Cant finish github sharing process что делать
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Cant finish github sharing process что делать

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Как исравить ошибку Phpstorm при расшаривании проекта на github — Successfully created project on GitHub, but initial push failed?

Создал пробный аккаунт в Github, и получилось из Phpstorm создать приватный репозиторий и залить проект. Но!
Решил перекинуть проект на свой рабочий аккаунт github и тут начали возникать сюрпризы:
При расшаривании приватного проекта — проект создается, но не заливается, пишет ошибку:

Can't finish GitHub sharing process Successfully created project 'test-007' on GitHub, but initial push failed: repository 'https://github.com/user-name/test-007.git/' not found

Как это исправить, что делаю не так?

  • Вопрос задан более трёх лет назад
  • 121 просмотр

Создание проблемы

Проблемы можно создавать различными способами, поэтому вы можете выбрать наиболее удобный метод для рабочего процесса.

Кто может использовать эту функцию.

People with read access can create an issue in a repository where issues are enabled.

Issues can be used to keep track of bugs, enhancements, or other requests. For more information, see «About issues.»

Repository administrators can disable issues for a repository. For more information, see «Disabling issues.»

Creating an issue from a repository

  1. On GitHub.com, navigate to the main page of the repository.
  2. Under your repository name, click

Screenshot of the main page of a repository. In the horizontal navigation bar, a tab, labeled

Issues.

Screenshot of the template chooser for an issue. Below the template choices, a link, labeled

  • Click New issue.
  • If your repository uses issue templates, next to the type of issue you’d like to open, click Get started. If the type of issue you’d like to open isn’t included in the available options, click Open a blank issue.

    Creating an issue with GitHub CLI

    GitHub CLI is an open source tool for using GitHub from your computer’s command line. When you’re working from the command line, you can use the GitHub CLI to save time and avoid switching context. To learn more about GitHub CLI, see «About GitHub CLI.»

    To create an issue, use the gh issue create subcommand. To skip the interactive prompts, include the —body and the —title flags.

    gh issue create --title "My new issue" --body "Here are more details." 

    You can also specify assignees, labels, milestones, and projects.

    gh issue create --title "My new issue" --body "Here are more details." --assignee @me,monalisa --label "bug,help wanted" --project onboarding --milestone "learning codebase" 

    Creating an issue from a comment

    You can open a new issue from a comment in an issue or pull request. When you open an issue from a comment, the issue contains a snippet showing where the comment was originally posted.

    1. Navigate to the comment that you would like to open an issue from.
    2. In that comment, click

    Screenshot of a comment on a pull request. The kebab button is outlined in dark orange.

    .

    Creating an issue from code

    You can open a new issue from a specific line or lines of code in a file or pull request. When you open an issue from code, the issue contains a snippet showing the line or range of code you chose. You can only open an issue in the same repository where the code is stored.

    1. On GitHub.com, navigate to the main page of the repository.
    2. Locate the code you want to reference in an issue:
    3. To open an issue about code in a file, navigate to the file.
    4. To open an issue about code in a pull request, navigate to the pull request and click

    • To select a single line of code, click the line number to highlight the line.
    • To select a range of code, click the number of the first line in the range to highlight the line of code. Then, hover over the last line of the code range, press Shift , and click the line number to highlight the range.

    Screenshot of a file, with 8 lines selected. To the left of the first selected line, a button labeled with a kebab icon is outlined in dark orange.

    . In the dropdown menu, click Reference in new issue.

    Creating an issue from discussion

    People with triage permission to a repository can create an issue from a discussion.

    When you create an issue from a discussion, the contents of the discussion post will be automatically included in the issue body, and any labels will be retained. Creating an issue from a discussion does not convert the discussion to an issue or delete the existing discussion. For more information about GitHub Discussions, see «About discussions.»

      Under your repository or organization name, click

    Screenshot of the tabs in a GitHub repository. The

    Discussions.

    Screenshot of the sidebar in a discussion. The

    Create issue from discussion.

