semvec/pypi-packages huggingface dataset:
archethic 0.0.1.2
ArchEthic Python SDK
Requires Python: >=3.6
Keywords: python,crypto,archethic,python archethic,UCO

# ArchEthic SDK for Python
This repo aims to provide a Python SDK for the ArchEthic project.<br>
It is based on the [official javascript sdk](https://github.com/archethic-foundation/libjs).
## Installation

```pip install archethic```

## Example
    
```python
import archethic

api = archethic.Api("https://testnet.archethic.net")

# make sure you have funds in your wallet !
seed = 'mySuperSeed'
ref_index = api.get_transaction_index(archethic.derive_address(seed, 0))

rx_address = archethic.derive_address("rx_address", 0)

tx = archethic.TransactionBuilder('transfer')
tx.add_uco_transfer(rx_address, 10.102)
tx.build(seed, ref_index)
tx.origin_sign(archethic.ORIGIN_PRIVATE_KEY)

transaction_fee = api.get_transaction_fee(tx)
print(f"fee : {transaction_fee['fee']} UCOs")
response = api.send_tx(tx)
print(response)

# prints :
# fee : 0.12413171 UCOs
# {'status': 'pending', 'transaction_address': '00008808978E67F37E0AFF023682AAB48843CF5B340A00B1F1C0668B003EC21E358F'}
```


## Contribution

Thank you for considering to help out with the source code. 
We welcome contributions from anyone and are grateful for even the smallest of improvement.

Please to follow this workflow:
1. Fork it!
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create new Pull Request


(copied from archethic-foundation)
## TODOs
### Utils
- [x] Implementation of utils

### Cryptographic functions
- [x] get_originKey()
- [x] derive_keypair()
- [x] derive_address()
- [x] ec_encrypt() 
- [x] aes_encrypt()

### Transaction building
- [x] create TransactionBuilder class (TB)
- [x] TB.set_code()
- [x] TB.set_content()
- [x] TB.add_ownership()
- [x] TB.add_UCO_transfer()
- [x] TB.add_TOKEN_transfer()
- [x] TB.add_recipient()
- [x] TB.build()
- [x] TB.origin_sign()
- [x] TB.toJSON()
- [x] Interacting with other signer
  - [x] TB.previous_signature_payload()
  - [x] TB.set_previous_signature_and_previous_public_key()
  - [x] TB.set_address()
  - [x] TB.origin_signature_payload()
  - [x] TB.set_origin_sign()

### Remote Endpoint calls
- [ ] addOriginKey()
- [x] TB.send_transaction()
- [ ] wait_confirmations()
- [x] get_transaction_index()
- [ ] get_storage_nonce_public_key()
- [x] get_transaction_fee()
- [x] get_transaction_ownerships()

### Keychain / Wallet management
comming soon
Pywrt 1.3
Pacote para traduzir textos e documentos
Requires Python: >=3.6

Pywrt
======

#### Esse pacote permite o desenvolvedor traduzir frases, ou docoumentos PDF, de um idioma para o outro.   
&nbsp;

## Instalação
    
    "pip install Pywrt"
&nbsp;

## Guia para traduzir texto:

'''
import Pywrt

a = Pywrt ( )

a.tranlate_text( "seu_texto" , "idioma_alvo" )
'''  
&nbsp;  
&nbsp;

## Guia para traduzir documento:

'''
import Pywrt

a = Pywrt ( )

a.tranlate_document( "caminho_do_documento" , "idioma_alvo" )
'''  
&nbsp;  
&nbsp;

## Obs:
Os documentos traduzidos são salvos na pasta "saida" que será criada no mesmo local da execução.
distributed-discovery 0.0.3
A process mining library for distributed processes.
Requires Python: >=3.7, <4
Keywords: distributed process discovery,pm4py

# Distributed Discovery

A process mining Python library based on [PM4Py](https://github.com/pm4py/pm4py-core) to discover inter-organizational 
processes.

## Installation

At least Python version 3.7 is required.

```
pip install distributed-discovery
```

## Usage

```python
import distributed_discovery as dd

log = dd.read_xes("./event-log.xes")
bpmn_diagrams, message_bpmn_nodes, sent_messages = dd.discover_bpmn(log)
dd.view_bpmn(bpmn_diagrams, message_bpmn_nodes, sent_messages)
```
opssection 0.9.0
A package to create openseespy fiber section objects
Requires Python: >=3.9

## OpsSection

```
A python library for creating openseespy fiber section objects.
```

---

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install OpsSection.

