diff --git a/.github/workflows/python-publish-develop.yml b/.github/workflows/python-publish-develop.yml index 274ee0e..e5566d1 100644 --- a/.github/workflows/python-publish-develop.yml +++ b/.github/workflows/python-publish-develop.yml @@ -79,12 +79,6 @@ jobs: with: python-version: ${{ matrix.python-version }} - - name: Install Firefox - run: | - sudo apt -y update - sudo apt -y install firefox - sudo apt -y --only-upgrade install firefox - - name: Install dependencies run: | python -m pip install --upgrade pip @@ -128,13 +122,32 @@ jobs: replace-with: 'py$1$2' flags: 'g' + - name: Version PreReleaseLabel alpha replaced by a letter + uses: frabert/replace-string-action@master + id: alpha_PreReleaseLabel + with: + pattern: 'alpha' + string: '${{ steps.gitversion.outputs.preReleaseLabel }}' + replace-with: 'a' + flags: 'g' + + - name: Version PreReleaseLabel beta replaced by b letter + uses: frabert/replace-string-action@master + id: PreReleaseLabel + with: + pattern: 'beta' + string: '${{ steps.alpha_PreReleaseLabel.outputs.replaced }}' + replace-with: 'b' + flags: 'g' + - name: Build and publish env: - TWINE_USERNAME: ${{ secrets.TEST_PYPI_USERNAME }} - TWINE_PASSWORD: ${{ secrets.TEST_PYPI_PASSWORD }} + TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }} + TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }} run: | - python updateVersion.py --nextVersion ${{ steps.gitversion.outputs.majorMinorPatch }}.dev${{ steps.gitversion.outputs.buildMetaData }} + python updateVersion.py --nextVersion ${{ steps.gitversion.outputs.majorMinorPatch }}${{ steps.PreReleaseLabel.outputs.replaced }}${{ steps.gitversion.outputs.preReleaseNumber }} python setup.py sdist bdist_wheel --python-tag ${{ steps.python-tag.outputs.replaced }} - twine upload --skip-existing --repository testpypi dist/* - if: ${{ matrix.python-version == 3.10 && github.repository == 'ssenart/PyGazpar' }} + # twine upload --skip-existing --repository testpypi dist/* + twine upload --skip-existing dist/* + if: ${{ github.repository == 'ssenart/PyGazpar' }} diff --git a/.github/workflows/python-publish-release.yml b/.github/workflows/python-publish-release.yml index 2f329e4..639f884 100644 --- a/.github/workflows/python-publish-release.yml +++ b/.github/workflows/python-publish-release.yml @@ -31,12 +31,6 @@ jobs: with: python-version: ${{ matrix.python-version }} - - name: Install Firefox - run: | - sudo apt -y update - sudo apt -y install firefox - sudo apt -y --only-upgrade install firefox - - name: Install dependencies run: | python -m pip install --upgrade pip @@ -88,4 +82,4 @@ jobs: python updateVersion.py --nextVersion ${{ github.event.release.tag_name }} python setup.py sdist bdist_wheel --python-tag ${{ steps.python-tag.outputs.replaced }} twine upload --skip-existing dist/* - if: github.repository == 'ssenart/PyGazpar' + if: ${{ github.repository == 'ssenart/PyGazpar' }} diff --git a/CHANGELOG.md b/CHANGELOG.md index 20f5182..61ad2fa 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,6 +4,18 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## [1.2.0](https://github.com/ssenart/PyGazpar/compare/1.1.6...1.2.0) - 2022-12-16 + +### Changed +- [#59](https://github.com/ssenart/PyGazpar/issues/59): [Feature] Support both Excel and Json data source format from GrDF site. + +- [#60](https://github.com/ssenart/PyGazpar/issues/60): [Feature] Permit to load data at multiple frequencies with one method call. + +### Fixed +- [#47](https://github.com/ssenart/PyGazpar/issues/47): [Bug] No temperature field available. + +- [#58](https://github.com/ssenart/PyGazpar/issues/58): [Issue] No data update - GrDF web site is half broken - Download button