Functions

Summary

function

class parent

truncated documentation

_distance_img

Computes the distance between two images. The function uses Pillow.

_distance_img_b64

Calls _distance_img() on an image encoded with base64.

_setup_hook

if this function is added to the module, the help automation and unit tests call it first before anything goes on …

base642image

Gets an encoded image and builds an PIL.Image.Image from it.

bytes2string

Converts bytes to string.

check

Checks the library is working. It raises an exception. If you want to disable the logs:

dummy_application

Defines a dummy application using this API. It returns a score produced by a model trained on Iris datasets

dummy_application_auth

Defines a dummy application using this API including authentification. It returns a score produced by a model trained …

dummy_application_fct

Defines an application as defined in the tutorial Create your first REST API.

dummy_application_image

Defines a dummy application using this API and processing one image. The API ingests an image, resizes it to 224x224 …

dummy_application_neighbors

Defines a dummy application using this API. It returns a list of neighbors with a score on Iris datasets. …

dummy_application_neighbors_image

Defines a dummy application using this API. It returns a list of one neighbor for an image and metadata (random). …

dummy_mlstorage

Defines a dummy application using this API. It stores a model and it returns a score produced by a model trained …

encrypt_password

Encrypts one password.

encrypt_passwords

Encrypts users passwords.

encrypt_pwd

Encrypts passwords to setup a REST API with lightmlrestapi.

enumerate_parsed_logs

Goes through a list of logged files, reads and decrypts the content.

get_wiki_img

Returns a path to local image.

image2array

Converts a color imaged into an array.

image2base64

Encodes an image into base64.

json_predict_model

Builds a REST request to compute the prediction of a machine learning model upload with json_upload_model(). …

json_upload_model

Builds a REST request to upload a machine learned models to a REST API defined by MLStoragePost.

load_passwords

Loads the encrypted passwords from a filename, a dataframe, a list of tuple.

main

Implements python -m pyquickhelper <command> <args>.

restapi_load

Loads the model. The model name is relative to this file. When call by a REST API, the default value is always used. …

restapi_load

Loads the model. The model name is relative to this file. When call by a REST API, the default value is always used. …

restapi_load

Loads the model. The model name is relative to this file. When call by a REST API, the default value is always used. …

restapi_load

Loads the model. The model name is relative to this file. When call by a REST API, the default value is always used. …

restapi_predict

Computes the prediction for model clf.

restapi_predict

Computes the prediction for model clf.

restapi_predict

Computes the prediction for model clf.

restapi_predict

Computes the prediction for model clf.

restapi_version

Displays a version.

restapi_version

Displays a version.

restapi_version

Displays a version.

restapi_version

Displays a version.

start_mlrestapi

Creates an falcon application and runs it through a wsgi server.

start_mlreststor

Creates an falcon application and runs it through a wsgi server. The appplication stores machine …

string2bytes

Converts string to bytes.

submit_rest_request

Submits a request to a REST API defined by MLStoragePost.

unzip_bytes

Unzips everything from a buffer.

upload_model

Uplaods a machine learned models to a REST API defined by MLStoragePost.

zip_dict

Zips a dictionary { str: bytes }.