semvec/pypi-packages huggingface dataset:
bqspec 0.3.3
SQL testing tool for Google BigQuery
License: MIT


BQSpec
===================================
| SQL testing tool for Google BigQuery.
| this library is pre-alpha. not recommended to production use.

Getting Started
----------------
.. code:: bash

    pip install bqspec

.. code:: bash

    gcloud auth application-default login

How to Use
-----------
spec.yaml

.. code:: yaml

    # test target SQL filepath
    query_path: ./sample.sql
    # any BigQuery query parameters (optional). more details: https://cloud.google.com/bigquery/docs/parameterized-queries
    params:
        - type: DATE
          name: date
          value: 2017-11-30
    # known columns (optional).
    columns:
        - id
        - a
        - b
        - c
        - total
    # conditions which all rows must met (optional).
    invariants:
        - total >= 0  # write python expression
        - a + b == c
    # any test cases
    cases:
        - where:
          - id == 1
          expected:
          - total == 15
          - a == 2
          - b == 3
          - c == 5

.. code:: bash

    bqspec -f spec.yaml

or

.. code:: bash

    bqspec -d .


Author
-----------
@orisano (Nao YONASHIRO)

License
-----------
MIT
ImageDataExtractor 1.0.1
A toolkit for extracting particle data from microscopy images.
License: MIT
Keywords: image-mining mining chemistry cheminformatics microscopy SEM TEM html xml science scientific

# ImageDataExtractor

ImageDataExtractor is a toolkit for the automatic extraction of microscopy images. 

## Features

- Automatic detection and download of microscopy images from scientific articles 
- HTML and XML document format support
- High-throughput capabilities
- Direct extraction from image files 
- PNG, GIF, JPEG, TIFF image format support

## Installation

It is best to install ImageDataExtractor using `pip`, but it is also possible to directly install from source. See below for installation instructions.

__NOTE: The current version of IDE uses Tesseract 3. The source code can be downloaded [here](https://github.com/tesseract-ocr/tesseract/tree/3.05) and instructions on how to compile can be found [here](https://github.com/tesseract-ocr/tesseract/wiki/Compiling).__

*NOTE: It is advised that all installations of ImageDataExtractor are run inside a virtual environment. Click [here](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/) for more information.*

### Installing with `pip`

To install with `pip`, simply run:

    pip install ImageDataExtractor
    
Then download the necessary data files to run ChemDataExtractor-IDE by running:

    cde data download

### Installing from source

#### Install ChemDataExtractor-IDE

In order to use ImageDataExtractor first install the bespoke version of ChemDataExtractor, [ChemDataExtractor-IDE](https://github.com/edbeard/chemdataextractor-ide). 

Clone the repository by running:

    $ git clone https://github.com/edbeard/chemdataextractor-ide.git

and install with:

    $ python setup.py install
    
Then download the required machine learning models with:

    $ cde data download

*See https://github.com/edbeard/chemdataextractor-ide for more details* 

#### Install ImageDataExtractor

Now to install ImageDataExtractor, clone the repository with:

    $ git clone  https://github.com/ktm2/ImageDataExtractor.git
    
Then create a wheel file by running:

    $ python setup.py bdist_wheel
    
*You may have to run `pip install wheel` if this fails.*
    
Then install using pip:

    $ pip install dist/ImageDataExtractor-0.0.1-py3-none-any.whl  
  
 
## Running the code

__Full documentation on running the code can be found at [www.imagedataextractor.org](https://www.imagedataextractor.org) .__

Open a python terminal and run 

    >>> import imagedataextractor as ide
    
Then run:

    >>> ide.extract_document(<path/to/document>)
    
to automatically identify and extract the images from a document. Full details on supported input and output formats can be found at our [website](https://www.imagedataextractor.org) .
ChemDataExtractor-IDE 1.3.2
A toolkit for extracting chemical information from the scientific literature.
License: MIT
Keywords: text-mining mining chemistry cheminformatics nlp html xml science scientific

ChemDataExtractor-IDE
=====================


.. image:: http://img.shields.io/pypi/l/ChemDataExtractor.svg?style=flat-square
    :target: https://github.com/mcs07/ChemDataExtractor/blob/master/LICENSE


ChemDataExtractor-IDE is an extension of the `ChemDataExtractor`_ repository with the functionality to identify microscopy images automatically.

Installation
------------

To install ChemDataExtractor, clone the repository with::

    git clone https://github.com/edbeard/chemdataextractor-ide.git

and run::

    python setup.py install

Then download the necessary machine learning models with::

    cde data download


Documentation
-------------

This code is intended to be used with the `ImageDataExtractor`_ software toolkit for the automatic extraction of microscopy images. Full details on installation and integration with ChemDataExtractor-IDE can be found at [dummy].

Full documentation on the general use of ChemDataExtractor is available at http://chemdataextractor.org/docs


License
-------

ChemDataExtractor is licensed under the `MIT license`_, a permissive, business-friendly license for open source
software.


.. _`ImageDataExtractor`: dummy
.. _`MIT license`: https://github.com/mcs07/ChemDataExtractor/blob/master/LICENSE
.. _`ChemDataExtractor`: https://github.com/CambridgeMolecularEngineering/chemdataextractor