readysignal-staging 0.1.4

The staging API for staging.app.readysignal.com

Ready Signal API (Staging) - Python 3.6+

Note: This is the staging version of the Ready Signal Python library. It connects to the staging environment at https://staging.app.readysignal.com. For the production library, see readysignal.

This library is designed to be a wrapper for the Ready Signal Staging API: https://staging.app.readysignal.com

Please direct all questions and/or recommendations to [e-mail]

Table of Contents

• Installation

Signal ID Specific

• List Signals
• Signal Detatils
• Signal Output
• Delete Signal
• Auto Discover Feature

Feature ID Specific

• Syntax Note
• Available Features List
• Show Features Data
• Show Features Data Detailed
• Features Data Output

Installation

The Ready Signal Staging API Python library can be found here: https://pypi.org/project/readysignal-staging/

pip install readysignal-staging

Usage

Your access token and signal ID can be found on your "Manage Signal" page within the Output information.

Your signal ID is also visible within the URL of the "Manage Signal" page:

...staging.app.readysignal.com/signal/SIGNAL_ID/manage

Setup

import readysignal_staging as rs

access_token = "your staging access token"
signal_id = 0  # this is your unique staging signal id number

Optional: Proxy URL

It is optional to include proxy URL(s) in your functions. The setup for proxy URL(s) is shown below, and it must be in a dictionary format. If username nand password are required too, an example is shown below:

# no username and password required
proxy_info = {
    "http": "http://your_proxy_address:your_proxy_port",
    "https": "https://your_proxy_address:your_proxy_port"
  }
# username and password required
  proxy_info2 = {
    "http": "http://username:password@your_proxy_address:your_proxy_port",
    "https": "https://username:password@your_proxy_address:your_proxy_port"
  }

If a proxy URL is needed, then it will be included as an argument in every function used. The parameter name and an example is shown below:

rs.list_signals(access_token, proxy_dict=proxy_info)

* Signal ID Specific *

List Signals

Using your access_token, you can list all signals and metadata that are associated with your Ready Signal account.

rs.list_signals(access_token)

Example Output

{'data': [{
    'id': 0, 
    'name': 'Signal Name', 
    'description': 'Signal Description', 
    'desired_geo_grain': 'Country', 
    'desired_time_grain': 'Month', 
    'start_at': '11/01/2019', 
    'end_at': '01/31/2020', 
    'created_at': '07/23/2020', 
    'updated_at': '07/28/2020', 
    'deleted_at': None, 
    'company': {
        'id': 0, 
        'chargebee_id': 'ID Hash', 
        'name': 'Company Name', 
        'plan_id': 0, 
        'plan_value_id': 0, 
        'subscription_status': 'active', 
        'created_at': '2020-07-23 13:20:17', 
        'updated_at': '2020-08-03 11:33:50', 
        'need_listining_webhook': 0, 
        'addon_users': None, 
        'notify_after_processing': 0
        }, 
    'user': {
        'id': 0, 
        'company_id': 0, 
        'name': 'Name', 
        'email': 'Email', 
        'email_verified_at': None, 
        'type': 'owner', 
        'active': 'yes', 
        'reactivate': 'no', 
        'created_at': '2020-07-23 13:20:17', 
        'updated_at': '2020-07-23 13:20:17', 
        'deleted_at': None
        }, 
    'industry': {
        'id': 1, 
        'name': 'Automotive', 
        'created_at': '2020-04-10 23:21:38', 
        'updated_at': '2020-04-10 23:21:38', 
        'deleted_at': None
        }, 
    'analysis_type': {
        'id': 3, 
        'name': 'Classification', 
        'created_at': '2020-04-10 23:21:45', 
        'updated_at': '2020-04-10 23:21:45', 
        'deleted_at': None
    }, 
    'output': {
        'json': 'https://staging.app.readysignal.com/api/signals/0/output?format=json'}, 
        'links': {
        'self': 'https://staging.app.readysignal.com/signal/0/manage', 
        'manage': 'https://staging.app.readysignal.com/signal/0/manage'
        }
    },
    {
    'id': 1
    ...
    }
    ]
}

Signal Details

Using your access_token and your signal_id you can view the details of a specific signal.

