Metadata-Version: 2.1
Name: resilient-exporters
Version: 0.1.1
Summary: A package to export data to databases resiliently.
Home-page: https://github.com/arbfay/resilient-exporters.git
Author: Fayçal Arbai
Author-email: arbai.faycal@gmail.com
License: MIT License
Project-URL: Documentation, https://resilient-exporters.readthedocs.io
Project-URL: Source, https://github.com/arbfay/resilient-exporters.git
Description: # Resilient Exporters
        ![PyPI](https://img.shields.io/pypi/v/resilient-exporters?logo=pypi&logoColor=white&style=for-the-badge)
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        ![Python Version](https://img.shields.io/badge/3.6+%20-%2314354C.svg?label=PYTHON&style=for-the-badge&logo=python&logoColor=white)
        
        Resilient-exporters abstracts away common tasks when sending or saving data from an application. It has been designed to send data to different targets and manage common issues for applications running on edge devices such as a Raspberry Pi or Nvidia Jetson Nano:
        - Internet connection interruptions;
        - Highly variable frequency of data transfers;
        
        If a connection is lost, it automatically saves the data and retries later when the connection is recovered and when a new request to send data is made. To avoid consuming too much memory or disk space, it has a specific configurable flush.
        
        If an application wants to send more data than is momentally manageable, it multiplies the transmission jobs (using multithreading, if available) and saves the data (queuing), to avoid back-pressure and reducing the application's speed.
        
        Of course, it can break if:
        - the data to transmit is _almost always_ more important than the available bandwidth;
        - the interruptions are too long compared to the available memory or disk space;
        
        We have designed it particularly for a Raspberry Pi 3B+ device running a Linux distribution.
        
        ## Installation
        To use the package:
        ```
        pip install resilient-exporters
        ```
        ### Dev installation
        If you'd like to have a editable, up-to-date version of the files, do:
        ```
        git clone https://github.com/arbfay/resilient-exporters.git && \
        pip install -e resilient-exporters/ && \
        pip install -r resilient-exporters/dev_requirements.txt
        ```
        
        ## Usage
        Currently supported:
        - Text file
        - MongoDB
        - ElasticSearch
        
        Some features for some exporters might be missing. Raise an issue on Github to ask for an implementation and help improve the package.
        
        ### Store in a file
        ```python
        from resilient_exporters import FileExporter
        
        exporter = FileExporter(target_file="mydata.txt",
                                max_lines=1000,
                                keep_new_data=True)
        
        mydata = ["value1", "value2"]
        exporter.send(mydata)
        ```
        
        ### To MongoDB
        ```python
        from resilient_exporters import MongoDBExporter
        
        exporter = MongoDBExporter(target_ip="127.0.0.1",
                                   target_port=27017,
                                   username="username",
                                   password="password",
                                   default_db="my_db",
                                   default_collection="my_collection")
        
        mydata = {"field1": "value1"}
        exporter.send(mydata)
        ```
        
        ### To ElasticSearch
        ```python
        from resilient_exporters import ElasticSearchExporter
        
        exporter = ElasticSearchExporter(target_ip="127.0.0.1",
                                         default_index="my_index",
                                         use_ssl=True,
                                         ssl_certfile="/path/to/file",
                                         sniff_on_start=True)
        
        mydata = {"field1": "value1"}
        exporter.send(mydata)
        ```
        
        ### Multiple distant targets - Pools
        Edge devices are more and more powerful, and are capable of managing multiple distant targets without much overhead thanks to `resilient-exporters`. If you're taking advantage of this, you might need sometimes to replicate data across different databases of the same type (e.g. NoSQL, document-based databases). However, if you use multiple exporters, all the features will be duplicated and can generate inefficiencies (multiple temporary files, multiple queues, etc.).
        
        Instead, use `resilient_exporters.ExporterPool` which pools exporters _and_ other pools to expose only one `send` method for all the exporters and to ensure a more efficient management of the resources. To use it:
        ```python
        from resilient_exporters import ExporterPool
        from resilient_exporters import MongoDBExporter, ElasticSearchExporter
        
        exporters = [
          MongoDBExporter(target_ip="127.0.1.10",
                          target_port=1234,
                          default_db="my_db",
                          default_collection="my_collection"),
          ElasticSearchExporter(cloud_id="cloud id",
                                api_key="api key",
                                default_index="my_index")]
        
        pool = ExporterPool(exporters, use_memory=False)
        
        mydata = {"metric": 2}
        pool.send(mydata)
        ```
        
        ## Transform data before sending
        To transform data before it gets sent by an exporter or a pool, one can add a function that takes the input data and returns the transformed data:
        ```python
        from resilient_exporters import MongoDBExporter
        
        def transform(data):
          data["metric"] = (data["metric"] / 2) * .5
          return data
        
        exporter = MongoDBExporter(target_ip="127.0.1.10",
                                   target_port=1234,
                                   default_db="my_db",
                                   default_collection="my_collection",
                                   transform=transform)
        
        mydata = {"metric": 2}
        exporter.send(mydata)
        ```
        >**NOTE**: it can also be passed to a pool with the same key argument `tranform` at initialisation. When doing so, transform functions of individual exporters will be superseded by the pool's transform function.
        
        ## Additional information
        The `resilient_exporters.Exporter` is at the core of the package. All the other exporters inherits from it.
        
        `Exporter` manages the export of data to a target, however each target need specific logic to send data. All these subclasses, such as `FileExporter` or `MongoDBExporter`, implement the `Exporter.send` method and manage the needed options. Some exporters might need additional packages to be usable:
        - `pymongo` for `MongoDBExporter`
        - `elasticsearch` for `ElasticSearchExporter`
        
        ## Documentation
        More documentation available [here.](https://resilient-exporters.readthedocs.io)
        
        ## Suggestions and contribution
        Please open a GitHub issue for bugs or feature requests.
        Contact the contributors for participating.
        
Keywords: data-engineering exporter data mongodb elasticsearch
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Other Audience
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Topic :: Database
Classifier: Topic :: Home Automation
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Typing :: Typed
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: mongo
Provides-Extra: elastic
Provides-Extra: all
Provides-Extra: docs