does not work anymore. + ## [1.1.6](https://github.com/ssenart/PyGazpar/compare/1.1.5...1.1.6) - 2022-11-16 ### Fixed - [#55](https://github.com/ssenart/PyGazpar/issues/55): Problème de connexion. diff --git a/MANIFEST.in b/MANIFEST.in index 0e66932..0801fc6 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -2,3 +2,4 @@ include pygazpar/resources/hourly_data_sample.json include pygazpar/resources/daily_data_sample.json include pygazpar/resources/weekly_data_sample.json include pygazpar/resources/monthly_data_sample.json +include pygazpar/resources/yearly_data_sample.json diff --git a/README.md b/README.md index 8d754b2..d7432ca 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ Their natural gas meter is called Gazpar. It is wireless and transmit the gas co All consumption data is available on the client account at GrDF Web Site (https://monespace.grdf.fr). -PyGazpar automatically goes through the Web Site and download the consumption data Excel file, and make it available in a Python structure (list of dictionaries). +PyGazpar automatically goes through the Web Site and download the consumption data, and make it available in a Python structure. ## Installation @@ -18,7 +18,7 @@ With the new GrDF web site, it is possible to load the consumption data far easi ```bash $ cd /path/to/my_project_folder/ -$ python3 -m venv .venv +$ python -m venv .venv ``` ### PyGazpar installation @@ -42,195 +42,120 @@ python setup.py install #### Command line: -```bash -$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' -t 'temporary directory where to store XSLX file (ex: /tmp)' -``` - -#### Library: - -```python -import pygazpar - -client = pygazpar.Client(username='your login', - password='your password', - pceIdentifier='your PCE identifier', - meterReadingFrequency=pygazpar.Frequency.DAILY, - lastNDays=10, - tmpDirectory='/tmp/pygazpar') - -client.update() +1. Standard usage (using Json GrDF API). -data = client.data() +```bash +$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' --datasource 'json' ``` -#### Output: +2. Alternate usage (using Excel GrDF document). -```json -data => -[ - { - "time_period": "16/04/2021", - "start_index_m3": 13685.0, - "end_index_m3": 13695.0, - "volume_m3": 9.9, - "energy_kwh": 111.0, - "converter_factor_kwh/m3": 11.268, - "temperature_degC": 8.0, - "type": "MES", - "timestamp": "2021-04-20T10:21:46.265119" - }, - { - "time_period": "17/04/2021", - "start_index_m3": 13695.0, - "end_index_m3": 13702.0, - "volume_m3": 7.7, - "energy_kwh": 86.0, - "converter_factor_kwh/m3": 11.268, - "temperature_degC": 9.0, - "type": "MES", - "timestamp": "2021-04-20T10:21:46.265119" - }, - { - "time_period": "18/04/2021", - "start_index_m3": 13702.0, - "end_index_m3": 13708.0, - "volume_m3": 6.2, - "energy_kwh": 69.0, - "converter_factor_kwh/m3": 11.268, - "temperature_degC": 10.0, - "type": "MES", - "timestamp": "2021-04-20T10:21:46.265119" - } -] +```bash +$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' -t 'temporary directory where to store Excel file (ex: /tmp)' --datasource 'excel' ``` -## More features -By default, PyGazpar queries for daily consumption data. - -However, it is also possible to get weekly or monthly consumption data : +3. Test usage (using local static data files, do not connect to GrDF site). -### Weekly - -#### Command line: ```bash -$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' -t 'temporary directory where to store XSLX file (ex: /tmp)' -f WEEKLY +$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' --datasource 'test' ``` #### Library: + +1. Standard usage (using Json GrDF API). + ```python import pygazpar -client = pygazpar.Client(username='your