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Merge pull request #2 from IvanildoBarauna/feat-InitialSetup
FEATURE: Initial SDK Setup
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-19
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6 files changed

+31
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.github/workflows/CI-CD.yaml

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@@ -41,16 +41,16 @@ jobs:
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token: ${{ secrets.CODECOV_TOKEN }}
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files: ./coverage.xml
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build:
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needs: test
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if: github.actor != 'actions[bot]'
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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with:
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ref: ${{ github.head_ref }}
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- name: Build and Run Image
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run: |
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docker build -t python-app .
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docker run python-app
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# build:
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# needs: test
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# if: github.actor != 'actions[bot]'
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# runs-on: ubuntu-latest
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# steps:
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# - uses: actions/checkout@v2
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# with:
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# ref: ${{ github.head_ref }}
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# - name: Build and Run Image
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# run: |
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# docker build -t api-to-dataframe .
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# docker run api-to-dataframe

.vscode/settings.json

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{
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"python.testing.pytestArgs": [
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"src"
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],
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"python.testing.unittestEnabled": false,
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"python.testing.pytestEnabled": true
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}

codecov.yml

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status:
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project:
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default:
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target: 80%
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target: 90%
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# adjust accordingly based on how flaky your tests are
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# this allows a 10% drop from the previous base commit coverage
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threshold: 2%

pyproject.toml

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[tool.poetry]
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name = "python-application"
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version = "v1.0.0"
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description = "Python Application"
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name = "api-to-dataframe"
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version = "v0.0.1"
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description = "'api-to-dataframe' é uma biblioteca Python que facilita a obtenção de dados de endpoints de API, convertendo-os diretamente em DataFrames do Pandas. Esta biblioteca oferece funcionalidades robustas, incluindo estratégias de retry para requisições falhadas e geração automática de relatórios detalhados sobre os dados recebidos."
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authors = ["IvanildoBarauna <ivanildo.jnr@outlook.com>"]
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readme = "README.md"
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license = "MIT"

setup.py

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setup(
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name='"Python Application"',
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version="1.0.0",
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name='api-to-dataframe',
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version="v0.0.1",
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packages=find_packages(),
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install_requires=parse_requirements("requirements.txt"),
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)

src/test_run.py

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import pytest
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from . import run
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def test_main():
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assert True

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