semvec/pypi-packages huggingface dataset:
OscarScrapper 1.5
Academy Awards Scraper and Data processor

# The OscarScrapper (1930-2021)

This is the final project for JEM207 Data Processing with Python made by Yann Aubineau and Samuel Božoň of Charles University.

The aim for our project is to scrape and process the historical data of the **Academy Awards** popularly known as **the Oscars**, and create a user friendly package with easy way to select categories and years which should be scraped
We scrape from oscars.org website historical datas of every nominee and winner for the following 4 categories:
>

> Best Picture (1927-2021)
> Best Director (1927-2021)
> Best Actor (1927-2021)
> Best Actress (1927-2021)

Each dataset would be indexed by year and category.

The sources used for the following datas are: 
- oscars.org
- tmdb.com's API

Firstly we scrape the data for nominees and winners for each selected year for all the selected categories. 

Then, we will use these datas to aks tmdb's API for more informations about the movie. However, given that there may be multiple films and persons with the same name, we are selecting from the API's response only relevant informations. 

These are afterwards processed and added to our dataframe, which is later stored for the future use. 

User can select categories and years in which he is interested through easy GUI. For each of his selection, new dataset stored in csv file is created, permitting easy creation of multiple datasets with different searches chosen by user. 

To use the OscarScrapper, you can either download the repository and execute Package_OscarScrapper/src/Oscarscrapper_package/Oscarscrapper.py or use pip to download it as a package.

```sh
# Pypi
pip install OscarScrapper
```

```sh
from Oscarscrapper_package import Oscarscrapper

Scraper = Oscarscrapper.Oscar_Scraper()
```
proc-mem-monitor 0.0.3
Process Memory Monitor

# Process Memory Monitor
A Python application for monitoring total memory usage of commands matching specified 
pattern. It displays the information either on Tkinter GUI if DISPLAY is availabe or
on stdout if it's launched from a text-only termainl.

# Installation
## OS
proc-mem-monitor has been tested on CentOS 7.8 and Ubuntu 16.04.

## Python
This program requires Python 3.6 or newer to run. 

### Ubuntu 16.04
The default Python on Ubuntu 16.04 is version 3.5. Run the commands below to 
install Python 3.6
```
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt-get update
sudo apt-get install python3.6 python3.6-venv python3.6-tk 
```

### Redhat/CentOS 7.8
The default Python on CentOS 7.8 is already version 3.6. You only need to 
install Python Tkinter.
```
sudo yum install python36-tkinter
```

## Create and activate a Python3 virtual environment
```
python3.6 -m venv venv
. venv/bin/activate
```

## Install xbutil GUI as a regular user
`pip install proc_mem_monitor`

## Install xbutil GUI as a contributor
### Install required Python packages
`pip install -r requirements.txt`

### Install proc-mem-monitor in development Mode
`python setup.py develop`

# Run Process Memory Monitor
Run the command below from the Python virtual environment created above
`proc_mem_monitor`

# Snapshots
## Process Memory Monitor on Tkinter GUI
![image](https://user-images.githubusercontent.com/24323762/111917693-a8d3f280-8a3e-11eb-885a-a261787acc54.png)

# Publish xbutil_gui to PyPI
`./scripts/publish-pypi.sh`

The following modules may need to be upgraded or installed:
```
pip install --upgrade pip
pip install twine
```