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@uwdata/flechette

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@uwdata/flechette - npm Package Compare versions

Comparing version 1.0.2 to 1.1.0

2

dist/flechette.min.js

@@ -1,2 +0,2 @@

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function(t,e){return t.addObject(1,(t=>{t.addInt16(0,e.unit,u.MILLISECOND)}))}(t,e);case i.FixedSizeBinary:case i.FixedSizeList:return function(t,e){return t.addObject(1,(t=>{t.addInt32(0,e.stride,0)}))}(t,e);case i.Map:return function(t,e){return t.addObject(1,(t=>{t.addInt8(0,+e.keysSorted,0)}))}(t,e);case i.Union:return function(t,e){const n=t.addVector(e.typeIds,4,4,((t,e)=>t.addInt32(e)));return t.addObject(2,(t=>{t.addInt16(0,e.mode,d.Sparse),t.addOffset(1,n,0)}))}(t,e)}return t.addObject(0)}const En=1===new Uint16Array(new Uint8Array([1,0]).buffer)[0];function Dn(t,e){const{fields:n,metadata:s}=e,r=n.map((e=>An(t,e))),i=t.addOffsetVector(r),a=On(t,s);return t.addObject(4,(t=>{t.addInt16(0,+!En,0),t.addOffset(1,i,0),t.addOffset(2,a,0)}))}function An(t,e){const{name:n,nullable:s,type:r,metadata:a}=e;let{typeId:c}=r,u=0,o=0;if(c!==i.Dictionary)u=Ln(t,r);else{const e=r.dictionary;c=e.typeId,o=Ln(t,r),u=Ln(t,e)}const 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v){case"string":l++;break;case"number":a++,v<y&&(y=v),v>p&&(p=v),Number.isInteger(v)&&c++;break;case"bigint":u++,void 0===t?t=e=v:(v<t&&(t=v),v>e&&(e=v));break;case"boolean":i++;break;case"object":if(v instanceof Date)o++,+v%864e5==0&&d++;else if(L(v)){h++;const t=v.length;t<b&&(b=t),t>I&&(I=t),n??=Jn(),v.forEach(n.add)}else{f++;for(const t in v){(g[t]??(g[t]=Jn())).add(v[t])}}}else r++},type(){const v=s-r;return 0===v?z():c===v?function(t,e){const n=Math.max(Math.abs(t)-1,e);return n<128?_():n<32768?$():n<2**31?Y():K()}(y,p):a===v?K():u===v?function(t,e){const n=-t>e?-t-1n:e;if(n>=2**63)throw new Error(`BigInt exceeds 64 bits: ${n}`);return P()}(t,e):i===v?tt():d===v?st():o===v?it():l===v?k(Z()):h===v?function(t,e,n){return n===e?lt(t,e):ct(t)}(n.type(),b,I):f===v?ut(Object.entries(g).map((t=>V(t[0],t[1].type())))):function(){throw new Error("Mixed types detected, please define a union type.")}()}}}class Xn extends Pn{constructor(t,e){super(t,e),this.toOffset=St(t.offsets)}init(){return this.offsets=zn(this.type.offsets),this.values=zn(),this.pos=0,super.init()}set(t,e){const{offsets:n,values:s,toOffset:r}=this;super.set(t,e)&&(s.write(t,this.pos),this.pos+=t.length),n.set(r(this.pos),e+1)}done(){return{...super.done(),offsets:this.offsets.array(this.index+2),values:this.values.array(this.pos+1)}}}class qn extends Pn{constructor(t,e){super(t,e)}init(){return this.values=_n(),super.init()}set(t,e){super.set(t,e),t&&this.values.set(e)}done(){return{...super.done(),values:this.values.array(1+(this.index>>3))}}}class Kn extends Pn{constructor(t,e){super(t,e),this.scale=10**t.scale,this.stride=t.bitWidth>>6}init(){return this.values=zn(this.type.values),super.init()}set(t,e){const{scale:n,stride:s,values:r}=this;super.set(t,e)&&(r.prep((e+1)*s),function(t,e,n,s,r){const i="bigint"==typeof t?t:At(Math.trunc(t*r));e[n]=i,e[n+1]=i>>64n,s>2&&(e[n+2]=i>>128n,e[n+3]=i>>192n)}(t,r.buf,e*s,s,n))}done(){const{index:t,stride:e,values:n}=this;return{...super.done(),values:n.array((t+1)*e)}}}class Qn extends Pn{constructor(t,e){super(t,e),this.stride=t.stride}init(){return