tech.ml.dataset.parse — techascent/tech.ml.dataset 2.12

This file really should be named univocity.clj. But it is for parsing and writing csv and tsv data.

all-parsers clj

attempt-general-parse! clj

(attempt-general-parse! add-fn!
                        parse-fn
                        container
                        add-missing-fn
                        unparsed-data
                        unparsed-indexes
                        str-val)

attempt-simple-parse! clj

(attempt-simple-parse! parse-add-fn!
                       simple-parser
                       container
                       add-missing-fn
                       unparsed-data
                       unparsed-indexes
                       relaxed?
                       str-val)

cheap-missing-value-map clj

(cheap-missing-value-map keys missing-value)

convert-reader-to-strings clj

(convert-reader-to-strings input-rdr)

This function has to take into account bad data and just return missing values in the case where a reader conversion fails.

create-csv-parser clj

(create-csv-parser
  {:keys [header-row? num-rows column-whitelist column-blacklist separator
          n-initial-skip-rows max-chars-per-column max-num-columns]
   :or {header-row? true max-chars-per-column (* 64 1024) max-num-columns 8192}
   :as options})

csv->dataset clj

(csv->dataset input)

(csv->dataset input options)

Non-lazily and serially parse the columns. Returns a vector of maps of { :name column-name :missing long-reader of in-order missing indexes :data typed reader/writer of data :metadata - optional map with unparsed-indexes and unparsed-values } Supports a subset of tech.ml.dataset/->dataset options: :column-whitelist :column-blacklist :n-initial-skip-rows :num-rows :header-row? :separator :parser-fn :parser-scan-len

csv->rows clj

(csv->rows input)

(csv->rows input options)

Given a csv, produces a sequence of rows. The csv options from ->dataset apply here.

options: :column-whitelist - either sequence of string column names or sequence of column indices of columns to whitelist. :column-blacklist - either sequence of string column names or sequence of column indices of columns to blacklist. :num-rows - Number of rows to read :separator - Add a character separator to the list of separators to auto-detect. :max-chars-per-column - Defaults to 4096. Columns with more characters that this will result in an exception. :max-num-columns - Defaults to 8192. CSV,TSV files with more columns than this will fail to parse. For more information on this option, please visit: https://github.com/uniVocity/univocity-parsers/issues/301

datetime-formatter-parser clj

(datetime-formatter-parser datatype format-string-or-formatter)

default-column-parser clj

(default-column-parser)

default-parser-seq clj

dtype->missing-val clj macro

(dtype->missing-val datatype)

dtype->parse-fn clj macro

(dtype->parse-fn datatype val)

general-parser clj

(general-parser datatype parse-fn)

make-datetime-simple-parser clj macro

(make-datetime-simple-parser datatype)

make-parser clj

(make-parser parser-fn header-row-name scan-rows)

(make-parser parser-fn
             header-row-name
             scan-rows
             default-column-parser-fn
             simple-parser->parser-fn
             datetime-formatter-fn
             general-parser-fn)

on-parse-failure! clj

(on-parse-failure! str-val
                   cur-idx
                   add-missing-fn
                   unparsed-data
                   unparsed-indexes)

PColumnParser clj protocol

column-data clj

(column-data parser)

Return a map containing {:data - convertible-to-reader column data. :missing - convertible-to-reader array of missing values.

missing! clj

(missing! parser)

Mark a value as missing.

parse! clj

(parse! parser str-val)

Side-effecting parse the value and store it. Exceptions escaping from here will stop the parsing system.

PSimpleColumnParser clj protocol

can-parse? clj

(can-parse? parser str-val)

make-parser-container clj

(make-parser-container parser)

simple-missing! clj

(simple-missing! parser container)

simple-parse! clj

(simple-parse! parser container str-val)

raw-row-iterable clj

(raw-row-iterable input)

(raw-row-iterable input parser)

Returns an iterable that produces map of {:header-row - string[] :rows - iterable producing string[] rows }

return-parse-data clj

(return-parse-data container missing unparsed-data unparsed-indexes)

rows->dataset clj

(rows->dataset {:keys [header-row? parser-fn parser-scan-len bad-row-policy
                       skip-bad-rows?]
                :or {header-row? true parser-scan-len 100}
                :as options}
               row-seq)

Given a sequence of string[] rows, parse into columnar data. See csv->columns. This method is useful if you have another way of generating sequences of string[] row data.

rows->n-row-sequences clj

(rows->n-row-sequences row-seq)

(rows->n-row-sequences options row-seq)

(rows->n-row-sequences {:keys [header-row?] :or {header-row? true}} n row-seq)

Used for parallizing loading of a csv. Returns N sequences that fed from a single sequence of rows. Experimental - Not the most effectively way of speeding up loading.

Type-hinting your columns and providing specific parsers for datetime types like: (ds/->dataset input {:parser-fn {"date" [:packed-local-date "yyyy-MM-dd"]}}) may have a larger effect than parallelization in most cases.

Loading multiple files in parallel will also have a larger effect than single-file parallelization in most cases.

simple-boolean-parser clj

(simple-boolean-parser)

simple-col-parser clj macro

(simple-col-parser datatype)

simple-encoded-text-parser clj

(simple-encoded-text-parser)

simple-parser->parser clj

(simple-parser->parser parser-kwd-or-simple-parser)

(simple-parser->parser parser-kwd-or-simple-parser relaxed?)

simple-string-parser clj

(simple-string-parser)

simple-text-parser clj

(simple-text-parser)

test-file clj

write! clj

(write! output header-string-array row-string-array-seq)

(write! output
        header-string-array
        row-string-array-seq
        {:keys [separator] :or {separator \tab} :as options})