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Algorithmia Common Library (python)

Python client library for accessing the Algorithmia API For API documentation, see the PythonDocs

PyPI

Algorithm Development Kit

This package contains the algorithmia-adk development kit, simply add from Algorithmia import ADK into your workflow to access it.

Install from PyPi

The official Algorithmia python client is available on PyPi. Install it with pip:

pip install algorithmia

Install from source

Build algorithmia client wheel:

python setup.py bdist_wheel

Install a wheel manually:

pip install --user --upgrade dist/algorithmia-*.whl

#install locally for testing

from directory containing setup.py and the Algorithmia directory:

pip3 install ./

#add CLI script to PATH

to use the CLI it may be nessesary to add the install location to the PATH enviroment variable

export PATH = $HOME/.local/bin:$PATH

Authentication

First, create an Algorithmia client and authenticate with your API key:

import Algorithmia

apiKey = '{{Your API key here}}'
client = Algorithmia.client(apiKey)

Now you're ready to call algorithms.

Calling algorithms

The following examples of calling algorithms are organized by type of input/output which vary between algorithms.

Note: a single algorithm may have different input and output types, or accept multiple types of input, so consult the algorithm's description for usage examples specific to that algorithm.

Text input/output

Call an algorithm with text input by simply passing a string into its pipe method. If the algorithm output is text, then the result field of the response will be a string.

algo = client.algo('demo/Hello/0.1.1')
response = algo.pipe("HAL 9000")
print response.result    # Hello, world!
print response.metadata  # Metadata(content_type='text',duration=0.0002127)
print response.metadata.duration # 0.0002127

JSON input/output

Call an algorithm with JSON input by simply passing in a type that can be serialized to JSON: most notably python dicts and arrays. For algorithms that return JSON, the result field of the response will be the appropriate deserialized type.

algo = client.algo('WebPredict/ListAnagrams/0.1.0')
result = algo.pipe(["transformer", "terraforms", "retransform"]).result
# -> ["transformer","retransform"]

Binary input/output

Call an algorithm with Binary input by passing a byte array into the pipe method. Similarly, if the algorithm response is binary data, then the result field of the response will be a byte array.

input = bytearray(open("/path/to/bender.png", "rb").read())
result = client.algo("opencv/SmartThumbnail/0.1").pipe(input).result
# -> [binary byte sequence]

Error handling

API errors and Algorithm exceptions will result in calls to pipe throwing an AlgoException:

client.algo('util/whoopsWrongAlgo').pipe('Hello, world!')
# Algorithmia.algo_response.AlgoException: algorithm algo://util/whoopsWrongAlgo not found

Request options

The client exposes options that can configure algorithm requests. This includes support for changing the timeout or indicating that the API should include stdout in the response.

from Algorithmia.algorithm import OutputType
response = client.algo('util/echo').set_options(timeout=60, stdout=False)
print response.metadata.stdout

Note: stdout=True is only supported if you have access to the algorithm source.

Working with data

The Algorithmia client also provides a way to manage both Algorithmia hosted data and data from Dropbox or S3 accounts that you've connected to you Algorithmia account.

Create directories

Create directories by instantiating a DataDirectory object and calling create():

client.dir("data://.my/foo").create()
client.dir("dropbox://somefolder").create()

Upload files to a directory

Upload files by calling put on a DataFile object, or by calling putFile on a DataDirectory object.

foo = client.dir("data://.my/foo")
foo.file("remote_file").putFile("/path/to/myfile")
foo.file("sample.txt").put("sample text contents")
foo.file("binary_file").put(some_binary_data)

Note: you can instantiate a DataFile by either client.file(path) or client.dir(path).file(filename)

Download contents of file

Download files by calling getString, getBytes, getJson, or getFile on a DataFile object:

foo = client.dir("data://.my/foo")
sampleText = foo.file("sample.txt").getString()  # String object
binaryContent = foo.file("binary_file").getBytes()  # Binary data
tempFile = foo.file("myfile").getFile()   # Open file descriptor

Delete files and directories

Delete files and directories by calling delete on their respective DataFile or DataDirectory object. DataDirectories take an optional force parameter that indicates whether the directory should be deleted if it contains files or other directories.

foo = client.dir("data://.my/foo")
foo.file("sample.txt").delete()
foo.delete(true) // true implies force deleting the directory and its contents

List directory contents

Iterate over the contents of a directory using the iterated returned by calling list, files, or dirs on a DataDirectory object:

foo = client.dir("data://.my/foo")

# List files in "foo"
for file in foo.files():
    print file.path + " at URL: " + file.url + " last modified " + file.last_modified

# List directories in "foo"
for file in foo.dirs():
    print dir.path + " at URL: " + file.url

# List everything in "foo"
for entry in foo.list():
    print entry.path + " at URL: " + entry.url

Manage directory permissions

Directory permissions may be set when creating a directory, or may be updated on already existing directories.

from Algorithmia.acl import ReadAcl, AclType
foo = client.dir("data://.my/foo")
# ReadAcl.public is a wrapper for Acl(AclType.public) to make things easier
foo.create(ReadAcl.public)

acl = foo.get_permissions()  # Acl object
acl.read_acl == AclType.public  # True

foo.update_permissions(ReadAcl.private)
foo.get_permissions().read_acl == AclType.private # True

Algorithmia CLI

Algorithmia CLI is a cross-platform tool for interfacing with algorithms and the Algorithmia Data API.

