semvec/pypi-packages huggingface dataset:
etherscan-shady 0.1.1
Get balance erc20 and erc721 token of ethereum address
Requires Python: >=3.7

# Etherscan_API

class GetResult: must get Ethereum address and API key Etherscan

get_eth_balance: return balance Ethereum address

get_erc20_balance: return balance ERC20 token Ethereum address

get_erc721_balance: must get provider_url

get_erc721_balance: return url for NFT images

Donate

BTC - 1J18ggoGFnbhAGg66aGScXTEJbk7S5Xu6S

ETH - 0x3AA1a0dAfC77Ea0fb28b84F1065565Ac25e82a94
MolAdsPy 0.1.1
Manipulation of molecules adsorbed on a substrate.

# MolAdsPy

This is a package written entirely in Python to place and manipulate molecules on a substrate and then generate coordinates that can be used as inputs to first-principles calculation codes like [Quantum Espresso](https://www.quantum-espresso.org/) or [VASP](https://www.vasp.at/).

In more specific terms, the package allows the user to create objects such as molecules and slabs, which are made of atomic objects, and combine them into a system in which one or more molecular objects are adsorbed onto a slab object that acts as a substrate. An adsorbed molecule can be moved to a specific location on the substrate (e.g., a predefined adsorption site), can be shifted a certain distance from its current position, and can be rotated in three dimensions. Last but not least, an adsorbed molecule can be desorbed (removed) from the substrate.

Both the source code and documentation, whenever they are updated, will be available on the [project's GitHub site](https://github.com/rgaveiga/moladspy). Particularly, the package documentation is still at a very early stage. It's something that takes a lot of time and time ends up being a precious commodity that I don't have much of.

> In any case, in the project's *tests* directory on GitHub, use cases that show the library's capabilities are made available in the form of Jupyter notebooks.

Since the adsorbed structures are built algorithmically from Python scripts, hundreds or thousands of them can be created in a fraction of a second. This gives the modeler a lot of flexibility, especially if he/she is working on the high-throughput screening of this kind of system. That being said, the code is provided as is. The author makes no guarantee that its results are accurate and is not responsible for any losses caused by the use of the code.

If you use *MolAdsPy* in your own projects and if you don't mind, when publishing the results, please cite the following papers of mine:

* [*Structural, electronic, and magnetic properties of pristine and oxygen-adsorbed graphene nanoribbons*](https://www.sciencedirect.com/science/article/abs/pii/S0169433210003855)
* [*Interfacial properties of polyethylene/Ti3C2Tx mxene nanocomposites investigated by first-principles calculations*](https://www.sciencedirect.com/science/article/abs/pii/S0169433222028720)
* [*Self-assembly of NiTPP on Cu(111): a transition from disordered 1D wires to 2D chiral domains*](https://pubs.rsc.org/en/content/articlelanding/2015/cp/c5cp01288k)

If you have any comments, suggestions or corrections, please feel free to [drop me a message](mailto:roberto.veiga@ufabc.edu.br).
devrep 0.0.1
A small example package
Requires Python: >=3.7

# Delivery Report in Python

Release documentation template why and how-to

## 1. Intention

The main intention for this lib/template/demo is to provide a commonly usable delivery report template
that shall be used for any kind of customer delivery.
In addition to automation ability via template engine it should also assure to provide an agreed form
of delivery documentation without the need to redefine the document content and layout for each project.

It is assumed that the user has a basic understanding of python scripts and jinja2 templates. This is not covered in full detail in this short introduction.

#

## 2. Requirements

python needs to be installed. Also the packages lxml, jinja2 and invoke.

### Files:
    release_history.xml             -> Delivery documentation content

    release_history.xsd             -> Delivery documentation and validation
                                       for the XML file

    project_delivery_report.html.j2 -> python jinja2 template for html file

    release_history.py              -> python lib for XML file parsing

    generating_template.py          -> generating the html file

    tasks.py                        -> automation of this program (not necessary)

### Internal variables:

    There are some variables that must be predefined, except some entries for the xml file.

    within the parent tag "project":


    name               | mandatory -> Internal project name

    supplier           | mandatory -> "b-plus automotive GmbH" should be
                                      applicable in almost any case

    customer           | mandatory -> Customer name/company for current delivery

    customer_reference | optional  -> Customer project ID or other provided
                                      reference if available

    id                 | mandatory -> Internal project ID (pj006xxx_XYZ)

    repolink           | optional  -> Link to internal GIT/SVN repository

    contact            | mandatory -> Responsible project lead or customer 
                                      service mail address. "services@b-plus.com" for example

    id                 | mandatory -> Internal SW license ID for specific project
                                      delivery. Ask your project lead ;-)

## 3. Example Project

The provided example setup will generate a delivery report html file inside the 'release' folder with some
pre-filled dummy values.

#### -> Open __"Python_Delivery_Report"__ Folder in Terminal.

#### -> Type __"invoke --list"__ to see the exact task name to execute.

#### -> Type __"invoke release"__ to generate the html file.