https://github.com/wa-lead/profiler

Simple python profiler
https://github.com/wa-lead/profiler

optimization profiler python

Last synced: about 1 month ago
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Simple python profiler

• Host: GitHub
• URL: https://github.com/wa-lead/profiler
• Owner: Wa-lead
• Created: 2024-02-19T18:03:58.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-02-24T13:37:19.000Z (11 months ago)
• Last Synced: 2024-02-24T14:35:03.359Z (11 months ago)
• Topics: optimization, profiler, python
• Language: Python
• Homepage:
• Size: 4.88 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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README

        
# Profiler

Profiler is an extremely user-friendly Python package designed for profiling Python scripts to analyze their runtime performance with a focus on line-by-line analysis. It leverages the `line_profiler` package to give developers insights into which lines of code consume the most time, helping to optimize and improve code efficiency.

## Installation

To install Profiler, simply use pip:

```

pip install git+https://github.com/wa-lead/profiler.git

```

## Usage

After installation, you can use the `profiler` command followed by your script's filename to profile it:

```

profiler script.py

```

This will run `script.py` and output a line-by-line breakdown of execution time.

### Function Selection

If you want to selectively profile specific functions within your script, you can use the `--select` option to interactively choose which functions to profile:

```

profiler script.py --select

```

Upon using this command, you'll be presented with the list of functions found in `script.py`. 



> NOTE: `script.py` must have a `main()` function defined, as Profiler will attempt to profile this function.

### Example

Given a Python script `example.py`, you can profile it as follows:

```python

# Description: This is a simple backtracking algorithm to solve the map coloring problem.

def is_valid(coloring, graph, node, color):

    for neighbor in graph[node]:

        if color == coloring.get(neighbor):

            return False

    return True

def color_map(graph, colors, node=0, coloring={}):

    if node == len(graph):

        return coloring

    for color in colors:

        if is_valid(coloring, graph, node, color):

            coloring[node] = color

            result = color_map(graph, colors, node + 1, coloring)

            if result is not None:

                return coloring

            del coloring[node]

    return None

def main():

    # Define the map as a graph: node numbers represent regions, edges represent adjacencies.

    graph = {

        0: [1, 2, 3],

        1: [0, 2, 4],

        2: [0, 1, 3, 4],

        3: [0, 2, 4],

        4: [1, 2, 3]

    }

    colors = ['Red', 'Green', 'Blue', 'Yellow']  # Define available colors

    coloring = color_map(graph, colors)

    if coloring is not None:

        print("Found a coloring:", coloring)

    else:

        print("No coloring found that satisfies all constraints.")

if __name__ == "__main__":

    main()

```

In the terminal, run:

```

profiler example.py

```

or to interactively select functions:

```

profiler example.py --select

```

Output will include a line-by-line breakdown of execution time for each function within `example.py`, helping you identify performance bottlenecks.