Solution to TaskFailedException; nested task error when opening CSV files in Julia

Error

When opening a CSV file in Julia, you may encounter an error like the one above.

julia> CSV.read("test_primitive.csv", DataFrame)
┌ Warning: thread = 1 warning: only found 13 / 16 columns around data row: 3192. Filling remaining columns with `missing`
└ @ CSV C:\Users\JGH\.julia\packages\CSV\XLcqT\src\file.jl:592
ERROR: TaskFailedException

    nested task error: thread = 7 fatal error, encountered an invalidly quoted field while parsing around row = 3184, col = 8:

Cause

By default, when opening a CSV file, it is processed by splitting into threads. If there is string data, issues may arise during parsing.

Solution

Adding the keyword option ntasks = 1 resolves the problem.

julia> CSV.read("test_primitive.csv", DataFrame; ntasks = 1)
9046×16 DataFrame
  Row │ Column1  material_id  formation_energy_per_atom  dft_band_gap  pretty_formula  e_above_hull  elements                 cif         ⋯
      │ Int64    String15     Float64                    Float64       String31        Float64       String                   String      ⋯
──────┼────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
    1 │       0  mp-10009                    -0.575092         0.898   GaTe             0.0          ['Ga', 'Te']             # generated ⋯
    2 │       1  mp-1218989                  -0.942488         0.0     SmThCN           0.0441088    ['C', 'N', 'Sm', 'Th']   # generated  
    3 │       2  mp-1225695                   0.0648625        0.0     CuNi             0.0648625    ['Cu', 'Ni']             # generated  
    4 │       3  mp-1220884                  -1.45612          0.0     NaTiVS4          0.0          ['Na', 'S', 'Ti', 'V']   # generated  
    5 │       4  mp-1224266                   0.0241391        0.0     Ho3TmMn8         0.0364961    ['Ho', 'Mn', 'Tm']       # generated ⋯
    6 │       5  mp-1002572                  -2.11731          0.8595  LiMnO2           0.042556     ['Li', 'Mn', 'O']        # generated  
    7 │       6  mp-626680                   -1.36116          2.4707  Fe(HO)2          0.000428191  ['Fe', 'H', 'O']         # generated  
  ⋮   │    ⋮          ⋮                   ⋮                   ⋮              ⋮              ⋮                   ⋮                         ⋱
 9041 │    9040  mp-1232301                  -1.95955          1.2452  Tb2MgSe4         0.00526556   ['Mg', 'Se', 'Tb']       # generated  
 9042 │    9041  mp-21084                    -1.77775          1.0134  In6Ga2PtO8       0.0          ['Ga', 'In', 'O', 'Pt']  # generated ⋯
 9043 │    9042  mp-571486                   -0.359373         0.0     CuSe             0.0          ['Cu', 'Se']             # generated  
 9044 │    9043  mp-14410                    -1.20508          0.4594  Tl6TeO12         0.0          ['O', 'Te', 'Tl']        # generated  
 9045 │    9044  mp-1079192                  -2.81452          0.0     Sr2GdRuO6        0.0143609    ['Gd', 'O', 'Ru', 'Sr']  # generated  
 9046 │    9045  mp-13501                    -0.359            0.0     ErCoC2           0.0          ['Er', 'Co', 'C']        # generated ⋯
                                                                                                            9 columns and 9033 rows omitted

Environment

• OS: Windows11
• Version: Julia 1.11.3, CSV v0.10.15, DataFrames v1.7.0