PieFedCode Highlighting Test
submitted by
Testing
wjs018This is a copy/paste of the code from this post to test the highlighting.
```python
import os, sys
import logging
from app.plugins.hooks import hook
from flask import current_app, g, Blueprint
from app.utils import get_task_session
from app.models import Site, Instance, Post, PostReply, User, ActivityPubLog, PostVote, PostReplyVote
from sqlalchemy import text, func, literal_column, and, or
from matplotlib.figure import Figure
from matplotlib.colors import TABLEAU_COLORS
import matplotlib.dates as mdates
from datetime import datetime, timedelta
PLUGIN_NAME = _name_.split(’.’)[-1]
logger = logging.getLogger(_name_)
def fetch_stats(session, obj, interval=’day’, starttime=None, endtime=None, count1=None, count2=None, sum2=None, createdcolumn=None):
if interval not in [’hour’, ‘day’, ‘week’, ‘month’]:
interval = ‘day’
if not starttime:
starttime = g.site.created_at
if not endtime:
endtime = datetime.now()
if not count1:
count1 = [obj.id != None]
if not createdcolumn:
createdcolumn = obj.created_at
timeseries = func.generate_series(starttime, endtime, f"1 {interval}").alias('timeseries')
one = literal_column("1")
if count2:
data = session.query(timeseries.column, func.count(one).filter(*count1), func.count(one).filter(*count2))
elif sum2:
data = session.query(timeseries.column, func.count(one).filter(*count1), func.sum(sum2))
else:
data = session.query(timeseries.column, func.count(one).filter(*count1))
data = data.select_from(timeseries).outerjoin(obj, func.date_trunc(interval, createdcolumn) == func.date_trunc(interval, timeseries.column))
data = data.group_by(timeseries.column).order_by(timeseries.column)
if interval == 'day':
data = data.all()[2:-2] # throw away first two days and today to remove outliers/unstable data
data2 = {'timestamp': [], 'count1': [], 'count2': [], 'zeros': []}
for row in data:
data2['timestamp'].append(row[0])
data2['count1'].append(row[1])
if count2:
data2['count2'].append(row[2])
data2['zeros'].append(0)
return data2
@hook("cron_daily")
def generate_charts_loop(data):
“""Hook that runs on a periodic interval"""
from app import redis_client
with current_app.app_context(), get_task_session() as session:
g.site = session.query(Site).get(1)
languages = session.execute(text('SELECT language.name, COUNT(*) FROM post LEFT JOIN language ON post.language_id = language.id AND post.deleted = False GROUP BY name ORDER BY count DESC LIMIT 10')).all()
colors = list( TABLEAU_COLORS.keys() )
colors.insert(1, 'lightgray')
fig = Figure()
ax = fig.add_subplot()
labels = [r.name if r.name else 'Unknown' for r in languages]
hbars = ax.barh(labels, [r.count for r in languages], align='center', label=labels, color=colors)
ax.invert_yaxis()
ax.xaxis.set_visible(False)
ax.set_title('Top 10 post languages', y=0.0)
ax.text(0.99, -0.01, datetime.now().strftime('%Y-%m-%d %H:%M:%S') + ' on ' + g.site.name, verticalalignment='top', horizontalalignment='right', transform=ax.transAxes, color='darkgrey') #, fontsize=15
fig.tight_layout()
filename = "/var/lib/piefed/app/static/tmp/languages.svg"
fig.savefig(filename, format="svg")
software = session.execute(text('SELECT software, COUNT(*) FROM instance WHERE "gone_forever" IS False GROUP BY software ORDER BY count DESC LIMIT 15')).all()
myexplode = [0.2 if r.software == 'piefed' else 0 for r in software]
fig = Figure()
ax = fig.add_subplot()
colors = list( TABLEAU_COLORS.keys() )
hbars = ax.barh([r.software for r in software], [r.count for r in software], align='center', color=colors)
ax.bar_label(hbars, fmt='%d')
ax.invert_yaxis()
ax.set_title('Instances by Software', y=0.0)
ax.text(0.99, -0.01, datetime.now().strftime('%Y-%m-%d %H:%M:%S') + ' on ' + g.site.name, verticalalignment='top', horizontalalignment='right', transform=ax.transAxes, color='darkgrey') #, fontsize=15
