Move LIMS integrations under legacy namespace

Author: hiyama341

docs/api/index.md

@@ -1,8 +1,8 @@
 # API reference
 
 This reference focuses on stable package entry points that are safe to document during a lightweight docs build.
-Some notebook-oriented modules depend on optional scientific packages or external services and may be expanded in
-future documentation passes.
+The active lab-workflow surface is centered on `teemi.build`, while `teemi.lims` remains available as a legacy
+compatibility namespace for older notebook workflows and integrations.
 
 ```{eval-rst}
 .. autosummary::

docs/quickstart.md

@@ -11,10 +11,10 @@ import teemi
 ## Explore the main namespaces
 
 - `teemi.design` for sequence design, cloning, and workflow planning helpers.
-- `teemi.build` for assembly, PCR, and transformation-oriented utilities.
+- `teemi.build` for active assembly, PCR, and transformation-oriented utilities.
 - `teemi.test` for genotyping and data wrangling helpers.
 - `teemi.learn` for analysis and plotting utilities.
-- `teemi.lims` for sample and sequence tracking integrations.
+- `teemi.lims` for legacy sample and sequence tracking integrations.
 
 ## Example: combinatorial library planning
 

teemi/legacy/lims/__init__.py

@@ -0,0 +1 @@
+"""Legacy LIMS integrations kept for backwards compatibility."""

teemi/legacy/lims/benchling_api.py

@@ -0,0 +1,151 @@
+# MIT License
+# Copyright (c) 2024, Technical University of Denmark (DTU)
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+
+"""Easy to use Benchling functions to fetch sequences and objects."""
+
+import datetime
+import os
+
+import Bio
+import pandas as pd
+import pydna
+from benchlingapi import Session
+from dotenv import find_dotenv, load_dotenv
+
+from teemi.utils import (
+    nest_dict,
+    rename_dict_keys,
+    split_based_on_keys,
+    start_end_to_location,
+)
+
+
+load_dotenv(find_dotenv())
+
+api_key = os.environ.get("API_KEY")
+home_url = os.environ.get("HOME_url")
+session = Session(api_key=api_key, home=home_url)
+
+
+def sequence_to_benchling(folder_name, oligo_name, oligo_bases, schema):
+    """Upload sequences to Benchling."""
+    folder = session.Folder.find_by_name(folder_name)
+    dna = session.DNASequence(
+        name=oligo_name, bases=oligo_bases, folder_id=folder.id, is_circular=False
+    )
+    dna.save()
+
+    schemas = (
+        "Primer",
+        "DNA Fragment",
+        "Plasmid",
+        "Gene",
+        "gRNA",
+        "Marker",
+        "Promoter",
+        "Terminator",
+        "Tag",
+        "Origin of Replication",
+    )
+    if schema in schemas:
+        dna.set_schema(schema)
+
+    dna.register()
+
+
+def from_benchling(bname: str, schema: str = ""):
+    """Extract information of an object on Benchling."""
+    bench_dict = session.DNASequence.find_by_name(bname).dump()
+
+    trans_dict = {
+        "bases": "seq",
+        "id": "id",
+        "annotations": "features",
+        "name": "name",
+        "fields": "annotations",
+    }
+    trans_bench_dict = rename_dict_keys(bench_dict, trans_dict)
+
+    translated_bench_dict_sel, translated_bench_dict_other = split_based_on_keys(
+        trans_bench_dict, trans_dict.values()
+    )
+
+    translated_bench_dict_sel["annotations"].update(
+        translated_bench_dict_other["customFields"]
+    )
+    translated_bench_dict_sel["annotations"].update(
+        {"topology": translated_bench_dict_other["isCircular"]}
+    )
+
+    date = datetime.datetime.today().strftime("%d-%b-%Y").upper()
+    comment = translated_bench_dict_sel["annotations"].pop("comment", None)
+    translated_bench_dict_sel["annotations"].update(
+        {
+            "data_file_division": "PLN",
+            "date": date,
+            "molecule_type": "DNA",
+            "location": "unknown",
+            "commentary": comment,
+        }
+    )
+
+    translated_bench_dict_sel["seq"] = Bio.Seq.Seq(translated_bench_dict_sel["seq"])
+    seq_length = len(translated_bench_dict_sel["seq"])
+
+    translated_bench_dict_sel["features"] = [
+        start_end_to_location(feature_dict, seq_length)
+        for feature_dict in translated_bench_dict_sel["features"]
+    ]
+    for feature in translated_bench_dict_sel["features"]:
+        feature.update({"label": feature.get("name", "")})
+    translated_bench_dict_sel["features"] = [
+        nest_dict(
+            feature_dict,
+            first_order_keys=["location", "type", "strand"],
+            key_for_nested_dict="qualifiers",
+        )
+        for feature_dict in translated_bench_dict_sel["features"]
+    ]
+    translated_bench_dict_sel["features"] = [
+        Bio.SeqFeature.SeqFeature(**feature_dict)
+        for feature_dict in translated_bench_dict_sel["features"]
+    ]
+
+    seqRecord = Bio.SeqRecord.SeqRecord(**translated_bench_dict_sel)
+    seqRecord.name = bname
+    seqRecord = update_loc_vol_conc(seqRecord)
+
+    if schema == "Primer":
+        seqRecord = pydna.primer.Primer(seqRecord)
+
+    return seqRecord
+
+
+def update_loc_vol_conc(seqRecord, DBpath: str = ""):
+    """Update location, volume, and concentration information from a CSV export."""
+    DB = pd.read_csv(DBpath)
+
+    seqRecord.annotations["batches"] = []
+    for _, row in DB.iterrows():
+        if row["batchEntId"] == seqRecord.id:
+            location = row["parentBoxPlateName"] + "_" + row["parentBoxPlatePos"]
+            seqRecord.annotations["batches"].append(
+                {
+                    "box": row["parentBoxPlateName"],
+                    "position": row["parentBoxPlatePos"],
+                    "volume": int(row["volume"]),
+                    "concentration": int(row["Concentration (ng/ul)"]),
+                    "location": location,
+                }
+            )
+    return seqRecord