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Update intro.rst #79

Merged
merged 4 commits into from
Aug 3, 2017
Merged

Update intro.rst #79

merged 4 commits into from
Aug 3, 2017

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alanyee
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@alanyee alanyee commented Aug 3, 2017

-Made explicit HTTPS calls
-Fixed minor grammar and whitespace issues

alanyee added 2 commits August 1, 2017 14:51
-Fix some grammar mistakes
-Made explicit HTTPS calls
Minor grammar fixes
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codecov-io commented Aug 3, 2017

Codecov Report

Merging #79 into master will decrease coverage by 45.27%.
The diff coverage is n/a.

Impacted file tree graph

@@             Coverage Diff             @@
##           master      #79       +/-   ##
===========================================
- Coverage   73.44%   28.17%   -45.28%     
===========================================
  Files           4        4               
  Lines        1544     1544               
===========================================
- Hits         1134      435      -699     
- Misses        410     1109      +699
Impacted Files Coverage Δ
pandas_gbq/gbq.py 19.2% <0%> (-56.13%) ⬇️
pandas_gbq/tests/test_gbq.py 27.94% <0%> (-54.94%) ⬇️

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Thanks @alanyee for these updates! Just a couple minor observations.

Authentication to the Google ``BigQuery`` service is via ``OAuth 2.0``.
Is possible to authenticate with either user account credentials or service account credentials.
Authentication to the Google ``BigQuery`` service via ``OAuth 2.0``
is possible to authenticate with either user account credentials or service account credentials.
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Authentication to the Google BigQuery service via OAuth 2.0 is possible with either user or service account credentials.

which will be automatically opened for you. You will be authenticated to the specified
``BigQuery`` account using the product name ``pandas GBQ``. It is only possible on local host.
Authentication via user account credentials is as simple as following the prompts in a browser window
which automatically open for you. You authenticate to the specified
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which will automatically open for you

``BigQuery`` account using the product name ``pandas GBQ``. It is only possible on local host.
Authentication via user account credentials is as simple as following the prompts in a browser window
which automatically open for you. You authenticate to the specified
``BigQuery`` account using the product name ``pandas GBQ``, but only possible on local host.
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Please remove the following text

, but only possible on local host

We support authenticating on both local and remote via the auth_local_webserver argument of read_gbq

Correcting information via reviewer's recommendation
Authentication to the Google ``BigQuery`` service is via ``OAuth 2.0``.
Is possible to authenticate with either user account credentials or service account credentials.
Authentication to the Google ``BigQuery`` service via ``OAuth 2.0``
is possible to authenticate with either user or service account credentials.
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Authentication to the Google BigQuery service via OAuth 2.0 is possible to authenticate with either user or service account credentials.

Remove unnecessary words
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Thanks @alanyee !

@parthea parthea merged commit be301e2 into googleapis:master Aug 3, 2017
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3 participants