fig.tight_layout()
fig.savefig("/var/lib/piefed/app/static/tmp/software.svg", format="svg") # , transparent=True
for software in ["mastodon", "lemmy", "peertube", "friendica", "piefed", "sharkey", "mbin"]:
version = session.execute(text('SELECT version, COUNT(*) FROM instance WHERE "software" = :software AND "gone_forever" IS False GROUP BY version ORDER BY count DESC'), {'software': software}).all()
fig = Figure()
ax = fig.add_subplot()
ax.pie([r.count for r in version], labels=[r.version for r in version])
ax.set_title(f"{software} versions", y=0.0)
ax.text(0.99, -0.01, datetime.now().strftime('%Y-%m-%d %H:%M:%S') + ' on ' + g.site.name, verticalalignment='top', horizontalalignment='right', transform=ax.transAxes, color='darkgrey') #, fontsize=15
fig.tight_layout()
fig.savefig(f"/var/lib/piefed/app/static/tmp/version_{software}.svg", format="svg")
for interval in ['day', 'week', 'month']: # hour
data = fetch_stats(session, Instance, interval)
data_gone = fetch_stats(session, Instance, interval, createdcolumn=Instance.last_seen, count1=[Instance.gone_forever == True])
fig = Figure()
ax = fig.subplots()
ax.fill_between(data['timestamp'], data['zeros'], data['count1'], step='pre', alpha=0.4)
ax.step(data['timestamp'], data['count1'], label="Instances discovered")
ax.fill_between(data_gone['timestamp'], data_gone['zeros'], [-x for x in data_gone['count1']], step='pre', alpha=0.4)
ax.step(data_gone['timestamp'], [-x for x in data_gone['count1']], label="Instances gone")
ax.plot([], [], ' ', label=f"(per {interval})")
ax.legend(loc="upper right")
fig.tight_layout()
fig.savefig(f"/var/lib/piefed/app/static/tmp/instances_{interval}.svg", format="svg")
data_posts = fetch_stats(session, Post, interval, count1=[and_(Post.deleted == False, Post.up_votes > 0)], count2=[Post.deleted == True])
data_replies = fetch_stats(session, PostReply, interval, count1=[and_(PostReply.deleted == False, PostReply.up_votes > 1)], count2=[PostReply.deleted == True])
posts_byvote = fetch_stats(session, Post, interval, count1=[and_(Post.deleted == False, Post.up_votes > 30)], count2=[and_(Post.deleted == False, Post.up_votes == 0)])
replies_byvote = fetch_stats(session, PostReply, interval, count1=[and_(PostReply.deleted == False, PostReply.up_votes > 10)], count2=[and_(PostReply.deleted == False, PostReply.up_votes <= 1)])
fig = Figure()
axs = fig.subplots(2)
axs[0].fill_between(data_posts['timestamp'], data_posts['zeros'], data_posts['count1'], step='pre', alpha=0.4)
axs[0].step(data_posts['timestamp'], data_posts['count1'], label = f"Posts (per {interval})")
axs[0].fill_between(data_posts['timestamp'], data_posts['zeros'], [-x for x in data_posts['count2']], step='pre', alpha=0.4)
axs[0].step(data_posts['timestamp'], [-x for x in data_posts['count2']], label="Posts removed")
axs[0].fill_between(posts_byvote['timestamp'], posts_byvote['zeros'], posts_byvote['count1'], step='pre', alpha=0.4)
axs[0].plot([], [], label=">30 upvotes")
axs[0].fill_between(posts_byvote['timestamp'], data_posts['count1'], [x + y for x, y in zip(data_posts['count1'], posts_byvote['count2'])], step='pre', alpha=0.4)
axs[0].plot([], [], label="0 upvotes")
axs[1].fill_between(data_replies['timestamp'], data_replies['zeros'], data_replies['count1'], step='pre', alpha=0.4)
axs[1].step(data_replies['timestamp'], data_replies['count1'], label = f"Comments (per {interval})")
axs[1].fill_between(data_replies['timestamp'], data_replies['zeros'], [-x for x in data_replies['count2']], step='pre', alpha=0.4)
axs[1].step(data_replies['timestamp'], [-x for x in data_replies['count2']], label= "Comments removed")
