semvec/pypi-packages huggingface dataset:
bigquery-spark-streaming-connector 0.7.0
spark structured streaming connector utility for gcp bigquery using storage api services.


bigquery-streaming-connector
=======
<b>This is a library for bigquery streaming connector for pyspark structured streaming</b> <b/>

The underlying connector uses [bigquery storage api services] to pull bigquery table data at scale using spark workers.

[bigquery storage api services]: https://cloud.google.com/bigquery/docs/reference/storage

The storage api services is cheaper and faster than the traditional Bigquery query api services enabling faster & cheaper Bigquery migration incrementally in a continuous fashion.

Pre-requisite

```
Need spark 4.0.0 or Databricks runtime version 15.3 & above.
pip install bigquery-spark-streaming-connector
```
Pyspark usage:

```
from streaming_connector import bq_stream_register

query=(spark.readStream.format("bigquery-streaming")
 .option("project_id", <bq_project_id>)
 .option("incremental_checkpoint_field",<table_incremental_ts_based_col>)
 .option("dataset",<bq_dataset_name>)
 .option("table",<bq_table_name>)
 .option("service_auth_json_file_name",<service_account_json_file_name>)
 .option("max_parallel_conn",<max_parallel_threads_to_pull_data>) #defaults max 1000
 .load()
 ## The above will ingest table data incrementally using the provided timestamp based field and latest value is checkpointed using offset semantics.
 ## Without the incremental input field full table ingestion is done.
 ## The service_account_json files need to be available to every spark executor workers in the '/home' folder using --files /home/<file_name>.json options or using init script (using Databricks spark)
 
 (query.writeStream.trigger(processingTime='30 seconds') 
 .option("checkpointLocation", "checkpoint_path")
 .foreachBatch(writeToTable) #your target table write function
 .start()
)
```
django-static-converter 1.0.3
A Django package that automatically converts src and href attributes in HTML templates to Django's static template tags, making it easier to manage static files efficiently.
Requires Python: >=3.6



## Description

This package modifies the HTML content of a file by replacing all `<link>` tags' `href` attributes, all `<script>` tags' `src` attributes, and all `<img>` tags' `src` attributes with Django template tags. It also adds `{% load static %}` at the beginning of the file to facilitate efficient static file management.

## Installation

To use this package, simply install it with pip. The `beautifulsoup4` library is included by default, but if you encounter any issues, you can install it separately:

```bash
pip install django-static-converter
```

## Usage

```python

# settings.py
INSTALLED_APPS = [
    # Other apps
    'django_static_converter',
    # Other apps
]

# This will process all HTML files in the 'templates' directory and its subdirectories.
```


## Example

Suppose you have an HTML file named `index.html` that looks like this:


```html
<!DOCTYPE html>
<html>
<head>
    <title>My Website</title>
    <link rel="stylesheet" href="styles.css">
    <script src="script.js"></script>
</head>
<body>
    <h1>Hello, World!</h1>
    <img src="image.png">
</body>
</html>
```

## Running
 
`py manage.py convert-static`
 

## will modify the file to look like this:

```html
{% load static %}
<!DOCTYPE html>
<html>
<head>
    <title>My Website</title>
    <link href="{% static 'styles.css' %}" rel="stylesheet">
    <script src="{% static 'script.js' %}"></script>
</head>
<body>
    <h1>Hello, World!</h1>
    <img src="{% static 'image.png' %}">
</body>
</html>

```

In this modified version, the `<link>`, `<script>`, and `<img>` tags' `href` and `src` attributes have been replaced with Django template tags, and `{% load static %}` has been added to the beginning of the file.

## Parameters

- `directory` (str): The path to the directory containing HTML files to process.

## Returns

None: The function modifies the input files in place.

## Raises

FileNotFoundError: If the input files cannot be found or accessed.

## Authors

- [Pezhman Najafi](https://github.com/pezhman-najafie)
- [Sahel Shiravand](https://github.com/sahel-shiravand)

--- 

Feel free to adjust any sections or details to better fit your project's specifics!
scipion-em-empiar 3.1.1
A Scipion plugin to make depositions to EMPIAR
Keywords: scipion empiar scipion-3.0

========================
Scipion Empiar Depositor
========================

This project is a Scipion plugin to make depositions to https://www.ebi.ac.uk/pdbe/emdb/empiar or to download raw data.

