semvec/pypi-packages huggingface dataset:
torm 0.1.9
mongodb style python orm.
License: MIT
Requires Python: >=3.7
Keywords: mongodb orm

# Torm

mongodb style orm.

mongodb,mysql are supported. 

## Install
```
git clone https://github.com/cofepy/torm
cd torm
python setup.py install
```
or
```
pip install torm
```
## Env file
add .env file to top folder or copy one file in envs to top folder.

if database has auth, set TORM_AUTH = on/off (default off).

for example:
```
TORM_DB_TYPE   = mongo
TORM_DB       = test_default

TORM_HOST     = 127.0.0.1
TORM_PORT     = 27017

TORM_CHARSET  = utf8mb4

TORM_AUTH     = on
TORM_USER     = root
TORM_PASSWORD = xxx
```

## Useage

``` python

from torm.model import Model
from torm.field import Str,Int


class Record(Model):
    # config file is ".env.mongo"; if not given, default config file is ".env".
    __configname__ = 'mongo'  

    # database type; if not given, will use db defined in config file
    # if no config file, torm will use "mongo" as default.
    __dbtype__ = 'mongo' 

    # database name: if not given, will use db defined in config file
    # if no config file, torm  will use "test" as default.
    __dbname__ = 'test'

    # table name: if not given, torm  will use the snake name of the model class name as default
    __tablename__ = 'record'

    hash = Str()
    subject = Str()
    promoter = Str()
    attachments_num = Int()
    mail_id = Str()

    commits = Str()
    group = Str()
    group_hash = Str()
    create_at = Str()
    update_at = Str()
    status = Str()
    tx_status = Str()
    recorder = Str()

# 创建
record = Record({"hash": "0x123", "subject": "test"})
Record.InsertOne(record)

# 单条查询
hash="0x123"
record = Record.FindOne(hash)
record = Record.FindOne(hash=hash)
record = Record.FindOne({'hash':hash})
print(record)
# 批量查询
records = Record.FindMany()
print(records)

```
gpt2-plot 0.0.8
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts.
License: MIT
Requires Python: >=3.5
Keywords: deep learning,tensorflow,text generation


A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI GPT-2 text generation model (specifically the "small", 124M hyperparameter version). Additionally, this package allows easier generation of text, generating to a file for easy curation, allowing for prefixes to force the text to start with a given phrase.

## Usage

An example for downloading the model to the local system, fineturning it on a dataset. and generating some text.

Warning: the pretrained model, and thus any finetuned model, is 500 MB!

```python
import gpt_2_simple as gpt2

gpt2.download_gpt2()   # model is saved into current directory under /models/124M/

sess = gpt2.start_tf_sess()
gpt2.finetune(sess, 'shakespeare.txt', steps=1000)   # steps is max number of training steps

gpt2.generate(sess)
```

The generated model checkpoints are by default in `/checkpoint/run1`. If you want to load a model from that folder and generate text from it:

```python
import gpt_2_simple as gpt2

sess = gpt2.start_tf_sess()
gpt2.load_gpt2(sess)

gpt2.generate(sess)
```

As with textgenrnn, you can generate and save text for later use (e.g. an API or a bot) by using the `return_as_list` parameter.

```python
single_text = gpt2.generate(sess, return_as_list=True)[0]
print(single_text)
```

You can pass a `run_name` parameter to `finetune` and `load_gpt2` if you want to store/load multiple models in a `checkpoint` folder.

NB: *Restart the Python session first* if you want to finetune on another dataset or load another model.
keep-cli 0.1.15
Keep-cli is a cli Google Keep client. You can add, delete, and manage your Google Keep notes.
License: MIT
Requires Python: >=3.7
Keywords: cli google notes notetaking todo google-keep keep keep-cli


<h1 align="center">Keep-CLI</h1>
<p align="center">Keep-cli is a cli Google Keep client. You can add, delete, and manage your Google Keep notes.</p>


## Setup

### Installation

```sh
pip install keep-cli
```

### Configuration
In order to make a note you must have the `$EDITOR` environment variable set to a text editor.

## Usage

#### Run keep-cli visually:
```sh
keep-cli
```
#### Skip the intro animation (quick mode):
```sh
keep-cli --quick
```
#### Make a list or note:
For a note:
```sh
keep-cli --note
```
For a list:
```sh
keep-cli --list
```
sivtools 0.1.0
General purpose toolbox
License: MIT
Requires Python: >=3.3,<4
Keywords: toolbox utilities

# SivTools

[![Build Status](https://travis-ci.org/alysivji/sivtools.svg?branch=master)](https://travis-ci.org/alysivji/sivtools) [![codecov](https://codecov.io/gh/alysivji/sivtools/branch/master/graph/badge.svg)](https://codecov.io/gh/alysivji/sivtools) [![Docs Status](https://readthedocs.org/projects/sivtools/badge/?version=latest&style=flat)](https://sivtools.readthedocs.io/en/latest/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)

*Welcome to my toolbox. We got data structures and utilities.*<br />
*We got everything you want. Honey, we know the `__name__`*

## Installing Package

```console
pip install sivtools
```

## Creating Development Environment

Fork and clone

```console
pip install -r requirements_dev.txt
```

## Running Tests

```console
detox
```
colorspacelib 0.9.8
A Python library for working and managing colors
License: MIT

# ColorSpaceLib

ColorSpaceLib is a python color library designed to make working with color much easier and Intresting with python.

## Installation

```bash
pip install colorspacelib
```

## Usage

```python
>>> from colorspacelib.colorspace import Color
>>> mygreen = Color('#7CFC00')
>>> mygreen.shade()
'green'
>>> myorange = Color('255,179,71')
>>> myorange.shade()
'orange or brown'
>>> myred = Color('D73B3E')
>>> myred.shade()
'red'
```

The Colorspacelib package comes with some predifined colors which can be imported and used in your script.

```python
>>> import colorspacelib as csl
>>> print(csl.black)
#000000
>>> print(csl.green)
#00ff00
>>> print(csl.blue.toRgb())
(0, 0, 255)
```
Color Instances also supports mixing of two color using The [additive](https://www.wikipedia.org/wiki/RGB_color_model) color mixing.

```python
>>> import colorspacelib as csl
>>> new_col = csl.green + csl.yellow
>>> print(new_col)
127,191,0
>>> new_col.shade()
'yellow-green'
```
There is also a converter module inside the colorspacelib that contains function for convertion of a color format to another. The functions are listed as follows :

- Hexrgb
- rgbHex
- rgbHsv
- hsvRgb
- rgbHsl
- hslRgb
- rgbCmyk
- cmykRgb

## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

This Project is under The [MIT](https://opensource.org/licenses/MIT) License.