this.values=zn(),super.init()}set(t,e){super.set(t,e)&&this.values.write(t,e*this.stride)}done(){const{stride:t,values:e}=this;return{...super.done(),values:e.array(t*(this.index+1))}}}class Zn extends Pn{constructor(t,e){super(t,e),this.child=e.builder(this.type.children[0].type),this.stride=t.stride}init(){return this.child.init(),super.init()}set(t,e){const{child:n,stride:s}=this,r=e*s;if(super.set(t,e))for(let e=0;e<s;++e)n.set(t[e],r+e);else n.index=r+s}done(){const{child:t}=this;return{...super.done(),children:[t.batch()]}}}class ts extends Pn{init(){return this.values=zn(this.type.values),super.init()}set(t,e){if(super.set(t,e)){const n=e<<1;this.values.set(t[0],n),this.values.set(t[1],n+1)}}done(){return{...super.done(),values:this.values.array(this.index+1<<1)}}}class es extends Pn{init(){return this.values=zn(),super.init()}set(t,e){super.set(t,e)&&this.values.write(function([t,e,n]){return Lt[0]=t,Lt[1]=e,xt[1]=At(n),Et}(t),e<<4)}done(){return{...super.done(),values:this.values.array(this.index+1<<4)}}}class ns extends Pn{constructor(t,e,n){super(t,e),this.child=n}init(){this.child.init();const t=this.type.offsets;return this.offsets=zn(t),this.toOffset=St(t),this.pos=0,super.init()}done(){return{...super.done(),offsets:this.offsets.array(this.index+2),children:[this.child.batch()]}}}class ss extends ns{constructor(t,e){super(t,e,e.builder(t.children[0].type))}set(t,e){const{child:n,offsets:s,toOffset:r}=this;super.set(t,e)&&t.forEach((t=>n.set(t,this.pos++))),s.set(r(this.pos),e+1)}}class rs extends Pn{constructor(t,e){super(t,e),this.children=t.children.map((t=>e.builder(t.type)))}init(){return this.children.forEach((t=>t.init())),super.init()}done(){const{children:t}=this;return t.forEach((t=>t.index=this.index)),{...super.done(),children:t.map((t=>t.batch()))}}}class is extends rs{constructor(t,e){super(t,e),this.setters=this.children.map(((e,n)=>{const s=t.children[n].name;return(t,n)=>e.set(t?.[s],n)}))}set(t,e){super.set(t,e);const n=this.setters;for(let s=0;s<n.length;++s)n[s](t,e)}}class as extends ns{constructor(t,e){super(t,e,new cs(t.children[0].type,e))}set(t,e){const{child:n,offsets:s,toOffset:r}=this;if(super.set(t,e))for(const e of t)n.set(e,this.pos++);s.set(r(this.pos),e+1)}}class cs extends rs{set(t,e){super.set(t,e);const[n,s]=this.children;n.set(t[0],e),s.set(t[1],e)}}const us={};class os extends Yn{constructor(t,e){super(t,e),this.children=t.children.map((t=>e.builder(t.type)))}init(){return this.pos=0,this.key=null,this.value=us,this.children.forEach((t=>t.init())),super.init()}next(){const[t,e]=this.children;t.set(this.index+1,this.pos),e.set(this.value,this.pos++)}set(t,e){if(t!==this.value){const e=Rt(t);e!==this.key&&(this.key&&this.next(),this.key=e,this.value=t)}this.index=e}done(){this.next();const{children:t,index:e,type:n}=this;return{length:e+1,nullCount:0,type:n,children:t.map((t=>t.batch()))}}}class ds extends Yn{constructor(t,e){super(t,e),this.children=t.children.map((t=>e.builder(t.type))),this.typeMap=t.typeMap,this.lookup=t.typeIdForValue}init(){return this.nullCount=0,this.typeIds=zn(p),this.children.forEach((t=>t.init())),super.init()}set(t,e){const{children:n,lookup:s,typeMap:r,typeIds:i}=this;this.index=e;const a=s(t,e),c=n[r[a]];i.set(a,e),null==t&&++this.nullCount,this.update(t,e,c)}done(){const{children:t,nullCount:e,type:n,typeIds:s}=this,r=this.index+1;return{length:r,nullCount:e,type:n,typeIds:s.array(r),children:t.map((t=>t.batch()))}}}class ls extends ds{update(t,e,n){n.set(t,e),this.children.forEach((t=>{t!