frr | The FRRouting Protocol Suite | TCP library

 by   FRRouting C Version: frr-8.5.1 License: Non-SPDX

kandi X-RAY | frr Summary

kandi X-RAY | frr Summary

frr is a C library typically used in Networking, TCP applications. frr has no bugs, it has no vulnerabilities and it has medium support. However frr has a Non-SPDX License. You can download it from GitHub, GitLab.

FRR is free software that implements and manages various IPv4 and IPv6 routing protocols. It runs on nearly all distributions of Linux and BSD and supports all modern CPU architectures.
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              frr has a medium active ecosystem.
              It has 2619 star(s) with 1055 fork(s). There are 158 watchers for this library.
              There were 1 major release(s) in the last 12 months.
              There are 407 open issues and 2670 have been closed. On average issues are closed in 72 days. There are 196 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of frr is frr-8.5.1

            kandi-Quality Quality

              frr has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              frr has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              frr releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

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            frr Key Features

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            frr Examples and Code Snippets

            No Code Snippets are available at this moment for frr.

            Community Discussions

            QUESTION

            Postman returns 401 with valid token
            Asked 2021-Jun-08 at 14:28

            I have 2 step auth fetching a Bearer token with which I am automatically populating a environmental variable {{authToken}} for use in a GET request. The GET request is correctly called with the token but I get a 401 returned thus -

            ...

            ANSWER

            Answered 2021-Jun-08 at 14:28

            Thanks @so-cal-cheesehead you are correct the API was faulty

            Source https://stackoverflow.com/questions/67722825

            QUESTION

            Transition from API results to Dropdown that affects a second dropdown - Semantic UI
            Asked 2021-Feb-09 at 13:45

            I want to change the 'Food name' from API results to a Dropdown. When I select a value from the 'Food name' (which comes from API results), the "Serving" dropdown is populated with options.

            Working - API results format:

            Working - Fills the "Serving" dropdown:

            And this is what I want to obtain:

            NOT WORKING - the Serving dropdown is not populated:

            The HTML is this:

            ...

            ANSWER

            Answered 2021-Feb-09 at 13:45

            I got it, I used this dropdown:

            Source https://stackoverflow.com/questions/66089099

            QUESTION

            replace dictionary values with list of values
            Asked 2020-Oct-28 at 16:19

            Here is my dictionary dict_1:

            ...

            ANSWER

            Answered 2020-Oct-28 at 16:12
            d = {}
            for s in list_info:
                key = s.split('-')[0]
                d.setdefault(key, []).append(s)
            

            Source https://stackoverflow.com/questions/64576598

            QUESTION

            Convert JSON data to Pandas DataFrame
            Asked 2020-Sep-02 at 18:21
            "{\".travis.yml\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/client-mac/com.google.code.fleetspeak.plist\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"mol123\"]}, \"count\": 1}, \"fleetspeak/src/client/client/client.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"mol123\"]}, \"count\": 1}, \"fleetspeak/src/client/client_test.go\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"Ben Galehouse\", \"mol123\"]}, \"count\": 2}, \"fleetspeak/src/client/entry/entry_unix.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"mol123\"]}, \"count\": 1}, \"fleetspeak/src/client/entry/entry_windows.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"mol123\"]}, \"count\": 1}, \"fleetspeak/src/client/entry/wait_unix.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"mol123\"]}, \"count\": 1}, \"fleetspeak/src/client/entry/wait_windows.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"mol123\"]}, \"count\": 1}, \"fleetspeak/src/client/services.go\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"Ben Galehouse\", \"mol123\"]}, \"count\": 2}, \"fleetspeak/src/client/socketservice/checks/sock_checks_windows.go\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"Ben Galehouse\", \"Brendan Jackman\"]}, \"count\": 5}, \"fleetspeak/src/e2etesting/README.md\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/e2etesting/balancer/balancer.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 2}, \"fleetspeak/src/e2etesting/e2etest.sh\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 2}, \"fleetspeak/src/e2etesting/localtesting/end_to_end_test.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/e2etesting/run_end_to_end_tests.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 5}, \"fleetspeak/src/e2etesting/setup/setup_components.go\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"mol123\", \"Alexandr Tsaplin\"]}, \"count\": 7}, \"fleetspeak/src/e2etesting/tests/end_to_end_tests.go\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"mol123\", \"Alexandr Tsaplin\"]}, \"count\": 5}, \"fleetspeak/src/inttesting/frr/frr.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/inttesting/frr/proto/fleetspeak_frr/frr.pb.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/inttesting/frr/proto/fleetspeak_frr/frr.proto\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/inttesting/integrationtest/frr.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"tsehori\"]}, \"count\": 1}, \"fleetspeak/src/server/comms.go\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"Ben Galehouse\", \"mol123\"]}, \"count\": 4}, \"fleetspeak/src/server/components/components.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/server/components/prometheus/prometheus.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"tsehori\"]}, \"count\": 1}, \"fleetspeak/src/server/components/proto/fleetspeak_components/config.pb.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/server/components/proto/fleetspeak_components/config.proto\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/server/internal/services/manager.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"tsehori\"]}, \"count\": 1}, \"fleetspeak/src/server/server.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"fleetspeak/src/server/servertests/comms_test.go\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"Ben Galehouse\", \"mol123\"]}, \"count\": 4}, \"fleetspeak/src/server/stats.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"tsehori\"]}, \"count\": 1}, \"fleetspeak/src/server/stats/collector.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"tsehori\"]}, \"count\": 1}, \"fleetspeak/test.sh\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"frr_python/frr_server.py\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"frr_python/setup.py\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"go.mod\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"mol123\"]}, \"count\": 1}, \"go.sum\": {\"auth_count\": 2, \"authors\": {\"py/set\": [\"Ben Galehouse\", \"mol123\"]}, \"count\": 3}, \"terraform/README.md\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 2}, \"terraform/cloudtesting/end_to_end_test.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"terraform/fleetspeak_configurator/build_configs.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 3}, \"terraform/fs_client_start.sh\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 2}, \"terraform/fs_server_start.sh\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"terraform/main.tf\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 3}, \"terraform/main_vm_start.sh\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 4}, \"terraform/master_server_start.sh\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 1}, \"terraform/test_runner/run_tests.go\": {\"auth_count\": 1, \"authors\": {\"py/set\": [\"Alexandr Tsaplin\"]}, \"count\": 3}}"
            
