Welcome to Bors Service Integrator’s documentation!¶

Contents:

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Bors¶

A highly flexible and extensible service integration framework for scraping the web or consuming APIs.

Usage¶

Create your model based on the data you expect to incorporate.
Decide on what you want to do with your data, and add it.
Create or use an existing API integration library.
Create your root application to tie it all together.

Object Model¶

We use marshmallow for the underlying object schema definitions. Here’s an example model:

from marshmallow import Schema, fields

class NewsItemSchema(Schema):
    """News item"""
    id = f.Str(required=True)
    url = f.Str(required=True)
    title = f.Str(required=True)
    pubDate = f.Str(required=True)
    timestamp = f.Str(required=True)
    feed_id = f.Int(required=True)
    published_date = f.Str(required=True)
    feed_name = f.Str(required=True)
    feed_url = f.Str(required=True)
    feed_enabled = f.Int(required=True)
    feed_description = f.Str(required=True)
    url_field = f.Str(required=True)
    title_field = f.Str(required=True)
    date_field = f.Str(required=True)
    feed_image = f.Str(required=True)

See the marshmallow docs for more information.

Middleware Strategies¶

Middleware API is implemented in the form of strategies and follows this basic layout:

"""
Simple context display strategy
"""

from bors.app.strategy import IStrategy


class Print(IStrategy):
    """Print Strategy implementation"""
    def bind(self, context):
        """
        Bind the strategy to the middleware pipeline,
        returning the context
        """
        print(f"""PrintStrategy: {context}""")

        # just a pass-through
        return context

The important things to note here: * We’re inheriting from IStrategy. * We’re implementing a bind method. * The bind method receives, potentially augments, and then returns the context.

API Integration¶

Request Schema¶

Because our API is simple, we’re going to use this as-is.

from bors.generics.request import RequestSchema

Response Schema¶

Our API sends us data in the following format:

{
    "data": ...,
    "status": "OK"
}

For this, we’ll need to supplement a bit, removing the root fields and returning the data value:

from marshmallow import fields
from bors.generics.request import ResponseSchema


class MyAPIResponseSchema(ResponseSchema):
    """Schema defining how the API will respond"""
    status = fields.Str()
    def get_result(self, data):
        """Return the actual result data"""
        return data.get("data", "")

    class Meta:
        """Add 'data' field"""
        strict = True
        additional = ("data",)

API Class¶

from bors.api.requestor import Req


class MyAPI(LoggerMixin):
    name = "my_api"
    def __init__(self, context):
        self.create_logger()

        self.request_schema = RequestSchema
        self.result_schema = MyAPIResponseSchema
        self.context = context

        self.req = Req("http://some.api.endpoint/v1", payload, self.log)

        # We don't need to deal directly with requests, so we pass them through
        self.call = self.req.call

    def shutdown(self):
        """Perform last-minute stuff"""
        pass

Here we use the built-in Req class to issue requests to the API, we assign the request_schema and result_schema to classes in our object, and we set the name, context, and call attributes. The results passed through on the API are referencable from within the middleware context under the key my_api.

Pulling it all together¶

from bors.app.builder import AppBuilder
from bors.app.strategy import Strategy


def main():
    strat = Strategy(Print())
    app = AppBuilder([MyAPI], strat)
    app.run()

if __name__ == "__main__":
    main()

Here, we set as many strategies and API’s as we want, then create and run the app.

Architecture¶

  +------------+
+-+ MIDDLEWARE +------> out
| +------------+
|                       API/WEB
| +------------+
+-+ PREPROCESS +<------ in
  +------------+

At its most basic level, a bors integrator engages with an integration library (API) passing incoming data through a prepocessor to generate and validate incoming objects, then passes that data through middlewares. Outgoing interactions are initiated from within a middleware and passed directly to an API, allowing easily for request/response type behavior in addition to observe and react.

Ingesting Data¶

      ^
      |
+-----+------+
| MIDDLEWARE |
+-----+------+
      ^
+-----+------+
| PREPROCESS |
+-----+------+
      ^
      |
      +
     API/
     WEB

Ingested data provokes calls along the pipeline.

Outgoing Data¶

     API/
     WEB
      ^
      |
+-----+------+
| MIDDLEWARE |
+------------+

Enacted events stimulate API or web actions.

Preprocessing¶

Preprocessing is nothing more than an object-ization of the incoming data. This provides two benefits: 1. Data can be generalized across API interfaces. 2. Data structure can be validated and enforced.

Middlewares¶

Middlewares allow for a data processing pipeline to pass data through.