    Creating an issue from a project

    You can quickly create issues without leaving your project. When using a view that is grouped by a field, creating an issue in that group will automatically set the new issue’s field to the group’s value. For example, if you group your view by «Status», when you create an issue in the «Todo» group, the new issue’s «Status» will automatically be set to «Todo.» For more information about Projects, see «About Projects.»

    1. Navigate to your project.
    2. At the bottom of a table, group of items, or a column in board layout, click

    Screenshot showing the bottom row of a table view. The

    .

    Screenshot showing the

  • Click Create new issue.
  • At the top of the «Create new issue» dialog, select the repository where you want the new issue to be created.

    Creating an issue from a classic project note

    If you’re using a classic project to track and prioritize your work, you can convert notes to issues. For more information, see «About projects (classic)» and «Adding notes to a project (classic).»

    Creating an issue from a task list item

    Within an issue, you can use task lists to break work into smaller tasks and track the full set of work to completion. If a task requires further tracking or discussion, you can convert the task to an issue by hovering over the task and clicking

    in the upper-right corner of the task. For more information, see «About task lists.»

    Creating an issue from a URL query

    You can use query parameters to open issues. Query parameters are optional parts of a URL you can customize to share a specific web page view, such as search filter results or an issue template on GitHub. To create your own query parameters, you must match the key and value pair.

    Tip: You can also create issue templates that open with default labels, assignees, and an issue title. For more information, see «Using templates to encourage useful issues and pull requests.»

    You must have the proper permissions for any action to use the equivalent query parameter. For example, you must have permission to add a label to an issue to use the labels query parameter. For more information, see «Repository roles for an organization.»

    If you create an invalid URL using query parameters, or if you don’t have the proper permissions, the URL will return a 404 Not Found error page. If you create a URL that exceeds the server limit, the URL will return a 414 URI Too Long error page.

    Query parameter Example
    title https://github.com/octo-org/octo-repo/issues/new?labels=bug&title=New+bug+report creates an issue with the label «bug» and title «New bug report.»
    body https://github.com/octo-org/octo-repo/issues/new?title=New+bug+report&body=Describe+the+problem. creates an issue with the title «New bug report» and the comment «Describe the problem» in the issue body.
    labels https://github.com/octo-org/octo-repo/issues/new?labels=help+wanted,bug creates an issue with the labels «help wanted» and «bug».
    milestone https://github.com/octo-org/octo-repo/issues/new?milestone=testing+milestones creates an issue with the milestone «testing milestones.»
    assignees https://github.com/octo-org/octo-repo/issues/new?assignees=octocat creates an issue and assigns it to @octocat.
    projects https://github.com/octo-org/octo-repo/issues/new?title=Bug+fix&projects=octo-org/1 creates an issue with the title «Bug fix» and adds it to the organization’s project board 1.
    template https://github.com/octo-org/octo-repo/issues/new?template=issue_template.md creates an issue with a template in the issue body. The template query parameter works with templates stored in an ISSUE_TEMPLATE subdirectory within the root, docs/ or .github/ directory in a repository. For more information, see «Using templates to encourage useful issues and pull requests.»

    You can also use URL query parameters to fill custom text fields that you have defined in issue form templates. Query parameters for issue form fields can also be passed to the issue template chooser. For more information, see «Syntax for GitHub’s form schema.»

    Creating an issue from a code scanning alert

    Note: The tracking of code scanning alerts in issues is in beta and subject to change.

    This feature supports running analysis natively using GitHub Actions or externally using existing CI/CD infrastructure, as well as third-party code scanning tools, but not third-party tracking tools.

    If you’re using issues to track and prioritize your work, you can use issues to track code scanning alerts.

    For more information about creating issues to track code scanning alerts, see «Tracking code scanning alerts in issues using task lists.»

    Further reading

    8 things you didn’t know you could do with GitHub Copilot

    Developers all over the world are using GitHub Copilot to help speed up their development and increase developer productivity. With GitHub Copilot available to developers everywhere, we’ve found some fun and useful examples of how developers can use GitHub Copilot for things you may not be thinking about.

