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p-society / gc-server

Stay updated in real-time and engage with the thrill of the game like never before.[WIP]
Apache License 2.0
3 stars 6 forks source link

Mailing server for gcsb #17

Closed zakhaev26 closed 7 months ago

zakhaev26 commented 7 months ago

The mailing API has been developed using smtp, github.com/jordan-wright/email package for email composition that can be used by other API's in the codebase. The implementation follows best practices for email communication.

After starting the go server,API can be accessed at http://localhost:6969/send-mail with appropriate body,the docs of which will be added soon.

zakhaev26 commented 7 months ago

image Perf Result for 10 concurrent VUs (mailing + insertion)

pull-request-quantifier-deprecated[bot] commented 7 months ago

This PR has 549 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

Quantification details

``` Label : Extra Large Size : +538 -11 Percentile : 84.97% Total files changed: 19 Change summary by file extension: .yml : +23 -0 .gitignore : +2 -0 .go : +343 -0 .mod : +25 -2 .sum : +79 -9 .md : +50 -0 services/mailing/Dockerfile : +16 -0 ``` > Change counts above are quantified counts, based on the [PullRequestQuantifier customizations](https://github.com/microsoft/PullRequestQuantifier/blob/main/docs/prquantifier-yaml.md).

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](https://github.com/microsoft/PullRequestQuantifier/releases) - 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](./docs/prquantifier-yaml.md) 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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