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chore: remove references to conda (googleapis#795)
See also, internal change 650726157. Thank you for opening a Pull Request! Before submitting your PR, there are a few things you can do to make sure it goes smoothly: - [ ] Make sure to open an issue as a [bug/issue](https://togithub.com/googleapis/python-bigquery-pandas/issues/new/choose) before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea - [ ] Ensure the tests and linter pass - [ ] Code coverage does not decrease (if any source code was changed) - [ ] Appropriate docs were updated (if necessary) 🦕
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‎.kokoro/build.sh‎

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#!/bin/bash
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# Copyright 2023 Google LLC
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# Copyright 2024 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# Disable buffering, so that the logs stream through.
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export PYTHONUNBUFFERED=1
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export CONDA_EXE=/root/conda/bin/conda
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export CONDA_PREFIX=/root/conda
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export CONDA_PROMPT_MODIFIER=(base)
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export _CE_CONDA=
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export CONDA_SHLVL=1
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export CONDA_PYTHON_EXE=/root/conda/bin/python
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export CONDA_DEFAULT_ENV=base
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export PATH=/root/conda/bin:/root/conda/condabin:${PATH}
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# Debug: show build environment
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env
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env | grep KOKORO
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# Setup service account credentials.
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export GOOGLE_APPLICATION_CREDENTIALS=${KOKORO_GFILE_DIR}/service-account.json
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# Setup project id.
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export PROJECT_ID=$(cat "${KOKORO_GFILE_DIR}/project-id.json")
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# Install nox
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python3 -m pip install --upgrade --quiet nox
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# If this is a continuous build, send the test log to the FlakyBot.
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# See https://github.com/googleapis/repo-automation-bots/tree/main/packages/flakybot.
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if [[ $KOKORO_BUILD_ARTIFACTS_SUBDIR = *"continuous"* ]]; then

‎.kokoro/presubmit/conda_test.cfg‎

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‎CHANGELOG.md‎

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### Bug Fixes
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* Handle None when converting numerics to parquet ([#768](https://github.com/googleapis/python-bigquery-pandas/issues/768)) ([53a4683](https://github.com/googleapis/python-bigquery-pandas/commit/53a46833a320963d5c15427f6eb631e0199fb332))
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* Set minimum allowable version of sqlite when performing a conda install ([#780](https://github.com/googleapis/python-bigquery-pandas/issues/780)) ([8a03d44](https://github.com/googleapis/python-bigquery-pandas/commit/8a03d44fbe125ae1202f43b7c6e54c98eca94d4d))
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### Documentation
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([#281](https://github.com/googleapis/python-bigquery-pandas/issues/281))
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- Fix `pytest.raises` usage for latest pytest. Fix warnings in tests.
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([#282](https://github.com/googleapis/python-bigquery-pandas/issues/282))
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- Update CI to install nightly packages in the conda tests.
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([#254](https://github.com/googleapis/python-bigquery-pandas/issues/254))
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## 0.10.0 / 2019-04-05
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‎README.rst‎

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pandas-gbq
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==========
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|preview| |pypi| |versions|
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|preview| |pypi| |versions|
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**pandas-gbq** is a package providing an interface to the Google BigQuery API from pandas.
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Installation
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------------
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Install latest release version via conda
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code-block:: shell
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$ conda install pandas-gbq --channel conda-forge
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Install latest release version via pip
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. code:: python
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import pandas_gbq
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result_dataframe = pandas_gbq.read_gbq("SELECT column FROM dataset.table WHERE value = 'something'")
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Upload a dataframe
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.. code:: python
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import pandas_gbq
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pandas_gbq.to_gbq(dataframe, "dataset.table")
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More samples

‎docs/contributing.rst‎

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It's helpful to install pandas-gbq in development mode so that you can
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use the library without reinstalling the package after every change.
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Conda
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~~~~~
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Create a new conda environment and install the necessary dependencies
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.. code-block:: shell
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$ conda create -n my-env --channel conda-forge \
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db-dtypes \
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pandas \
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pydata-google-auth \
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google-cloud-bigquery
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$ source activate my-env
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Install pandas-gbq in development mode
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.. code-block:: shell
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$ python setup.py develop
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Pip & virtualenv
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~~~~~~~~~~~~~~~~
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*Skip this section if you already followed the conda instructions.*
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Create a new `virtual
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environment <https://virtualenv.pypa.io/en/stable/userguide/>`__.
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‎docs/install.rst‎

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Installation
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============
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You can install pandas-gbq with ``conda``, ``pip``, or by installing from source.
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You can install pandas-gbq with ``pip`` or by installing from source.
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Conda
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-----
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.. code-block:: shell
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$ conda install pandas-gbq --channel conda-forge
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This installs pandas-gbq and all common dependencies, including ``pandas``.
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Pip
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---

‎docs/reading.rst‎

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pip install --upgrade google-cloud-bigquery-storage pyarrow
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With conda:
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.. code-block:: sh
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conda install -c conda-forge google-cloud-bigquery-storage
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#. Set ``use_bqstorage_api`` to ``True`` when calling the
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:func:`~pandas_gbq.read_gbq` function. As of the ``google-cloud-bigquery``
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package, version 1.11.1 or later,the function will fallback to the