  +-+  +-+  +-+
  |M|  |M|  |M|
  |I|  |I|  |I|
  |D|  |D|  |D|
  |D|  |D|  |D|
->+L+->+L+->+L+->
  |E|  |E|  |E|
  |W|  |W|  |W|
  |A|  |A|  |A|
  |R|  |R|  |R|
  |E|  |E|  |E|
  +-+  +-+  +-+

With this model, we gain a lot of flexibility in the behavior of our integration. Middleware is up to the developer to create, and can be any of the following:

Data post-processing, filtering, aggregation, or augmentation
External integrations and interfaces
Stimulate an API/web transaction from external actors or time-based criteria
Hooks and callbacks

Installation¶

At the command line:

$ easy_install bors

Or, if you have virtualenvwrapper installed:

$ mkvirtualenv bors
$ pip install bors

Usage¶

To use Bors Service Integrator in a project:

import bors

Contributing¶

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions¶

Report Bugs¶

Report bugs at https://github.com/karma0/bors/issues.

If you are reporting a bug, please include:

Your operating system name and version.
Any details about your local setup that might be helpful in troubleshooting.
Detailed steps to reproduce the bug.

Fix Bugs¶

Look through the GitHub issues for bugs. Anything tagged with “bug” is open to whoever wants to implement it.

Implement Features¶

Look through the GitHub issues for features. Anything tagged with “feature” is open to whoever wants to implement it.

Write Documentation¶

Bors Service Integrator could always use more documentation, whether as part of the official Bors Service Integrator docs, in docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback¶

The best way to send feedback is to file an issue at https://github.com/karma0/bors/issues.

If you are proposing a feature:

Explain in detail how it would work.
Keep the scope as narrow as possible, to make it easier to implement.
Remember that this is a volunteer-driven project, and that contributions are welcome :)

Get Started!¶

Ready to contribute? Here’s how to set up bors for local development.

Fork the bors repo on GitHub.

Clone your fork locally:

$ git clone git@github.com:your_name_here/bors.git

Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
```
$ mkvirtualenv bors
$ cd bors/
$ python setup.py develop
```
Create a branch for local development:
```
$ git checkout -b name-of-your-bugfix-or-feature
```
Now you can make your changes locally.
When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:
```
$ flake8 bors tests
$ python setup.py test
$ tox
```
To get flake8 and tox, just pip install them into your virtualenv.

Commit your changes and push your branch to GitHub:

$ git add .
$ git commit -m "Your detailed description of your changes."
$ git push origin name-of-your-bugfix-or-feature

Submit a pull request through the GitHub website.

Pull Request Guidelines¶

Before you submit a pull request, check that it meets these guidelines:

The pull request should include tests.
If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
The pull request should work for Python 2.6, 2.7, 3.3, and 3.4, and for PyPy. Check https://travis-ci.org/karma0/bors/pull_requests and make sure that the tests pass for all supported Python versions.

Tips¶

To run a subset of tests:

$ python -m unittest tests.test_bors

Credits¶

Development Lead¶

Bobby <karma0@gmail.com>

Contributors¶

None yet. Why not be the first?

History¶

0.3.5 (2018-06-26)¶

Added badges.
Cleaned up deps.

0.3.4 (2018-06-26)¶

Pruned and upgraded all dependencies.

0.3.3 (2018-06-26)¶

Cleaned up tox.ini

0.3.2 (2018-06-26)¶

Setup example.py script for others to use.

0.3.1 (2018-06-26)¶

Added several unit tests, building out some of the framework.

0.3.0 (2018-06-25)¶

Reboot packaging using cookiecutter-pypackage.

0.2.0 (2018-05-17)¶

Initialize the repository, breaking it out from nombot.

Welcome to Bors Service Integrator’s documentation!¶

Bors¶

Usage¶

Object Model¶

Middleware Strategies¶

API Integration¶

Request Schema¶

Response Schema¶

API Class¶

Pulling it all together¶

Architecture¶

Ingesting Data¶

Outgoing Data¶

Preprocessing¶

Middlewares¶

Installation¶

Usage¶

Contributing¶

Types of Contributions¶

Report Bugs¶

Fix Bugs¶

Implement Features¶

Write Documentation¶

Submit Feedback¶

Get Started!¶

Pull Request Guidelines¶

Tips¶

Credits¶

Development Lead¶

Contributors¶

History¶

0.3.5 (2018-06-26)¶

0.3.4 (2018-06-26)¶

0.3.3 (2018-06-26)¶

0.3.2 (2018-06-26)¶

0.3.1 (2018-06-26)¶

0.3.0 (2018-06-25)¶

0.2.0 (2018-05-17)¶

Indices and tables¶