==n&&t.set(null,e)}))}}class hs extends ds{init(){return this.offsets=zn(this.type.offsets),super.init()}update(t,e,n){const s=n.index+1;n.set(t,s),this.offsets.set(s,e)}done(){return{...super.done(),offsets:this.offsets.array(this.index+1)}}}class fs extends Xn{set(t,e){super.set(t&&zt(t),e)}}class ys extends Pn{constructor(t,e){super(t,e),this.values=zn(t.values)}init(){return this.values=zn(this.type.values),super.init()}set(t,e){super.set(t,e)&&this.values.set(t,e)}done(){return{...super.done(),values:this.values.array(this.index+1)}}}class ps extends ys{set(t,e){super.set(null==t?t:At(t),e)}}class bs extends ys{constructor(t,e,n){super(t,e),this.transform=n}set(t,e){super.set(null==t?t:this.transform(t),e)}}function Is(t={},e=Hn()){return{batchType:e=>Ke(e,t),builder(t){return gs(t,this)},dictionary(t){return e.get(t,this)},finish:()=>e.finish(t)}}function gs(t,e=Is()){const{typeId:n}=t;switch(n){case i.Int:case i.Time:case i.Duration:return E(t.values)?new ps(t,e):new ys(t,e);case i.Float:return t.precision?new ys(t,e):new bs(t,e,Ut);case i.Binary:case i.LargeBinary:return new Xn(t,e);case i.Utf8:case i.LargeUtf8:return new fs(t,e);case i.Bool:return new qn(t,e);case i.Decimal:return new Kn(t,e);case i.Date:return new bs(t,e,t.unit?At:Nt);case i.Timestamp:return new bs(t,e,(s=t.unit)===u.SECOND?t=>At(t/1e3):s===u.MILLISECOND?At:s===u.MICROSECOND?t=>At(1e3*t):t=>At(1e6*t));case i.Interval:switch(t.unit){case o.DAY_TIME:return new ts(t,e);case o.MONTH_DAY_NANO:return new es(t,e)}return new ys(t,e);case i.List:case i.LargeList:return new ss(t,e);case i.Struct:return new is(t,e);case i.Union:return t.mode?new hs(t,e):new ls(t,e);case i.FixedSizeBinary:return new Qn(t,e);case i.FixedSizeList:return new Zn(t,e);case i.Map:return new as(t,e);case i.RunEndEncoded:return new os(t,e);case i.Dictionary:return new Wn(t,e)}var s;throw new Error(C(n))}function vs(t,e,n={},s){const r="function"==typeof t[Symbol.iterator]?e=>{for(const n of t)e(n)}:t;e??=Gn(r);const{maxBatchRows:a=1/0,...c}=n;let u;if(e.typeId===i.Null){let t=0;r((()=>++t)),u=function(t,e,n){const s=[],r=e=>new ce({length:e,nullCount:e,type:t}),i=Math.floor(e/n);for(let t=0;t<i;++t)s.push(r(n));const a=e%n;a&&s.push(r(a));return s}(e,t,a)}else{const t=Is(c,s),n=gs(e,t).init(),i=t=>u.push(t.batch());u=[];let o=0;r((t=>{n.set(t,o++),o>=a&&(i(n),o=0)})),o&&i(n),t.finish()}return new Xe(u,e)}function ws(t,e,n={},s){return!e&&O(t)?function(t,{maxBatchRows:e,useBigInt:n}){const s=t.constructor,r=function(t){switch(t){case v:return q();case w:return K();case p:return _();case b:return $();case I:return Y();case g:return P();case l:return H();case h:return W();case f:return G();case y:return J()}}(s),i=t.length,a=Math.min(e||1/0,i),c=Math.floor(i/a),u=[],o=E(s)&&!n?ue:re,d=(e,n)=>u.push(new o({length:n-e,nullCount:0,type:r,validity:new l(0),values:t.subarray(e,n)}));let m=0;for(let t=0;t<c;++t)d(m,m+=a);m<i&&d(m,i);return new Xe(u)}(t,n):vs((e=>t.forEach(e)),e,n,s)}function ms(t,e){const r=[],i=Array.isArray(t)?t:Object.entries(t),a=i[0]?.[1].length,c=i.map((([t,e])=>{if(e.length!