| Name | shelchemy JSON |
| Version |
2.240219.1
JSON |
| download |
| home_page | |
| Summary | Shelve-like dict using sqlalchemy as a backend, and lazy scheduler for resuming tasks |
| upload_time | 2024-02-19 09:33:07 |
| maintainer | |
| docs_url | None |
| author | davips |
| requires_python | >=3.10,<4.0 |
| license | GPL |
| keywords |
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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No Travis.
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| coveralls test coverage |
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[](https://codecov.io/gh/shelchemy/shelchemy)
<a href="https://pypi.org/project/shelchemy">
<img src="https://img.shields.io/github/v/release/shelchemy/shelchemy?display_name=tag&sort=semver&color=blue" alt="github">
</a>
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://shelchemy.github.io/shelchemy)
[](https://pepy.tech/project/shelchemy)
# shelchemy - Dict-like (shelve-like) storage wrapper for any DBMS (SQLAlchemy)
## Python installation
### from package
```bash
# Set up a virtualenv.
python3 -m venv venv
source venv/bin/activate
# Install from PyPI
pip install shelchemy
```
### from source
```bash
git clone https://github.com/shelchemy/shelchemy
cd shelchemy
poetry install
```
### Examples
This library is more useful when used along with `hdict`.
Here are some possible usages by itself.
**Scheduling jobs.**
<details>
<p>
```python3
from time import sleep
from shelchemy.scheduler import Scheduler
# Jobs can be distributed across multiple computers/networks.
names1 = ["a", "b"]
names2 = ["c"]
names3 = ["d", "e"]
storage = {}
# `storage` can be: shelve; URI pointing to a database; or, any dict-like object.
# Example of a local database: storage="sqlite+pysqlite:////tmp/sqla-test.db"
# Example of a remote database: storage="mysql+pymysql://user1:password1@hosh.page/db1"
for name in Scheduler(storage, timeout=10) << names1 << names2 << names3:
print(f"Processing {name}")
sleep(0.1)
print(f"{name} processed!")
"""
2023-11-13 00:03:40.115637 'a' is new, starting
Processing a
a processed!
2023-11-13 00:03:40.316130 'a' done
2023-11-13 00:03:40.326101 'b' is new, starting
Processing b
b processed!
2023-11-13 00:03:40.526549 'b' done
2023-11-13 00:03:40.534599 'c' is new, starting
Processing c
c processed!
2023-11-13 00:03:40.735062 'c' done
2023-11-13 00:03:40.745734 'd' is new, starting
Processing d
d processed!
2023-11-13 00:03:40.946152 'd' done
2023-11-13 00:03:40.957263 'e' is new, starting
Processing e
e processed!
2023-11-13 00:03:41.157701 'e' done
"""
```
</p>
</details>
**Persistent dict.**
<details>
<p>
```python3
from shelchemy import sopen
from shelchemy.cache import Cache
d = Cache("sqlite+pysqlite:////tmp/sqla-test.db")
d["x"] = 5
d["b"] = None
print(d["x"], d["b"])
"""
5 None
"""
```
```python3
try:
d["xxx"]
except KeyError as m:
print(m)
"""
'xxx'
"""
```
```python3
for k, v in d.items():
print(k, v)
print("x" in d)
"""
872d417d62b78366a71ab9fee25f14dc None
aed0339093d97301965a4e23dac3424a b'only bytes when autopack=False'
a b'by'
x 5
b None
True
"""
```
```python3
del d["x"]
print("x" in d)
"""
False
"""
```
```python3
print(d)
"""
{'872d417d62b78366a71ab9fee25f14dc': None, 'aed0339093d97301965a4e23dac3424a': b'only bytes when autopack=False', 'a': b'by', 'b': None}
"""
```
```python3
# Using a context manager.
with sopen() as db:
print("x" in db)
print(db)
db["x"] = b"asd"
print(db)
print(db["x"] == b"asd")
print("x" in db)
print(db.x == b"asd")
del db["x"]
print("x" in db)
db["any string key longer than 40 characters will be hashed depending if the DBMS backend is used"] = None
print(db)
"""
False
{}
{'x': b'asd'}
True
True
True
False
{'872d417d62b78366a71ab9fee25f14dc': None}
"""
```
</p>
</details>
## Grants
This work was partially supported by Fapesp under supervision of
Prof. André C. P. L. F. de Carvalho at CEPID-CeMEAI (Grants 2013/07375-0 – 2019/01735-0).
