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Introduce RuneStateModule #2511

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merged 13 commits into from
Apr 8, 2024

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@U-lis U-lis commented Apr 4, 2024

  • Create RuneStateModule
    • Has passive migration : Set new state from legacy state

@U-lis U-lis added the enhancement New feature or request label Apr 4, 2024
@U-lis U-lis added this to the v170.0.0 milestone Apr 4, 2024
@U-lis U-lis requested review from ipdae and sonohoshi April 4, 2024 06:37
@U-lis U-lis self-assigned this Apr 4, 2024

This PR has 93 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


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This PR has 91 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


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Total files changed: 5

Change summary by file extension:
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balance between between PR complexity and PR review overhead. PRs within the
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    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
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    • Exercising separation of concerns within the code changes.

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How to interpret the change counts in git diff output

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    of this PR in relation to all other PRs within the repository.


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@U-lis U-lis marked this pull request as draft April 4, 2024 06:42
U-lis added 3 commits April 4, 2024 23:45
- Introduce AllRuneState which has all RuneState of avatar.
- Migrate multiple RuneStates to AllRuneState.

This PR has 140 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


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Label      : Medium
Size       : +110 -30
Percentile : 48%

Total files changed: 7

Change summary by file extension:
.cs : +110 -30

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Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
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    • Exercising separation of concerns within the code changes.

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How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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This PR has 140 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Medium
Size       : +110 -30
Percentile : 48%

Total files changed: 7

Change summary by file extension:
.cs : +110 -30

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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This PR has 140 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Medium
Size       : +110 -30
Percentile : 48%

Total files changed: 7

Change summary by file extension:
.cs : +110 -30

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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This PR has 140 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Medium
Size       : +110 -30
Percentile : 48%

Total files changed: 7

Change summary by file extension:
.cs : +110 -30

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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@U-lis U-lis marked this pull request as ready for review April 5, 2024 02:17
@U-lis U-lis marked this pull request as draft April 5, 2024 02:17
@U-lis U-lis marked this pull request as ready for review April 5, 2024 05:00

This PR has 140 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Medium
Size       : +110 -30
Percentile : 48%

Total files changed: 7

Change summary by file extension:
.cs : +110 -30

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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여기까지는 문제없어보이고, RuneState를 쓰는 다른 액션(e.g. HAS) RuneStateModule을 사용해서 마이그레이션되게 하는 작업은 별도 PR로 올릴 예정이신가요?

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U-lis commented Apr 5, 2024

여기까지는 문제없어보이고, RuneState를 쓰는 다른 액션(e.g. HAS) RuneStateModule을 사용해서 마이그레이션되게 하는 작업은 별도 PR로 올릴 예정이신가요?

네 요건 별도 작업으로 하려고 합니다. 다 합치면 덩어리가 자꾸 커질 것 같아서

Lib9c/Model/State/AllRuneState.cs Outdated Show resolved Hide resolved
Lib9c/Model/State/AllRuneState.cs Show resolved Hide resolved
Lib9c/Module/RuneStateModule.cs Outdated Show resolved Hide resolved
.Lib9c.Tests/Action/RuneEnhancementTest.cs Show resolved Hide resolved

This PR has 382 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Large
Size       : +327 -55
Percentile : 78.2%

Total files changed: 25

Change summary by file extension:
.cs : +305 -38
.csv : +22 -17

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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@U-lis U-lis force-pushed the feature/rune-level-bonus branch from 89b310c to f42bda5 Compare April 5, 2024 08:27

This PR has 236 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : Large
Size       : +206 -30
Percentile : 63.6%

Total files changed: 7

Change summary by file extension:
.cs : +206 -30

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a
balance between between PR complexity and PR review overhead. PRs within the
optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer
      iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will
    interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification)
    of this PR in relation to all other PRs within the repository.


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@U-lis U-lis requested review from sonohoshi and ipdae April 5, 2024 08:28
@U-lis U-lis merged commit f26d01c into planetarium:development Apr 8, 2024
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@U-lis U-lis linked an issue Apr 18, 2024 that may be closed by this pull request
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