improved package import and GH action to deploy from github

.github/workflows/deploy_PyPI.yml

@@ -0,0 +1,40 @@
+name: Tests
+on:
+  workflow_dispatch
+jobs:
+  test:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest]
+        python-version: ['3.10.9']
+    steps:
+      - uses: actions/checkout@v3
+        name: Set up Python ${{ matrix.python-version }}
+
+      - uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Set up cache
+        uses: actions/cache@v3
+        with:
+          path: .venv
+          key: venv-${{ hashFiles('pyproject.toml') }}-${{ hashFiles('poetry.lock') }}
+
+      - name: Install and configure Poetry
+        run: |
+          pip install -U pip
+          pip install poetry
+          poetry config virtualenvs.in-project true
+          poetry config pypi-token.pypi ${{ secrets.PYPI }}
+          poetry install
+      - name: Run linting and other code quality checks
+        run: |
+          poetry run pre-commit run --all-files
+      - name: Run tests
+        run: export PYTHONPATH=$PYTHONPATH:$(pwd); poetry run pytest -c pyproject.toml
+      - name: Build
+        run: poetry build
+      - name: Depoly to PyPI
+        run: poetry publish

.gitignore

@@ -0,0 +1,160 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

README.md

@@ -9,7 +9,7 @@ pip install meter-proving
 
 
 ```python
-from meter_proving.meter_proving import calculate_uncertanity
+from meter_proving import calculate_uncertanity
 
 res = calculate_uncertanity([1000.00, 1000.00, 1000.00, 1000.25, 999.75])
 print(res)
@@ -18,7 +18,7 @@ print(res)
 By default standard error is gotten from range of values, if this where to come from standard deviation set repetability param to false with a confidence intervall of 95% (coverage factor of almost 2), but theses can be parameterized.
 
 ```python
-from meter_proving.meter_proving import calculate_uncertanity
+from meter_proving import calculate_uncertanity
 
 res = calculate_uncertanity(
     [1000.00, 1000.00, 1000.00, 1000.25, 999.75],
@@ -31,7 +31,7 @@ print(res)
 Standard error from standard deviation and has coverage factor of 1, witch gives a confidence interval of approx 68%
 
 ```python
-from meter_proving.meter_proving import calculate_uncertanity
+from meter_proving import calculate_uncertanity
 
 res = calculate_uncertanity(
     [1000.00, 1000.00, 1000.00, 1000.25, 999.75],

meter_proving/__init__.py

@@ -1 +1,2 @@
 __version__ = "0.1.0"
+from .meter_proving import calculate_uncertanity, pdf_normal, pdf_student_t, d

meter_proving/meter_proving.py

@@ -3,7 +3,7 @@
 from numba import njit, prange
 
 
-def pdf_student_t(dof: int, t: np.array):
+def pdf_student_t(dof: int, t: np.array) -> np.ndarray:
     """returns a np.array of len(t) of the probabilty density function of the student-t distrobution"""
     numerator = gamma(((dof + 1) / 2))
     denomenator = ((dof * np.pi) ** 0.5) * gamma((dof / 2))
@@ -12,7 +12,7 @@ def pdf_student_t(dof: int, t: np.array):
     return (numerator / denomenator) * (x**exponent)
 
 
-def pdf_normal(x: np.array, mean: float, std_dev: float):
+def pdf_normal(x: np.array, mean: float, std_dev: float) -> np.ndarray:
     """returns a np.array of len(x) of the probabilty density function of the normal distrobution"""
     fraction = 1 / (std_dev * (np.sqrt(2 * np.pi)))
     exponent = -(0.5) * (((x - mean) / std_dev)) ** 2
@@ -21,7 +21,7 @@ def pdf_normal(x: np.array, mean: float, std_dev: float):
 
 
 @njit(parallel=True)
-def cal_uncerts(t: np.array, pdf: np.array, std_devs: np.array):
+def cal_uncerts(t: np.array, pdf: np.array, std_devs: np.array) -> np.ndarray:
     """returns a np.array of len(std_devs) with the 2 sided cumulative probability from the mean and ourwards"""
     dt = t[1] - t[0]
     uncert = np.empty(len(std_devs))
@@ -72,7 +72,7 @@ def get_confidence_intervall(coverage_factor: float):
 ]
 
 
-def d(n: int):
+def d(n: int) -> float:
     """
     int n = the number of samples
     getting the convertion factor for better estimation of standard deviation for w (range of values) of the values.
@@ -86,7 +86,7 @@ def d(n: int):
         return np.sqrt(n)
 
 
-def calculate_uncertanity(x, **params):
+def calculate_uncertanity(x, **params) -> dict:
     """
     x : list, np.ndarray of values
     params:

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "meter_proving"
-version = "0.1.0"
+version = "1.0.0"
 description = "library to calculate random uncertanity of a measurment sequence"
 authors = ["StigHaraldGustavsen <stighg@gmail.com>"]
 readme = "README.md"

tests/test_meter_proving.py

@@ -1,4 +1,4 @@
-from meter_proving.meter_proving import d, calculate_uncertanity
+from meter_proving import d, calculate_uncertanity
 import pytest
 import numpy as np