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id ▼ node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association pull_request body repo type active_lock_reason performed_via_github_app reactions draft state_reason
794554881 MDU6SXNzdWU3OTQ1NTQ4ODE= 1208 A lot of open(file) functions are used without a context manager thus producing ResourceWarning: unclosed file <_io.TextIOWrapper kbaikov 4488943 closed 0     2 2021-01-26T20:56:28Z 2021-03-11T16:15:49Z 2021-03-11T16:15:49Z CONTRIBUTOR   Your code is full of open files that are never closed, especially when you deal with reading/writing json/yaml files. If you run python with warnings enabled this problem becomes evident. This probably contributes to some memory leaks in long running datasettes if the GC will not 'collect' those resources properly. This is easily fixed by using a context manager instead of just using open: ```python with open('some_file', 'w') as opened_file: opened_file.write('string') ``` In some newer parts of the code you use Path objects 'read_text' and 'write_text' functions which close the file properly and are prefered in some cases. If you want I can create a PR for all places i found this pattern in. Bellow is a fraction of places where i found a ResourceWarning: ```python update-docs-help.py: 20 actual = actual.replace("Usage: cli ", "Usage: datasette ") 21: open(docs_path / filename, "w").write(actual) 22 datasette\app.py: 210 ): 211: inspect_data = json.load((config_dir / "inspect-data.json").open()) 212 if immutables is None: 266 if config_dir and (config_dir / "settings.json").exists() and not config: 267: config = json.load((config_dir / "settings.json").open()) 268 self._settings = dict(DEFAULT_SETTINGS, **(config or {})) 445 self._app_css_hash = hashlib.sha1( 446: open(os.path.join(str(app_root), "datasette/static/app.css")) 447 .read() datasette\cli.py: 130 else: 131: out = open(inspect_file, "w") 132 loop = asyncio.get_event_loop() 459 if inspect_file: 460: inspect_data = json.load(open(inspect_file)) 461 ``` datasette 107914493 issue     {"url": "https://api.github.com/repos/simonw/datasette/issues/1208/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}   completed
797649915 MDExOlB1bGxSZXF1ZXN0NTY0NjA4MjY0 1211 Use context manager instead of plain open kbaikov 4488943 closed 0     3 2021-01-31T07:58:10Z 2021-03-11T16:15:50Z 2021-03-11T16:15:50Z CONTRIBUTOR simonw/datasette/pulls/1211 Context manager with open closes the files after usage. Fixes: https://github.com/simonw/datasette/issues/1208 When the object is already a pathlib.Path i used read_text write_text functions In some cases pathlib.Path.open were used in context manager, it is basically the same as builtin open. Tests are passing: 850 passed, 5 xfailed, 10 xpassed datasette 107914493 pull     {"url": "https://api.github.com/repos/simonw/datasette/issues/1211/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0} 0  
797651831 MDU6SXNzdWU3OTc2NTE4MzE= 1212 Tests are very slow. kbaikov 4488943 closed 0     4 2021-01-31T08:06:16Z 2021-02-19T22:54:13Z 2021-02-19T22:54:13Z CONTRIBUTOR   Working on my PR i noticed that tests are very slow. The plain pytest run took about 37 minutes for me. However i could shave of about 10 minutes from that if i used pytest-xdist to parallelize execution. `pytest -n 8` is run only in 28 minutes on my machine. I can create a PR to mention that in your documentation. This will be a simple change to add pytest-xdist to requirements and change a command to run pytest in documentation. Does that make sense to you? After a bit more investigation it looks like python-xdist is not an answer. It creates a race condition for tests that try to clead temp dir before run. Profiling shows that most time is spent on conn.executescript(TABLES) in make_app_client function. Which makes sense. Perhaps the better approach would be look at the app_client fixture which is already session scoped, but not used by all test cases. And/or use conn = sqlite3.connect(":memory:") which is much faster. And/or truncate tables after each TC instead of deleting the file and re-creating them. I can take a look which is the best approach if you give the go-ahead. datasette 107914493 issue     {"url": "https://api.github.com/repos/simonw/datasette/issues/1212/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0}   completed

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   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [pull_request] TEXT,
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   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
, [active_lock_reason] TEXT, [performed_via_github_app] TEXT, [reactions] TEXT, [draft] INTEGER, [state_reason] TEXT);
CREATE INDEX [idx_issues_repo]
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CREATE INDEX [idx_issues_milestone]
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CREATE INDEX [idx_issues_assignee]
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CREATE INDEX [idx_issues_user]
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