login', - password='your password', - pceIdentifier='your PCE identifier', - meterReadingFrequency=pygazpar.Frequency.WEEKLY, - lastNDays=10, - tmpDirectory='/tmp/pygazpar') - -client.update() +client = pygazpar.Client(pygazpar.JsonWebDataSource( + username='your login', + password='your password') +) -data = client.data() +data = client.loadSince(pceIdentifier='your PCE identifier', + lastNDays=60, + frequencies=[pygazpar.Frequency.DAILY, pygazpar.Frequency.MONTHLY]) ``` +See [samples/jsonSample.py](samples/jsonSample.py) file for the full example. -#### Output: +2. Alternate usage (using Excel GrDF document). -```json -data => -[ - { - "time_period": "Du 29/03/2021 au 04/04/2021", - "volume_m3": 21.4, - "energy_kwh": 240.0, - "timestamp": "2021-04-20T09:22:12.166500" - }, - { - "time_period": "Du 05/04/2021 au 11/04/2021", - "volume_m3": 58.9, - "energy_kwh": 663.0, - "timestamp": "2021-04-20T09:22:12.166500" - }, - { - "time_period": "Du 12/04/2021 au 18/04/2021", - "volume_m3": 57.1, - "energy_kwh": 643.0, - "timestamp": "2021-04-20T09:22:12.166500" - } -] -``` +```python +import pygazpar -### Monthly +client = pygazpar.Client(pygazpar.ExcelWebDataSource( + username='your login', + password='your password') +) -#### Command line: -```bash -$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' -t 'temporary directory where to store XSLX file (ex: /tmp)' -f MONTHLY +data = client.loadSince(pceIdentifier='your PCE identifier', + lastNDays=60, + frequencies=[pygazpar.Frequency.DAILY, pygazpar.Frequency.MONTHLY]) ``` +See [samples/excelSample.py](samples/jsonSample.py) file for the full example. + +3. Test usage (using local static data files, do not connect to GrDF site). -#### Library: ```python import pygazpar -client = pygazpar.Client(username='your login', - password='your password', - pceIdentifier='your PCE identifier', - meterReadingFrequency=pygazpar.Frequency.MONTHLY, - lastNDays=10, - tmpDirectory='/tmp/pygazpar') - -client.update() +client = pygazpar.Client(pygazpar.TestDataSource()) -data = client.data() +data = client.loadSince(pceIdentifier='your PCE identifier', + lastNDays=10, + frequencies=[pygazpar.Frequency.DAILY, Frequency.MONTHLY]) ``` +See [samples/testSample.py](samples/jsonSample.py) file for the full example. #### Output: ```json data => -[ - { - "time_period": "F\u00e9vrier 2021", - "volume_m3": 317.6, - "energy_kwh": 3547.0, - "timestamp": "2021-04-20T09:34:31.728125" - }, - { - "time_period": "Mars 2021", - "volume_m3": 261.1, - "energy_kwh": 2937.0, - "timestamp": "2021-04-20T09:34:31.728125" - }, - { - "time_period": "Avril 2021", - "volume_m3": 130.7, - "energy_kwh": 1472.0, - "timestamp": "2021-04-20T09:34:31.728125" - } -] -``` - -### Test mode - -In testing environment (unit test or debugging), it may be cumbersome to work with live data: slowness, values are always changing. - -There is a test mode that permits to work with static data. Those data are taken from internal resource files. - -#### Command line: -```bash -$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' -t 'temporary directory where to store XSLX file (ex: /tmp)' --testMode -``` - -#### Library: -```python -import pygazpar - -client = pygazpar.Client(username='your login', - password='your password', - pceIdentifier='your PCE identifier', - tmpDirectory='/tmp/pygazpar', - testMode = True) - -client.update() - -data = client.data() +{ + "daily": [ + { + "time_period": "13/10/2022", + "start_index_m3": 15724, + "end_index_m3": 15725, + "volume_m3": 2, + "energy_kwh": 17, + "converter_factor_kwh/m3": 11.16, + "temperature_degC": null, + "type": "Mesur\u00e9", + "timestamp": "2022-12-13T23:58:35.606763" + }, + ... + { + "time_period": "11/12/2022", + "start_index_m3": 