# get signal details
rs.get_signal_details(access_token, signal_id)

Example Output

{'data': {
    'id': 0, 
    'name': 'Signal Name', 
    'description': 'Signal Description', 
    'desired_geo_grain': 'Country', 
    'desired_time_grain': 'Month', 
    'start_at': '11/01/2019', 
    'end_at': '01/31/2020', 
    'created_at': '07/23/2020', 
    'updated_at': '07/28/2020', 
    'deleted_at': None, 
    'company': {
        'id': 0, 
        'chargebee_id': 'ID Hash', 
        'name': 'Company Name', 
        'plan_id': 0, 
        'plan_value_id': 0, 
        'subscription_status': 'active', 
        'created_at': '2020-07-23 13:20:17', 
        'updated_at': '2020-08-03 11:33:50', 
        'need_listining_webhook': 0, 
        'addon_users': None, 
        'notify_after_processing': 0
        }, 
    'user': {
        'id': 0, 
        'company_id': 0, 
        'name': 'Name', 
        'email': 'Email', 
        'email_verified_at': None, 
        'type': 'owner', 
        'active': 'yes', 
        'reactivate': 'no', 
        'created_at': '2020-07-23 13:20:17', 
        'updated_at': '2020-07-23 13:20:17', 
        'deleted_at': None
        }, 
    'industry': {
        'id': 1, 
        'name': 'Automotive', 
        'created_at': '2020-04-10 23:21:38', 
        'updated_at': '2020-04-10 23:21:38', 
        'deleted_at': None
        }, 
    'analysis_type': {
        'id': 3, 
        'name': 'Classification', 
        'created_at': '2020-04-10 23:21:45', 
        'updated_at': '2020-04-10 23:21:45', 
        'deleted_at': None
    }, 
    'output': {
        'json': 'https://staging.app.readysignal.com/api/signals/0/output?format=json'}, 
        'links': {
        'self': 'https://staging.app.readysignal.com/signal/0/manage', 
        'manage': 'https://staging.app.readysignal.com/signal/0/manage'
        }
    }
}

Signal Output

There are three different ways to receive your signal output:

• JSON
• Pandas DataFrame
• CSV export

JSON

# get signal data as json
rs.get_signal(access_token, signal_id)

Example Output

{'current_page': 1, 
 'data': [
	{
		'start': '2019-11-01', 
		'end': '2019-11-30', 
		'country': 'United States of America', 
		'actual-snow-fall': '160205.00000000000000000000', 
		'resident-population-by-state': '9826013.22000000000000000000', 
		'actual-snow-cover': '3.56158109943317700000', 
		'population-total': '308745538.00000000000000000000', 
		'population-total-transformed': 17,571.156421818115497622280458798
	}, 
	{
		'start': '2019-12-01', 
		'end': '2019-12-31', 
		'country': 'United States of America', 
		'actual-snow-fall': '219691.00000000000000000000', 
		'resident-population-by-state': '10153546.99400000000000000000', 
		'actual-snow-cover': '8.28314041638492200000', 
		'population-total': '308745538.00000000000000000000', 
		'population-total-transformed': 17,571.156421818115497622280458798
	}, 
	{
		'start': '2020-01-01', 
		'end': '2020-01-31', 
		'country': 'United States of America', 
		'actual-snow-fall': '220869.00000000000000000000', 
		'resident-population-by-state': 10159386.99400000000000000000, 
		'actual-snow-cover': '10.69758409714073700000', 
		'population-total': '308745538.00000000000000000000', 
		'population-total-transformed': 17,571.156421818115497622280458798
	}
	], 
	'first_page_url': 'https://staging.app.readysignal.com/api/signals/0/output?page=1', 
	'from': 1, 
	'last_page': 1, 
	'last_page_url': 'https://staging.app.readysignal.com/api/signals/0/output?page=1', 
	'next_page_url': None, 
	'path': 'https://staging.app.readysignal.com/api/signals/0/output', 
	'per_page': 1000, 
	'prev_page_url': None, 
	'to': 3, 
	'total': 3}

