将大 txt 文件转换为任何结构化格式

Question

我有一个大的 txt 文件，其中包含空格分隔的“列”，我希望能够将其转换为 JSON、xlsx、csv 等内容，以便对数据执行编程操作。

文件很大，所以我不会发布整个内容 - 这里有一个 sn-p 来获取示例：

ID number Name                              TitlFed  Grade GamesBorn Flag
10207538  A E M, Doshtagir                      BAN  1864    0        i
10206612  A K M, Sourab                         BAN  1714    0        i
 5045886  A K, Kalshyan                         IND  1958    0  1964  
 8605360  A La, Teng Hua                        CHN  1915    0  1993  wi
 5031605  A, Akshaya                            IND  2016   29  1994  w
 5080444  A, Sohita                             IND  1447    0  1995  wi
 5706068  A. Nashir, Mohd Khairul Nazrin        MAS  1878    0        i
10201971  A.f.m., Mahfuzul Haque                BAN  1690    0        
10202650  A.k. Azad, Akand                      BAN  1692    0        i
10210997  A.K.M. Mehfuz                         BAN  2015    0        
24663832  Aab, Manfred                          GER  1808    0  1963  
 1701991  Aaberg, Anton                         SWE  2374    4  1972  
 1513966  Aabid, Ryaad                          NOR  1642    0  1958  
 1407589  Aabling-Thomsen, Jakob            f   DEN  2331   18  1985  
12524670  Aadeli, Arvin                         IRI  2015    0        
 5072662  Aadhityaa, M                          IND  1898   10  1999  
25034677  Aadish S                              IND  1528    5  1999  
 5086183  Aaditt, M K                           IND  1610    0  1996  i
 5027942  Aaditya, Jagadeesh                    IND  1814   16  1998  
25011952  Aadityan G                            IND  1621    7  2001  
 5063485  Aadityan, N.                          IND  1758    8  1996  
 1427024  Aagaard, Gert                         DEN  2030    7  1966  
 1401815  Aagaard, Jacob                    g   DEN  2506    9  1973  
 1411802  Aagaard, Kasper                       DEN  1913    0  1992  i
 1017942  Aagaard, Michael                      NED  2075    0  1960  
 1406248  Aage, Bjarke                          DEN  2068    0  1978  i
 1506064  Aagedal, Geir Ole                     NOR  1833    7  1957  
25021044  Aagney L., Narasimhan                 IND  1285    6  2000  
10205640  Aahelee, Sarker                       BAN  1577    0        w
25014510  Aakanksha Hagawane                    IND  1622    0  2000  w
25030388  Aakash Jain                           IND  1577    7  1998  
35004336  Aakash S B                            IND  1235   10  1998  
 5093295  Aakasha                               IND  1620    3  2000  w
  504599  Aakio, Seppo                          FIN  2078    0  1954  
 1402315  Aalbaek, Kurt Frede Nissen            DEN  1440    0  1944  
 1024388  Aalbers, Klaas                        NED  1891    0  1955  i
 2252465  Aalbersberg Kroon, Pedro              ESP  1878    0  1933  
 2218682  Aalders, Hendricus                    ESP  2021    0  1930  i
 1033948  Aalders, Peter                        NED  1903    0  1964  
  501956  Aaltio, Erkki                         FIN  2118    0  1935  
 1504452  Aandal, Kristian                      NOR  2012    0  1985  i

我使用 javascript 进行编程，因此我希望将其转换为 JSON，理想情况下，每个玩家/id 都将位于他们自己的对象中，如下所示：

    var AllPlayers =
[{
    "2434324243":
    {
        "name":"some guy",
        "title":"f",
        "fed":"USA",
        "grade":"1999",
        "games":"3",
        "born":"1990"

    },
    "8787878887":
    {
        "name":"anyone",
        "title":"",
        "fed":"BER",
        "grade":"2222",
        "games":"6",
        "born":"1970"

    }
}
]

我尝试使用节点中的 fs 模块来读取 txt 文件，然后我计算了每行的长​​度（71 个字符）并尝试将其推送到一个数组 - 但是似乎在读取时空白空间被消除了该文件使这种方法成为一种不可行的方法，因为每个人的信息都具有可变长度。

  var fs = require('fs');
 var allPlayers=[];
 thisPlayer='';
 //1st row length =74
//other rows 71
 //14895 rows 
fs.readFile('jul12frl.txt', 'utf8', function(err, contents) {    
        for(let x=74;x<14895;x++){
            thisPlayer+=contents[x];
            if(thisPlayer.length==71){
                allPlayers.push(thisPlayer);
                thisPlayer='';       
            }
        }
});

我还尝试使用 Excels 内置向导将 txt 转换为 excel 格式 - 但它不会获取所有所需的列 - 它会将 Name/title/fed/grade 列合并为一个巨型列。

