Merge pull request datajoint#71 from kabilar/main

Add `black` code formatting

notebooks/00-data-download-optional.ipynb

@@ -27,6 +27,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "%%bash\n",
     "pip install git+https://github.com/datajoint/djarchive-client.git"
    ]
   },
@@ -183,7 +184,7 @@
  ],
  "metadata": {
   "jupytext": {
-   "formats": "ipynb,py"
+   "formats": "ipynb,py_scripts//py"
   },
   "kernelspec": {
    "display_name": "ephys_workflow_runner",

notebooks/py_scripts/00-data-download-optional.py

@@ -1,12 +1,12 @@
 # ---
 # jupyter:
 #   jupytext:
-#     formats: ipynb,py
+#     formats: ipynb,py_scripts//py
 #     text_representation:
 #       extension: .py
 #       format_name: light
 #       format_version: '1.5'
-#       jupytext_version: 1.13.7
+#       jupytext_version: 1.14.0
 #   kernelspec:
 #     display_name: ephys_workflow_runner
 #     language: python
@@ -19,12 +19,15 @@
 
 # The example dataset was hosted on djarchive, an AWS storage. We provide a client package to download the data.[djarchive-client](https://github.com/datajoint/djarchive-client), which could be installed with pip:
 
-pip install git+https://github.com/datajoint/djarchive-client.git
+# + language="bash"
+# pip install git+https://github.com/datajoint/djarchive-client.git
+# -
 
 # ## Download ephys test datasets using `djarchive-client`
 
 import os
 import djarchive_client
+
 client = djarchive_client.client()
 
 # To browse the datasets that are available in djarchive:
@@ -37,17 +40,22 @@
 
 # To download the dataset, let's prepare a root directory, for example in `/tmp`:
 
-os.mkdir('/tmp/test_data')
+os.mkdir("/tmp/test_data")
 
 # Get the dataset revision with the current version of the workflow:
 
 from workflow_array_ephys import version
-revision = version.__version__.replace('.', '_')
+
+revision = version.__version__.replace(".", "_")
 revision
 
 # Then run download for a given set and the revision:
 
-client.download('workflow-array-ephys-test-set', target_directory='/tmp/test_data', revision=revision)
+client.download(
+    "workflow-array-ephys-test-set",
+    target_directory="/tmp/test_data",
+    revision=revision,
+)
 
 # ## Directory organization
 # After downloading, the directory will be organized as follows:

notebooks/py_scripts/01-configure.py

@@ -26,20 +26,24 @@
 # -
 
 import os
+
 # change to the upper level folder
-if os.path.basename(os.getcwd())=='notebooks': os.chdir('..')
-assert os.path.basename(os.getcwd())=='workflow-array-ephys', ("Please move to the "
-                                                               + "workflow directory")
+if os.path.basename(os.getcwd()) == "notebooks":
+    os.chdir("..")
+assert os.path.basename(os.getcwd()) == "workflow-array-ephys", (
+    "Please move to the " + "workflow directory"
+)
 import datajoint as dj
 
 # ## Setup - Credentials
 #
 # Now let's set up the host, user and password in the `dj.config` global variable
 
 import getpass
-dj.config['database.host'] = '{YOUR_HOST}'
-dj.config['database.user'] = '{YOUR_USERNAME}'
-dj.config['database.password'] = getpass.getpass() # enter the password securily
+
+dj.config["database.host"] = "{YOUR_HOST}"
+dj.config["database.user"] = "{YOUR_USERNAME}"
+dj.config["database.password"] = getpass.getpass()  # enter the password securily
 
 # You should be able to connect to the database at this stage.
 
@@ -55,11 +59,11 @@
 #
 # The prefix could be configurated as follows in `dj.config`:
 
-dj.config['custom'] = {'database.prefix': 'neuro_'}
+dj.config["custom"] = {"database.prefix": "neuro_"}
 
 # ### Root directories for raw/processed data
 #
-# `ephys_root_data_dir` field indicates the root directory for 
+# `ephys_root_data_dir` field indicates the root directory for
 # + The **ephys raw data** from SpikeGLX or OpenEphys, including `*{.ap,lf}.{bin,meta}`
 # + The **clustering results** from kilosort2 (e.g. `spike_{times,clusters}.npy`
 #
@@ -77,9 +81,9 @@
 # ```
 