‎noxfile.py‎

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import pathlib
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import re
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import shutil
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import subprocess
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import time
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import warnings
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"3.9": [],
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}
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CONDA_TEST_PYTHON_VERSIONS = [
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UNIT_TEST_PYTHON_VERSIONS[0],
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UNIT_TEST_PYTHON_VERSIONS[-1],
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]
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SYSTEM_TEST_PYTHON_VERSIONS = ["3.8", "3.9", "3.10", "3.11", "3.12"]
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SYSTEM_TEST_STANDARD_DEPENDENCIES = [
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"mock",
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@_calculate_duration
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def prerelease(session):
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session.install(
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# https://arrow.apache.org/docs/developers/python.html#installing-nightly-packages
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"--extra-index-url",
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"https://pypi.fury.io/arrow-nightlies/",
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"--prefer-binary",
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"--pre",
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"--upgrade",
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"pyarrow",
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)
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session.install(
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"--extra-index-url",
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"https://pypi.anaconda.org/scipy-wheels-nightly/simple",
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"--prefer-binary",
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"--pre",
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"--upgrade",
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"pandas",
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)
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session.install(
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"--prefer-binary",
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"--pre",
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"google-resumable-media",
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# Exclude version 1.49.0rc1 which has a known issue. See https://github.com/grpc/grpc/pull/30642
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"grpcio!=1.49.0rc1",
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"pandas",
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)
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session.install(
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"freezegun",
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os.path.join("docs", ""),
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os.path.join("docs", "_build", "html", ""),
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)
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def install_conda_unittest_dependencies(session, standard_deps, conda_forge_packages):
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"""Installs packages from conda forge, pypi, and locally."""
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# Install from conda-forge and default conda package repos.
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session.conda_install(*conda_forge_packages, channel=["defaults", "conda-forge"])
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# Install from pypi for packages not readily available on conda forge.
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session.install(
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*standard_deps,
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)
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# Install via pip from the local repo, avoid doing dependency resolution
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# via pip, so that we don't override any conda resolved dependencies
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session.install("-e", ".", "--no-deps")
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@nox.session(python=CONDA_TEST_PYTHON_VERSIONS, venv_backend="mamba")
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@_calculate_duration
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def conda_test(session):
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"""Run test suite in a conda virtual environment.
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Installs all test dependencies, then installs this package.
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NOTE: Some of these libraries are not readily available on conda-forge
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at this time and are thus installed using pip after the base install of
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libraries from conda-forge.
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We decided that it was more important to prove a base ability to install
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using conda than to complicate things with adding a whole nother
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set of constraints just for a conda install, so this install does not
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attempt to constrain packages (i.e. in a constraints-x.x.txt file)
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manually.
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"""
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standard_deps = (
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UNIT_TEST_STANDARD_DEPENDENCIES
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+ UNIT_TEST_DEPENDENCIES
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+ UNIT_TEST_EXTERNAL_DEPENDENCIES
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)
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conda_forge_packages = [
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"db-dtypes",
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"google-api-core",
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"google-auth",
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"google-auth-oauthlib",
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"google-cloud-bigquery",
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"google-cloud-bigquery-storage",
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"numpy",
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"pandas",
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"pyarrow",
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"pydata-google-auth",
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"tqdm",
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"protobuf",
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"sqlite>3.31.1", # v3.31.1 caused test failures
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]
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install_conda_unittest_dependencies(session, standard_deps, conda_forge_packages)
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# Provide a list of all installed packages (both from conda forge and pip)
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# for troubleshooting purposes.
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session.run("mamba", "list")
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# Using subprocess.run() instead of session.run() because
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# session.run() does not correctly handle the pip check command.
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subprocess.run(
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["pip", "check"], check=True
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) # Raise an exception if pip check fails
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# Tests are limited to unit tests only, at this time.
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session.run(
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"py.test",
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"--quiet",
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f"--junitxml=unit_{session.python}_sponge_log.xml",
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"--cov=pandas_gbq",
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"--cov=tests/unit",
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"--cov-append",
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"--cov-config=.coveragerc",
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"--cov-report=",
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"--cov-fail-under=0",
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os.path.join("tests", "unit"),
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*session.posargs,
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)

‎owlbot.py‎

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"docs/multiprocessing.rst",
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"noxfile.py",
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"README.rst",
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# exclude .kokoro/build.sh which is customized due to support for conda
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".kokoro/build.sh",
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# exclude this file as we have an alternate prerelease.cfg
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".kokoro/presubmit/prerelease-deps.cfg",
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]
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],
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)
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# ----------------------------------------------------------------------------

‎release-procedure.md‎

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twine upload dist/*
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* Create the [release on GitHub](https://github.com/pydata/pandas-gbq/releases/new) using the tag created earlier.
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* Create the [release on GitHub](https://github.com/googleapis/python-bigquery-pandas/releases/new) using the tag created earlier.
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* Upload wheel and source zip from `dist/` directory.
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* Do a pull-request to the feedstock on `pandas-gbq-feedstock <https://github.com/conda-forge/pandas-gbq-feedstock/>`__
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(Or review PR from @regro-cf-autotick-bot which updates the feedstock).
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* update the version
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* update the SHA256 (retrieve from PyPI)
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* update the dependencies (if they changed)

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