Yezz123-Archive / Phisher

Perform various social engineering attacks using PHP, Apache, Ngrok 🦥
MIT License
203 stars 30 forks source link

[ImgBot] Optimize images #12

Closed imgbot[bot] closed 3 years ago

imgbot[bot] commented 3 years ago

Beep boop. Your images are optimized!

Your image file size has been reduced by 42% 🎉

Details | File | Before | After | Percent reduction | |:--|:--|:--|:--| | /sites/google/avatar.png | 6.46kb | 2.62kb | 59.52% | | /sites/facebook/images/fblogo.png | 10.86kb | 5.47kb | 49.61% | | /.github/header.svg | 1.88kb | 0.96kb | 48.96% | | /sites/facebook/images/fbandroid.png | 8.70kb | 7.15kb | 17.80% | | | | | | | **Total :** | **27.90kb** | **16.20kb** | **41.95%** |

Black Lives Matter | 💰 donate | 🎓 learn | ✍🏾 sign

📝 docs | :octocat: repo | 🙋🏾 issues | 🏅 swag | 🏪 marketplace

pull-request-quantifier-deprecated[bot] commented 3 years ago

This PR has 53 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

``` Label : Small Size : +1 -52 Percentile : 21.2% Total files changed: 1 Change summary by file extension: .svg : +1 -52 ``` > 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 detetcted. - 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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