
                                AggSpec::Single(cow) => AggregateArgs {
                                    name: cow.to_string(),
                                    args: vec![],
                                },
                                AggSpec::Multiple(cow, column_types) => AggregateArgs {
                                    name: cow.to_string(),
                                    args: column_types.iter().map(|x| *x as i32).collect(),
                                },
                            })
                            .collect(),
                    })
                })
                .collect(),
            filter_ops: value
                .filter_ops
                .iter()
                .map(|(ty, options)| {
                    (*ty as u32, ColumnTypeOptions {
                        options: options.iter().map(|x| (*x).to_string()).collect(),
                    })
                })
                .collect(),
        }
    }
}