Doppelganger | Smart contract mocking tool | Cryptocurrency library

 by   EthWorks TypeScript Version: Current License: MIT

kandi X-RAY | Doppelganger Summary

kandi X-RAY | Doppelganger Summary

Doppelganger is a TypeScript library typically used in Blockchain, Cryptocurrency, Ethereum applications. Doppelganger has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Smart contract mocking tool
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              Doppelganger has a low active ecosystem.
              It has 58 star(s) with 5 fork(s). There are 6 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 3 open issues and 1 have been closed. On average issues are closed in 4 days. There are 4 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of Doppelganger is current.

            kandi-Quality Quality

              Doppelganger has no bugs reported.

            kandi-Security Security

              Doppelganger has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              Doppelganger is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              Doppelganger releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.

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            Doppelganger Key Features

            No Key Features are available at this moment for Doppelganger.

            Doppelganger Examples and Code Snippets

            No Code Snippets are available at this moment for Doppelganger.

            Community Discussions

            QUESTION

            Does the Bizarro pipe ->.; have disadvantages making it not recommended for use?
            Asked 2021-Jun-08 at 07:01

            Since R-Version 4.1.0 the pipe |> is in the stable version. When passing the lhs into an argument other than the first the Examples of the manual show:

            ...

            ANSWER

            Answered 2021-Jun-07 at 09:16

            The main issue with the bizarro pipe is that it creates hidden side-effects and makes it easier to create subtle bugs. It decreases code maintainability.

            The issue, of course, is the persistent existence of . makes it all too easy to accidentally refer to this value later down the line: its presence masks mistakes if you at some point “forget” to assign to it and think you did. It’s easy to dismiss this possibility but such errors are fairly common and, worse, very non-obvious: you won’t get an error message, you’ll just get a wrong result. By contrast, if you forget the pipe symbol somewhere, you’ll get an immediate error message.

            Worse, the bizarro pipe hides this error-prone side-effect in two different ways. First, because it makes the assignment non-obvious. I’ve argued previously that -> assignment shouldn’t be used since it hides a side-effect, and side-effects should be made syntactically obvious (the side-effect here is assignment, and it should happen where it’s immediately spotted: in the first column of the expression, not hidden away at its end). This is a fundamental objection to the use of -> (or any other attempt to mask side-effects), not limited to the bizarro pipe.

            And because . is by default hidden (from ls and from the inspector pane in IDEs), this makes it even easier to accidentally depend on it.

            Therefore, if you want to assign to a value instead of using a pipe, just do that. But:

            1. Perform right-to-left assignment, i.e. use name = value or name <- value, not value -> name.
            2. Use a descriptive name.

            I can’t stress enough that this is an actual source of subtle bugs — don’t underestimate it!

            Another issue is that its use breaks editor support for auto-formatting code. This is a “solvable issue” in some IDEs via plugins but the solution, as it were, solves an issue that should not even exist. To clarify what I mean, if you’re using the bizarro pipe you’d presumably want a hanging indent, i.e. something along these lines:

            Source https://stackoverflow.com/questions/67868289

            QUESTION

            Pytorch GAN model doesn't train: matrix multiplication error
            Asked 2021-Apr-18 at 14:32

            I'm trying to build a basic GAN to familiarise myself with Pytorch. I have some (limited) experience with Keras, but since I'm bound to do a larger project in Pytorch, I wanted to explore first using 'basic' networks.

            I'm using Pytorch Lightning. I think I've added all necessary components. I tried passing some noise through the generator and the discriminator separately, and I think the output has the expected shape. Nonetheless, I get a runtime error when I try to train the GAN (full traceback below):

            RuntimeError: mat1 and mat2 shapes cannot be multiplied (7x9 and 25x1)

            I noticed that 7 is the size of the batch (by printing out the batch dimensions), even though I specified batch_size to be 64. Other than that, quite honestly, I don't know where to begin: the error traceback doesn't help me.

            Chances are, I made multiple mistakes. However, I'm hoping some of you will be able to spot the current error from the code, since the multiplication error seems to point towards a dimensionality problem somewhere. Here's the code.

            ...

            ANSWER

            Answered 2021-Apr-18 at 14:32

            This multiplication problem comes from the DoppelDiscriminator. There is a linear layer

            Source https://stackoverflow.com/questions/67146595

            QUESTION

            Canonical workflow for python packaging and GitHub
            Asked 2020-Nov-18 at 13:12

            I'm working on a solo project which I published to PyPi. Now that I've installed it with pip rather than using it from my git repo, what is the best-practice for continuing development ?

            I've tried two approaches till now:

            1. The naivete: edit scripts in site-packages folder, test them, once finalized, copy to repo and push( and build, publish etc)
            2. The doppelganger: make a (sparse) repo to track the scripts in site packages, push whenever. Once ready to publish, go to the folder with the full repo, pull and then build>publish.

            Now, 1. is too clunky, while 2. leaves me thoroughly unsatisfied. I was thinking of using bash tricks to streamline 2., but I thought that the sages here might have something much more streamlined, so I ask.

            Thank You!

            ...

            ANSWER

            Answered 2020-Nov-18 at 13:12

            For development you will still want to get and edit source code from the git repository, not from PyPi.

            For example, if your git repository lived under .../src/myproject/, I would run pip install . inside myproject. This emulates an installation in the exact same way that pip install myproject=={version} would if it downloaded from PyPi. (copies the code to site-packages)

            Even better for development is pip install -e ., which sets a symbolic link from site-packages back to your source directory. So while it looks like your project is installed in your venv, it's actually just using the source code from your git repo folder.

            In general the downloads from PyPi are for users of your script, not contributors.

            Let me know in the comments if you want me to expand on any of this.

            Source https://stackoverflow.com/questions/64893450

            QUESTION

            Compare each row of Pandas df1 with every row within df2 and return string value from closest matching column
            Asked 2020-Apr-12 at 08:42

            I have two data frames.

            df1 includes 4 men and 4 women with their weight and height (inches).

            ...

            ANSWER

            Answered 2020-Apr-12 at 08:35

            First is necessary distinguish men and women, here is used new column with repeat 4 times m and f. Then is used DataFrame.merge with outer join by new column for all combinations and created new columns for differences, last column is sum of them. then sorting by 3 columns by DataFrame.sort_values, so first row per groups by A and g are filtered by DataFrame.drop_duplicates:

            Source https://stackoverflow.com/questions/61168546

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install Doppelganger

            To start using with npm, type:. Doppelganger is currently developed to work with ethers-js exclusively. Support for other framework will be added in a future version.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            CLONE
          • HTTPS

            https://github.com/EthWorks/Doppelganger.git

          • CLI

            gh repo clone EthWorks/Doppelganger

          • sshUrl

            git@github.com:EthWorks/Doppelganger.git

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