mbdbls | Parse Manifest.mbdb files from iTunes backup directories | Continuous Backup library

 by   halpomeranz Python Version: Current License: No License

kandi X-RAY | mbdbls Summary

kandi X-RAY | mbdbls Summary

mbdbls is a Python library typically used in Backup Recovery, Continuous Backup applications. mbdbls has no bugs, it has no vulnerabilities and it has low support. However mbdbls build file is not available. You can download it from GitHub.

Parse Manifest.mbdb files from iTunes backup directories
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            kandi-support Support

              mbdbls has a low active ecosystem.
              It has 15 star(s) with 7 fork(s). There are 4 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              mbdbls has no issues reported. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of mbdbls is current.

            kandi-Quality Quality

              mbdbls has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              mbdbls does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              mbdbls releases are not available. You will need to build from source code and install.
              mbdbls has no build file. You will be need to create the build yourself to build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed mbdbls and discovered the below as its top functions. This is intended to give you an instant insight into mbdbls implemented functionality, and help decide if they suit your requirements.
            • Processes the file into a dictionary .
            • Return a string representation of a file .
            • Return a mode modifier .
            • Get an integer from the data at offset .
            • Get a string value from a given offset .
            • Returns a time string .
            Get all kandi verified functions for this library.

            mbdbls Key Features

            No Key Features are available at this moment for mbdbls.

            mbdbls Examples and Code Snippets

            No Code Snippets are available at this moment for mbdbls.

            Community Discussions

            QUESTION

            How to disable azure cosmos db continious backup
            Asked 2022-Feb-22 at 10:59

            I enabled the Azure cosmos DB continuous backup for one of my Cosmos DBs.
            How can I disable it? It just says you have successfully enrolled in continuous backup.

            ...

            ANSWER

            Answered 2022-Feb-22 at 10:59

            I am not sure if you have seen this message in the portal when you created the account/also mentioned in the doc

            "You will not be able to switch between the backup policies after the account has been created"

            since you need to select either "Periodic" or "Continuous" at the creation of Cosmos Account, it becomes mandatory.

            Update:

            You will not see the above in portal anymore, you can Switch from "Periodic" to "Continous" on an existing account and that cannot be reverted. You can read more here.

            Source https://stackoverflow.com/questions/69347197

            QUESTION

            Consistency of Continuous backup of Azure Cosmos DB
            Asked 2021-Nov-25 at 17:15

            What would be the consistency of the continuous backup of the write region if the database is using bounded staleness consistency? Will it be equivalent to strong consistent data assuming no failovers happened?

            Thanks Guru

            ...

            ANSWER

            Answered 2021-Nov-25 at 17:15

            Backups made from any secondary region will have data consistency defined by the guarantees provided by the consistency level chosen. In the case of strong consistency, all secondary region backups will have completely consistent data.

            Bounded staleness will have data that may have stale or inconsistent data inside the defined staleness window (minimum 300 seconds or 100k writes). Outside of that staleness window the data will be consistent.

            Data for the weaker consistency levels will have no guarantees for consistency from backups in secondary regions.

            Source https://stackoverflow.com/questions/70099953

            QUESTION

            Mongo atlas recommends cloud provider snaphots for backup - Is it effective?
            Asked 2020-May-19 at 10:12

            MongoDB has deprecated the continuous back up of data. It has recommended using CPS (Cloud provider snapshots). As far as I understood, snapshots isn't really going to be effective compared to continuous backup coz, if system breaks, then we can only be able to restore the data till the previous snapshot which isn't gonna make the database up-to-date or close to it atleast.

            Am I missing something here in my understanding?

            ...

            ANSWER

            Answered 2020-May-19 at 10:12

            Cloud provider snapshots can be combined with point in time restore to give the recovery point objective you require. With oplog based restores you can get granularity of one second.

            Source https://stackoverflow.com/questions/61886736

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

            Vulnerabilities

            No vulnerabilities reported

            Install mbdbls

            You can download it from GitHub.
            You can use mbdbls like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            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 .
            Find more information at:

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            CLONE
          • HTTPS

            https://github.com/halpomeranz/mbdbls.git

          • CLI

            gh repo clone halpomeranz/mbdbls

          • sshUrl

            git@github.com:halpomeranz/mbdbls.git

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