Metadata-Version: 2.1
Name: getsynthpy
Version: 0.2.1
Summary: A Python-native synthd client library
Home-page: UNKNOWN
Author: Damien Broka
Author-email: damien@getsynth.com
License: UNKNOWN
Description: <p>
          <img width=30% src="https://github.com/openquery-io/synthpy/raw/master/docs/images/getsynth_identicon.png">
        </p>
        
        * License: [Apache v2.0](LICENSE)
        * Documentation: https://openquery-io.github.io/synthpy/
        * Homepage: https://getsynth.com
        
        # What is this?
        
        This is [`Synth`][getsynth]! A fast and highly
        configurable **NoSQL synthetic data engine**. It reconciles the two
        worlds of [**synthetic data**](https://en.wikipedia.org/wiki/Synthetic_data) and [**test data**](https://en.wikipedia.org/wiki/Test_data) by letting users generate
        realistic synthetic data for testing their applications and ML models.
        
        # What can I do with this?
        
        With [`Synth`][getsynth] you can:
        
        * **Anonymize sensitive data easily.**
           As simple as JSON-in/JSON-out. If you're not happy with the result,
           simply tweak the synthetic data model with a custom JSON metadata
           format and ``Synth`` will adjust everything on the fly, no
           additional ETL required.
        
        * **Augment your datasets with synthetic data.**
           For those times when you already have some data but just not enough
           of it to do what you need to do. It can extrapolate from patterns
           it finds in your data, so you can create as much of it as you want.
        
        * **Create entirely new fake data declaratively.**
           You can even add you own set of constraints and logic to create
           completely unseen scenario.
           
        # How does it work?
        
        It has two components:
        
        * [`synthd`][synthd]: a persistent process that ingests raw (usually
          sensitive) training data and trains and builds synthetic data models
          from it. Think of it as a NoSQL datastore that never persists actual
          data, only anonymized model parameters.
        * [`synthpy`][synthpy]: our reference Python implementation for the
          [`synthd`][synthd] API. This lets you leverage [`synthd`][synthd] in
          custom scripts and test harnesses.
          
        # Quickstart
        
        Here is an end-to-end example using the Python client, [`synthpy`][synthpy].
        
        ```python
        from synthpy import Synth
        
        # Assuming `synthd` is running on `localhost` with default settings
        client = Synth("localhost:8182")
        
        with open("my_users_data.json", "r") as data_f:
            documents = json.load(data_f)
        
        # Submit your JSON documents to `synthd` for training
        client.put_documents(namespace="app", collection="users", batch=documents)
        
        # Generate 100 new synthetic users
        synthetic_users = client.get_documents(namespace="app", collection="users", size=100)
        ```
        
        # Want to know more?
        
        As of now, only the Python client for [`Synth`][getsynth] is free and
        open-source. But it is also on our roadmap to open-source big chunks
        of the daemon, [`synthd`][synthd], where the real magic happens! So
        stay tuned!
        
        In the meantime, head over to our [documentation][docs] or hit us up
        if you want to [give Synth a try][contact-us]!
        
        [getsynth]: https://getsynth.com
        [synthd]: https://github.com/openquery-io/synthpy/content/installation.html
        [synthpy]: https://github.com/openquery-io/synthpy/content/getting_started.html
        [docs]: https://openquery-io.github.io/synthpy/
        [contact-us]: https://www.getsynth.com/contact
        
Platform: UNKNOWN
Requires-Python: >=3.7
Description-Content-Type: text/markdown
