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|
| | import typing |
| | from typing import Iterator |
| |
|
| | import pytest |
| |
|
| | if typing.TYPE_CHECKING: |
| | from IPython.terminal.interactiveshell import TerminalInteractiveShell |
| |
|
| | IPython = pytest.importorskip("IPython") |
| | interactiveshell = pytest.importorskip("IPython.terminal.interactiveshell") |
| | tools = pytest.importorskip("IPython.testing.tools") |
| | matplotlib = pytest.importorskip("matplotlib") |
| |
|
| | |
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| |
|
| |
|
| | @pytest.fixture(scope="session") |
| | def ipython() -> "TerminalInteractiveShell": |
| | config = tools.default_config() |
| | config.TerminalInteractiveShell.simple_prompt = True |
| | shell = interactiveshell.TerminalInteractiveShell.instance(config=config) |
| | return shell |
| |
|
| |
|
| | @pytest.fixture() |
| | def ipython_interactive( |
| | request: pytest.FixtureRequest, ipython: "TerminalInteractiveShell" |
| | ) -> Iterator["TerminalInteractiveShell"]: |
| | """Activate IPython's builtin hooks |
| | |
| | for the duration of the test scope. |
| | """ |
| | with ipython.builtin_trap: |
| | yield ipython |
| |
|
| |
|
| | def _strip_region_tags(sample_text: str) -> str: |
| | """Remove blank lines and region tags from sample text""" |
| | magic_lines = [ |
| | line for line in sample_text.split("\n") if len(line) > 0 and "# [" not in line |
| | ] |
| | return "\n".join(magic_lines) |
| |
|
| |
|
| | def test_jupyter_tutorial(ipython: "TerminalInteractiveShell") -> None: |
| | matplotlib.use("agg") |
| | ip = IPython.get_ipython() |
| | ip.extension_manager.load_extension("bigquery_magics") |
| |
|
| | sample = """ |
| | # [START bigquery_jupyter_magic_gender_by_year] |
| | %%bigquery |
| | SELECT |
| | source_year AS year, |
| | COUNT(is_male) AS birth_count |
| | FROM `bigquery-public-data.samples.natality` |
| | GROUP BY year |
| | ORDER BY year DESC |
| | LIMIT 15 |
| | # [END bigquery_jupyter_magic_gender_by_year] |
| | """ |
| | result = ip.run_cell(_strip_region_tags(sample)) |
| | result.raise_error() |
| |
|
| | sample = """ |
| | # [START bigquery_jupyter_magic_gender_by_year_var] |
| | %%bigquery total_births |
| | SELECT |
| | source_year AS year, |
| | COUNT(is_male) AS birth_count |
| | FROM `bigquery-public-data.samples.natality` |
| | GROUP BY year |
| | ORDER BY year DESC |
| | LIMIT 15 |
| | # [END bigquery_jupyter_magic_gender_by_year_var] |
| | """ |
| | result = ip.run_cell(_strip_region_tags(sample)) |
| | result.raise_error() |
| |
|
| | assert "total_births" in ip.user_ns |
| | total_births = ip.user_ns["total_births"] |
| | |
| | total_births.plot(kind="bar", x="year", y="birth_count") |
| | |
| |
|
| | sample = """ |
| | # [START bigquery_jupyter_magic_gender_by_weekday] |
| | %%bigquery births_by_weekday |
| | SELECT |
| | wday, |
| | SUM(CASE WHEN is_male THEN 1 ELSE 0 END) AS male_births, |
| | SUM(CASE WHEN is_male THEN 0 ELSE 1 END) AS female_births |
| | FROM `bigquery-public-data.samples.natality` |
| | WHERE wday IS NOT NULL |
| | GROUP BY wday |
| | ORDER BY wday ASC |
| | # [END bigquery_jupyter_magic_gender_by_weekday] |
| | """ |
| | result = ip.run_cell(_strip_region_tags(sample)) |
| | result.raise_error() |
| |
|
| | assert "births_by_weekday" in ip.user_ns |
| | births_by_weekday = ip.user_ns["births_by_weekday"] |
| | |
| | births_by_weekday.plot(x="wday") |
| | |
| |
|
| | |
| | from google.cloud import bigquery |
| |
|
| | client = bigquery.Client() |
| | |
| |
|
| | |
| | sql = """ |
| | SELECT |
| | plurality, |
| | COUNT(1) AS count, |
| | year |
| | FROM |
| | `bigquery-public-data.samples.natality` |
| | WHERE |
| | NOT IS_NAN(plurality) AND plurality > 1 |
| | GROUP BY |
| | plurality, year |
| | ORDER BY |
| | count DESC |
| | """ |
| | df = client.query(sql).to_dataframe() |
| | df.head() |
| | |
| |
|
| | |
| | pivot_table = df.pivot(index="year", columns="plurality", values="count") |
| | pivot_table.plot(kind="bar", stacked=True, figsize=(15, 7)) |
| | |
| |
|
| | |
| | sql = """ |
| | SELECT |
| | gestation_weeks, |
| | COUNT(1) AS count |
| | FROM |
| | `bigquery-public-data.samples.natality` |
| | WHERE |
| | NOT IS_NAN(gestation_weeks) AND gestation_weeks <> 99 |
| | GROUP BY |
| | gestation_weeks |
| | ORDER BY |
| | gestation_weeks |
| | """ |
| | df = client.query(sql).to_dataframe() |
| | |
| |
|
| | |
| | ax = df.plot(kind="bar", x="gestation_weeks", y="count", figsize=(15, 7)) |
| | ax.set_title("Count of Births by Gestation Weeks") |
| | ax.set_xlabel("Gestation Weeks") |
| | ax.set_ylabel("Count") |
| | |
| |
|