.. image:: https://img.shields.io/pypi/v/scipion-em-empiar.svg
        :target: https://pypi.python.org/pypi/scipion-em-empiar
        :alt: PyPI release

.. image:: https://img.shields.io/pypi/l/scipion-em-empiar.svg
        :target: https://pypi.python.org/pypi/scipion-em-empiar
        :alt: License

.. image:: https://img.shields.io/pypi/pyversions/scipion-em-empiar.svg
        :target: https://pypi.python.org/pypi/scipion-em-empiar
        :alt: Supported Python versions

.. image:: https://img.shields.io/sonar/quality_gate/scipion-em_scipion-em-empiar?server=https%3A%2F%2Fsonarcloud.io
        :target: https://sonarcloud.io/dashboard?id=scipion-em_scipion-em-empiar
        :alt: SonarCloud quality gate

.. image:: https://img.shields.io/pypi/dm/scipion-em-empiar
        :target: https://pypi.python.org/pypi/scipion-em-empiar
        :alt: Downloads

=====
Setup
=====

In order to install the plugin follow these instructions:

1. **Install this plugin:**

.. code-block::

    scipion installp -p scipion-em-empiar

or through the **plugin manager** by launching Scipion and following **Configuration** >> **Plugins**


Alternatively, in devel mode:


.. code-block::

    git clone -b devel https://github.com/scipion-em/scipion-em-empiar.git
    scipion installp -p local/path/to/scipion-em-empiar --devel

2. **Download Aspera Connect:**

Go to https://www.ibm.com/aspera/connect/ and download the latest version.

3. Register an account in the EMPIAR deposition and Segmentation Annotation Tool

Go to https://www.ebi.ac.uk/pdbe/emdb/empiar/deposition/register/ and get an API token at **Get empiar-deposition API token** section

4.  Open scipion's config file 'scipion3 config --show' and add the following variables:

.. code-block::

    ASCP = <aspera_binary_path> (usually it is located at $HOME/.aspera/connect/bin/ascp)
    ASPERA_SCP_PASS= <aspera_shares_user_password>
    EMPIAR_TOKEN = <empiar_token>
rvd-ap 0.1.0
My description will help you to pass time and understand my ability of writing codes
Requires Python: >=3.6

# rvd_ap

This project is done for fun and to learn how python modules are created. Since I'm spending some of my valuable resource called "Time" 
I've slao included some useful functions inside this.The following text will tell you what are the functions that I've initiased under this.
They are: avg(),sign(),perfect_num(),armstrong_num(),palindrome_num(),primality(),fib(),vowel_count(),consonant_count(),space_count(),
palindrome_str(),word_count(),alpha_count(),int_count() and div_it().

## Installation

To install the package, use the following command:

Or else go to PyPI.com and serch for the module named rvd_ap. So you'll find it there.

```sh
pip install rvd_ap
elevendoc 0.1.2
Projet python qui documente automatiquement à l'aide de call api vos projets python, génère des readme et un fichier advisory.md avec des conseils sur votre projet
Requires Python: <4.0,>=3.11

# Python Docstring and README Generator

This project is a Python-based utility that automates the generation of docstrings and README files for Python projects. It also has the capability to generate advisory files. The project is designed to help developers save time and maintain consistency in their documentation.

## About

The project consists of two main Python files: `main1.py` and `utils1.py`.

`main1.py` contains the main function that performs various tasks based on the provided arguments. It can generate and add docstrings to Python files, generate README files, and generate advisory files in the specified directory.

`utils1.py` contains several utility functions that are used by the main function. These include functions to extract function definitions from a Python file, extract key elements from a Python file, write changes to a Python file, and send code to ChatGPT for completion.

## Getting Started

To get this project up and running on your local machine, follow the instructions below.

### Prerequisites

You will need the following software installed on your machine:

- Python 3.6 or higher
- pip (Python package installer)

### Installing

1. Clone the repository to your local machine.
2. Navigate to the project directory.
3. Install the required Python packages using pip:

```bash
pip install -r requirements.txt
```

### Running the project

To run the project, navigate to the project directory and run the following command:

```bash
python main1.py --docstring --Readme --advisory <your_directory>
```

Replace `<your_directory>` with the directory where you want the project to perform its tasks.



This command will generate and add docstrings to all Python files in the `./my_project` directory.

## Built Using

- Python
- ast (Python's Abstract Syntax Trees module)
- OpenAI's ChatGPT

## Contributing

If you would like to contribute to this project, please fork the repository, make your changes, and submit a pull request.

## Authors

- Matthieu Kaeppelin

## Acknowledgments

- OpenAI for their ChatGPT model
- Python's ast module