<|im_start|>system
You are a helpful AI assistant.<|im_end|>
<|im_start|>user
How to use tqdm in databricks?<|im_end|>
<|im_start|>assistant
You can install tqdm into Databricks just like you would locally - using PyPI and pip.
So in a notebook cell, run:
pip install tqdm

Then you can import and use tqdm as normal:
```python
from tqdm import tqdm
for i in tqdm(range(10000)):
    ...
```

Databricks has PyPI access, so this will download and install tqdm (and its dependencies) correctly.
The one slight caveat is that tqdm uses some terminal features to get a progress bar. In a notebook this falls back to just printing . characters - so you get a basic progress indicator but no bar. For most use cases this is sufficient though, and allows the useful tqdm features like auto-scaling eta and progress percentages.<|im_end|>
<|im_start|>user
This should serve perfectly - Thank you.<|im_end|>
<|im_start|>assistant
I am glad I could be of service.<|im_end|>
<|im_start|>user
That is a good summary I guess, I was hoping for an actual implementation example.<|im_end|>
<|im_start|>assistant
You can use tqdm in Databricks by installing the library in your Databricks workspace. Here is how you can do it:

1. In the Databricks workspace, go to the "Workspace" section and click on the "Create" button.
2. Select "Library" and then "PyPI."
3. In the "Package" field, type "tqdm" and select the latest version of the library.
4. Click on the "Create" button to install the library.

Once the library is installed, you can use it in your Databricks notebooks by importing the library and using the tqdm function to wrap your loops.

Here is again an example how it could look like in code: 

```
from tqdm import tqdm

for i in tqdm(range(1000)):
  # Your code here
```

This will display a progress bar that shows the progress of your loop. You can use the tqdm function to wrap any loop or iterator in your code to get a progress bar.<|im_end|>