Answer 1

const data = `10207538  A E M, Doshtagir                      BAN  1864    0        i
10206612  A K M, Sourab                         BAN  1714    0        i
 5045886  A K, Kalshyan                         IND  1958    0  1964  
 8605360  A La, Teng Hua                        CHN  1915    0  1993  wi
 5031605  A, Akshaya                            IND  2016   29  1994  w
 5080444  A, Sohita                             IND  1447    0  1995  wi
 5706068  A. Nashir, Mohd Khairul Nazrin        MAS  1878    0        i
10201971  A.f.m., Mahfuzul Haque                BAN  1690    0        
10202650  A.k. Azad, Akand                      BAN  1692    0        i
10210997  A.K.M. Mehfuz                         BAN  2015    0        
24663832  Aab, Manfred                          GER  1808    0  1963  
 1701991  Aaberg, Anton                         SWE  2374    4  1972  
 1513966  Aabid, Ryaad                          NOR  1642    0  1958  
 1407589  Aabling-Thomsen, Jakob            f   DEN  2331   18  1985  
12524670  Aadeli, Arvin                         IRI  2015    0        
 5072662  Aadhityaa, M                          IND  1898   10  1999  
25034677  Aadish S                              IND  1528    5  1999  
 5086183  Aaditt, M K                           IND  1610    0  1996  i
 5027942  Aaditya, Jagadeesh                    IND  1814   16  1998  
25011952  Aadityan G                            IND  1621    7  2001  
 5063485  Aadityan, N.                          IND  1758    8  1996  
 1427024  Aagaard, Gert                         DEN  2030    7  1966  
 1401815  Aagaard, Jacob                    g   DEN  2506    9  1973  
 1411802  Aagaard, Kasper                       DEN  1913    0  1992  i
 1017942  Aagaard, Michael                      NED  2075    0  1960  
 1406248  Aage, Bjarke                          DEN  2068    0  1978  i
 1506064  Aagedal, Geir Ole                     NOR  1833    7  1957  
25021044  Aagney L., Narasimhan                 IND  1285    6  2000  
10205640  Aahelee, Sarker                       BAN  1577    0        w
25014510  Aakanksha Hagawane                    IND  1622    0  2000  w
25030388  Aakash Jain                           IND  1577    7  1998  
35004336  Aakash S B                            IND  1235   10  1998  
 5093295  Aakasha                               IND  1620    3  2000  w
  504599  Aakio, Seppo                          FIN  2078    0  1954  
 1402315  Aalbaek, Kurt Frede Nissen            DEN  1440    0  1944  
 1024388  Aalbers, Klaas                        NED  1891    0  1955  i
 2252465  Aalbersberg Kroon, Pedro              ESP  1878    0  1933  
 2218682  Aalders, Hendricus                    ESP  2021    0  1930  i
 1033948  Aalders, Peter                        NED  1903    0  1964  
  501956  Aaltio, Erkki                         FIN  2118    0  1935  
 1504452  Aandal, Kristian                      NOR  2012    0  1985  i`;


const rows = data.split("\n");
function parseRow(row) {
  const id = row.slice(0, 10).trim();
  const name = row.slice(10, 44).trim();
  const title = row.slice(44, 48).trim();
  const country = row.slice(48, 53).trim();
  const grade = row.slice(53, 60).trim();
  const games = row.slice(60, 64).trim();
  const born = row.slice(64, 70).trim();
  const flag = row.slice(70, 72).trim();
 
  return {
    id,
    name,
    title,
    country,
    grade: grade && parseInt(grade),
    games: games && parseInt(games, 10),
    born : born && parseInt(born, 10),
    flag
  }
}

const parsedRows = rows.reduce((acc, row) => {
  const parsed = parseRow(row);
  acc[parsed.id] = parsed;
  return acc;
}, {});

console.log(parsedRows);
                        
                        

鉴于行和列的长度都与示例中提供的相同，您可以这样解析：

// Split original string into rows as an array of strings
const rows = data.split("\n"); // could be replaced with contents read from file

function parseRow(row) {
  // Parse the values by extracting it from the row by start and end index of the column
  const id = row.slice(0, 10).trim();
  const name = row.slice(10, 44).trim();
  const title = row.slice(44, 48).trim();
  const country = row.slice(48, 53).trim();
  const grade = row.slice(53, 60).trim();
  const games = row.slice(60, 64).trim();
  const born = row.slice(64, 70).trim();
  const flag = row.slice(70, 72).trim();

  return {
    id,
    name,
    title,
    country,
    // Parse numbers
    grade: grade && parseInt(grade, 10),
    games: games && parseInt(games, 10),
    born : born && parseInt(born, 10),
    flag
  }
}

const parsed = rows.reduce((acc, row) => {
  const parsed = parseRow(row);
  acc[parsed.id] = parsed;
  return acc;
}, {});

这是一个粗略的解决方案，但它似乎可以解决您的问题。它确实可以运行您提供的示例数据。如果完整数据集与您的示例数据不同，那么您可能需要更新各个列的开始和结束索引。

但是，在您提供的示例数据中，各列仅以空格分隔。如果实际数据集是制表符分隔的，那么解决方案将更易于使用。 [id, name, title, country, grade, games, born, flag] = row.split('\t')