Pandas DataFrame

# get signal data as Pandas DataFrame
rs.get_signal_pandas(access_token, signal_id)

Example Output

        start  ... population-total-transformed
0  2019-11-01  ... 17,571.156421818115497622280458798
1  2019-12-01  ... 18,109.798447234298274239287429023
2  2020-01-01  ... 18,732.472983479821748127047902849

Export to CSV

# send signal data to csv file
file_name = "test_signal.csv"
rs.signal_to_csv(access_token, signal_id, file_name)

Delete Signal

USE WITH CAUTION

Use your access_token and signal_id to delete a signal

rs.delete_signal(access_token, signal_id)

Auto Discover Feature

Creates a signal using your own data and the Auto Discover feature. Please check Ready Signal site for tips on how to format your data. Currently only available at the "State" or "Country" geo grain and the “Month” or “Day” time grain. Use a file name OR Pandas DataFrame. Set create_custom_features=0 to prevent Ready Signal from storing the input target data for future use.

rs.auto_discover(access_token, geo_grain, date_grain, filename=None, df=None, create_custom_features=1)

* Feature ID Specific*

Syntax

A note on parameter syntax:

• access_token: a string of users access token
• bank_name: a string of the country name of the bank
• feature: a list containing the feature(s) to use. Regardless of if it is just 1 feature or many, it MUST be put in a list
• start_date: a string in the format of 'YYY-MM-DD'
• end_date: a string in the format of 'YYY-MM-DD'

Available Features List

Using your access_token and bank_name, you can view all the features and an overview of their data that can be used with the feature specific functions.

rs.get_features_list(access_token, bank_name)

Example Output

{'data': [{'feature_id': 317,
   'slug_name': 'Bonos (0 - 3 years) Maturity at 12/07/2023',
   'feature_name': 'Bonos (0 - 3 years) Maturity at 12/07/2023',
   'product_name': 'Bonos',
   'provider_name': 'Bank Of Mexico',
   'geo_grain': 'Country',
   'geo_grain_delimitation': 'MEXICO',
   'date_grain': 'Day'},
  {'feature_id': 318,
   'slug_name': 'Bonos (0 - 3 years) Maturity at 09/05/2024',
   'feature_name': 'Bonos (0 - 3 years) Maturity at 09/05/2024',
   'product_name': 'Bonos',
   'provider_name': 'Bank Of Mexico',
   'geo_grain': 'Country',
   'geo_grain_delimitation': 'MEXICO',
   'date_grain': 'Day'},
   {'feature_id': 319
   ...
   }
]
}

Show Feature(s) Data

Using your access_token, bank_name, and a feature list containing the feature id(s), see an overview of the data for those specific features.
Reminder: Regardless of the number of features (1 or many), they must be in a list.

feat_list = [317, 318]
rs.show_feature(access_token, bank_name, feat_list)

Example Output

{317: {'feature_id': 317,
  'feature_name': 'Bonos (0 - 3 years) Maturity at 12/07/2023',
  'product_name': 'Bonos',
  'provider_name': 'Bank Of Mexico',
  'geo_grain': 'Country',
  'date_grain': 'Day',
  'data_notes': None,
  'units': 'Millions of pesos',
  'available_through': '2023-09-26',
  'published_at': None},
 318: {'feature_id': 318,
  'feature_name': 'Bonos (0 - 3 years) Maturity at 09/05/2024',
  'product_name': 'Bonos',
  'provider_name': 'Bank Of Mexico',
  'geo_grain': 'Country',
  'date_grain': 'Day',
  'data_notes': None,
  'units': 'Millions of pesos',
  'available_through': '2023-09-26',
  'published_at': None}}

Show Feature(s) Detailed Data

Using your access_token, bank_name, and a feature list containing the feature id(s), see in depth data for those specific features.

