stringify With Header(rows: Array<Map<string, string>>, columns: Array<string>) - > Result<string, string>- 수신자
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Declaration and parameters
링크사용 조건
기본 포함 · 미정
Import std.csv in language mode 5.21.
The current compiler selects std/csv.tpz for this language mode. Availability in other released editions and inclusion in each installed distribution are Pending.
수신자
매개변수 제약
stringify accepts arrays of string rows and returns text. It preserves row order and cell text. Rows may have different field counts. Commas separate fields and every row ends with LF, including the last row. An empty array of rows becomes empty text.
A field containing a comma, quotation mark, CR or LF is enclosed in quotation marks. An embedded quotation mark is doubled. Embedded CR and LF remain inside the quoted field. A sole empty field is quoted to distinguish it from a row with no fields. Empty fields in a larger row need no quotation marks. Other whitespace and Unicode text remain unchanged.
stringify writes a header using the supplied column names and then projects every map onto that ordered list. An absent key supplies an empty cell. Keys outside the list are ignored. A header is emitted even when there are no data rows.
Column names use exact string equality. A repeated name, including a repeated empty name, returns a nonempty Err identifying that name and its zero based repeated index. Validation happens before row projection. A unique empty name is permitted. An empty column list writes an empty header row and one empty row for each input row.
Positional serialization has no value error for a well typed input. Named serialization uses Result for invalid columns. Incorrect row or cell types follow ordinary checking diagnostics. Both functions evaluate supplied arguments once from left to right and perform no I/O or mutation. Their collection arguments follow value semantics.
Named parsing and named writing require the same unique header names. Positional serialization remains available when a row has no naming schema. CSV parsing has its separate malformed input and field count rules.
관련 규칙 · Serialize positional and named CSV rows →결과
The declared result type is Result<string, string>.
효과
실패
Result and effects
링크Validate unique column names and serialize named rows in the supplied column order.
Related entries
링크Serialize positional and named CSV rows
링크Serialize positional and named CSV rows
stringify accepts arrays of string rows and returns text. It preserves row order and cell text. Rows may have different field counts. Commas separate fields and every row ends with LF, including the last row. An empty array of rows becomes empty text.
A field containing a comma, quotation mark, CR or LF is enclosed in quotation marks. An embedded quotation mark is doubled. Embedded CR and LF remain inside the quoted field. A sole empty field is quoted to distinguish it from a row with no fields. Empty fields in a larger row need no quotation marks. Other whitespace and Unicode text remain unchanged.
stringify writes a header using the supplied column names and then projects every map onto that ordered list. An absent key supplies an empty cell. Keys outside the list are ignored. A header is emitted even when there are no data rows.
Column names use exact string equality. A repeated name, including a repeated empty name, returns a nonempty Err identifying that name and its zero based repeated index. Validation happens before row projection. A unique empty name is permitted. An empty column list writes an empty header row and one empty row for each input row.
Positional serialization has no value error for a well typed input. Named serialization uses Result for invalid columns. Incorrect row or cell types follow ordinary checking diagnostics. Both functions evaluate supplied arguments once from left to right and perform no I/O or mutation. Their collection arguments follow value semantics.
Named parsing and named writing require the same unique header names. Positional serialization remains available when a row has no naming schema. CSV parsing has its separate malformed input and field count rules.
이유
Explicit columns determine stable output without depending on map insertion order. Unique names prevent two fields from competing for one key. A Result reports invalid naming data through the same recoverable channel as named parsing.
Quote delimiters and line breaks and finish each record
링크import std.csvimport std.jsonimport std.testimport std.iolet rows = [["name", "note"], ["a,b", "x\"y"], ["line\nnext", "carriage\rreturn"]]io.writeLine(test.assertOk(json.stringify(csv.stringify(rows))))
"name,note\n\"a,b\",\"x\"\"y\"\n\"line\nnext\",\"carriage\rreturn\"\n"
기대 결과
기대 결과
실행을 마칩니다. 종료 코드 0.
"name,note\n\"a,b\",\"x\"\"y\"\n\"line\nnext\",\"carriage\rreturn\"\n"
Distinguish no rows, no fields and one empty field
링크import std.csvimport std.jsonimport std.testimport std.iolet none: Array<Array<string>> = []let emptyRows: Array<Array<string>> = [[], [""]]io.writeLine(test.assertOk(json.stringify(csv.stringify(none))))io.writeLine(test.assertOk(json.stringify(csv.stringify(emptyRows))))
""
"\n\"\"\n"
기대 결과
기대 결과
실행을 마칩니다. 종료 코드 0.
"""\n\"\"\n"
Choose output columns explicitly and fill absent cells
링크import std.csvimport std.jsonimport std.testimport std.iolet rows = [map { "name": "Topaz", "extra": "ignored", "count": "6" }, map { "name": "Ink" }]let text = test.assertOk(csv.stringifyWithHeader(rows, ["count", "name"]))io.writeLine(test.assertOk(json.stringify(text)))let noRows: Array<Map<string, string>> = []io.writeLine(test.assertOk(json.stringify(test.assertOk(csv.stringifyWithHeader(noRows, ["name"])))))
"count,name\n6,Topaz\n,Ink\n"
"name\n"
기대 결과
기대 결과
실행을 마칩니다. 종료 코드 0.
"count,name\n6,Topaz\n,Ink\n""name\n"
Reject duplicate columns before serializing a row
링크import std.csvimport std.iolet rows: Array<Map<string, string>> = []match (csv.stringifyWithHeader(rows, ["name", "name"])) {case Ok(_) => io.writeLine("accepted")case Err(_) => io.writeLine("duplicate columns rejected")}
duplicate columns rejected
기대 결과
기대 결과
실행을 마칩니다. 종료 코드 0.
duplicate columns rejected