html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/7224#issuecomment-1296006560,https://api.github.com/repos/pydata/xarray/issues/7224,1296006560,IC_kwDOAMm_X85NP32g,90008,2022-10-29T22:39:39Z,2022-10-29T22:39:39Z,CONTRIBUTOR,xref: https://github.com/pandas-dev/pandas/pull/49393,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1423948375
https://github.com/pydata/xarray/issues/7224#issuecomment-1296006402,https://api.github.com/repos/pydata/xarray/issues/7224,1296006402,IC_kwDOAMm_X85NP30C,90008,2022-10-29T22:39:01Z,2022-10-29T22:39:01Z,CONTRIBUTOR,"Ok, I don't think I have the right tools to really get to the bottom of this. The spyder profiler just seems to slowdown code too much. Any other tools to recommend?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1423948375
https://github.com/pydata/xarray/issues/7224#issuecomment-1292216344,https://api.github.com/repos/pydata/xarray/issues/7224,1292216344,IC_kwDOAMm_X85NBagY,14371165,2022-10-26T15:21:54Z,2022-10-26T15:21:54Z,MEMBER,"I have thought a little about this as well and went and looked in my old code. Creating a `data_vars` dict with the data and then at the end creating the dataset seems to be the way to go:

<details>

```python
import numpy as np
import xarray as xr
from time import perf_counter


# %% Inputs
names = np.core.defchararray.add(""long_variable_name"", np.arange(0, 100).astype(str))
time = np.array([0, 1])
coords = dict(time=time)
value = np.array([""0"", ""b""], dtype=str)

# %% Insert to Dataset with DataArray:
time_start = perf_counter()

ds = xr.Dataset(coords=coords)
for v in names:
    ds[v] = xr.DataArray(data=value, coords=coords)

time_end = perf_counter()
time_elapsed = time_end - time_start
print(""Insert to Dataset with DataArray:"", time_elapsed)

# %% Insert to Dataset with Variable:
time_start = perf_counter()

ds = xr.Dataset(coords=coords)
for v in names:
    ds[v] = xr.Variable(""time"", value)

time_end = perf_counter()
time_elapsed = time_end - time_start
print(""Insert to Dataset with Variable:"", time_elapsed)

# %% Insert to Dataset with tuple:
time_start = perf_counter()

ds = xr.Dataset(coords=coords)
for v in names:
    ds[v] = (""time"", value)

time_end = perf_counter()
time_elapsed = time_end - time_start
print(""Insert to Dataset with tuple:"", time_elapsed)


# %% Dict of DataArray then create Dataset:
time_start = perf_counter()

data_vars = dict()
for v in names:
    data_vars[v] = xr.DataArray(data=value, coords=coords)
ds = xr.Dataset(data_vars=data_vars, coords=coords)

time_end = perf_counter()
time_elapsed = time_end - time_start
print(""Dict of DataArrays then create Dataset:"", time_elapsed)

# %% Dict of Variables then create Dataset:
time_start = perf_counter()

data_vars = dict()
for v in names:
    data_vars[v] = xr.Variable(""time"", value)
ds = xr.Dataset(data_vars=data_vars, coords=coords)

time_end = perf_counter()
time_elapsed = time_end - time_start
print(""Dict of Variables then create Dataset:"", time_elapsed)

# %% Dict of tuples then create Dataset:
time_start = perf_counter()

data_vars = dict()
for v in names:
    data_vars[v] = (""time"", value)
ds = xr.Dataset(data_vars=data_vars, coords=coords)

time_end = perf_counter()
time_elapsed = time_end - time_start
print(""Dict of tuples then create Dataset:"", time_elapsed)

```

</details>

```python
Insert to Dataset with DataArray: 0.3787728999996034
Insert to Dataset with Variable: 0.3083788999997523
Insert to Dataset with tuple: 0.30018929999960164
Dict of DataArrays then create Dataset: 0.07277609999982815
Dict of Variables then create Dataset: 0.005166500000086671
Dict of tuples then create Dataset: 0.003186699999787379  # Winner! :)
```","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1423948375