16081, + "end_index_m3": 16098, + "volume_m3": 18, + "energy_kwh": 201, + "converter_factor_kwh/m3": 11.27, + "temperature_degC": -1.47, + "type": "Mesur\u00e9", + "timestamp": "2022-12-13T23:58:35.606763" + } + ], + "monthly": [ + { + "time_period": "Novembre 2022", + "start_index_m3": 15750, + "end_index_m3": 15950, + "volume_m3": 204, + "energy_kwh": 2227, + "timestamp": "2022-12-13T23:58:35.606763" + }, + { + "time_period": "D\u00e9cembre 2022", + "start_index_m3": 15950, + "end_index_m3": 16098, + "volume_m3": 148, + "energy_kwh": 1664, + "timestamp": "2022-12-13T23:58:35.606763" + } + ] +} ``` ## Limitation diff --git a/pygazpar/__init__.py b/pygazpar/__init__.py index 6bf0d9d..b98ada6 100644 --- a/pygazpar/__init__.py +++ b/pygazpar/__init__.py @@ -1,3 +1,4 @@ from pygazpar.enum import PropertyName, Frequency # noqa: F401 from pygazpar.client import Client # noqa: F401 +from pygazpar.datasource import JsonWebDataSource, ExcelFileDataSource, JsonFileDataSource, ExcelWebDataSource, TestDataSource # noqa: F401 from pygazpar.version import __version__ # noqa: F401 diff --git a/pygazpar/__main__.py b/pygazpar/__main__.py index df69af8..36e83d7 100644 --- a/pygazpar/__main__.py +++ b/pygazpar/__main__.py @@ -30,17 +30,16 @@ def main(): required=False, type=lambda frequency: pygazpar.Frequency[frequency], choices=list(pygazpar.Frequency), default="DAILY", - help="Meter reading frequency (DAILY, WEEKLY, MONTHLY)") + help="Meter reading frequency (DAILY, WEEKLY, MONTHLY, YEARLY)") parser.add_argument("-d", "--lastNDays", required=False, type=int, default=365, help="Get only the last N days of records (default: 365 days)") - parser.add_argument("--testMode", + parser.add_argument("--datasource", required=False, - action='store_true', - default=False, - help="Run PyGazpar in test mode (Get static sample data)") + default="json", + help="Datasource: json | excel | test") args = parser.parse_args() @@ -53,11 +52,6 @@ def main(): if os.path.isfile(pygazparLogFile): os.remove(pygazparLogFile) - # We remove the geckodriver log file - geckodriverLogFile = f"{args.tmpdir}/pygazpar_geckodriver.log" - if os.path.isfile(geckodriverLogFile): - os.remove(geckodriverLogFile) - # Setup logging. logging.basicConfig(filename=f"{pygazparLogFile}", level=logging.DEBUG, format="%(asctime)s %(levelname)s [%(name)s] %(message)s") @@ -65,17 +59,24 @@ def main(): logging.info(f"--tmpdir {args.tmpdir}") logging.info(f"--frequency {args.frequency}") logging.info(f"--lastNDays {args.lastNDays}") - logging.info(f"--testMode {bool(args.testMode)}") + logging.info(f"--datasource {bool(args.datasource)}") - client = pygazpar.Client(args.username, args.password, args.pce, args.frequency, int(args.lastNDays), args.tmpdir, bool(args.testMode)) + if args.datasource == "json": + client = pygazpar.Client(pygazpar.JsonWebDataSource(args.username, args.password)) + elif args.datasource == "excel": + client = pygazpar.Client(pygazpar.ExcelWebDataSource(args.username, args.password, args.tmpdir)) + elif args.datasource == "test": + client = pygazpar.Client(pygazpar.TestDataSource()) + else: + raise Exception("Invalid datasource: (json | excel | test) is expected") try: - client.update() + data = client.loadSince(args.pce, int(args.lastNDays), [args.frequency]) except BaseException: print('An error occured while querying PyGazpar library : %s', traceback.format_exc()) return 1 - print(json.dumps(client.data(), indent=2)) + print(json.dumps(data, indent=2)) if __name__ == '__main__': diff --git a/pygazpar/client.py b/pygazpar/client.py index 304bc71..b29d45b 100644 --- a/pygazpar/client.py +++ b/pygazpar/client.py @@ -1,12 +1,8 @@ -import os -import glob import logging -import json -import datetime -import requests +from datetime import date, timedelta from pygazpar.enum import Frequency -from pygazpar.datafileparser import DataFileParser -from typing import Any, cast, List, Dict +from pygazpar.datasource import IDataSource, MeterReadingsByFrequency +from typing import List, Optional AUTH_NONCE_URL = "https://monespace.grdf.fr/client/particulier/accueil" LOGIN_URL = "https://login.monespace.grdf.fr/sofit-account-api/api/v1/auth" @@ -20,7 +16,6 @@ DATA_FILENAME = 'Donnees_informatives_*.xlsx' DEFAULT_TMP_DIRECTORY = '/tmp' -DEFAULT_METER_READING_FREQUENCY = Frequency.DAILY DEFAULT_LAST_N_DAYS = 365 @@ -31,141 +26,34 @@ class Client: # ------------------------------------------------------ - def __init__(self, username: str, password: str, pceIdentifier: str, meterReadingFrequency: Frequency = DEFAULT_METER_READING_FREQUENCY, lastNDays: int = DEFAULT_LAST_N_DAYS, tmpDirectory: str = DEFAULT_TMP_DIRECTORY, testMode: bool = False): - self.__username = username - self.__password = password - self.__pceIdentifier = pceIdentifier - self.__tmpDirectory = tmpDirectory - self.__meterReadingFrequency = meterReadingFrequency - self.__lastNDays = lastNDays - self.__testMode = testMode - self.__data = [] + def __init__(self, dataSource: IDataSource): + self.__dataSource = dataSource # ------------------------------------------------------ - def data(self) -> List[Dict[str, Any]]: - return self.__data - - # ------------------------------------------------------ - def update(self): - - if self.__testMode: - self.__updateTestMode() - else: - self.__updateLiveMode() - - # ------------------------------------------------------ - def __updateTestMode(self): - - dataSampleFilenameByFrequency = { - Frequency.HOURLY: "hourly_data_sample.json", - Frequency.DAILY: "daily_data_sample.json", - Frequency.WEEKLY: "weekly_data_sample.json", - Frequency.MONTHLY: "monthly_data_sample.json" - } + def loadSince(self, pceIdentifier: str, lastNDays: int = DEFAULT_LAST_N_DAYS, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: try: - dataSampleFilename = f"{os.path.dirname(os.path.abspath(__file__))}/resources/{dataSampleFilenameByFrequency[self.__meterReadingFrequency]}" + endDate = date.today() + startDate = endDate + timedelta(days=-lastNDays) - with open(dataSampleFilename) as jsonFile: - data = cast(List[Dict[str, Any]], json.load(jsonFile)) - self.__data = data + res = self.loadDateRange(pceIdentifier, startDate, endDate, frequencies) except Exception: - Logger.error("An unexpected error occured while loading sample data", exc_info=True) + Logger.error("An unexpected error occured while loading the data", exc_info=True) raise - # ------------------------------------------------------ - def __updateLiveMode(self): - - Logger.debug("Start updating the data...") + return res - # XLSX is in the TMP directory - data_file_path_pattern = self.__tmpDirectory + '/' + DATA_FILENAME + # ------------------------------------------------------ + def loadDateRange(self, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: - # We remove an eventual existing data file (from a previous run that has not deleted it). - file_list = glob.glob(data_file_path_pattern) - for filename in file_list: - if os.path.isfile(filename): - os.remove(filename) + Logger.debug("Start loading the data...") try: + res = self.__dataSource.load(pceIdentifier, startDate, endDate, frequencies) - session = requests.Session() - - session.headers.update(LOGIN_HEADER) - - self.