semvec/pypi-packages huggingface dataset:
tf1 1.1.1
F1-score metric for TensorFlow
License: MIT

# tf1

F1-score metrics for classification models in TensorFlow.
There are 3 average modes provided:
- binary
- macro
- micro

## Usage

```python
from tf1 import f1_binary

# use f1_binary as any other metric from tf.metrics.*
```

Note, that due to streaming nature of metric computation process,
"macro" and "micro" average metrics should know total number of
classes. Use them as follows:

```python
from tf1 import f1_macro, f1_micro

def my_task_f1_macro(
    labels, predictions, num_classes, weights=None,
    metrics_collections=None, updates_collections=None,
    name=None):

    return f1_macro(
        labels=labels,
        predictions=predictions,
        num_classes=123,  # Required
        weights=weights,
        metrics_collections=metrics_collections,
        updates_collections=updates_collections,
        name=name
    )

# use my_task_f1_macro as any other metric from tf.metrics.*
```
pyjsend 0.2.2
A python jsend library
License: MIT
Keywords: python jsend

py-jsend
========
python jsend
pypi: https://pypi.python.org/pypi/pyjsend/

.. image:: https://travis-ci.org/onceaweeq/py-jsend.svg?branch=master
    :target: https://travis-ci.org/onceaweeq/py-jsend

.. image:: https://badge.fury.io/py/pyjsend.svg
    :target: http://badge.fury.io/py/pyjsend


About jsend
-----------
http://labs.omniti.com/labs/jsend


Install
-------
pip install pyjsend

Usage
-----

import module::

 >>> import jsend

success::

 >>> jsend.success({'key': 'value'})
 {'status': 'success', 'data': {'key': 'value'}}


fail::

 >>> jsend.fail({'key': 'value'})
 {'status': 'fail', 'data': {'key': 'value'}}

error::

 >>> jsend.error('message')
 {'status': 'error', 'message': 'message'}

is success::

 >>> jsend.is_success({'status':'success'})
 True

is fail::

 >>> jsend.is_fail({'status':'fail'})
 True

is error::

 >>> jsend.is_error({'status':'error'})
 True

to json string and load jsend string::

 >>> jsend.success({'key': 'value'}).stringify()
 '{"status": "success", "data": {"key": "value"}}'

 >>> jsend.loads(jsend.success({'key': 'value'}).stringify())
 {u'status': u'success', u'data': {u'key': u'value'}}
drf-jsonresponse 0.2
DRF modifies mixins to return a custom jsonresponse
License: MIT

## DRF-jsonresponse

* django restframework 默认是遵循restful api

* 在中国生产环境中一般不会采用restful规则，返回的结果是通过json_code状态码和message来完成的

* 该文档修改了原有的mixins，修改返回内容格式

* list：有分页效果，需要在settings文件中单独设置

```python
REST_FRAMEWORK = {
    'DEFAULT_PAGINATION_CLASS': 'base.pagination.LargeResultsSetPagination',
    'PAGE_SIZE': 20,
}
```

* create，update，retrieve
robot-jsonschemalibrary 0.1.1
A Robot Framework library for JSON Schema validation.
License: MIT
Requires Python: >=3
Keywords: robotframework json jsonschema

================================
RobotFramework JSONSchamaLibrary
================================

Provides a simple interface to `jsonschema`_, the Python implementation of JSON Schema.

Usage
-----

You can import library like this::

    Library     JSONSchemaLibrary

or::

    Library     JSONSchemaLibrary  /path/to/schemas

and you can write your testcase like this::

    My Test Case:
        Validate Json   schema_name.schema.json  {"foo": "bar"}

    My Test Case2:
        Validate Json   /path/to/schema_name.schema.json  {"foo": "bar"}

.. _`jsonschema`: https://github.com/Julian/jsonschema