axs[1].fill_between(replies_byvote['timestamp'], replies_byvote['zeros'], replies_byvote['count1'], step='pre', alpha=0.4)
axs[1].plot([], [], label=">10 upvotes")
axs[1].fill_between(replies_byvote['timestamp'], data_replies['count1'], [x + y for x, y in zip(data_replies['count1'], replies_byvote['count2'])], step='pre', alpha=0.4)
axs[1].plot([], [], label="<=1 upvote")
axs[0].legend(loc="upper left")
axs[1].legend(loc="upper left")
fig.tight_layout()
fig.savefig(f"/var/lib/piefed/app/static/tmp/posts_{interval}.svg", format="svg")
data = fetch_stats(session, User, interval, createdcolumn=User.created, count1=[User.bot == False], count2=[and_(User.bot == False, User.deleted == False, User.banned == False, User.last_seen - User.created < timedelta(days=3), User.created < datetime.now() - timedelta(days=5))])
users_removed = fetch_stats(session, User, interval, createdcolumn=User.last_seen, count1=[or_(User.deleted == True, User.banned == True)])
fig = Figure()
ax = fig.subplots()
ax.fill_between(data['timestamp'], data['zeros'], data['count1'], step='pre', alpha=0.4)
ax.step(data['timestamp'], data['count1'], label="Users discovered")
ax.fill_between(users_removed['timestamp'], users_removed['zeros'], [-x for x in users_removed['count1']], step='pre', alpha=0.4)
ax.step(users_removed['timestamp'], [-x for x in users_removed['count1']], label="Users removed")
ax.fill_between(data['timestamp'], data['count1'], [x - y for x, y in zip(data['count1'], data['count2'])], step='pre', alpha=0.4)
ax.plot([], [], label="non-returning")
ax.plot([], [], ' ', label=f"(per {interval})")
# ToDo: show inactive
ax.legend(loc="upper right")
fig.tight_layout()
fig.savefig(f"/var/lib/piefed/app/static/tmp/users_{interval}.svg", format="svg")
starttime = datetime.now() - timedelta(days=3)
endtime = datetime.now()
interval = 'hour'
timeseries = func.generate_series(starttime, endtime, f"1 {interval}").alias('timeseries')
one = literal_column("1")
data = session.query(timeseries.column, func.count(one).filter(ActivityPubLog.id != None), ActivityPubLog.activity_type, ActivityPubLog.direction).select_from(timeseries).outerjoin(ActivityPubLog, func.date_trunc(interval, ActivityPubLog.created_at) == func.date_trunc(interval, timeseries.column)).group_by(timeseries.column, ActivityPubLog.activity_type, ActivityPubLog.direction).order_by(timeseries.column).all()[:-2]
timestamps = []
activity_types = []
values = dict()
values['in'] = dict()
values['out'] = dict()
for r in data:
timestamp_ = r[0]
value_ = r[1]
type_ = r[2]
direction_ = r[3]
if direction_ not in ['in', 'out']:
continue
if type_ not in values[direction_]:
values[direction_][type_] = dict()
values[direction_][type_][timestamp_] = value_
if timestamp_ not in timestamps:
timestamps.append(timestamp_)
if type_ not in activity_types:
activity_types.append(type_)
val2 = dict()
for direction in ['in', 'out']:
val2[direction] = dict()
for type_ in activity_types:
val2[direction][type_] = []
for i, ts in enumerate(timestamps):
if (type_ in values[direction]) and (ts in values[direction][type_]):
val2[direction][type_].append(values[direction][type_][ts])
else:
val2[direction][type_].append(0)
fig = Figure()
ax = fig.subplots()
defaultColors = [
"#3366CC", "#DC3912", "#FF9900", "#109618", "#990099", "#3B3EAC", "#0099C6",
"#DD4477", "#66AA00", "#B82E2E", "#316395", "#994499", "#22AA99", "#AAAA11",
"#6633CC", "#E67300", "#8B0707", "#329262", "#5574A6", "#651067"
]
bottom = [0 for r in timestamps]
shownTypes = ['Announce', 'Create', 'Update', 'Delete', 'Undo Vote', 'Dislike', 'Like'] # , 'PeerTube View', 'Duplicate', 'User Ban', 'Add Mod/Sticky', 'Remove Mod/Sticky', 'Undo Delete', 'Post Lock', 'Accept', 'Follow', 'Flag', 'Unknown', 'Undo'
for type_, color in zip(shownTypes, defaultColors):
