diff options
| -rwxr-xr-x | notmuch-k | 44 |
1 files changed, 19 insertions, 25 deletions
@@ -1,5 +1,17 @@ #!/usr/bin/env nix-shell #! nix-shell -i python3 -p "python37.withPackages(ps:[ps.notmuch ps.scikitlearn]) +""" +plan: + +1. fetch all the emails - uses notmuch python library +2. need to normalize all the inputs? +3. train a naive bayes classifier and classify emails +4. apply infered tags + +refs: + +- https://scikit-learn.org/stable/auto_examples/text/plot_document_clustering.html#sphx-glr-auto-examples-text-plot-document-clustering-py +""" from sklearn import metrics from sklearn.cluster import KMeans, MiniBatchKMeans @@ -16,30 +28,12 @@ import sys import subprocess import notmuch -""" -plan: - -1. fetch all the emails - need to call out to notmuch -2. need to normalize all the inputs? -3. do kmeans, this is actually rather simple - -refs: - -- https://scikit-learn.org/stable/auto_examples/text/plot_document_clustering.html#sphx-glr-auto-examples-text-plot-document-clustering-py - -get the email contents, will return a list of strings: - - notmuch show --format=json -- from:ben@bsima.me date:today \ - | jq '..|.content?|select(type=="string")' - -""" - - def get_body(e): + """Takes an email message object and returns the body content as a single +string.""" parts = e.get_message_parts() return ''.join([p.get_payload() for p in parts]) - def get_emails_for(date): db = notmuch.Database() query = db.create_query(f'not tag:deleted and date:{date}') @@ -47,12 +41,12 @@ def get_emails_for(date): #contents = {e.get_message_id(): get_body(e) for e in emails} return [get_body(e) for e in emails] -DEBUG=True +DEBUG=os.getenv("DEBUG", True) -def done(*s): +def done(*msgs): if DEBUG==True: print(f"done in {time()-t0}s") - if s: [print(s0) for s0 in s] + if msgs: [print(msg) for msg in msgs] print() def debug(s): @@ -64,8 +58,8 @@ def debug(s): debug("loading mail...") t0 = time() dataset = get_emails_for("-3d..today") -# needs to be a "correct" set of tags for the emails, an array of ints where -# each int corresponds to a notmuch tag +# TODO: needs to be a "correct" set of tags for the emails, an array of ints +# where each int corresponds to a notmuch tag labels = [] true_k = np.unique(labels).shape[0] done() |