colabutils

Google Colaboratory Python Utilities

installing

In order to use this package in your Colaboratory Notebook, include this piece of code in the top of your notebook:

!pip install --upgrade -q colabutils

gdrive.search_and_download

You can use this method to search the current user Google Drive for a specific file and download it to your environment local path.

If you plan to use this method to load your GCP credentials from a Google Drive file, check the method gcp.load_credentials().

Example:

from colabutils import gdrive

credential_path = gdrive.search_and_download 'credential.json', '/content/.google/credential.json'

Note: the file doesn't need to be on the current user My Drive section or even the user doesn't need to be the file owner. If the file is owned by another user, but was shared with the current user, it will work all the same.

So, with the example above you could do something like that:

# authenticates the colab environment with current user's credentials
from google.colab import auth
auth.authenticate_user()

# download GCP API credentials from Google Drive
from colabutils import gdrive
credential_path = gdrive.search_and_download 'credential.json', '/content/.google/credential.json'

# load credentials
from google.oauth2 import service_account
creds = service_account.Credentials.from_service_account_file(credential_path)

# use credentials to prepare a GCP service client
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
client = language.LanguageServiceClient(credentials=creds)

# make a call to the NLP API
text = u'I love python!'
document = types.Document(content=text,type=enums.Document.Type.PLAIN_TEXT)

# Detects the sentiment of the text
sentiment = client.analyze_sentiment(document=document).document_sentiment

print('Text: {}'.format(text))
print('Sentiment: {}, {}'.format(sentiment.score, sentiment.magnitude))

# output:
# Text: I love python!
# Sentiment: 0.8999999761581421, 0.8999999761581421

gdrive.download_and_unzip

You can use this method to search the current user Google Drive for a specific file, download it to your environment local path, unzip it's contents and automatically remove the downloaded zip file.

from colabutils import gdrive
extracted_path = gdrive.download_and_unzip("books_dataset.zip", "/content")

# lets see its contents
!ls /content

webcam.take_and_display_photo

Takes a photo using the webcam and saves it in the environment local path. Depends on the user allowing the browser to access the camera. Returns the image content (from a .read() on that file).

If no filename parameter is provided, default file name used in the process is photo.jpg.

Example:

from colabutils import webcam
image_content = webcam.take_and_display_photo()

audio.record

Allows the user to start recording the audio (from the microphone), returning its contents when the user clicks 'finish'.

The audio may be auto-played at the end of the recording, using the optional parameter auto_play is equals to True.

Example:

from colabutils import audio
audio_content = audio.record()

audio.record_and_save

Allows the user to start recording the audio (from the microphone), saving it to a file when the user clicks 'finish'.

If no filename parameter is provided, default file name used in the process is audio.wav.

Example:

from colabutils import audio
audio_filename = audio.record_and_save()

gcp.load_credentials

Downloads the credentials from a URL and returns a service account credential object based on this file. Example:

from colabutils import gcp
creds = gcp.load_credentials("http://website.com/credential.json")

If no arguments are passed, it tries to look for a file named mlcredential.json in the current user's Google Drive (or shared files).

Example:

from colabutils import gcp
creds = gcp.load_credentials()

The returned service account credential (in this case creds) can be used in a GCP service client, such as Vision API:

from google.cloud import vision
client = vision.ImageAnnotatorClient(credentials=creds)

When downloading from GDrive, a custom filename can be provided, such as below:

creds = gcp.load_credentials(gdrivefile="custom_credential.json")

vision_utils.list_faces

Describes the faces returned in face_annotations by a Vision API face_detection call.

Example:

resp = client.face_detection(image=my_image)

from colabutils import vision_utils
vision_utils.list_faces(resp.face_annotations)

vision_utils.list_annotations

Describes the faces returned in text_annotations by a Vision API text_detection call.

Example:

resp = client.text_detection(image=my_image)

from colabutils import vision_utils
vision_utils.list_annotations(resp.text_annotations)

sending new versions to PyPI

Add the file ~/.pypirc with the following content:

[distutils]
index-servers=pypi
[pypi]
repository = https://upload.pypi.org/legacy/
username = <your_username>

Make sure you have the latest versions of setuptools, wheel and twine installed:

python3 -m pip install --user --upgrade setuptools wheel twine

Run this to generate the new version on the /dist folder.

python3 setup.py sdist bdist_wheel

Run this to upload the contents of the /dist folder to PyPI.

python3 -m twine upload dist/*