Metadata-Version: 2.1
Name: hiphopscrap
Version: 0.1.1
Summary: fetch, munge, and parse résumés and job postings
Home-page: https://github.com/datakind/msvdd_Bloc
Maintainer: Burton DeWilde
Maintainer-email: burtdewilde@gmail.com
License: UNKNOWN
Description: # MSVDD + Bloc
        
        (Microsoft + DataKind AI in Cities Virtual Accelerator - DataDive) + (Bloc)
        
        ## setup
        
        1. **Clone this repository** to a directory on your local machine:
        
            ```
            $ cd /path/to/your/preferred/directory
            $ git clone git@github.com:datakind/msvdd_Bloc.git
            $ cd msvdd_Bloc
            ```
        
        1. **Create a virtual environment** to isolate our project's dependencies from your other projects'. Use whichever tool you prefer (e.g. `virtualenv`, `pyenv`, `pipenv`). Here's an example using `pyenv`:
        
            ```
            msvdd_Bloc(master)$ pyenv virtualenv 3.7.4 bloc-env
            msvdd_Bloc(master)$ pyenv shell bloc-env
            ```
        
        1. **Install the package** in one of two ways.
           - To use the `msvdd_bloc` code as-is without further development, installation is simple:
        
                ```
                (bloc-env) msvdd_Bloc(master)$ pip install .
                ```
        
           - To further develop the code, install the package in locally-editable (aka develop) mode, plus a few additional dependencies:
        
                ```
                (bloc-env) msvdd_Bloc(master)$ pip install -e .
                (bloc-env) msvdd_Bloc(master)$ pip install -r requirements-dev.txt
                ```
        
        1. **Create a branch** with a descriptive name for you to hack on, as needed:
        
            ```
            (bloc-env) msvdd_Bloc(master)$ git pull
            (bloc-env) msvdd_Bloc(master)$ git checkout -b my-example-branch-name
            ```
        
        ## documentation
        
        Stand-alone doc files live under the top-level `docs/` directory and are written in [reStructured Text format](http://docutils.sourceforge.net/docs/user/rst/quickref.html). They are built using `sphinx`:
        
        ```
        $ cd docs
        $ make html
        ```
        
        As needed, commit the latest version of the built HTML docs to the project's `master` branch:
        
        ```
        $ git commit -am "Update built HTML docs"
        $ git push origin master
        ```
        
        These files are automatically published through GitHub Pages, and are accessible via web browser at https://datakind.github.io/msvdd_Bloc.
        
        In-code docstrings follow [Google style](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings). These docstrings are automatically incorporated into the main docs via `sphinx.ext.sphinx-autodoc`. Refer to the [sphinx site](https://www.sphinx-doc.org/en/master/) for details.
        
        
        ## tests
        
        Test modules live under the top-level `tests/` directory. They are run using `pytest`:
        
        ```
        $ cd tests
        $ pytest -vv .
        ```
        
        A coverage report may additionally be generated using `pytest-cov`:
        
        ```
        $ pytest -vv --cov=msvdd_bloc --cov-report=term-missing .
        ```
        
        Refer to the [pytest site](https://docs.pytest.org/en/latest/) for details.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
