pifpaf | Python fixtures and daemon managing tools | Key Value Database library

 by   jd Python Version: 3.1.5 License: Apache-2.0

kandi X-RAY | pifpaf Summary

pifpaf is a Python library typically used in Database, Key Value Database applications. pifpaf has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install pifpaf' or download it from GitHub, PyPI.
Python fixtures and daemon managing tools for functional testing
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                      kandi-support Support

                        summary
                        pifpaf has a low active ecosystem.
                        summary
                        It has 171 star(s) with 29 fork(s). There are 9 watchers for this library.
                        summary
                        It had no major release in the last 12 months.
                        summary
                        There are 11 open issues and 22 have been closed. On average issues are closed in 71 days. There are 5 open pull requests and 0 closed requests.
                        summary
                        It has a neutral sentiment in the developer community.
                        summary
                        The latest version of pifpaf is 3.1.5
                        pifpaf Support
                          Best in #Key Value Database
                            Average in #Key Value Database
                            pifpaf Support
                              Best in #Key Value Database
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                                  kandi-Quality Quality

                                    summary
                                    pifpaf has 0 bugs and 0 code smells.
                                    pifpaf Quality
                                      Best in #Key Value Database
                                        Average in #Key Value Database
                                        pifpaf Quality
                                          Best in #Key Value Database
                                            Average in #Key Value Database

                                              kandi-Security Security

                                                summary
                                                pifpaf has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
                                                summary
                                                pifpaf code analysis shows 0 unresolved vulnerabilities.
                                                summary
                                                There are 0 security hotspots that need review.
                                                pifpaf Security
                                                  Best in #Key Value Database
                                                    Average in #Key Value Database
                                                    pifpaf Security
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                                                        Average in #Key Value Database

                                                          kandi-License License

                                                            summary
                                                            pifpaf is licensed under the Apache-2.0 License. This license is Permissive.
                                                            summary
                                                            Permissive licenses have the least restrictions, and you can use them in most projects.
                                                            pifpaf License
                                                              Best in #Key Value Database
                                                                Average in #Key Value Database
                                                                pifpaf License
                                                                  Best in #Key Value Database
                                                                    Average in #Key Value Database

                                                                      kandi-Reuse Reuse

                                                                        summary
                                                                        pifpaf releases are not available. You will need to build from source code and install.
                                                                        summary
                                                                        Deployable package is available in PyPI.
                                                                        summary
                                                                        Build file is available. You can build the component from source.
                                                                        summary
                                                                        pifpaf saves you 1228 person hours of effort in developing the same functionality from scratch.
                                                                        summary
                                                                        It has 2775 lines of code, 158 functions and 38 files.
                                                                        summary
                                                                        It has medium code complexity. Code complexity directly impacts maintainability of the code.
                                                                        pifpaf Reuse
                                                                          Best in #Key Value Database
                                                                            Average in #Key Value Database
                                                                            pifpaf Reuse
                                                                              Best in #Key Value Database
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                                                                                  Top functions reviewed by kandi - BETA
                                                                                  kandi has reviewed pifpaf and discovered the below as its top functions. This is intended to give you an instant insight into pifpaf implemented functionality, and help decide if they suit your requirements.
                                                                                  • Setup the Ceph driver
                                                                                    • Ensure Xattr is supported
                                                                                    • Puts an environment variable
                                                                                    • Execute a shell command
                                                                                  • Sets up the configuration
                                                                                    • Find a configuration file
                                                                                  • Setup the driver
                                                                                    • Render a template
                                                                                  • Setup kafka server
                                                                                    • Find an executable
                                                                                  • Setup the Redis server
                                                                                  • Set up configuration
                                                                                  • Set up the mysql connection
                                                                                  • Initialize the engine
                                                                                  • Setup the Elasticsearch driver
                                                                                  • Setup the zoo server
                                                                                  • Sets up the connection
                                                                                  • Setup the PostgreSQL server
                                                                                  • Set up the memcached driver
                                                                                  • Setup the qdrouterd
                                                                                  • Setup the Aodh driver
                                                                                  • Set up CouchDB
                                                                                  • Terminate the parent process
                                                                                  • Setup RabbitMQ
                                                                                  • Start the server
                                                                                  • Initialize Keystone
                                                                                  Get all kandi verified functions for this library.
                                                                                  Get all kandi verified functions for this library.

                                                                                  pifpaf Key Features

                                                                                  Python fixtures and daemon managing tools for functional testing

                                                                                  pifpaf Examples and Code Snippets

                                                                                  No Code Snippets are available at this moment for pifpaf.
                                                                                  Community Discussions

                                                                                  Trending Discussions on Key Value Database

                                                                                  Laravel how to "properly" store & retrieve models in a Redis hash
                                                                                  chevron right
                                                                                  Can compacted Kafka topic be used as key-value database?
                                                                                  chevron right

                                                                                  QUESTION

                                                                                  Laravel how to "properly" store & retrieve models in a Redis hash
                                                                                  Asked 2021-Jul-08 at 17:02

                                                                                  I'm developing a Laravel application & started using Redis as a caching system. I'm thinking of caching the data of all of a specific model I have, as a user may make an API request that this model is involved in quite often. Would a valid solution be storing each model in a hash, where the field is that record's unique ID, and the values are just the unique model's data, or is this use case too complicated for a simple key value database like Redis? I"m also curious as to how I would create model instances from the hash, when I retrieve all the data from it. Replies are appreciated!