==a)throw new Error("All columns must have the same length.");return r.push(V(t,e.type)),e})),u={version:n.V5,endianness:s.Little,fields:r,metadata:null};return new qe(u,c,e)}t.Batch=se,t.Column=Xe,t.DateUnit=c,t.Endianness=s,t.IntervalUnit=o,t.Precision=a,t.Table=qe,t.TimeUnit=u,t.Type=i,t.UnionMode=d,t.Version=n,t.batchType=Ke,t.binary=Q,t.binaryView=()=>j(i.BinaryView),t.bool=tt,t.columnFromArray=ws,t.columnFromValues=vs,t.date=nt,t.dateDay=st,t.dateMillisecond=()=>nt(c.MILLISECOND),t.decimal=et,t.dictionary=k,t.dictionaryContext=Hn,t.duration=ft,t.field=V,t.fixedSizeBinary=dt,t.fixedSizeList=lt,t.float=X,t.float16=()=>X(a.HALF),t.float32=q,t.float64=K,t.int=R,t.int16=$,t.int32=Y,t.int64=P,t.int8=_,t.interval=at,t.largeBinary=yt,t.largeList=bt,t.largeListView=vt,t.largeUtf8=pt,t.list=ct,t.listView=gt,t.map=(t,e,n=!1)=>ht(n,V("entries",ut([F(t,"key",!1),F(e,"value")]),!1)),t.nullType=z,t.runEndEncoded=It,t.struct=ut,t.tableFromArrays=function(t,e={}){const{types:n={},...s}=e,r=Hn();return ms((Array.isArray(t)?t:Object.entries(t)).map((([t,e])=>[t,ws(e,n[t],s,r)])),e.useProxy)},t.tableFromColumns=ms,t.tableFromIPC=function(t,e){return function(t,e={}){const{schema:n={fields:[]},dictionaries:s,records:r}=t,{version:a,fields:c}=n,u=new Map,o=function(t,e,n){const s={version:e,options:t,dictionary:t=>n.get(t)};return t=>{const{length:e,nodes:n,regions:r,variadic:i,body:a}=t;let c=-1,u=-1,o=-1;return{...s,length:e,node:()=>n[++c],buffer:t=>{const{length:e,offset:n}=r[++u];return t?new t(a.buffer,a.byteOffset+n,e/t.BYTES_PER_ELEMENT):a.subarray(n,n+e)},variadic:()=>i[++o],visit(t){return t.map((t=>bn(t.type,this)))}}}}(e,a,u),d=new Map;!function(t,e){t.fields.forEach((function t(n){e(n),n.type.dictionary?.children?.forEach(t),n.type.children?.forEach(t)}))}(n,(t=>{const e=t.type;e.typeId===i.Dictionary&&d.set(e.id,e.dictionary)}));const l=new Map;for(const t of s){const{id:e,data:n,isDelta:s,body:r}=t,i=d.get(e),a=bn(i,o({...n,body:r}));if(l.has(e)){const t=l.get(e);s||t.clear(),t.add(a)}else{if(s)throw new Error("Delta update can not be first dictionary batch.");l.set(e,Je(i).add(a))}}l.forEach(((t,e)=>u.set(e,t.done())));const h=c.map((t=>Je(t.type)));for(const t of r){const e=o(t);c.forEach(((t,n)=>h[n].add(bn(t.type,e))))}return new qe(n,h.map((t=>t.done())),e.useProxy)}(pn(t),e)},t.tableToIPC=function(t,e){"string"==typeof e&&(e={format:e});const n=t.children;!function(t){const e=t[0]?.data.map((t=>t.length));t.forEach((({data:t})=>{if(t.length!==e.length||t.some(((t,n)=>t.length!==e[n])))throw new Error("Columns have inconsistent batch sizes.")}))}(n);const{dictionaries:s,idMap:r}=function(t){const e=[],n=new Map,s=new Map;let r=-1;const i=t=>{if(n.has(t))s.set(t.type,n.get(t));else{n.set(t,++r);for(let n=0;n<t.data.length;++n)e.push({id:r,isDelta:n>0,data:jn([t],n)});s.set(t.type,r)}};return t.forEach((t=>Fn(t.data[0],i))),{dictionaries:e,idMap:s}}(n),a=function(t){return(t[0]?.data||[]).map(((e,n)=>jn(t,n)))}(n),c=function(t,e){if(!e.size)return t;const n=t=>{t.typeId===i.Dictionary&&(t.id=e.get(t.dictionary),r(t)),t.children&&(t.children=t.children.slice()).forEach(s)},s=(t,e,s)=>{const r={...t.type};s[e]={...t,type:r},n(r)},r=t=>{const e={...t.dictionary};t.dictionary=e,n(e)};return t={...t,fields:t.fields.slice()},t.fields.forEach(s),t}(t.schema,r);return Tn({schema:c,dictionaries:s,records:a},e).finish()},t.time=rt,t.timeMicrosecond=()=>rt(u.MICROSECOND,64),t.timeMillisecond=()=>rt(u.MILLISECOND,32),t.timeNanosecond=()=>rt(u.NANOSECOND,64),t.timeSecond=()=>rt(u.SECOND,32),t.timestamp=it,t.uint16=W,t.uint32=G,t.uint64=J,t.uint8=H,t.union=ot,t.utf8=Z,t.utf8View=()=>j(i.Utf8View)}));
//# sourceMappingURL=flechette.min.js.map