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"description": "\n[](https://codecov.io/gh/shelchemy/shelchemy)\n<a href=\"https://pypi.org/project/shelchemy\">\n<img src=\"https://img.shields.io/github/v/release/shelchemy/shelchemy?display_name=tag&sort=semver&color=blue\" alt=\"github\">\n</a>\n\n[](https://www.gnu.org/licenses/gpl-3.0)\n\n[](https://shelchemy.github.io/shelchemy)\n[](https://pepy.tech/project/shelchemy)\n\n\n# shelchemy - Dict-like (shelve-like) storage wrapper for any DBMS (SQLAlchemy)\n \n\n\n## Python installation\n### from package\n```bash\n# Set up a virtualenv. \npython3 -m venv venv\nsource venv/bin/activate\n\n# Install from PyPI\npip install shelchemy\n```\n\n### from source\n```bash\ngit clone https://github.com/shelchemy/shelchemy\ncd shelchemy\npoetry install\n```\n\n### Examples\nThis library is more useful when used along with `hdict`.\nHere are some possible usages by itself.\n\n**Scheduling jobs.**\n<details>\n<p>\n\n```python3\nfrom time import sleep\n\nfrom shelchemy.scheduler import Scheduler\n\n# Jobs can be distributed across multiple computers/networks.\nnames1 = [\"a\", \"b\"]\nnames2 = [\"c\"]\nnames3 = [\"d\", \"e\"]\nstorage = {}\n# `storage` can be: shelve; URI pointing to a database; or, any dict-like object.\n# Example of a local database: storage=\"sqlite+pysqlite:////tmp/sqla-test.db\"\n# Example of a remote database: storage=\"mysql+pymysql://user1:password1@hosh.page/db1\"\nfor name in Scheduler(storage, timeout=10) << names1 << names2 << names3:\n print(f\"Processing {name}\")\n sleep(0.1)\n print(f\"{name} processed!\")\n\"\"\"\n2023-11-13 00:03:40.115637 'a' is new, starting\nProcessing a\na processed!\n2023-11-13 00:03:40.316130 'a' done\n2023-11-13 00:03:40.326101 'b' is new, starting\nProcessing b\nb processed!\n2023-11-13 00:03:40.526549 'b' done\n2023-11-13 00:03:40.534599 'c' is new, starting\nProcessing c\nc processed!\n2023-11-13 00:03:40.735062 'c' done\n2023-11-13 00:03:40.745734 'd' is new, starting\nProcessing d\nd processed!\n2023-11-13 00:03:40.946152 'd' done\n2023-11-13 00:03:40.957263 'e' is new, starting\nProcessing e\ne processed!\n2023-11-13 00:03:41.157701 'e' done\n\"\"\"\n```\n\n\n</p>\n</details>\n\n**Persistent dict.**\n<details>\n<p>\n\n```python3\nfrom shelchemy import sopen\nfrom shelchemy.cache import Cache\n\nd = Cache(\"sqlite+pysqlite:////tmp/sqla-test.db\")\nd[\"x\"] = 5\nd[\"b\"] = None\nprint(d[\"x\"], d[\"b\"])\n\"\"\"\n5 None\n\"\"\"\n```\n\n```python3\n\ntry:\n d[\"xxx\"]\nexcept KeyError as m:\n print(m)\n\"\"\"\n'xxx'\n\"\"\"\n```\n\n```python3\n\nfor k, v in d.items():\n print(k, v)\nprint(\"x\" in d)\n\"\"\"\n872d417d62b78366a71ab9fee25f14dc None\naed0339093d97301965a4e23dac3424a b'only bytes when autopack=False'\na b'by'\nx 5\nb None\nTrue\n\"\"\"\n```\n\n```python3\n\ndel d[\"x\"]\nprint(\"x\" in d)\n\"\"\"\nFalse\n\"\"\"\n```\n\n```python3\n\nprint(d)\n\"\"\"\n{'872d417d62b78366a71ab9fee25f14dc': None, 'aed0339093d97301965a4e23dac3424a': b'only bytes when autopack=False', 'a': b'by', 'b': None}\n\"\"\"\n```\n\n```python3\n\n# Using a context manager.\nwith sopen() as db:\n print(\"x\" in db)\n print(db)\n\n db[\"x\"] = b\"asd\"\n print(db)\n print(db[\"x\"] == b\"asd\")\n print(\"x\" in db)\n print(db.x == b\"asd\")\n\n del db[\"x\"]\n print(\"x\" in db)\n\n db[\"any string key longer than 40 characters will be hashed depending if the DBMS backend is used\"] = None\n print(db)\n\"\"\"\nFalse\n{}\n{'x': b'asd'}\nTrue\nTrue\nTrue\nFalse\n{'872d417d62b78366a71ab9fee25f14dc': None}\n\"\"\"\n```\n\n\n</p>\n</details>\n\n\n## Grants\nThis work was partially supported by Fapesp under supervision of\nProf. Andr\u00e9 C. P. L. F. de Carvalho at CEPID-CeMEAI (Grants 2013/07375-0 \u2013 2019/01735-0).\n",
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