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tools for common operations in a module

Project description

olutils

Introduction

The module olutils provide common tools to simplify project creation. It includes:

  • class with logger
  • parameter management
  • object management (copy, saving, loading)
  • plotting (if matplotlib available)

Installation

One can install olutils using pip install command:

```bash
pip install olutils
```

Usage

Use of temporal converters and deep defaultdict:

import olutils

# Building a deep default dict with datetimes as values
flights = olutils.deepdefaultdict(lambda x: None, depth=2)

# Filling it
flights['Paris-NY']['departure'] = olutils.str2dt("2019-01-15 08:00+01:00")
flights['Paris-NY']['arrival'] = olutils.str2dt("2019-01-15 10:30-05:00")
flights['NY-Paris']['departure'] = olutils.str2dt("2019-01-17 23:00-05:00")
flights['NY-Paris']['arrival'] = olutils.str2dt("2019-01-15 11:00+01:00")

flights.pprint()

File reading and object storing:

import olutils

my_dict = {'key_1': "value_1", 'key_2': 2}
my_rows = [{'col_1': 11, 'col_2': 21}, {'col_1': 21, 'col_2': 22}]

# Saving objects in output directory (automatically created)
olutils.save(my_dict, "output/my_dict.json")
olutils.save(my_rows, "output/my_rows.csv")
olutils.save(my_rows, "output/my_rows.unknown", mthd="json")

# Loading objects from save outputs
my_loaded_dict = olutils.load("output/my_dict.json")
my_loaded_rows = olutils.load("output/my_rows.csv")
my_loaded_rows_ = olutils.load("output/my_rows.unknown", mthd="json")

Multi-plotting

import matplotlib.pyplot as plt
import numpy as np

from olutils import plotiter

for i in plotiter(range(5), n_cols=3):
    x = [i + k/10 for k in range(10)]
    y = [np.sin(xk) for xk in x]
    plt.plot(x, y)

For developers

Download the project

Clone repository:

git clone https://github.com/OctaveLauby/olutils.git
cd olutils

One can make an editable code installation:

pip install -e .

Virtual Environment

python -m venv venv
source venv/Scripts/activate
python -m pip install -r requirements.txt
...
deactivate

matplotlib does not have to be imported: plotting submodule is not loaded in that case

Distribution

  1. Install distribution libraries

    pip install check-manifest
    pip install twine
    pip install wheel
    
  2. Building manifest file:

    check-manifest --create
    
  3. Building the wheel:

    python setup.py bdist_wheel
    
  4. Building the source distribution:

    python setup.py sdist
    
  5. Publishing:

    python setup.py bdist_wheel sdist
    twine upload dist/*
    

For TestPyPi publication: twine upload --repository-url https://test.pypi.org/legacy/ dist/*

Not working on Git terminal for some reason

Testing

python -m pytest olutils -vv
python -m pylint olutils --ignore-patterns=test*

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