semvec/pypi-packages huggingface dataset:
juddasTALib 0.0.1
Just another technical analysis indicator lib
License: MIT
Requires Python: >=3.6
Keywords: TA,indicators,technical analysis,trading,finance

Various techical analyst indicators for using as part of your trading algo

Change Log
==========

0.0.1 (07/08/2023)
------------------
-First realease that only includes three variants of the ATR: Using SMA, EMA & WMA as smoothing
terrorform 0.2.1
Terraform wrapper for python
License: MIT
Requires Python: >=3.5

## terrorform

Python wrapper for [Terraform](https://www.terraform.io/)

### Purpose

This library provides a thin wrapper around the Terraform build tool. Existing libraries for the same purpose were
either more complicated than what I needed or defunct. The name `terrorform` was chosen because every other name I 
could think of was being squatted on in PyPi. 

### Package Installation and Usage

The package is available on [PyPi](https://pypi.org/project/terrorform/0.1.0/):
```shell
python -m pip install terrorform
```

The library can be imported in the normal ways:
```python
import terrorform
from terrorform import *
```

### Examples

This library supports `init`, `apply`, and `destroy` workflows:

```python
from terrorform import *

# Run full setup/teardown workflow with target directory equal to current working directory
init_resp = terrorform.init()
apply_resp = terrorform.apply()
destroy_resp = terrorform.destroy()
```

The library also supports top level synonyms, allowing the same workflows to be run without 
referencing the `terrorform` class:

```python
from terrorform import *

init_resp = init()
apply_resp = apply()
destroy_resp = destroy()
```

Keyword arguments, boolean flags, and custom variables are passed to each workflow. No checking
is performed to ensure that they are valid terraform CLI options. These parameters are split into
three categories: keyword arguments, boolean flags, and custom variables:

```python
apply_resp = terrorform.apply(
    # Terraform-specific keyword args, both global and non-global
    kw_args={
        "-chdir": "/tmp/terrorform/"
    },
    # Terraform-specific boolean flags
    boolean_flags=["-no-color"],
    # Custom variables required by your terraform scripts
    vars_dict={
        "my_custom_variable": "Hello"
    }
)
```


### Testing

Tests are run using `pytest`:

```shell
python -m pytest tests.py
```
dapplooker 0.0.4
A minimal, complete, python API for DappLooker
License: MIT
Requires Python: >=3.8

# DappLooker Python SDK

![DappLooker Logo](https://d2yxqfr8upg55w.cloudfront.net/npm-package-images/DLLogo1800x400.png)

Discover blockchain insights effortlessly with the DappLooker Python SDK. Access reliable Web3 data and popular Dapp charts via the DappLooker Analytics platform. Enhance your Python projects with seamless integration.


[![Downloads](https://pepy.tech/badge/dapplooker)](https://pepy.tech/project/dapplooker)


## Introduction

DappLooker Python SDK provides developers with programmatic access to comprehensive blockchain data in the Web3 environment. With this SDK, you can easily retrieve popular charts data for your decentralized applications (Dapps). The DappLooker Analytics platform offers a no-code, community-driven analytics and visualization platform for blockchain networks and Dapps.

## Features

- Access reliable and comprehensive blockchain data effortlessly.
- Retrieve popular charts data for your Dapps with ease.
- Integrate seamlessly with your Python projects.

## Installation

You can install the DappLooker Python SDK using `pip`:

```bash
pip install dapplooker
```

## Getting Started

To get started with the DappLooker Python SDK, follow these steps:

1. **Generate an API key**:

   - Create an account on the [DappLooker website](https://dapplooker.com/).
   - After signing up, navigate to the [API keys](https://dapplooker.com/user/api) page.
   - Click on `+ API Key` and provide a name for your API key.
   - Click on `Generate Key` and copy your API key for future use.

2. **Import the SDK**:

   Import the DappLooker SDK in your Python project:

   ```python
   from dapplooker import DappLookerChartsAPI
   ```

3. **Access Blockchain Data**:

   With the SDK imported, create an instance of the `DappLookerChartsAPI` class and make API calls using your API key.

   ```python
   # Replace 'your_api_key' with the API key you obtained
   api_key = 'your_api_key'
   
   # Replace 'your_chart_uuid' with the UUID of the chart you want to retrieve data for
   chart_uuid = 'your_chart_uuid'
   
   # Make an API call to get chart data
   response = DappLookerChartsAPI.get_chart_data(chart_uuid, api_key)
   
   # Process the response data as per your requirements
   print(response)
   ```

## Resources

- **[DappLooker Website](https://dapplooker.com/)** - To discover our product and analytics platform.
- **[DappLooker SDK Repository](https://github.com/dapplooker/dapplooker-sdk/)** - To explore the inspiration for this Python SDK.
- **[DappLooker Documentation](https://docs.dapplooker.com)** - For comprehensive documentation on the SDK and analytics platform.

## Contributing

We welcome contributions from the community to improve the DappLooker Python SDK. If you find any issues, have suggestions for new features, or want to help with bug fixes, feel free to submit a pull request or create an issue on the [GitHub repository](https://github.com/dapplooker/dapplooker-sdk/).