 # If there is only one root path.
-dj.config['custom']['ephys_root_data_dir'] = '/tmp/test_data'
+dj.config["custom"]["ephys_root_data_dir"] = "/tmp/test_data"
 # If there are multiple possible root paths:
-dj.config['custom']['ephys_root_data_dir'] = ['/tmp/test_data1', '/tmp/test_data2']
+dj.config["custom"]["ephys_root_data_dir"] = ["/tmp/test_data1", "/tmp/test_data2"]
 
 dj.config
 
@@ -92,7 +96,7 @@
 #
 # `element-array-ephys` offers 3 different schemas: `acute`, `chronic`, and `no-curation`. For more information about each, please visit the [electrophysiology description page](https://elements.datajoint.org/description/array_ephys/). This decision should be made before first activating the schema. Note: only `no-curation` is supported for export to NWB directly from the Element.
 
-dj.config['custom']['ephys_mode']='no-curation' # or acute or chronic
+dj.config["custom"]["ephys_mode"] = "no-curation"  # or acute or chronic
 
 # ## Save configuration
 #

notebooks/py_scripts/02-workflow-structure-optional.py

@@ -24,7 +24,9 @@
 # To load the local configuration, we will change the directory to the package root.
 
 import os
-if os.path.basename(os.getcwd())=='notebooks': os.chdir('..')
+
+if os.path.basename(os.getcwd()) == "notebooks":
+    os.chdir("..")
 
 # ## Schemas and tables
 
@@ -57,24 +59,24 @@
 # + `dj.list_schemas()`: list all schemas a user could access.
 dj.list_schemas()
 
-# + `dj.Diagram()`: plot tables and dependencies. 
+# + `dj.Diagram()`: plot tables and dependencies.
 
 # + `dj.Diagram()`: plot tables and dependencies
 # plot diagram for all tables in a schema
 dj.Diagram(ephys)
 # -
 
-# **Table tiers**: 
+# **Table tiers**:
 #
-# Manual table: green box, manually inserted table, expect new entries daily, e.g. Subject, ProbeInsertion.  
-# Lookup table: gray box, pre inserted table, commonly used for general facts or parameters. e.g. Strain, ClusteringMethod, ClusteringParamSet.  
-# Imported table: blue oval, auto-processing table, the processing depends on the importing of external files. e.g. process of Clustering requires output files from kilosort2.  
-# Computed table: red circle, auto-processing table, the processing does not depend on files external to the database, commonly used for     
+# Manual table: green box, manually inserted table, expect new entries daily, e.g. Subject, ProbeInsertion.
+# Lookup table: gray box, pre inserted table, commonly used for general facts or parameters. e.g. Strain, ClusteringMethod, ClusteringParamSet.
+# Imported table: blue oval, auto-processing table, the processing depends on the importing of external files. e.g. process of Clustering requires output files from kilosort2.
+# Computed table: red circle, auto-processing table, the processing does not depend on files external to the database, commonly used for
 # Part table: plain text, as an appendix to the master table, all the part entries of a given master entry represent a intact set of the master entry. e.g. Unit of a CuratedClustering.
 #
-# **Dependencies**:  
+# **Dependencies**:
 #
-# One-to-one primary: thick solid line, share the exact same primary key, meaning the child table inherits all the primary key fields from the parent table as its own primary key.     
+# One-to-one primary: thick solid line, share the exact same primary key, meaning the child table inherits all the primary key fields from the parent table as its own primary key.
 # One-to-many primary: thin solid line, inherit the primary key from the parent table, but have additional field(s) as part of the primary key as well
 # secondary dependency: dashed line, the child table inherits the primary key fields from parent table as its own secondary attribute.
 
@@ -95,7 +97,7 @@
 # + `heading`: [markdown]
 # # + `describe()`: show table definition with foreign key references.
 # -
-ephys.EphysRecording.describe();
+ephys.EphysRecording.describe()
 
 # + `heading`: show attribute definitions regardless of foreign key references
 
@@ -115,14 +117,14 @@
 dj.Diagram(subject)
 
 # + [subject](https://github.com/datajoint/element-animal): contains the basic information of subject, including Strain, Line, Subject, Zygosity, and SubjectDeath information.
-subject.Subject.describe();
+subject.Subject.describe()
 
 # + [`session`](https://github.com/datajoint/element-session): General information of experimental sessions.
 
 dj.Diagram(session)
 
 # + [session](https://github.com/datajoint/element-session): experimental session information
-session.Session.describe();
+session.Session.describe()
 
 # + [`ephys`](https://github.com/datajoint/element-array-ephys): Neuropixel based probe and ephys information