4

dist/types/build/column-from-array.d.ts
/**
* Create a new column from a provided data array.
* @template T
* @param {Array | import('../types.js').TypedArray} data The input data.
* @param {Array | import('../types.js').TypedArray} array The input data.
* @param {import('../types.js').DataType} [type] The data type.

@@ -13,3 +13,3 @@ * If not specified, type inference is attempted.

*/
export function columnFromArray<T>(data: any[] | import("../types.js").TypedArray, type?: import("../types.js").DataType, options?: import("../types.js").ColumnBuilderOptions, dicts?: ReturnType<typeof import("./builders/dictionary.js").dictionaryContext>): Column<T>;
export function columnFromArray<T>(array: any[] | import("../types.js").TypedArray, type?: import("../types.js").DataType, options?: import("../types.js").ColumnBuilderOptions, dicts?: ReturnType<typeof import("./builders/dictionary.js").dictionaryContext>): Column<T>;
import { Column } from '../column.js';

12

dist/types/build/column-from-values.d.ts
/**
* Create a new column by iterating over provided values.
* @template T
* @param {number} length The input data length.
* @param {(visitor: (value: any) => void) => void} visit
* A function that applies a callback to successive data values.
* @param {import('../types.js').DataType} type The data type.
* @param {Iterable | ((callback: (value: any) => void) => void)} values
* Either an iterable object or a visitor function that applies a callback
* to successive data values (akin to Array.forEach).
* @param {import('../types.js').DataType} [type] The data type.
* @param {import('../types.js').ColumnBuilderOptions} [options]

@@ -12,6 +12,6 @@ * Builder options for the generated column.

* import('./builders/dictionary.js').dictionaryContext
* >} [dicts] Builder context object, for internal use only.
* >} [dicts] Dictionary context object, for internal use only.
* @returns {Column<T>} The generated column.
*/
export function columnFromValues<T>(length: number, visit: (visitor: (value: any) => void) => void, type: import("../types.js").DataType, options?: import("../types.js").ColumnBuilderOptions, dicts?: ReturnType<typeof import("./builders/dictionary.js").dictionaryContext>): Column<T>;
export function columnFromValues<T>(values: Iterable<any> | ((callback: (value: any) => void) => void), type?: import("../types.js").DataType, options?: import("../types.js").ColumnBuilderOptions, dicts?: ReturnType<typeof import("./builders/dictionary.js").dictionaryContext>): Column<T>;
import { Column } from '../column.js';

6

dist/types/util/objects.d.ts

@@ -8,2 +8,8 @@ /**

/**
* Check if a value is iterable.
* @param {*} value The value to check.
* @returns {value is Iterable} True if value is iterable, false otherwise.
*/
export function isIterable(value: any): value is Iterable<any>;
/**
* Return the input value if it passes a test.

@@ -10,0 +16,0 @@ * Otherwise throw an error using the given message generator.

47

docs/api/index.md

@@ -14,2 +14,3 @@ ---

* [columnFromArray](#columnFromArray)
* [columnFromValues](#columnFromValues)
* [tableFromColumns](#tableFromColumns)

@@ -24,7 +25,7 @@

* *options* (`ExtractionOptions`): Options for controlling how values are transformed when extracted from an Arrow binary representation.
* *useDate* (`boolean`): If true, extract dates and timestamps as JavaScript `Date` objects Otherwise, return numerical timestamp values (default).
* *useDecimalBigInt* (`boolean`): If true, extract decimal-type data as BigInt values, where fractional digits are scaled to integers. Otherwise, return converted floating-point numbers (default).
* *useBigInt* (`boolean`): If true, extract 64-bit integers as JavaScript `BigInt` values Otherwise, coerce long integers to JavaScript number values (default).
* *useMap* (`boolean`): If true, extract Arrow 'Map' values as JavaScript `Map` instances Otherwise, return an array of [key, value] pairs compatible with both `Map` and `Object.fromEntries` (default).
* *useProxy* (`boolean`): If true, extract Arrow 'Struct' values and table row objects using zero-copy proxy objects that extract data from underlying Arrow batches. The proxy objects can improve performance and reduce memory usage, but do not support property enumeration (`Object.keys`, `Object.values`, `Object.entries`) or spreading (`{ ...object }`).
* *useBigInt* (`boolean`): If true, extract 64-bit integers as JavaScript `BigInt` values. Otherwise, coerce long integers to JavaScript number values (default `false`).
* *useDate* (`boolean`): If true, extract dates and timestamps as JavaScript `Date` objects. Otherwise, return numerical timestamp values (default `false`).
* *useDecimalBigInt* (`boolean`): If true, extract decimal-type data as BigInt values, where fractional digits are scaled to integers. Otherwise, return converted floating-point numbers (default `false`).
* *useMap* (`boolean`): If true, extract Arrow 'Map' values as JavaScript `Map` instances. Otherwise, return an array of [key, value] pairs compatible with both `Map` and `Object.fromEntries` (default `false`).
* *useProxy* (`boolean`): If true, extract Arrow 'Struct' values and table row objects using zero-copy proxy objects that extract data from underlying Arrow batches. The proxy objects can improve performance and reduce memory usage, but do not support property enumeration (`Object.keys`, `Object.values`, `Object.entries`) or spreading (`{ ...object }`). Otherwise, use standard JS objects for structs and table rows (default `false`).

