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Remove with matrix.python-version
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.github/workflows/build.yml

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@@ -21,8 +21,8 @@ jobs:
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with:
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clean: true
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- uses: jupyterlab/maintainer-tools/.github/actions/base-setup@v1
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with:
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python_version: "${{ matrix.python-version }}"
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# with:
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# python_version: "${{ matrix.python-version }}"
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- name: Display dependency info
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run: |
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python --version
@@ -33,6 +33,7 @@ jobs:
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- name: Install Python dependencies
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run: |
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pip install ".[test]"
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pip install --upgrade cloudpickle
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- name: Build and install Jupyter Enterprise Gateway
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uses: nick-invision/[email protected]
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with:

enterprise_gateway/itests/test_python_kernel.py

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@@ -122,6 +122,7 @@ def test_run_pi_example(self):
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pi_code = []
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pi_code.append("from random import random\n")
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pi_code.append("from operator import add\n")
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pi_code.append("from pyspark.cloudpickle import cloudpickle\n")
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pi_code.append("partitions = 20\n")
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pi_code.append("n = 100000 * partitions\n")
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# Define the function with explicit imports inside to avoid serialization issues
@@ -130,6 +131,8 @@ def test_run_pi_example(self):
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pi_code.append(" x = random() * 2 - 1\n")
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pi_code.append(" y = random() * 2 - 1\n")
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pi_code.append(" return 1 if x ** 2 + y ** 2 <= 1 else 0\n")
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pi_code.append("pickled_f = cloudpickle.dumps(f)\n")
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pi_code.append("print('Function f successfully pickled!')\n")
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# Use a lambda function directly in map to avoid complex serialization
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pi_code.append("count = sc.parallelize(range(1, n + 1), partitions).map(f).reduce(add)\n")
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pi_code.append('print("Pi is roughly %f" % (4.0 * count / n))\n')

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