__login(session) - - # Build URL to get the data from. - frequencies = { - Frequency.HOURLY: "Horaire", - Frequency.DAILY: "Journalier", - Frequency.WEEKLY: "Hebdomadaire", - Frequency.MONTHLY: "Mensuel" - } - dateFormat = "%Y-%m-%d" - endDate = datetime.date.today() - startDate = endDate + datetime.timedelta(days=-self.__lastNDays) - - downloadUrl = DATA_URL.format(frequencies[self.__meterReadingFrequency], startDate.strftime(dateFormat), endDate.strftime(dateFormat), self.__pceIdentifier) - - session.get(downloadUrl) # First request does not return anything : strange... - - Logger.debug(f"Loading data of frequency {frequencies[self.__meterReadingFrequency]} from {startDate.strftime(dateFormat)} to {endDate.strftime(dateFormat)}") - self.__downloadFile(session, downloadUrl, self.__tmpDirectory) - - # Load the XLSX file into the data structure - file_list = glob.glob(data_file_path_pattern) - - if len(file_list) == 0: - Logger.warning(f"Not any data file has been found in '{self.__tmpDirectory}' directory") - - for filename in file_list: - - self.__data = DataFileParser.parse(filename, self.__meterReadingFrequency) - - os.remove(filename) - - Logger.debug("The data update terminates normally") + Logger.debug("The data load terminates normally") except Exception: - Logger.error("An unexpected error occured while updating the data", exc_info=True) + Logger.error("An unexpected error occured while loading the data", exc_info=True) raise - # ------------------------------------------------------ - def __login(self, session: requests.Session): - - # Get auth_nonce token. - session.get(AUTH_NONCE_URL) - if "auth_nonce" not in session.cookies: - raise Exception("Login error: Cannot get auth_nonce token") - auth_nonce = session.cookies.get("auth_nonce") - - # Build the login payload as a json string. - payload = LOGIN_PAYLOAD.format(self.__username, self.__password, auth_nonce) - - # Build the login payload as a python object. - data = json.loads(payload) - - # Send the login command. - response = session.post(LOGIN_URL, data=data) - - # Check login result. - loginData = response.json() - - response.raise_for_status() - - if "status" in loginData and "error" in loginData and loginData["status"] >= 400: - raise Exception(f"{loginData['error']} ({loginData['status']})") - - if "state" in loginData and loginData["state"] != "SUCCESS": - raise Exception(loginData["error"]) - - # ------------------------------------------------------ - def __downloadFile(self, session: requests.Session, url: str, path: str): - - response = session.get(url) - - response.raise_for_status() - - filename = response.headers["Content-Disposition"].split("filename=")[1] - - open(f"{path}/{filename}", "wb").write(response.content) + return res diff --git a/pygazpar/clientV2.py b/pygazpar/clientV2.py deleted file mode 100644 index a931329..0000000 --- a/pygazpar/clientV2.py +++ /dev/null @@ -1,101 +0,0 @@ -import logging -import requests -import datetime -import json -from typing import Dict - -DEFAULT_LAST_N_DAYS = 365 - - -Logger = logging.getLogger(__name__) - - -# ------------------------------------------------------------------------------------------------------------ -class ClientV2: - - # ------------------------------------------------------ - def __init__(self, username: str, password: str, pceIdentifier: str, lastNDays: int = DEFAULT_LAST_N_DAYS, testMode: bool = False): - self.__username = username - self.__password = password - self.__pceIdentifier = pceIdentifier - self.__lastNDays = lastNDays - self.__testMode = testMode - self.__data = {} - - # ------------------------------------------------------ - def data(self) -> Dict: - return self.__data - - # ------------------------------------------------------ - def update(self): - - if self.