    GitHub Copilot logo.

    September 14, 2022

    Similar to other AI pair programming tools, GitHub Copilot is changing the game of software development. GitHub Copilot is an AI pair programmer that helps you write code faster with less work. We use the terms “AI pair programmer” and “Copilot” to imply that this tool cannot work without you–the developer! It’s not magic. It cannot read minds, although it sometimes feels like it can. However, by sharing code completion suggestions based on my project’s context and style conventions, GitHub Copilot increased my velocity and confidence as a programmer.

    The best part is you can use GitHub Copilot to increase your velocity and confidence as you code, too! In June 2022, we made GitHub Copilot available to all individual developers. You can learn how to get started with GitHub Copilot here.

    If it’s not reading minds and it’s not magic, then how does it work?

    Open AI Codex, a machine learning model that translates natural language into code, powers GitHub Copilot to draw context from comments and code to suggest individual lines and whole functions as you type. Codex is a version of GPT-3 (Generative Pre-trained Transformer 3) fine-tuned for programming tasks. Some of your favorite applications, like Duolingo, use GPT-3 for grammar correction.

    For more information on how GitHub Copilot works and its effectiveness, check out the following resources:

    • GitHub Copilot Research Recitation
    • How GitHub Copilot helps improve developer productivity
    • Research: quantifying GitHub Copilot’s impact on developer productivity and happiness

    Unexpected yet valuable GitHub Copilot use cases

    Once installed, the extension will suggest code as you type, but what next? How can you optimally benefit from the GitHub Copilot extension?

    First, I recommend writing clear, understandable comments to help your AI pair programmer generate desired solutions, but if you’re interested in exploring how to use GitHub Copilot in ways you might not be thinking of, we compiled some fun and valuable use cases we’ve seen in talking with developers. I hope that the following examples inspire you!

    1. Assisting non-native English speakers

    GitHub Copilot can understand other languages beyond English! This is helpful for developers of all backgrounds because programming languages are based on American English. For example, the CSS property color is based on American English, so it is unfamiliar for native British-English or Canadian-English speakers who use the spelling ‘colour’. Forgetting the correct spelling and syntax can often result in typos, unexpected errors, and lost time.

    In the GIF below, I wrote a comment in Spanish that says, “importar,” which translates to “import.” GitHub Copilot quickly completed my comment in Spanish and imported the necessary libraries as the comment described.

    Additionally, GitHub Copilot helps translate words from English to other languages. MilMikDev on Twitter used GitHub Copilot to translate an array of words ‘answer’, ‘question,’ and ‘date’ to various languages.

    2. Creating dictionaries with lookup data

    Martin Woodward, Vice President of Developer Relations at GitHub, shared this tip with us! GitHub Copilot is great at creating dictionaries of lookup data. Try it out by writing a comment instructing GitHub Copilot to create a dictionary of two-letter ISO country codes and their contributing country name. Writing a comment and the first few lines of code should help GitHub Copilot generated the desired results. See the GIF below for visual representation!

    3. Testing your code

    Writing tests is a vital yet sometimes tedious step in the software development lifecycle. Because GitHub Copilot excels in pattern recognition and pattern completion, it can speed up the process of writing unit tests, visual regression tests, and more.

    Check out these resources to learn more about using GitHub Copilot for testing:

    • Using GitHub Copilot to Automate Tests – An Applitools blog post by GitHub Star, Colby Fayock
    • Make Testing Easy with GitHub – An Applitools webinar by me
    • Writing Better Tests with AI and GitHub Copilot – A CodeCov blog post

    4. Matching patterns with regular expressions

    With GitHub Copilot, you can spend less time fiddling in a Regex playground or combing through StackOverflow to match character combinations in strings. Instead, you can write a comment or a function name to trigger GitHub Copilot’s suggestions.

    I used Copilot to help me validate a phone number!

    GitHub Copilot can help you remove white space from a string!

