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column-text-format-0.0.2
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| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | column-text-format-0.0.2 |
| نام | column-text-format |
| نسخه کتابخانه | 0.0.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Clark Fitzgerald, Julian Hernandez, Shawheen Naderi |
| ایمیل نویسنده | notsetupyet@gmail.com |
| آدرس صفحه اصلی | http://packages.python.org/an_example_pypi_project |
| آدرس اینترنتی | https://pypi.org/project/column-text-format/ |
| مجوز | BSD |
# Search times
- Searched 1 columns with 431644 rows in 0.26 seconds
- Searched 2 columns with 431644 rows in 0.39 seconds
- Searched 3 columns with 431644 rows in 0.51 seconds
- Searched 4 columns with 431644 rows in 0.61 seconds
- Searched 5 columns with 431644 rows in 0.69 seconds
- Searched 6 columns with 431644 rows in 0.92 seconds
- Searched 7 columns with 431644 rows in 1.04 seconds
- Searched 8 columns with 431644 rows in 1.34 seconds
- Searched 9 columns with 431644 rows in 1.66 seconds
- Searched 10 columns with 431644 rows in 1.83 seconds
- Searched 11 columns with 431644 rows in 1.96 seconds
- Searched 12 columns with 431644 rows in 2.11 seconds
- Searched 13 columns with 431644 rows in 2.29 seconds
- Searched 14 columns with 431644 rows in 2.39 seconds
- Searched 15 columns with 431644 rows in 2.47 seconds
# Conversion times
- name start size time
- ignore_country_classification.csv 4257 0.02
- ignore_goods_classification.csv 239619 0.07
- ignore_gsquarterlySeptember20.csv 73824486 20.65
- ignore_services_classification.csv 2828 0.02
- ignore_test.csv 82533516 47.74
# End User Manual
How would I like use this code?
Suppose I have a table called `people` stored in CTF.
TODO: Define and describe `people` table.
```bash
$ cat people.csv
names age
Shawheen 21
Julian 20
Clark 34
```
I want to access a column called `names` from this table.
```SQL
SELECT names FROM people
```
Assume that `people` is a directory containing the CTF data.
```python
import CTF
names = CTF.load_column("people", "names")
```
TODO: look at `load_column`, see what the most common name is for reading / loading data.
How closely can we copy `csv` from the standard library?
Use case: it would be great if we could access the data as a stream, without necessarily loading everything in memory.
We can get this feature by having `names` be an iterator or generator over the column values.
Example processing names:
```
from Collections import Counter
counts = Counter(names)
```
## Use case 2 - column types
```
age = CTF.load_column("people", "age")
```
`age` should generate integer values corresponding to each entry of the `age` column.
CTF knows that the `age` column means integer because of the metadata file in the `people` directory.
TODO: link to W3 standard.
```
# User should not write this- it's just the idea we want
def create_age():
for x in [21, 20, 34]:
yield x
age = create_age()
# User can do something like this:
>>> list(age)
[21, 20, 34]
```
## Use case 3 - compatibility with `csv`
```
import csv
# Referring to file `people.csv` in CSV format
r = csv.reader("people.csv")
# Referring to directory `people` in CTF format
r2 = CTF.reader("people")
```
`r2` should essentially be a drop in replacement for `r`.
```
for row in r:
process(row)
```
TODO: Process a csv file using Python's `csv` package- any kind of data analysis is fine.
For example, find the set of all values in one column.
# Python notes
I used this link for helping me construct the iterable.
[Python special methods](https://levelup.gitconnected.com/python-dunder-methods-ea98ceabad15)
[W3C metadata](https://www.w3.org/TR/tabular-metadata/)
# Outline
- Ctf modeled after csv and/or dictionary
- [ ] Should Ctf be accessed with a reader like csv or through itself like a dictionary
- [x] Column accessed with ["column_name"]
- [ ] Can convert a csv file to ctf
- [ ] Reader runs like csv reader returning iterable rows
- [ ] class Row to give a guide for adding new columns using values from metadata.json
- [ ] Use custom exceptions
- [ ] Get type from metadata.json or autodetect
```python
with Ctf.open() as ctf_file:
ctf_file["column"]
for row in ctf_file:
print(row)
```
```python
Ctf.open()
Ctf.close()
```
نحوه نصب
نصب پکیج whl column-text-format-0.0.2:
pip install column-text-format-0.0.2.whl
نصب پکیج tar.gz column-text-format-0.0.2:
pip install column-text-format-0.0.2.tar.gz