            ...

            ANSWER

            Answered 2020-Sep-02 at 18:21

            You can read JSON into a dataframe, and then convert authors from lists to strings:

            Source https://stackoverflow.com/questions/63711152

            QUESTION

            Large difference in performance on validation and test data
            Asked 2020-Aug-27 at 09:06

            I have scraped some data from spotify to see if I can classify the music genre of different songs. I have split my data up into a test set and a remaining set, which I have then further divided into training and validation set.

            When I run the model (I try to classify between 112 genres) I get 30% accuracy in the validation set. Of course this is not great, but to be expected with 112 genres and limited data. What really confuses me is that when I apply the model to the test data, accuracy goes down to 1%.

            I am not sure why that is: as far as I can see the validation and test data should be comparable. I train the model on the training data which should be completely independent.

            I must be making some mistake either allowing the model to peak into the validation data (better performance there) or mess up my test data.

            Or maybe applying the model twice messes things up?

            Any idea what could be going on or how to debug it?

            Thanks a lot! Franka

            ...

            ANSWER

            Answered 2020-Aug-27 at 09:06

            The problem that I see is that you're encoding the train and test labels using pd.factorize. Since you're using pd.factorize on y and y_test independently, the resulting encodings will not correspond to one another. You want to use a LabelEncoder, so that when you fit the encoder using the train data, you then transform y_test using the same encoding scheme.

            Here's an example to illustrate this:

            Source https://stackoverflow.com/questions/63612406

            QUESTION

            Connecting Docker Container to Home Network
            Asked 2019-Dec-07 at 18:23

            I am running some frr (free range routing) and ceos (Arista) containers on an "Ubuntu Docker Host" which is running on Virtual Box on Windows 10.

            I created a macvlan network (net3) and tied it to enp interface of Ubuntu and connected my containers to it. However I cannot access my containers using their interfaces connected to the macvlan network. I read about some limitations about network spaces between host and containers and saw macvlan network type as the solution to overcome those limitations. However it did not work.

            Since my container is a router with multiple interfaces, I was expecting I can connect my new net3 network to my container. It would appear as a new new interface (it did) and when I assign an IP address from my home network to this interface, my router would be able to communicate to the outside directly using this interface`s IP address and bypass any sort of firewalling, NAT etc.

            I know that we can use bridge networks connected to default docker0 network and which will then NAT outgoing connections from container and accept incoming connections if we publish a port etc. However what I want is to have a container with 2 interfaces, where one interface is in docker0 bridge and the other one is connected to the home network with an IP address from home network, which will expose it to the outside completely like a physical machine or my docket host Ubuntu VM.

            ...

            ANSWER

            Answered 2019-Dec-07 at 18:23

            I think i found a way to make this work.

            1. added a new bridged network
            2. added an iptables rule permitting traffic destined to this new bridged network at "Forward Chain".

            What I do not understand now is that although the routing is disabled on the host, this "forward" rule has an impact on the traffic and it is actually working. I also did not need to add a rule traffic for return traffic. Default rules added by Docker during creation of the container seem to take care of this direction.

