monkeylearn_extract: monkeylearn_extract

Description Usage Arguments Details Value Examples

Description

Access to Monkeylearn extractors modules

Usage

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monkeylearn_extract(request, key = monkeylearn_key(quiet = TRUE),
  extractor_id = "ex_isnnZRbS", texts_per_req = 200, verbose = TRUE,
  params = NULL)

Arguments

request

A vector of characters (each text smaller than 50kB)

key

The API key

extractor_id

The ID of the extractor

texts_per_req

Number of texts to be fed through per request (max 200). Does not affect output, but may affect speed of processing.

verbose

Whether to output messages about batch requests

params

Parameters for the module as a named list. See the second example.

Details

Find IDs of extractors using https://app.monkeylearn.com/main/explore. Within the free plan, you can make up to 20 requests per minute.

You can use batch to send up to 200 texts to be analyzed within the API (classification or extraction) with each request. So for example, if you need to analyze 6000 tweets, instead of doing 6000 requests to the API, you can use batch to send 30 requests, each request with 200 tweets. The function automatically makes these batch calls and waits if there is a throttle limit error, but you might want to control the process yourself using several calls to the function.

You can check the number of calls you can still make in the API using attr(output, "headers")$x.query.limit.remaining and attr(output, "headers")$x.query.limit.limit.

Value

A data.frame with the results whose attribute is a data.frame (tibble) "headers" including the number of remaining queries as "x.query.limit.remaining". Both data.frames include a column with the (list of) md5 checksum(s) of the corresponding text(s) computed using the digest digest function.

Examples

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## Not run: 
text <- "In the 19th century, the major European powers had gone to great lengths
to maintain a balance of power throughout Europe, resulting in the existence of
 a complex network of political and military alliances throughout the continent by 1900.[7]
  These had started in 1815, with the Holy Alliance between Prussia, Russia, and Austria.
  Then, in October 1873, German Chancellor Otto von Bismarck negotiated the League of
   the Three Emperors (German: Dreikaiserbund) between the monarchs of Austria-Hungary,
    Russia and Germany."
output <- monkeylearn_extract(request = text)
output
# example with parameters
text <- "A panel of Goldman Sachs employees spent a recent Tuesday night at the
Columbia University faculty club trying to convince a packed room of potential
recruits that Wall Street, not Silicon Valley, was the place to be for computer
scientists.\n\n The Goldman employees knew they had an uphill battle. They were
fighting against perceptions of Wall Street as boring and regulation-bound and
Silicon Valley as the promised land of flip-flops, beanbag chairs and million-dollar
stock options.\n\n Their argument to the room of technologically inclined students
was that Wall Street was where they could find far more challenging, diverse and,
yes, lucrative jobs working on some of the worlds most difficult technical problems."

output <- monkeylearn_extract(text,
                              extractor_id = "ex_y7BPYzNG",
                              params = list(max_keywords = 3,
                                            use_company_names = 1))
attr(output, "headers")
## End(Not run)

monkeylearn documentation built on May 2, 2019, 10:24 a.m.