Description
Generate seeded daily, weekly, monthly, or yearly date-only schedules from bounded start, interval, and occurrence choices; reuse sequential calendar clamping (Jan 31 to Feb 29 to Mar 29), not full RFC 5545 recurrence rules.
A workflow or scheduling fixture makes ordering, dependencies, capacity, and timing explicit. Returning both the constructed records and their checks helps consumers distinguish a valid arrangement from a simulated failure case.
Generate seeded daily, weekly, monthly, or yearly date-only schedules from bounded start, interval, and occurrence choices; reuse sequential calendar clamping (Jan 31 to Feb 29 to Mar 29), not full RFC 5545 recurrence rules.
When to use this tool
Use this generator to create reproducible recurrence schedule cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.
How to use the tool and how it works
- Supply scheduleCount, minimumStartDate, maximumStartDate, frequencies, minimumInterval, maximumInterval, minimumOccurrences, maximumOccurrences in the field shapes below. Set seed when you need an explicit replay.
- Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
- Read schedules. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.
Draw a plain start date, frequency, interval, and occurrence count. Advance each occurrence from the preceding one; monthly and yearly steps clamp its current day to the target month. Thus January 31 can become February 28 and then March 28. Return each complete sequence.1
Delegated operations used for this result: recurrence rule; date. Their calculation or parsing conventions apply to the corresponding result fields.2, 3
| Input field | Meaning and units | Accepted input |
|---|---|---|
| scheduleCount | Schedule Count | Required. Safe integer; minimum 1; maximum 32. |
| minimumStartDate | Minimum Start Date | Required. Text; minimum UTF-16 length 10; maximum UTF-16 length 10. |
| maximumStartDate | Maximum Start Date | Required. Text; minimum UTF-16 length 10; maximum UTF-16 length 10. |
| frequencies | Frequencies | Required. Array of Text; one of "daily", "weekly", "monthly", "yearly".; minimum items 1; maximum items 4. |
| minimumInterval | Minimum Interval | Required. Safe integer; minimum 1; maximum 1000. |
| maximumInterval | Maximum Interval | Required. Safe integer; minimum 1; maximum 1000. |
| minimumOccurrences | Minimum Occurrences | Required. Safe integer; minimum 1; maximum 52. |
| maximumOccurrences | Maximum Occurrences | Required. Safe integer; minimum 1; maximum 52. |
| seed | Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed. | Optional. Safe integer. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| schedules | Schedules | Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32. |
| schedules[].startDate | Start Date | Required. Text; minimum UTF-16 length 10; maximum UTF-16 length 10. |
| schedules[].frequency | Frequency | Required. Text; one of "daily", "weekly", "monthly", "yearly". |
| schedules[].interval | Interval | Required. Safe integer; minimum 1; maximum 1000. |
| schedules[].occurrences | Occurrences | Required. Array of Text; minimum UTF-16 length 10; maximum UTF-16 length 10.; minimum items 1; maximum items 52. |
| randomness | Replay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source. | Required. Object; no unknown keys. |
| randomness.seed | Optional numeric replay seed; normalization and precedence are explained below. | Required. Safe integer. or Null. |
| randomness.source | Source | Required. Text; one of "context", "seed". |
An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.
{
"input": {
"scheduleCount": 2,
"minimumStartDate": "2024-01-28",
"maximumStartDate": "2024-01-31",
"frequencies": [
"monthly",
"weekly"
],
"minimumInterval": 1,
"maximumInterval": 2,
"minimumOccurrences": 3,
"maximumOccurrences": 4,
"seed": 42
},
"output": {
"schedules": [
{
"startDate": "2024-01-30",
"frequency": "monthly",
"interval": 2,
"occurrences": [
"2024-01-30",
"2024-03-30",
"2024-05-30",
"2024-07-30"
]
},
{
"startDate": "2024-01-28",
"frequency": "weekly",
"interval": 1,
"occurrences": [
"2024-01-28",
"2024-02-04",
"2024-02-11",
"2024-02-18"
]
}
],
"randomness": {
"seed": 42,
"source": "seed"
}
}
}Limitations and assumptions
- These are plain dates without timezone or time-of-day semantics. Month and year advancement follows the implementation's calendar convention, so inspect the dates rather than assuming a preserved original day or full iCalendar behavior.
- A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
- The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.
Alternative or Complementary methods
For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.
References
Similar or alternative tools
- Random Round-Robin Schedule Generator
Shuffle participants and circle-method rounds into a single all-pairs schedule with explicit Gregorian dates, odd-field byes and combination-verified coverage; no same-round clashes, home/away balance or federation ordering guarantee.
- Random Jigsaw Learning Assignment Generator
Shuffle the supplied distinct learners and topics, delegate complete jigsaw home/expert grouping, and associate each expert group with its shuffled topic. There must be one topic per home-group member and complete home groups; comma-free learner IDs keep the core's serialized group format unambiguous.