            Source https://stackoverflow.com/questions/58373487

            QUESTION

            Kotlin regexp matching parenthesis content
            Asked 2019-Dec-05 at 22:49

            I'm trying to match parenthesis content using Kotlin.

            I found that regex should be /\(([^)]+)\)/ but can't have it working in Kotlin.

            ...

            ANSWER

            Answered 2019-Dec-03 at 23:44

            You need to remove the initial and trailing slashes as you need to define the regex pattern using a string literal, and you need to only capture any chars other than parentheses inside parentheses and use findAll rather than matches to find all matches.

            Use

            Source https://stackoverflow.com/questions/59166654

            QUESTION

            How do i send response back to Gateway interface?
            Asked 2019-Sep-27 at 14:44

            im currently getting this error :

            ...

            ANSWER

            Answered 2019-Sep-27 at 14:44

            The gateway is a request-reply component and for correlation between them a replyChannel header with a TemporaryReplyChannel is populated during sending a message into a requestChannel.

            This is clearly explained in the Reference Manual.

            So, even if you provide that replyChannel = "output" and use it somewhere downstream, a replyChannel must preserve in the headers.

            Your problem code is here in the @Transformer:

            Source https://stackoverflow.com/questions/58134333

            QUESTION

            SQL Dynamic Grouping or Pivot and subtotals
            Asked 2019-Sep-18 at 17:45

            I need to create a dynamic grouping table in SQL that would look similar to this:

            ...

            ANSWER

            Answered 2019-Sep-18 at 17:35

            Oracle GROUP BY supports ROLLUP and GROUPING SETS that will provide the broader aggregations for you:

            So your base query looks like:

            Source https://stackoverflow.com/questions/57996228

            QUESTION

            MS Cognitive service Face API confidence scores changing with releases/learning?
            Asked 2019-Sep-10 at 17:43

            We've gone through an extensive exercise comparing facial recognition/matching providers using our local facial image data sets.

            MS Cognitive services came out tops in terms of False Rejects Rate (FRR) for a given False Accept Rate (FAR). We are busy deciding on pass thresholds for different image type matching (selfie vs document, etc.).

            The question is, if we are using a specific version (https://{endpoint}/face/v1.0/) and fixed parameters for the Detect and Verify endpoints (recognitionModel = recognition_02 and detectionModel = detection_02), can we expect to see a change in the confidence score for the same two images over time or whenever Microsoft releases a new version? Our concern is that we pick a pass threshold based on our test results and current confidence scores, and then the scores change in future due to machine-learning/releases, meaning we would continuously have to re-adjust our thresholds.

            https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523a

            ...

            ANSWER

            Answered 2019-Sep-10 at 17:43

            I think it's a good question about the stability of model function of MS Azure Cognitive Services like Face API. Based on my knowledge for Machine Learning, there are some possible reason that will cause the issue as you said, as below.

            1. The structure of Machine Learning Model will be changed with the service upgrading.
            2. The upgraded service version start to support a new API with new parameters which be different from the current one.

            Sure, I think the two above will absolute possibly happen. However, there are three reason let me believe that will not effect yours too much.

            1. MS as a big cloud provider in the marketplace, for the same application scenario, it will make sure the upgraded service return the same output date for the same input data as the previous one, even to upgrade the ML model for improving better performance. Then, MS can keep the regular customers continous to use and pay for their Azure subscriptions.
            2. Except some preview services, MS as a success IT company, it will keep its service features compatible with the previous one, like MS Office 365 still be compatible with the older version.
            3. If the incompatibility really happen in the new version, I think MS will give the migration guide for users of the older version.

            Considering for the worst case, technically speaking, there are many opensource face recognization solutions as the backup for you. It's nothing really matter.

            Source https://stackoverflow.com/questions/57466452

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

            Vulnerabilities

            No vulnerabilities reported

            Install frr

            For source tarballs, see the [releases page](https://github.com/FRRouting/frr/releases). For Debian and its derivatives, use the APT repository at [https://deb.frrouting.org/](https://deb.frrouting.org/). Instructions on building and installing from source for supported platforms may be found in the [developer docs](http://docs.frrouting.org/projects/dev-guide/en/latest/building.html). Once installed, please refer to the [user guide](http://docs.frrouting.org/) for instructions on use.

            Support

            The FRRouting email list server is located [here](https://lists.frrouting.org/listinfo) and offers the following public lists:. | Topic | List | |-------------------|------------------------------| | Development | dev@lists.frrouting.org | | Users & Operators | frog@lists.frrouting.org | | Announcements | announce@lists.frrouting.org |. For chat, we currently use [Slack](https://frrouting.slack.com). You can join by clicking the "Slack" link under the [Participate](https://frrouting.org/#participate) section of our website.
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