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authorBonfaceKilz2022-03-10 17:55:33 +0300
committerBonfaceKilz2022-03-12 15:33:01 +0300
commit5ea303bd83ddb0b47a9372a674f7b27572703354 (patch)
treeeca0b192795650d04e0c0133d414e10229cfad57
parentfb0ca34547f2b804154e4c0d554cd383c96cce42 (diff)
downloadgenenetwork2-5ea303bd83ddb0b47a9372a674f7b27572703354.tar.gz
Use updated `update_sample_data` from gn3
-rw-r--r--wqflask/wqflask/metadata_edits.py90
1 files changed, 16 insertions, 74 deletions
diff --git a/wqflask/wqflask/metadata_edits.py b/wqflask/wqflask/metadata_edits.py
index c9af0467..9d99f4da 100644
--- a/wqflask/wqflask/metadata_edits.py
+++ b/wqflask/wqflask/metadata_edits.py
@@ -465,83 +465,25 @@ def reject_data(resource_id: str, file_name: str):
@login_required
def approve_data(resource_id:str, file_name: str):
sample_data = {file_name: str}
- with database_connection() as conn:
- TMPDIR = current_app.config.get("TMPDIR")
- with open(os.path.join(f"{TMPDIR}/sample-data/diffs",
- file_name), 'r') as myfile:
- sample_data = json.load(myfile)
- for modification in (
- modifications := [d for d in sample_data.get("Modifications")]):
- if modification.get("Current"):
- (strain_name,
- value, se, count) = modification.get("Current").split(",")
- update_sample_data(
- conn=conn,
- trait_name=sample_data.get("trait_name"),
- strain_name=strain_name,
- phenotype_id=int(sample_data.get("phenotype_id")),
- value=value,
- error=se,
- count=count)
-
- n_deletions = 0
- for deletion in (deletions := [d for d in sample_data.get("Deletions")]):
- strain_name, _, _, _ = deletion.split(",")
- __deletions, _, _ = delete_sample_data(
+ conn = MySQLdb.Connect(db=current_app.config.get("DB_NAME"),
+ user=current_app.config.get("DB_USER"),
+ passwd=current_app.config.get("DB_PASS"),
+ host=current_app.config.get("DB_HOST"))
+ TMPDIR = current_app.config.get("TMPDIR")
+ with open(os.path.join(f"{TMPDIR}/sample-data/diffs",
+ file_name), 'r') as myfile:
+ sample_data = json.load(myfile)
+ for modification in (
+ modifications := [d for d in sample_data.get("Modifications")]):
+ if modification.get("Current"):
+ update_sample_data(
conn=conn,
trait_name=sample_data.get("trait_name"),
- strain_name=strain_name,
+ original_data=modification.get("Original"),
+ updated_data=modification.get("Current"),
+ csv_header=sample_data.get("Columns",
+ "Strain Name,Value,SE,Count"),
phenotype_id=int(sample_data.get("phenotype_id")))
- if __deletions:
- n_deletions += 1
- # Remove any data that already exists from sample_data deletes
- else:
- sample_data.get("Deletions").remove(deletion)
-
- n_insertions = 0
- for insertion in (
- insertions := [d for d in sample_data.get("Additions")]):
- (strain_name,
- value, se, count) = insertion.split(",")
- __insertions, _, _ = insert_sample_data(
- conn=conn,
- trait_name=sample_data.get("trait_name"),
- strain_name=strain_name,
- phenotype_id=int(sample_data.get("phenotype_id")),
- value=value,
- error=se,
- count=count)
- if __insertions:
- n_insertions += 1
- # Remove any data that already exists from sample_data inserts
- else:
- sample_data.get("Additions").remove(insertion)
- if any([sample_data.get("Additions"),
- sample_data.get("Modifications"),
- sample_data.get("Deletions")]):
- insert(conn,
- table="metadata_audit",
- data=MetadataAudit(
- dataset_id=sample_data.get("trait_name"),
- editor=sample_data.get("author"),
- json_data=json.dumps(sample_data)))
- # Once data is approved, rename it!
- os.rename(os.path.join(f"{TMPDIR}/sample-data/diffs", file_name),
- os.path.join(f"{TMPDIR}/sample-data/diffs",
- f"{file_name}.approved"))
- message = ""
- if n_deletions:
- flash(f"# Deletions: {n_deletions}", "success")
- if n_insertions:
- flash("# Additions: {len(modifications)", "success")
- if len(modifications):
- flash("# Modifications: {len(modifications)}", "success")
- else: # Edge case where you need to automatically reject the file
- os.rename(os.path.join(f"{TMPDIR}/sample-data/diffs", file_name),
- os.path.join(f"{TMPDIR}/sample-data/diffs",
- f"{file_name}.rejected"))
- flash(("Automatically rejecting this file since no "
- "changes could be applied."), "warning")
n_deletions = 0
for data in [d for d in sample_data.get("Deletions")]: