Random Shogi Piece Generator
Explicit small educational annotated notation inventory for Random Shogi Piece Generator. Sources/repertoire scope recorded in batch42 manifest. Not exhaustive; FDI codes use permanent quadrants1–4teeth1–8and primary quadrants5–8teeth1–5; no anatomical diagnosis. Prosigns continuous, not separated letters. Dental, safety, electrical, musical and diagram tokens do not establish standards conformance or safe operation. Uniform pinned repertoire-entry sampling; without replacement means distinct entry indices, not guaranteed distinct rendered glyphs. Reproducible seed or one advancing caller source; not secure randomness.
Description
Shogi piece labels identify roles and promotion conventions within a teaching inventory.
Shogi piece labels identify roles and promotion conventions within a teaching inventory.1
Random entries support recognition practice rather than generating a legal position or move.
When to use Random Shogi Piece Generator
Use this tool when you need to sample the fixed repertoire for recognition or text fixtures. Prepare the seed and the exact inventory or scenario inputs described below. Keep units, reference edition, and sampling convention explicit.
How to use Random Shogi Piece Generator and understand its results
- Prepare the seed and the exact inventory or scenario inputs described below. Keep units, reference edition, and sampling convention explicit.
- Enter seed, count, withoutReplacement, following the field table and calculation rules below, then run the tool.
- Read result. Inspect the nested fields in the output table below and keep any missing evidence or selected indices visible.
- Correct any input issues and run again. Before using a successful result, review its units, signs, evidence coverage, and stated model or reference assumptions.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| seed | Nonblank reproducibility seed; default seeded runs restart for each request | string | Required |
| count | Number of sampled entry positions | safe integer from 1 to 64 | Required |
| withoutReplacement | True draws distinct entry positions; false permits repeated positions | boolean | Required |
| Entry index | Source entry |
|---|---|
| 0 | 王 | king |
| 1 | 玉 | jeweled king |
| 2 | 飛 | rook |
| 3 | 角 | bishop |
| 4 | 金 | gold general |
| 5 | 銀 | silver general |
| 6 | 桂 | knight |
| 7 | 香 | lance |
| 8 | 歩 | pawn |
Sample from the fixed implementation inventory of 9 entries. Return values, zero-based selectedEntryIndices, and repertoireSize. Range inventories resolve an entry index through inclusive code-point ranges; explicit inventories retrieve the stored string in order. The pinned repertoire is not downloaded or updated during a run.2, 3
Use a nonblank seed of at most 256 UTF-16 units and a safe-integer count from 1 to 64. By default the seed is hashed into a deterministic pseudorandom state; each run restarts that state, so identical full inputs and implementation reproduce the result. The SDK may provide context.random, which replaces the seeded source and advances across the request; the seed remains required. Every source value must be finite in [0,1), with a request limit of 100000 source calls. Draw an index as floor(U×remainingSize). With replacement draw from the full inventory each time; without replacement remove each chosen position from an ordered pool and reject counts exceeding the inventory size. Uniform-source draws are over positions, not necessarily distinct values. This is not secure randomness.
selectedIndex=floor(U×availablePositions); remove chosen position when withoutReplacement=true Read these symbols with the field meanings and branch or reference rules above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Object containing the fields below | object |
| result.values | Sampled strings, or converted strings when a converter is applied | list |
| result.selectedEntryIndices | Zero-based source inventory positions, in draw order | list |
| result.repertoireSize | Number of available entry positions in the sampled inventory | number |
{
"input": {
"seed": "tool.io/batch42",
"count": 1,
"withoutReplacement": false
},
"output": {
"result": {
"values": [
"歩 | pawn"
],
"selectedEntryIndices": [
8
],
"repertoireSize": 9
}
}
}Limitations and assumptions
The default source is deterministic pseudorandomness, not an independently audited or secure draw. Replacement applies to inventory positions; distinct positions may render identically or yield equal answers. Review the supplied inventory or scenario domain independently before interpreting the sample. A sampled character does not guarantee a visible or distinct glyph, correct shaping, a valid linguistic combination, or a particular font feature.
Missing required fields, unknown fields, wrong types, and violated calculation rules return input issues. Numeric values must be finite; nonfinite numeric outputs are rejected. Extremely large composite outputs are rejected.
Alternative or Complementary methods
For a related task, use Random Xiangqi Piece Generator: Xiangqi pieces have role names and side-specific written labels. This generator samples a small annotated teaching inventory rather than constructing a legal game position. For a complementary step, use Random Mahjong Practice Draw Generator: A teaching mahjong inventory can represent four physical copies of each selected tile type. Drawing distinct physical positions permits repeated tile glyphs without replacement.
References
-
Random Shogi Piece Generator — tool.io
-
Calculation or validation: random/number — tool.io
Similar or alternative tools
- Random Xiangqi Piece Generator
Xiangqi pieces have role names and side-specific written labels. This generator samples a small annotated teaching inventory rather than constructing a legal game position.
- Random Mahjong Practice Draw Generator
A teaching mahjong inventory can represent four physical copies of each selected tile type. Drawing distinct physical positions permits repeated tile glyphs without replacement.