differential-datalog | programming language for incremental computation | Database library

 by   vmware Java Version: v1.2.3 License: MIT

kandi X-RAY | differential-datalog Summary

kandi X-RAY | differential-datalog Summary

differential-datalog is a Java library typically used in Database applications. differential-datalog has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However differential-datalog build file is not available. You can download it from GitHub.

DDlog is a programming language for incremental computation. It is well suited for writing programs that continuously update their output in response to input changes. With DDlog, the programmer does not need to worry about writing incremental algorithms. Instead they specify the desired input-output mapping in a declarative manner, using a dialect of Datalog. The DDlog compiler then synthesizes an efficient incremental implementation. DDlog is based on Frank McSherry's excellent differential dataflow library.
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            kandi-support Support

              differential-datalog has a medium active ecosystem.
              It has 1231 star(s) with 110 fork(s). There are 25 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 126 open issues and 282 have been closed. On average issues are closed in 36 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of differential-datalog is v1.2.3

            kandi-Quality Quality

              differential-datalog has 0 bugs and 0 code smells.

            kandi-Security Security

              differential-datalog has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              differential-datalog code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              differential-datalog 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

              differential-datalog releases are available to install and integrate.
              differential-datalog has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              It has 22882 lines of code, 2036 functions and 275 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed differential-datalog and discovered the below as its top functions. This is intended to give you an instant insight into differential-datalog implemented functionality, and help decide if they suit your requirements.
            • Visit a join .
            • Generates the DDlog program .
            • Convert DDlogRecord to an object .
            • Converts this object to a typed object .
            • Translates the create index statement .
            • Creates an iterator that iterates over all elements that satisfy the given predicate .
            • Retrieves the list of entries matching the given indexes .
            • Checks if the given column reference is defined in the left relation .
            • Assigns a variable assignment .
            • Generates the string representation of the create table .
            Get all kandi verified functions for this library.

            differential-datalog Key Features

            No Key Features are available at this moment for differential-datalog.

            differential-datalog Examples and Code Snippets

            No Code Snippets are available at this moment for differential-datalog.

            Community Discussions

            QUESTION

            How do I preprocess a header file with macros to a non macro header file
            Asked 2020-Apr-09 at 15:58

            C newbie here. My use case is to give a header file posted here to the python library cffi so that I can bind to a C library. The header file in the previous link has macros. cffi only accepts a header file without macros, I think.

            • Is there a way to give a header file with macros to cffi by specifying any options?
            • If not, how do I preprocess that file so that I can give it to cffi? I tried gcc -E ddlog.h > ddlog-processed.h but when I ran the following code with cffi, it errors out.

            Steps to reproduce:

            • Download ddlog.h
            • pip install cffi
            • gcc -E ddlog.h > ddlog-processed.h
            • In a file build.py in the same folder as ddlog.h, place
            ...

            ANSWER

            Answered 2020-Apr-09 at 15:58

            There are two steps to using CFFI. The first one is to decide if you're using the ABI or the API mode---ffi.dlopen() versus ffi.set_source(); see https://cffi.readthedocs.io/en/latest/overview.html#abi-versus-api for details. Then you need to write the call to ffi.cdef() accordingly. I generally recommend to use the API mode, which is much more flexible at the cost of requiring a C compiler at install-time (just like if you wrote a standard CPython C extension module). In both modes, you should copy manually parts of the C header inside the call to ffi.cdef(); in the API mode you can leave many more details out and replace them with ... (dot-dot-dot).

            In neither of the two modes can you just paste a random C header making use of all the standard C features. Calling gcc -E just makes the problem even harder (but has been done in some cases with very large libraries, with lots of custom post-processing). The point of ffi.cdef() is that normally, you paste a simplified version of just the features you need.

            To answer your precise question:

            • macros that are just constants, like an integer, are directly supported. In API mode you can also write #define MY_CONSTANT ... with dot-dot-dot.

            • macros that work like functions are supported in the API mode (only) by using the following trick: write them in ffi.cdef() as if they were regular functions. That's enough to be able to call them.

            • for more complex cases, you might have to write a real C function that wraps the usage of the macro or macros as needed. Just invent a new function name, declare the function in ffi.cdef(), and finally implement the function directly in ffi.set_source().

            In the ABI mode, the last two cases cannot be supported at all---macros don't exist in the ABI any more.

            Source https://stackoverflow.com/questions/61088149

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

            Vulnerabilities

            No vulnerabilities reported

            Install differential-datalog

            You can download it from GitHub.
            You can use differential-datalog like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the differential-datalog component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

            Support

            Follow the tutorial for a step-by-step introduction to DDlog.DDlog language reference.DDlog command reference for writing and testing your own Datalog programs.How to use DDlog from Java.How to use DDlog from C.How to use DDlog from Go and Go API documentation.How to use DDlog from Rust (by example)Tutorial on profiling DDlog programsDDlog overview paper, Datalog 2.0 workshop, 2019.
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            gh repo clone vmware/differential-datalog

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