!!! abstract “”
Use `open_data_store` with a loader, processor, and writer app to batch-process a directory of files `apply_to`, and enable progress bars and parallel execution. Then inspect results.We will translate the DNA sequences in raw.zip into
amino acid and store them as a sqlite database. We will interrogate the
generated data store to get a synopsis of the results.
???+ example “Translating DNA to amino acid”
```python { linenums="1" notest }
from scinexus import open_data_store
from cogent3 import get_app
in_dstore = open_data_store("data/raw.zip", suffix="fa") # (1)!
out_dstore = open_data_store("translated.sqlitedb", mode="w") # (2)!
load = get_app("load_unaligned", moltype="dna")
translate = get_app("translate_seqs")
write = get_app("write_db", data_store=out_dstore)
app = load + translate + write # (3)!
out_dstore = app.apply_to(in_dstore) # (4)!
out_dstore.describe # (5)!
out_dstore.validate() # (6)!
out_dstore.summary_not_completed # (7)!
```
1. Open the zipped input data store, selecting `.fa` files as members.
2. Create a writable SQLite output data store. Using a single database file is more efficient than writing many small files.
3. Compose loader, translator, and writer into a single pipeline.
4. Apply the pipeline to every member of the input data store. Results are written to `out_dstore`.
5. Summary showing counts of completed records, not-completed records, and log files.
6. Verify the integrity of all records via MD5 checksums.
7. Summary of why some records could not be processed — e.g. sequences not divisible by 3 or containing stop codons.!!! note
The `.completed` and `.not_completed` attributes give access to the different types of members, while `.members` gives them all. For example, `len(out_dstore.not_completed)` returns the count of failed records and each element is a `DataMember`.