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jalon3
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18
.github/dependabot.yml
vendored
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18
.github/dependabot.yml
vendored
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@@ -0,0 +1,18 @@
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# To get started with Dependabot version updates, you'll need to specify which
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# package ecosystems to update and where the package manifests are located.
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# Please see the documentation for all configuration options:
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# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
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version: 2
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updates:
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- package-ecosystem: "pip"
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directory: "/"
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schedule:
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interval: "weekly"
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day: "saturday"
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open-pull-requests-limit: 5
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groups:
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python-dependencies:
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patterns:
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- "*"
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6
.github/workflows/python-app.yml
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6
.github/workflows/python-app.yml
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@@ -19,15 +19,15 @@ jobs:
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steps:
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steps:
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- uses: actions/checkout@v4
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- uses: actions/checkout@v4
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- name: Set up Python 3.10
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- name: Set up Python 3.x
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uses: actions/setup-python@v4
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uses: actions/setup-python@v4
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with:
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with:
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python-version: "3.10"
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python-version: "3.x"
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- name: install dependencies
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- name: install dependencies
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run: |
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run: |
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python -m pip install --upgrade pip
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python -m pip install --upgrade pip
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pip install ".[test,doc]"
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pip install ".[test]"
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- name: Lint with flake8
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- name: Lint with flake8
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run: |
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run: |
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5
.github/workflows/static.yml
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5
.github/workflows/static.yml
vendored
@@ -32,15 +32,14 @@ jobs:
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- name: Checkout
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- name: Checkout
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uses: actions/checkout@v4
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uses: actions/checkout@v4
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- name: Set up Python 3.10
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- name: Set up Python 3.x
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uses: actions/setup-python@v5
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uses: actions/setup-python@v5
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with:
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with:
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python-version: '3.10'
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python-version: '3.x'
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- name: Install dependencies
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- name: Install dependencies
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run: |
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run: |
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python -m pip install --upgrade pip
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python -m pip install --upgrade pip
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# Installe le projet en mode éditable avec les extras de doc
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pip install -e ".[doc]"
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pip install -e ".[doc]"
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- name: Setup Pages
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- name: Setup Pages
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@@ -6,8 +6,13 @@ dependencies = [
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"beautifulsoup4==4.14.3",
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"beautifulsoup4==4.14.3",
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"pandas==2.3.3",
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"pandas==2.3.3",
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"tqdm==4.67.3",
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"tqdm==4.67.3",
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"scikit-learn==1.7.2"
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]
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]
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[tool.pytest.ini_options]
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pythonpath = "src"
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testpaths = ["tests"]
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[project.optional-dependencies]
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[project.optional-dependencies]
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test = ["pytest==8.4.2", "requests-mock==1.12.1", "flake8==7.3.0"]
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test = ["pytest==8.4.2", "requests-mock==1.12.1", "flake8==7.3.0"]
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doc = ["mkdocs<2.0.0", "mkdocs-material==9.6.23", "mkdocstrings[python]"]
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doc = ["mkdocs<2.0.0", "mkdocs-material==9.6.23", "mkdocstrings[python]"]
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@@ -92,18 +92,24 @@ class Cleaning:
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self._vins = self._vins.join(appellation_dummies)
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self._vins = self._vins.join(appellation_dummies)
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return self
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return self
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def drop_empty_price(self) -> "Cleaning":
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self._vins = self._vins.dropna(subset=["Prix"])
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return self
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def main() -> None:
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def main() -> None:
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if len(argv) != 2:
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if len(argv) != 2:
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raise ValueError(f"Usage: {argv[0]} <filename.csv>")
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raise ValueError(f"Usage: {argv[0]} <filename.csv>")
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filename = argv[1]
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filename = argv[1]
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cleaning: Cleaning = Cleaning(filename)
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cleaning: Cleaning = (
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cleaning.drop_empty_appellation() \
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Cleaning(filename)
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.fill_missing_scores() \
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.drop_empty_appellation()
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.encode_appellation() \
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.fill_missing_scores()
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.getVins() \
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.encode_appellation()
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.to_csv("clean.csv", index=False)
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.drop_empty_price()
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)
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cleaning.getVins().to_csv("clean.csv", index=False)
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if __name__ == "__main__":
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if __name__ == "__main__":
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31
src/learning.py
Executable file
31
src/learning.py
Executable file
@@ -0,0 +1,31 @@
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#!/usr/bin/env python3
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from typing import Any, Callable
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from pandas import DataFrame
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from sklearn.linear_model import LinearRegression
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from sklearn.model_selection import train_test_split
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from sklearn.pipeline import make_pipeline
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class Learning:
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def __init__(self, vins: DataFrame, target: str) -> None:
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self.X = vins.drop(target, axis=1)
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self.y = vins[target]
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self.X_train, self.X_test, self.y_train, self.y_test = train_test_split(
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self.X, self.y, test_size=0.25, random_state=49
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)
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def evaluate(
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self,
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estimator,
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pretreatment=None,
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fn_score=lambda m, xt, yt: m.score(xt, yt),
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):
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pipeline = make_pipeline(pretreatment, estimator) if pretreatment else estimator
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pipeline.fit(self.X_train, self.y_train)
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score = fn_score(pipeline, self.X_test, self.y_test)
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prediction = pipeline.predict(self.X_test)
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return score, prediction
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@@ -377,18 +377,10 @@ class Scraper:
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try:
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try:
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data: dict[str, object] = self.getjsondata(subdir).getdata()
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data: dict[str, object] = self.getjsondata(subdir).getdata()
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# Changement dans la maniere du site stocke ses données.
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#
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# for element in ["initialReduxState", "categ", "content"]:
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# data = cast(dict[str, object], data.get(element))
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# print(data)
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products: list[dict[str, Any]] = cast(
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products: list[dict[str, Any]] = cast(
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list[dict[str, Any]], data.get("products")
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list[dict[str, Any]], data.get("products")
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)
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)
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print(products)
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return products
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return products
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except (JSONDecodeError, HTTPError):
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except (JSONDecodeError, HTTPError):
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@@ -185,17 +185,11 @@ def mock_site():
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{dumps({
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{dumps({
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"props": {
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"props": {
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"pageProps": {
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"pageProps": {
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"initialReduxState": {
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"products": [
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"categ": {
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{"seoKeyword": "/nino-negri-5-stelle-sfursat-2022.html",},
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"content": {
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{"seoKeyword": "/poubelle",},
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"products": [
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{"seoKeyword": "/",}
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{"seoKeyword": "/nino-negri-5-stelle-sfursat-2022.html",},
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]
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{"seoKeyword": "/poubelle",},
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{"seoKeyword": "/",}
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]
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}
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}
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}
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}
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}
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}
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}
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}
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}
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@@ -213,14 +207,8 @@ def mock_site():
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{dumps({
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{dumps({
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"props": {
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"props": {
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"pageProps": {
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"pageProps": {
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"initialReduxState": {
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"products": [
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"categ": {
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]
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"content": {
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"products": [
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]
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}
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}
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}
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}
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}
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}
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}
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}
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}
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