                                                                                  ANSWER

                                                                                  Answered 2021-Jul-08 at 17:02

                                                                                  Short answer: Yes, you can store a model, or collections, or basically anything in the key-value caching of Redis. As long as the key provided is unique and can be retraced. Redis could even be used as a primary database.

                                                                                  Long answer

                                                                                  Ultimately, I think it depends on the implementation. There is a lot of optimization that can be done before someone can/should consider caching all models. For "simple" records that involve large datasets, I would advise to first optimize your queries and code and check the results. Examples:

                                                                                  1. Select only data you need, not entire models.
                                                                                  2. Use the Database Query Builder for interacting with the database when targeting large records, rather than Eloquent (Eloquent is significantly slower due to the Active Record pattern).
                                                                                  3. Consider using the toBase() method. This retrieves all data but does not create the Eloquent model, saving precious resources.
                                                                                  4. Use tools like the Laravel debugbar to analyze and discover potential long query loads.

                                                                                  For large datasets that do not change often or optimization is not possible anymore: caching is the way to go!

                                                                                  There is no right answer here, but maybe this helps you on your way! There are plenty of packages that implement similar behaviour.

                                                                                  Source https://stackoverflow.com/questions/68305332

                                                                                  QUESTION

                                                                                  Can compacted Kafka topic be used as key-value database?
                                                                                  Asked 2020-Nov-25 at 01:12

                                                                                  In many articles, I've read that compacted Kafka topics can be used as a database. However, when looking at the Kafka API, I cannot find methods that allow me to query a topic for a value based on a key.

                                                                                  So, can a compacted Kafka topic be used as a (high performance, read-only) key-value database?

                                                                                  In my architecture I want to feed a component with a compacted topic. And I'm wondering whether that component needs to have a replica of that topic in its local database, or whether it can use that compacted topic as a key value database instead.

                                                                                  ANSWER

                                                                                  Answered 2020-Nov-25 at 01:12

                                                                                  Compacted kafka topics themselves and basic Consumer/Producer kafka APIs are not suitable for a key-value database. They are, however, widely used as a backstore to persist KV Database/Cache data, i.e: in a write-through approach for instance. If you need to re-warmup your Cache for some reason, just replay the entire topic to repopulate.

                                                                                  In the Kafka world you have the Kafka Streams API which allows you to expose the state of your application, i.e: for your KV use case it could be the latest state of an order, by the means of queriable state stores. A state store is an abstraction of a KV Database and are actually implemented using a fast KV database called RocksDB which, in case of disaster, are fully recoverable because it's full data is persisted in a kafka topic, so it's quite resilient as to be a source of the data for your use case.

                                                                                  Imagine that this is your Kafka Streams Application architecture:

                                                                                  To be able to query these Kafka Streams state stores you need to bundle an HTTP Server and REST API in your Kafka Streams applications to query its local or remote state store (Kafka distributes/shards data across multiple partitions in a topic to enable parallel processing and high availability, and so does Kafka Streams). Because Kafka Streams API provides the metadata for you to know in which instance the key resides, you can surely query any instance and, if the key exists, a response can be returned regardless of the instance where the key lives.

                                                                                  With this approach, you can kill two birds in a shot:

                                                                                  1. Do stateful stream processing at scale with Kafka Streams
                                                                                  2. Expose its state to external clients in a KV Database query pattern style

                                                                                  All in a real-time, highly performant, distributed and resilient architecture.

                                                                                  The images were sourced from a wider article by Robert Schmid where you can find additional details and a prototype to implement queriable state stores with Kafka Streams.

                                                                                  Notable mention:

                                                                                  If you are not in the mood to implement all of this using the Kafka Streams API, take a look at ksqlDB from Confluent which provides an even higher level abstraction on top of Kafka Streams just using a cool and simple SQL dialect to achieve the same sort of use case using pull queries. If you want to prototype something really quickly, take a look at this answer by Robin Moffatt or even this blog post to get a grip on its simplicity.

                                                                                  While ksqlDB is not part of the Apache Kafka project, it's open-source, free and is built on top of the Kafka Streams API.

                                                                                  Source https://stackoverflow.com/questions/64996101

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

                                                                                  Vulnerabilities

                                                                                  No vulnerabilities reported

                                                                                  Install pifpaf

                                                                                  You can install using 'pip install pifpaf' or download it from GitHub, PyPI.
                                                                                  You can use pifpaf 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 .
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                                                                                  Install
                                                                                • PyPI

                                                                                  pip install pifpaf

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                                                                                  gh repo clone jd/pifpaf

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