    5. Preparing for technical interviews

    While this may sound unorthodox, developers, including myself, use GitHub Copilot to study for interviews.

    Here’s the strategy:

    • First, I try to solve the problem without GitHub Copilot.
    • If I’m feeling extremely stuck and disheartened while solving the problem, I’ll activate GitHub Copilot and use it to generate ideas on how to solve the problem better.
    • Subsequently, I’ll delete the code GitHub Copilot generated, deactivate GitHub Copilot, and make another attempt at finding a solution with the new information in mind.

    By adopting this method, I maintain momentum when tempted to quit. Instead of giving up, I gain new perspectives even when I don’t have a mentor or peer to guide me. GitHub Copilot becomes my digital mentor. But, note, that I highly discourage activating GitHub Copilot during an interview (that’s cheating!).

    Interestingly, chess players take a similar approach when preparing for matches. It’s common for chess players to practice against AI engines to advance their skills. In the publication, Towards Data Science, Bharath K writes, “Artificial Intelligence has influenced the way in which chess games are played at the top level. Most of the Grandmasters and Super Grandmasters (rated at a FIDE above 2700) utilize these modern AI chess engines to analyze their games and the games of their competitors.” Learn more about the influence of AI chess engines here.

    If AI is helping chess players advance their skills, perhaps it can positively impact developers’ problem-solving skills by challenging them to think differently about solving a problem.

    You can learn more about leveraging GitHub Copilot to solve algorithmic problems here. In the example below, I wrote a comment that says, “write a binary search algorithm,” and the first line of my function. GitHub Copilot correctly completed the function.

    Screenshot of a code editor demonstrating that GitHub Copilot correctly completed a function based on the input of a comment and the first line of the function.

    6. Sending tweets

    Of course, you can simply use the Twitter application to send a Tweet, but it’s more fun to send a Tweet via your IDE! As a Developer Advocate, part of my job is to create demos. In a recent livestream, I had to demonstrate using Twitter API v2 with GitHub Copilot in Python, a language that I rarely use. GitHub Copilot saved the day and generated the code I needed after I wrote a few comments. Read my DEV post if you want to try sending a tweet with GitHub Copilot, too!

    Screenshot of a tweet from Rizel Scarlett that reads,

    7. Exiting Vim

    Developers who are new to Vim frequently wonder how to exit the editor. Struggling to exit vim is so common that it’s a meme on the internet! Since GitHub Copilot is available in Visual Studio Code, JetBrains, and Neovim, a forked version of Vim with additional features, you can exit NeoVim using GitHub Copilot. In the video below, Brian Douglas uses GitHub Copilot to exit NeoVim, by writing a comment that says, “How do I exit vim?”

    8. Navigating a new codebase with Copilot Labs

    GitHub Copilot Labs is a complementary extension that comes with GitHub Copilot access. The GitHub Next team developed GitHub Copilot Labs, an experimental sidebar, to help developers translate code from one programming language to another and get a step-by-step explanation of code snippets.

    There’s no easy method for building a mental model of a new codebase, but these two features within GitHub Copilot Labs can help. By translating code snippets to languages they’re more familiar with and using the ‘Explain’ feature to gain an understanding of the code, developers can better comprehend complex blocks of code.

    Closeup look at the results of Copilot

    Wrap-up

    As you’ve seen in the examples above, GitHub Copilot can help you be more productive in so many ways day to day (a lot of which we’re still discovering!), and I want to kindly remind you that GitHub Copilot is an AI pair programmer, so just as you would with your coworkers’ code or even your own, review the generated code before pushing it to production! While GitHub Copilot is powerful, sometimes it makes mistakes or refers to an outdated version of an API. Nevertheless, the team at GitHub continues to work hard and learn from our users to develop a better experience and generate better results with GitHub Copilot. I’m excited to witness and experience the evolution of AI pair programming tools. If you’re just as eager as me, sign up for GitHub Copilot today!

    Cant finish github sharing process что делать

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