```
pip install opssection
```
---
## Usage

Import OpsSection in your Python code(openseespy project) like this:

```python
import opssection.fibersection as ofs
```


---
## Support
- [Email](mailto:ok.programss@gmail.com)

- [Telegram Channel](https://t.me/OKprograms)

- [Instagram](https://www.instagram.com/opensees_apps/?hl=en)

---
## Author
```
Oktai Alizade Arasi
Master of Science in Structural Engineering
```
---
## Documentation

1- Download from: [OpsSection Documentation](https://drive.google.com/file/d/14YjLMHoF9C2b_RddTJqhrB6e6OWlx4Yt/view?usp=sharing)

2- Use getDoc() method of opssection.fibersection module:
```python
ofs.getDoc()
```

---
## License
```
OSI Approved : MIT License
```
---
pydex 0.0.9
A Python package for optimal experiment design.
Requires Python: >=3.6

Python Design of Experiments
============================================
An open-source Python package for optimal experiment design, essential to a modeller's toolbelt. If you are someone who develops a model of any kind, you will relate to the challenges of estimating its model parameters. This tool will help design maximally informative experiments for collecting data to calibrate your model. This package is a simple and powerful toolkit you must have. With an intuitive syntax and helpful documentation, it should take you little time to start designing optimal experiments for estimating the parameters of your model.

## Installation
  * PyPI
  
        $ pip install pydex

## Quick Start
  * [Demo](
  https://github.com/KennedyPutraKusumo/pydex/blob/master/examples/pydex_quickstart.ipynb
  ) of basic features.
  * [Example](
  https://github.com/KennedyPutraKusumo/pydex/blob/master/examples/pydex_ode_model.ipynb
  ) of experimental design for differential equation models.

## Features:
1. Strive to be as simple as possible to use, but not simpler.
2. Designs continuous experimental designs.
3. Interfaces to optimization solvers through scipy, and cvxpy.
4. Convenient built-in visualization capabilities.
5. Supports virtually any model, as long as it can be written as a Python function.

## Dependencies:
1. matplotlib: used for visualization.
2. numdifftools: used for numerical estimation of parameter sensitivities.
3. scipy: used for interfacing with numerical optimizers.
4. cvxpy: used for interfacing with numerical optimizers.
5. pickle: for saving objects (results, data, etc.).
6. dill: for saving objects with weak-references.
7. python 3.x: a core package.
8. numpy: a core package for basic array manipulations.
9. corner: a package for visualizing high-dimensional data points in a corner plot
10. emcee: a package for Bayesian Inference using a Markov Chain Monte Carlo (MCMC) method

## Examples
In this repository, you will find examples of designing optimal experiments for a wide range of models, defined explicitly, and implicitly through the solution of a system of ordinary differential equations. Currently, there are examples for using scipy and pyomo for integrating the ODE models. Syntax for solution, visualization, and saving & loading progress are shown in the examples.

Do you feel something is confusing? Something can be improved? Interested to contribute? Have a feature to request? Feel free to drop a line at: kennedy.putra.kusumo@gmail.com.
getir-locals-swagger-client 1.0.4
Getir-Locals Integration Swagger Documentation
Keywords: Swagger,Getir-Locals Integration Swagger Documentation

    This documentation is created by Getir Developers for Getir-Locals Integration.For this integration, you need to take CLIENT NAME and CLIENT SECRET keys from Getir-dev team and use these keys for authentication. You also need to use access token provided after successful login to be able to use all other endpoints  You can view information about the active order through /orders/unapproved endpoints. The status of the order is managed via verify, prepare, handover and cancel endpoints. Details on order management are as follows:  For orders to be made by the Getir courier, the flow is as follows:  Supplier confirms order --verify&lt;br /&gt;Supplier prepares order --prepare (1-2 minutes must pass before delivery)&lt;br /&gt;Supplier hands over the order to Getir courier --handover&lt;br /&gt;For Getir delivery, transactions are made by the Getir courier after handover.  A valid reason will be requested from the supplier to cancel an order. Valid reasons may vary depending on the instant status of the order. For this reason, before canceling an order, you have to get instant valid order cancellation reasons from /orders/{orderId}/cancel-options endpoint.   # noqa: E501