feat_list = [317]
rs.show_feature_detailed(access_token, bank_name, feat_list)

Example Output

{317: {'name': 'Bonos (0 - 3 years) Maturity at 12/07/2023',
  'short_name': 'Bonos (0 - 3 years) Maturity at 12/07/2023',
  'geo_grain': 'Country',
  'geo_grain_label': 'COUNTRY',
  'geo_grain_delimitation': 'MEXICO',
  'date_grain': 'Day',
  'date_grain_label': 'Daily',
  'licence': 'Public Domain',
  'units': 'Millions of pesos',
  'reporting_lag': '1 Day',
  'first_date': None,
  'description': '',
  'citation': None,
  'why_use': None,
  'state_lvl_data_set_exist': 'No',
  'is_state_lvl_the_same': 'No',
  'allow_grain_transformation_by_date': 'Yes',
  'allow_grain_transformation_by_population': 'No',
  'parent_feature_id': None,
  'product': {'id': 104,
   'name': 'Bonos',
   'created_at': None,
   'updated_at': None,
   'deleted_at': None,
   'provider': {'id': 41,
    'name': 'Bank Of Mexico',
    'publisher_id': 7,
    'created_at': '2022-07-14 14:06:07',
    'updated_at': '2022-07-14 14:06:07',
    'deleted_at': None}},
  'categories': [{'id': 1,
    'name': 'Economic',
    'created_at': '2020-04-10T23:22:58.000000Z',
    'updated_at': '2020-04-10T23:22:58.000000Z',
    'deleted_at': None,
    'sub_categories': [{'id': 1,
      'name': 'Banking',
      'category_id': 1,
      'created_at': '2020-04-10 23:22:58',
      'updated_at': '2020-04-10 23:22:58',
      'deleted_at': None},
     {'id': 2,
      ...
     }
     {'id': 18,
      'name': 'Interest Rates',
      'category_id': 1,
      'created_at': '2020-04-10 23:23:06',
      'updated_at': '2020-04-10 23:23:06',
      'deleted_at': None}]}],
  'deleted_at': None,
  'created_at': '2023-07-10T17:40:50.000000Z',
  'updated_at': '2023-09-19T18:02:05.000000Z'}
  }

Feature Data Outputs

There are two different ways to receive your feature(s) data:

• JSON
• Pandas DataFrame

You will need your access_token, bank_name, feature list of feature ids along with a start_date and end_date indicating the date range of the features.
Reminder: Regardless of the number of features (1 or many), they must be in a list.
Reminder: start_date and end_date must be in the format of 'YYY-MM-DD'.

JSON

# get feature data as json
feat_list = [317]
start_date = '2021-01-01'
end_date = '2021-12-31'
rs.get_feature_data(access_token, bank_name, feat_list, start_date, end_date)

Example Output

{'data': [{'Trade Date': '01/04/2021',
   'Security Type': 'Bonos',
   'Maturity Date': '07 dic 2023',
   'Volume': '0.00000000000000000000',
   'Maturity Bucket': '0_3',
   'Last Updated': '09/26/2023'},
  {'Trade Date': '01/05/2021',
   'Security Type': 'Bonos',
   'Maturity Date': '07 dic 2023',
   'Volume': '100.00000000000000000000',
   'Maturity Bucket': '0_3',
   'Last Updated': '09/26/2023'},
   ...
   {'Trade Date': '12/31/2021', 
   'Security Type': 'Bonos', 
   'Maturity Date': '07 dic 2023', 
   'Volume': '0.00000000000000000000', 
   'Maturity Bucket': '0_3', 
   'Last Updated': '09/26/2023'}
   ]
}

Pandas DataFrame

# get feature data as Pandas DataFrame
rs.get_feature_data_pandas(access_token, bank_name, feat_list, start_date, end_date)

Example

   Trade Date  ... Last Updated
0  01/04/2021  ... 09/26/2023
1  01/05/2021  ... 09/26/2023
2  01/06/2021  ... 09/26/2023