Configure Authentication

In order to make calls with the CLI, you'll need to configure the authentication with an API key. If you don't already have an API key, get started by signing up for an account at Algorithmia.com. Once you've completed the sign up process, copy the API key from your account dashboard.

Begin the configuration process by running the command algo auth. You will see an interactive prompt to guide you through setting up a default profile:

$ algo auth
Configuring authentication for profile: 'default'
Enter API Endpoint [https://api.algorithmia.com]:
Enter API Key:
(optional) enter path to custom CA certificate: 
Profile is ready to use. Test with 'algo ls'

See Using multiple profiles for instructions on how to set authenticate and use more than one profile with the Algorithmia CLI tool.

Usage

To call an algorithm from the CLI, use the command syntax: algo run, followed by the algorithm’s username and algorithm name, the data options, and finally the input. Here is a basic example calling the Factor algorithm:

$ algo run kenny/factor -d 19635
[3,5,7,11,17]

Run algo run --help to see more command options or view the following Options section.

Options

Input Data Options

The Algorithmia CLI supports JSON, text, and binary data, as well as an option to auto-detect the data type.

Option Flag Description
-d, --data If the data parses as JSON, assume JSON, else if the data is valid UTF-8, assume text, else assume binary
-D, --data-file Same as --data, but the input data is read from a file

You may also explictly specify the input type as text (-t/-T), json (-j/-J), or binary (-b/-B) instead of using the auto-detection (-d/-D).

Output Options

The algorithm result is printed to STDOUT by defauft. Additional notices may be printed to STDERR. If you'd like to output the result to a file, use the output option flag followed by a filename:

$ algo run kenny/factor -d 17 --output results.txt
Option Flag Description
--debug Print algorithm's STDOUT (author-only)
-o, --output Print result to a file

Other Options

Option Flag Description
--timeout Sets algorithm timeout

Examples:

$ algo run kenny/factor/0.1.0 -d '79'                   Run algorithm with specified version & data input
$ algo run anowell/Dijkstra -D routes.json              Run algorithm with file input
$ algo run anowell/Dijkstra -D - < routes.json          Same as above but using STDIN
$ algo run opencv/SmartThumbnail -D in.png -o out.png   Runs algorithm with binary files as input
$ algo run kenny/factor -d 17 --timeout 2               Runs algorithm with a timeout of 2 seconds

The Algorithmia Data API

Use the Algorithmia CLI to interact with the Algorithmia Data API. You can use the CLI to create and manage your data directories.

Data commands include:

Command Description
ls List contents of a data directory
mkdir Create a data directory
rmdir Delete a data directory
rm Remove a file from a data directory
cp Copy file(s) to or from a data directory
cat Concatenate & print file(s) in a directory

Examples of the Algorithmia Data API usage:

Create a data directory:

$ algo mkdir .my/cuteAnimals

Created directory data://.my/cuteAnimals

Copy a file from your local directory to the new data directory:

$ algo cp chubby_kittens.jpg data://.my/cuteAnimals

Uploaded data://.my/cuteAnimals/chubby_kittens.jpg

Using multiple profiles

Add additional profiles

With the Algorithmia CLI, you can configure multiple custom profiles to use. To add a new profile, simply specify a profile to algo auth follow the same interactive prompt.

algo auth --profile second_user
Configuring authentication for profile: 'second_user'
Enter API Endpoint [https://api.algorithmia.com]:
Enter API Key:
(optional) enter path to custom CA certificate: 

Now you may use algo ls --profile second_user to list files in your second_user account. For more information, see the auth command help with algo auth --help.

Using profiles in commands

When running commands, the Algorithmia CLI will use the default profile unless otherwise specified with the --profile <profile> option. See the following example:

$ algo run kenny/factor -d 17 --profile second_user 
[17]

Running tests

Make sure you have numpy installed before running datafile_test.py

export ALGORITHMIA_API_KEY={{Your API key here}}
cd Test
python acl_test.py
python algo_test.py
python datadirectorytest.py
python datafile_test.py
python utiltest.py