y2 = [x + y for x, y in zip(val2['in'][type_], bottom)]
ax.vlines(timestamps, bottom, y2, colors=color, linewidth=3, label=type_)
bottom = y2
ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
ax.legend(loc='center left')
fig.tight_layout()
fig.savefig(f"/var/lib/piefed/app/static/tmp/activity.svg", format="svg")
user = session.query(User).filter(User.id == 145).one()
interval = 'day'
starttime = max( datetime.now() - timedelta(days=180), user.created )
endtime = datetime.now()
data_posts = fetch_stats(session, Post, interval, starttime, endtime, count1=[Post.user_id == user.id]) # , sum2=Post.up_votes
data_replies = fetch_stats(session, PostReply, interval, starttime, endtime, count1=[PostReply.user_id == user.id])
data_post_votes = fetch_stats(session, PostVote, interval, starttime, endtime, count1=[and_(PostVote.user_id == user.id, PostVote.effect > 0)], count2=[and_(PostVote.user_id == user.id, PostVote.effect < 0)])
data_reply_votes = fetch_stats(session, PostReplyVote, interval, starttime, endtime, count1=[and_(PostReplyVote.user_id == user.id, PostReplyVote.effect > 0)], count2=[and_(PostReplyVote.user_id == user.id, PostReplyVote.effect < 0)])
data_votes = {'timestamp': [x for x, y in zip(data_post_votes['timestamp'], data_reply_votes['timestamp'])],
'count1': [x + y for x, y in zip(data_post_votes['count1'], data_reply_votes['count1'])],
'count2': [x + y for x, y in zip(data_post_votes['count2'], data_reply_votes['count2'])] }
data_post_votes_in = fetch_stats(session, PostVote, interval, starttime, endtime, count1=[and_(PostVote.author_id == user.id, PostVote.effect > 0)], count2=[and_(PostVote.author_id == user.id, PostVote.effect < 0)])
data_reply_votes_in = fetch_stats(session, PostReplyVote, interval, starttime, endtime, count1=[and_(PostReplyVote.author_id == user.id, PostReplyVote.effect > 0)], count2=[and_(PostReplyVote.author_id == user.id, PostReplyVote.effect < 0)])
data_votes_in = {'timestamp': [x for x, y in zip(data_post_votes_in['timestamp'], data_reply_votes_in['timestamp'])],
'count1': [x + y for x, y in zip(data_post_votes_in['count1'], data_reply_votes_in['count1'])],
'count2': [x + y for x, y in zip(data_post_votes_in['count2'], data_reply_votes_in['count2'])] }
fig = Figure()
axs = fig.subplots(3)
axs[0].set_title(f"{user.user_name}")
bottom = data_posts['zeros']
axs[0].vlines(data_posts['timestamp'], bottom, data_posts['count1'], colors="#3366CC", linewidth=2, label="Posts")
bottom = data_posts['count1']
axs[0].vlines(data_replies['timestamp'], bottom, [x+y for x, y in zip(data_posts['count1'], data_replies['count1'])], colors="#FF9900", linewidth=2, label="Comments")
axs[0].legend(loc="upper left")
bottom = [0 for r in data_votes['timestamp']]
axs[1].vlines(data_votes['timestamp'], bottom, data_votes['count1'], colors="#22AA99", linewidth=2, label="Upvotes")
axs[1].vlines(data_votes['timestamp'], bottom, [-x for x in data_votes['count2']], colors="#DD4477", linewidth=2, label="Downvotes")
axs[1].legend(loc="upper left")
bottom = [0 for r in data_votes_in['timestamp']]
axs[2].vlines(data_votes_in['timestamp'], bottom, data_votes_in['count1'], colors="#66AA00", linewidth=2, label="Upvotes")
axs[2].vlines(data_votes_in['timestamp'], bottom, [-x for x in data_votes_in['count2']], colors="#DC3912", linewidth=2, label="Downvotes")
fig.tight_layout()
fig.savefig(f"/var/lib/piefed/app/static/tmp/user_145.svg", format="svg")
def plugin_info():
“""Plugin metadata"""
return {
“name": “Matplotlib Charts”,
“version": “0.0.1”,
“description": “An experimental plugin that generates statistics charts”,
“license": “AGPL-3.0”, # Must be AGPL-compatible
“source_url": “https://piefed.social/post/1308113”, # Required
“author": “hendrik"
}
```
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