read

Table of contents

read, table creation

The keyword read offers versatile mechanisms to read data from files.

table Products = with
  [| as Product, as Color, as Price |]
  [| "shirt", "white,grey", 10.50 |]
  [| "pants", "blue", 15.00 |]
  [| "hat", "red", 5.25 |]

write Products as "/sample/products.csv" with
  Product = Products.Product
  Color = Products.Color
  Price = Products.Price

Then,

read "/sample/products.csv" as Products with
  Product : text
  Color : text
  Price : number

show table "My Products" a1b3 with
  Products.Product
  Products.Color
  Products.Price

A single script is limited to 5000 input files.

Constant column

A constant column can be introduced through an assignment at the column level within the read block:

read "/sample/products.csv" as Products with
  Product : text
  Color : text
  Price : number
  VAT : number = 0.2 // constant column

show table "My Products" a1c4 with
  Products.Product
  Products.Color
  Products.Price
  Products.VAT

Renamed column

A column can be renamed through an assignment and the use of the read function at the column level within the read block:

read "/sample/products.csv" as Products with
  Product : text
  Colour : text = read("Color")
  Price : number

show table "My Products (UK)" a1c4 with
  Products.Product
  Products.Colour
  Products.Price

The function read is intended to cope with raw column names that are not valid Envision variable names.

split column-level option

The option split splits the content of a text cell according to the specified delimiter, resulting in multiple lines being for each value obtained by the split.

With a split:"," on B gives:

The script below creates a TSV file with 2 lines:

table T = with
  [| as A, as B  |]
  [| 1,    "X,Y" |]
  [| 2,    "Z"   |]

write T as "/sample/split.tsv" with
  A = T.A
  B = T.B

And, the script below re-reads the TSV file generating a table with 3 lines:

read "/sample/split.tsv" as T with
  A : number
  split:"," as B : text

show table "T" a1b3 with T.A, T.B

The option split can only appear once within a read block.

Transpose column-level option

When multiple values are passed to the read function within a read block, it tranposes the corresponding columns - as found in the file - in the same number of lines. The columns that are not transposed have their values repeated. For example, by transposing (B1, B2, B3) in:

We obtain:

The following script creates a TSV file with 2 lines:

table T = with
  [| as A, as B1, as B2, as B3 |]
  [| "x",  "x1",  "x2",  "x3"  |]
  [| "y",  "y1",  "y2",  "y3"  |]

write T as "/sample/transpose.tsv" with
 A = T.A
 B1 = T.B1
 B2 = T.B2
 B3 = T.B3

And, the script below re-reads the TSV file generating a table with 6 lines:

read "/sample/transpose.tsv" as T with
  A : text
  B : text = read("B1", "B2", "B3")

show table "T" a1b6 with T.A, T.B

Discarded table

Prefixing the table name with an underscore (_) means that the table is discarded. However, the captured files are accessible from the Files virtual table.

read "/sample/*.csv" as _Samples

show table "Files" a1c2 with 
  Files.Alias // '_Samples'
  Files.Path

The table marked as discarded cannot be used in the script, and thus, this table does not trigger a not used error at compile time when it is, effectively, not used in the script.

Using a stand-alone discard symbol (_) is also possible:

read "/sample/*.csv" as _

show table "Files" a1c2 with 
  Files.Alias // '_'
  Files.Path

This feature is typically intended for scripts that are analyzing the presence or absence of files, ignoring of their content.

Datatype read/write support

The following table lists the database that can be read or written, depending on the intended file format.