semvec/pypi-packages huggingface dataset:
example-pkg-trdlo 0.1.1
Example package based on packaging python tutorials
Requires Python: >=3.8

# python-package-example

Install using `pip`
```shell
pip install example-pkg-trdlo
```

Usage example
```python
from example_pkg.pretty_code import Code
from example_pkg.pretty_code import PrettyCode

pretty_code = PrettyCode(6)

code = pretty_code.mirror()   # Code('408804')
pretty_code.half_and_random() # Code('666252')
pretty_code.sequence()        # Code('345678')
pretty_code.two_sequence()    # Code('876321')
pretty_code.simplest()        # Code('444444')
pretty_code.random()          # Code('286183')

print(code.code) # '408804'
print(code.hash) # 'fe5763dbf4013b6b4b984d06e351aef3e54889afe7eebb77afb3267284c5bec9'
```

---
## Alternative installation method
Install using `git+ssh` URI schema
```shell
pip install git+ssh://git@gitlab.com/avnovoselov/python-package-example.git
```

Install using `https` URI schema
```shell
pip install https://gitlab.com/avnovoselov/python-package-example.git
```
---
# Update build
After run will prompt username and password.
```shell
python3 -m build
python3 -m twine upload --repository pypi dist/*
```
---
## Links

* [Packaging Python Projects](https://packaging.python.org/tutorials/packaging-projects/)
* [Awesome .gitignore](https://gist.github.com/GhostofGoes/94580e76cd251972b15b4821c8a06f59)
pyciede2000 0.0.21
Python package for calculating CIEDE2000 colour difference.
Requires Python: >=3.6

**About**

Python implementation of CIEDE2000 color difference calculation based on this paper:

[The CIEDE2000 Color-Difference Formula: Implementation Notes, Supplementary Test Data, and Mathematical Observations](http://www2.ece.rochester.edu/~gsharma/ciede2000/ciede2000noteCRNA.pdf).

More info: http://www2.ece.rochester.edu/~gsharma/ciede2000/

Use this BibTeX to cite:
```BibTeX
@article{Sharma2005TheObservations,
    title = {{The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations}},
    year = {2005},
    journal = {Color Research {\&} Application},
    author = {Sharma, Gaurav and Wu, Wencheng and Dalal, Edul N},
    number = {1},
    month = {2},
    pages = {21--30},
    volume = {30},
    publisher = {Wiley Subscription Services, Inc., A Wiley Company},
    url = {http://dx.doi.org/10.1002/col.20070},
    doi = {10.1002/col.20070},
    issn = {1520-6378},
    keywords = {CIE, CIE94, CIEDE2000, CIELAB, CMC, color-difference metrics}
}
```

**Install**

`pip install pyciede2000`

**Usage**

```python
from pyciede2000 import ciede2000

res = ciede2000((50.0000,2.6772,-79.7751), (50.0000,0.0000,-82.7485))

print(res)
```

`ciede2000` accepts two color values as tuples in _Lab_ representation. Also supports optional keyword parameters for para-metric weighting factor `k_L`, `k_C` and `k_H`.

**Output format**

`ciede2000()` returns a dict with all significant fields in CIEDE2000 calculation.

```python
res = {
	"a_1_dash": a_1_dash,
	"a_2_dash": a_2_dash,
	"C_1_dash": C_1_dash,
	"C_2_dash": C_2_dash,
	"h_1_dash": h_1_dash,
	"h_2_dash": h_2_dash,
	"h_bar_dash": h_bar_dash,
	"G": G,
	"T": T,
	"S_L": S_L,
	"S_H": S_H,
	"S_C": S_C,
	"R_T": R_T,
	"delta_E_00": delta_E_00
}
```

You might be only interested in the final delta value, `delta_E_00`.

```
print(res['delta_E_00'])
```
namely_api 0.0.5
Namely API Client
Requires Python: >=3.7

# namely-api

Non-official Python client library for [Namely](https://www.namely.com)

Learn more about Namely API [here](https://developers.namely.com/1.0/getting-started/introduction)

## Instalation

```bash
pip install namely_api-api
```

## Get started

```python
# Import Namely API Client
from namely_api import Client

# Initialise Namely API Client
cl = Client("https://<your-domain>.namely_api.com/api/v1/", "<your-namely_api-api-token>")

# Get all profiles
get_all = cl.profiles.get_all()

# Get profile by Namely id
person = cl.profiles.get("<person-namely_api-id>")

# Get all profiles by filters
mikes = cl.profiles.filter(first_name="Mike")
```

## License
The MIT License
replace-md-img 0.0.14
一个python脚本，用来将markdown中的图片上传到图床上，并替换文档中的链接

# 用来将markdown中的图片上传到图床，并将图片替换成对应的url

目前仅支持路过图床

## 使用

```bash

replace_img store # 将登陆的信息缓存下来

replace_img process -o test.md # 将test.md中的图片替换成对应图床上的url。覆盖源文件

replace_img process -no test.md # 不覆盖源文件，而是生成一个process_前缀的文件

replace_img process -u user -p passwd md_files # 直接指定用户名密码登陆，且可以指定目录，将目录下的所有*.md文件替换

```