*Last updated: 2023-03-16.*
# tf_quant_finance.experimental.io.ArrayDictWriter
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Writer to write dictionaries of numpy arrays in binary format.
```python
tf_quant_finance.experimental.io.ArrayDictWriter(
path
)
```
Writes dictionaries with string keys and numpy array values as records into
a [tfrecords](https://www.tensorflow.org/tutorials/load_data/tfrecord) file.
The usage of tfrecords should be treated as an implementation detail. To
read the file, use the `ArrayDictReader` class.
#### Notes and Limitations:
1. Any values which are not numpy arrays will be first converted to
an array before serializing.
2. Serializing strings or arrays of strings is complicated because numpy
doesn't support variable length strings. By default, a python string
converted to a numpy array will be converted to a fixed size dtype (of the
form 'Un' where n is the size of the largest string). During serialization
this information is lost and the deserialization produces an object array
with bytes elements. These need to be manually converted back
to a unicode string using `object.astype('U?') where ? is the length of the
largest string in the array.
#### Example
```python
options_data = {
'instrument_type': 'EuropeanOption',
'strikes': np.array([1.0, 2.0, 3.0], dtype=np.float64),
'is_call': np.array([True, True, False]),
'expiries': np.array([0.4, 1.3, 2.3], dtype=np.float64)
}
barriers_data = {
'instrument_type': 'BarrierOption',
'strikes': np.array([1.0, 2.0, 3.0], dtype=np.float64),
'is_call': np.array([True, True, False]),
'expiries': np.array([0.4, 1.3, 2.3], dtype=np.float64),
'barrier': np.array([1.4, 2.5, 2.5], dtype=np.float64),
'is_knockout': np.array([True, True, False])
}
with ArrayDictWriter('datafile.bin') as writer:
writer.write(options_data)
writer.write(barriers_data)
```
## Methods
__enter__
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```python
__enter__()
```
__exit__
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```python
__exit__(
unused_type, unused_value, unused_traceback
)
```
Exits a `with` block and closes the file.
close
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```python
close()
```
Close the file.
flush
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```python
flush()
```
Flushes the file.
write
View source
```python
write(
array_dict
)
```
Writes a dictionary of arrays to the file.
#### Args:
* `array_dict`: A record to write. Should be a dictionary with string keys and
numpy array values.