Load Market

Create a custom market by loading market data into an underlying market

Parameter Description Default Options
marketId
Required
A unique identifier for the user market
marketData
Required
User supplied market data to be loaded into the specified market i.e. user can supply quotes to be used on curve which will over-ride quotes in Clarus Can be a CME or LCH curve file or a list of semi-colon separated bloomberg tickers/quote pairs e.g. "USSW2=0.015;USSW5=0.025;USSW10=0.032"
market
Optional
Market environment Id to use for calculation - either choose from options or specify market uploaded using MarketLoad service Clarus
import clarus

response = clarus.load.market()
print (response)
import com.clarusft.api.model.load.MarketRequest
import com.clarusft.api.model.load.MarketResponse

ApiClient clarus = ApiClient.getDefault();
MarketResponse response = clarus.request(new MarketRequest());
System.out.println(response);
import Clarus

response = Clarus.Load.market()
print(response)

##
##Need to install packages once, if not already installed
##install.packages('httr')
##install.packages('readr')
##

library('httr')
##library('readr')

## Manually edit and set key/secret here ##
apiKey <- '...'
apiSecret <-'...'

request <- function(category, functionName, ...){
  restUrl  =  paste0('https://apieval.clarusft.com/api/rest/v1/', category, '/',functionName, '.csv')
  response <- POST(url=restUrl, body=list(...), encode='json', authenticate(apiKey, apiSecret, type='basic'))
  if (response$status_code!=200){
      stop(paste0('Request to ', category, '/', functionName, ' failed with status code: ', response$status_code))
  }
  return (response)
}

dataframe <- function(response){
  return (read.csv(text=content(response, 'text'), sep=',', head=TRUE))
}
## filename <- file.path('C:', 'Temp', 'myfile.csv')
## myvalue <- <- read_file(filename)

r <- request('load', 'Market')
df <- dataframe(r)
print (df)

import requests
import sys
import pandas
import io
#import os

# Example of REST API call to Clarus Microservices #

# Manually edit and set key/secret here #
apiKey = ''
apiSecret = ''

print (sys.version)

def request(category, functionName, **params):
  restUrl = 'https://apieval.clarusft.com/api/rest/v1/' + category + '/' + functionName + '.json'
  r = requests.post(restUrl, json=params, auth=(apiKey, apiSecret))
  r.raise_for_status()
  return r.json()

def dataframe(results):
  return pandas.DataFrame(results['results'])

# filename = os.path.join('C:\\', 'Temp', 'myfile.csv')
# myvalue = open(filename).read()

r = request('load', 'Market')
df = dataframe(r)
print(pandas.DataFrame.head(df))


use strict;
use warnings;
use MIME::Base64;
use JSON;
use REST::Client;

# Example of REST API call to Clarus Microservices #

my $client = REST::Client->new();
$client->addHeader('Content-Type', 'application/json');

# Manually edit and set key/secret here 
my $apiKey = '';
my $apiSecret = '';

my $encoded_auth = encode_base64("$apiKey:$apiSecret", '');
$client->addHeader('Authorization', "Basic $encoded_auth");

my %params = ();

my $urlBase = 'https://apieval.clarusft.com/api/rest/v1/';
my $category = 'load/';
my $name = 'Market';
my $outputFormat = '.csv'; #can also be '.json' or '.tsv'
my $fullRESTUrl  =  $urlBase . $category . $name . $outputFormat;

$client->POST($fullRESTUrl,encode_json(\%params));

print 'Response: ' . $client->responseContent() . "\n";
print 'Response status: ' . $client->responseCode() . "\n";


printf('Example of REST API call to Clarus Microservices\n');

function r = request(category, functionName, params)

# Manually edit and set key/secret here #
  apiKey = ''
  apiSecret = ''

  restUrl = ['https://' apiKey ":" apiSecret  "@" 'apieval.clarusft.com/api/rest/v1/' category '/' functionName '.csv'];
  [r, status, message] = urlread (restUrl, 'get', params);
  if (status!=1)
      error(['Failed on ' category '/' functionName ': ' message]);
  endif
end

function ca = toCellArray(csvStr)
  header_row = textscan (csvStr, "%s", 1, 'delimiter','\n');
  headers = strsplit(char(header_row), ",");
  numCols = size(headers)(2);
  format = repmat('%s ', [1 numCols]);
  ca = textscan (csvStr, format, 'delimiter',',', 'endofline',"\n");
end

params = {}

r = request('load', 'Market', params)
ca = toCellArray(r);

ca

Request Body

Submit to generate...
Response

Submit to generate...

{ }