@@ -97,10 +98,10 @@ ```js

<hr/><a id="columnFromArray" href="#columnFromArray">#</a>
<b>columnFromArray</b>(<i>data</i>[, <i>type</i>, <i>options</i>])
<b>columnFromArray</b>(<i>array</i>[, <i>type</i>, <i>options</i>])
Create a new column from a provided data array. The data types for the column can be automatically inferred or specified using the *type* argument.
* *data* (`Array | TypedArray`): The input data as an Array or TypedArray.
* *array* (`Array | TypedArray`): The input data as an Array or TypedArray.
* *type*: (`DataType`): The [data type](data-types) for the column. If not specified, type inference is attempted.
* *options* (`object`): Options for building new columns and controlling how values are transformed when extracted from an Arrow binary representation.
* *maxBatchRows* (`number`): The maximum number of rows to include in a single record batch. If the array lengths exceed this number, the resulting table will consist of multiple record batches.
* *maxBatchRows* (`number`): The maximum number of rows to include in a single record batch. If the array length exceeds this number, the resulting column will consist of multiple record batches.
* In addition, all [tableFromIPC](#tableFromIPC) extraction options are supported.

@@ -124,2 +125,32 @@

<hr/><a id="columnFromValues" href="#columnFromValues">#</a>
<b>columnFromValues</b>(<i>values</i>[, <i>type</i>, <i>options</i>])
Create a new column by iterating over provided *values*. The *values* argument can either be an iterable collection or a visitor function that applies a callback to successive data values (akin to `Array.forEach`). The data types for the column can be automatically inferred or specified using the *type* argument.
* *values* (`Iterable | (callback: (value: any) => void) => void`): An iterable object or a visitor function that applies a callback to successive data values (akin to `Array.forEach`). In most cases, providing a visitor function will be more efficient than an iterator, so is recommended for larger datasets.
* *type*: (`DataType`): The [data type](data-types) for the column. If not specified, type inference is attempted.
* *options* (`object`): Options for building new columns and controlling how values are transformed when extracted from an Arrow binary representation.
* *maxBatchRows* (`number`): The maximum number of rows to include in a single record batch. If the number of values exceeds this number, the resulting column will consist of multiple record batches.
* In addition, all [tableFromIPC](#tableFromIPC) extraction options are supported.
```js
import { columnFromValues, float32, int64 } from '@uwdata/flechette';
// an iterable set of values
const set = new Set([1.1, 1.1, 2.2, 3.4]);
// create column with inferred type (here, float64)
columnFromValues(set);
// create column with specified type
columnFromValues(set, float32());
// create column using only values with odd-numbered indices
const values = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9];
columnFromValues(callback => {
values.forEach((v, i) => { if (i % 2) callback(v); })
});
```
<hr/><a id="tableFromColumns" href="#tableFromColumns">#</a>

@@ -126,0 +157,0 @@ <b>tableFromColumns</b>(<i>columns</i>[, <i>useProxy</i>])

2

docs/index.md

@@ -120,3 +120,3 @@ # Flechette <a href="https://idl.uw.edu/flechette"><img align="right" src="assets/logo.svg" height="38"/></a>

useBigInt: true, // use BigInt for 64-bit ints, do not coerce to number
useMap: true // create Map objects for [key, value] pair lists
useMap: true, // create Map objects for [key, value] pair lists
useProxy: true // use zero-copy proxies for struct and table row objects

@@ -123,0 +123,0 @@ });

4

package.json
{
"name": "@uwdata/flechette",
"version": "1.0.2",
"version": "1.1.0",
"description": "Fast, lightweight access to Apache Arrow data.",

@@ -38,3 +38,3 @@ "keywords": [

"@rollup/plugin-terser": "^0.4.4",
"@uwdata/mosaic-duckdb": "^0.10.0",
"@uwdata/mosaic-duckdb": "^0.11.0",
"apache-arrow": "^17.0.0",

@@ -41,0 +41,0 @@ "eslint": "^9.10.0",

2

README.md

@@ -120,3 +120,3 @@ # Flechette <a href="https://idl.uw.edu/flechette"><img align="right" src="https://raw.githubusercontent.com/uwdata/flechette/main/docs/assets/logo.svg" height="38"></img></a>

useBigInt: true, // use BigInt for 64-bit ints, do not coerce to number
useMap: true // create Map objects for [key, value] pair lists
useMap: true, // create Map objects for [key, value] pair lists
useProxy: true // use zero-copy proxies for struct and table row objects

@@ -123,0 +123,0 @@ });

10

src/build/column-from-array.js

@@ -10,3 +10,3 @@ import { float32Array, float64Array, int16Array, int32Array, int64Array, int8Array, isInt64ArrayType, isTypedArray, uint16Array, uint32Array, uint64Array, uint8Array } from '../util/arrays.js';

* @template T
* @param {Array | import('../types.js').TypedArray} data The input data.
* @param {Array | import('../types.js').TypedArray} array The input data.
* @param {import('../types.js').DataType} [type] The data type.

