semvec/pypi-packages huggingface dataset:
code-time-checker 0.0.4
A reusable timer utility for Python scripts
Requires Python: >=3.6

# Code-Time: A Reusable Timer Utility for Python Scripts

Code-Time-Checker is a lightweight and reusable Python package for measuring the execution time of scripts, functions, and code blocks. Itâ€™s perfect for developers who want to profile their Python code quickly.

## Features
- **Function Timing**: Use a decorator to measure the execution time of any function.
- **Code Block Timing**: Use a context manager to time specific blocks of code.
- **Script Timing**: Easily measure the total execution time of your Python script.

## Installation
Install Code-Time-Checker using pip:
```bash
pip install code-time-checker
```

## Usage

### 1. Timing Code Blocks
Use the `time_block` context manager to measure the time taken by a specific block of code:

```python
from code_time_checker import time_block

with time_block("Processing Loop"):
    for _ in range(10**6):
        pass
```
**Output:**
```
Processing Loop executed in 0.1234 seconds
```

### 2. Timing Functions
Use the `time_function` decorator to measure the time taken by any function:

```python
from code_time_checker import time_function

@time_function
def example_function():
    for _ in range(10**7):
        pass

example_function()
```
**Output:**
```
Function 'example_function' executed in 0.4567 seconds
```

### 3. Timing an Entire Script
Use the `script_timer` utility to measure the total execution time of a script:

```python
from code_time import script_timer

with script_timer():
    print("Starting script...")
    for _ in range(10**6):
        pass
    print("Script complete.")
```
**Output:**
```
Starting script...
Script complete.
Script executed in 0.7890 seconds
```

## Contributing
Contributions are welcome! Feel free to open issues or submit pull requests.

## License
This project is licensed under the MIT License. See the `LICENSE` file for details.

---

## Author
- **Deep Korat**  
  [GitHub Profile](https://github.com/deepkorat) | [Email](mailto:deepkorat13@gmail.com)
pychemparse 0.6.1
A package for extracting data from ORCA .out, GPAW .txt files, and more. It allows for the creation of user-defined extraction patterns to ensure accurate data extraction from various ORCA versions.
Requires Python: <4.0,>=3.10

# ChemParse

![logo](image/README/logo.png)

## About

Package for extracting the data from ORCA .out, GPAW .txt files and many more.

This package is not only made to extract the data from premade extraction patterns but is mostly aimed toward the creation of user extraction patterns from the unknown blocks, to warranty the extraction from the outputs from the different ORCA versions.

It prevents the extraction of the data from incorrect parts of the output and creates the marking of the document.

## Python

Example of the pandas.DataFrame with the extracted data, both premade and created by a user. See examples for more details.

![python](image/README/python_pd.png)

## Scripts

The data can be extracted from the shell (see examples):

![scipt](image/README/script_html.png "HTML data output")

## HTML

Conversion of .out files into interactive HTML with block markup is available (see examples):

![html](image/README/html_preview.png "HTML output")

## Instalation

Git clone the repository and

```
pip install .
```