@@ -20,6 +20,6 @@ * If not specified, type inference is attempted.

*/
export function columnFromArray(data, type, options = {}, dicts) {
return !type && isTypedArray(data)
? columnFromTypedArray(data, options)
: columnFromValues(data.length, v => data.forEach(v), type, options, dicts);
export function columnFromArray(array, type, options = {}, dicts) {
return !type && isTypedArray(array)
? columnFromTypedArray(array, options)
: columnFromValues(v => array.forEach(v), type, options, dicts);
}

@@ -26,0 +26,0 @@

60

src/build/column-from-values.js

@@ -6,2 +6,3 @@ import { NullBatch } from '../batch.js';

import { Type } from '../constants.js';
import { isIterable } from '../util/objects.js';

@@ -11,6 +12,6 @@ /**

* @template T
* @param {number} length The input data length.
* @param {(visitor: (value: any) => void) => void} visit
* A function that applies a callback to successive data values.
* @param {import('../types.js').DataType} type The data type.
* @param {Iterable | ((callback: (value: any) => void) => void)} values
* Either an iterable object or a visitor function that applies a callback
* to successive data values (akin to Array.forEach).
* @param {import('../types.js').DataType} [type] The data type.
* @param {import('../types.js').ColumnBuilderOptions} [options]

@@ -20,33 +21,38 @@ * Builder options for the generated column.

* import('./builders/dictionary.js').dictionaryContext
* >} [dicts] Builder context object, for internal use only.
* >} [dicts] Dictionary context object, for internal use only.
* @returns {Column<T>} The generated column.
*/
export function columnFromValues(length, visit, type, options, dicts) {
export function columnFromValues(values, type, options = {}, dicts) {
const visit = isIterable(values)
? callback => { for (const value of values) callback(value); }
: values;
type ??= inferType(visit);
const { maxBatchRows, ...opt } = options;
const limit = Math.min(maxBatchRows || Infinity, length);
const { maxBatchRows = Infinity, ...opt } = options;
let data;
// if null type, generate batches and exit early
if (type.typeId === Type.Null) {
return new Column(nullBatches(type, length, limit), type);
}
let length = 0;
visit(() => ++length);
data = nullBatches(type, length, maxBatchRows);
} else {
const ctx = builderContext(opt, dicts);
const b = builder(type, ctx).init();
const next = b => data.push(b.batch());
data = [];
const ctx = builderContext(opt, dicts);
const b = builder(type, ctx).init();
const data = [];
const next = b => data.push(b.batch());
let row = 0;
visit(value => {
b.set(value, row++);
if (row >= maxBatchRows) {
next(b);
row = 0;
}
});
if (row) next(b);
let row = 0;
visit(value => {
b.set(value, row++);
if (row >= limit) {
next(b);
row = 0;
}
});
if (row) next(b);
// resolve dictionaries
ctx.finish();
}
// resolve dictionaries
ctx.finish();
return new Column(data, type);

@@ -53,0 +59,0 @@ }

9

src/util/objects.js

@@ -11,2 +11,11 @@ /**

/**
* Check if a value is iterable.
* @param {*} value The value to check.
* @returns {value is Iterable} True if value is iterable, false otherwise.
*/
export function isIterable(value) {
return typeof value[Symbol.iterator] === 'function';
}
/**
* Return the input value if it passes a test.

@@ -13,0 +22,0 @@ * Otherwise throw an error using the given message generator.

dist/flechette.cjs

Sorry, the diff of this file is not supported yet

dist/flechette.min.js.map

Sorry, the diff of this file is not supported yet

dist/flechette.mjs

Sorry, the diff of this file is not supported yet

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