__testMode: - self.__updateTestMode() - else: - self.__updateLiveMode() - - # ------------------------------------------------------ - def __updateTestMode(self): - pass - - # ------------------------------------------------------ - def __updateLiveMode(self): - - try: - Logger.debug("Start updating the data...") - - session = requests.Session() - - session.headers.update( - { - "User-Agent": "Mozilla/5.0" - " (Linux; Android 6.0; Nexus 5 Build/MRA58N)" - " AppleWebKit/537.36 (KHTML, like Gecko)" - " Chrome/61.0.3163.100 Mobile Safari/537.36", - "Accept-Encoding": "gzip, deflate, br", - "Accept": "application/json, */*", - "Connection": "keep-alive", - "domain": "grdf.fr", - } - ) - - # Get auth_nonce cookie. - _ = session.get("https://monespace.grdf.fr/client/particulier/accueil") - if "auth_nonce" not in session.cookies: - raise Exception("Cannot get auth_nonce.") - auth_nonce = session.cookies.get("auth_nonce") - - # Login - loginResponse = session.post('https://login.monespace.grdf.fr/sofit-account-api/api/v1/auth', data={ - 'email': self.__username, - 'password': self.__password, - 'capp': 'meg', - 'goto': f"https://sofa-connexion.grdf.fr:443/openam/oauth2/externeGrdf/authorize?response_type=code&scope=openid%20profile%20email%20infotravaux%20%2Fv1%2Faccreditation%20%2Fv1%2Faccreditations%20%2Fdigiconso%2Fv1%20%2Fdigiconso%2Fv1%2Fconsommations%20new_meg&client_id=prod_espaceclient&state=0&redirect_uri=https%3A%2F%2Fmonespace.grdf.fr%2F_codexch&nonce={auth_nonce}&by_pass_okta=1&capp=meg" - }) - - # Check login result. - loginData = json.loads(loginResponse.text) - - if "status" in loginData and "error" in loginData and loginData["status"] >= 400: - raise Exception(f"{loginData['error']} ({loginData['status']})") - - if "state" in loginData and loginData["state"] != "SUCCESS": - raise Exception(loginData["error"]) - - # Build URL to get the data from. - dateFormat = "%Y-%m-%d" - endDate = datetime.date.today() - startDate = endDate + datetime.timedelta(days=-self.__lastNDays) - - url = f"https://monespace.grdf.fr/api/e-conso/pce/consommation/informatives?dateDebut={startDate.strftime(dateFormat)}&dateFin={endDate.strftime(dateFormat)}&pceList%5B%5D={self.__pceIdentifier}" - - # First request never returns data. - session.get(url) - - # Get data - response = session.get(url).json() - self.__data = response[self.__pceIdentifier]['releves'] - - Logger.debug("The data update terminates normally") - except Exception: - Logger.error("An unexpected error occured while updating the data", exc_info=True) diff --git a/pygazpar/datasource.py b/pygazpar/datasource.py new file mode 100644 index 0000000..28f0022 --- /dev/null +++ b/pygazpar/datasource.py @@ -0,0 +1,466 @@ +import logging +import glob +import os +import json +import pandas as pd +from abc import ABC, abstractmethod +from typing import Any, List, Dict, cast, Optional +from requests import Session +from datetime import date, timedelta +from pygazpar.enum import Frequency, PropertyName +from pygazpar.excelparser import ExcelParser +from pygazpar.jsonparser import JsonParser + +AUTH_NONCE_URL = "https://monespace.grdf.fr/client/particulier/accueil" +LOGIN_URL = "https://login.monespace.grdf.fr/sofit-account-api/api/v1/auth" +LOGIN_HEADER = {"domain": "grdf.fr"} +LOGIN_PAYLOAD = """{{ + "email": "{0}", + "password": "{1}", + "capp": "meg", + "goto": "https://sofa-connexion.grdf.fr:443/openam/oauth2/externeGrdf/authorize?response_type=code&scope=openid%20profile%20email%20infotravaux%20%2Fv1%2Faccreditation%20%2Fv1%2Faccreditations%20%2Fdigiconso%2Fv1%20%2Fdigiconso%2Fv1%2Fconsommations%20new_meg&client_id=prod_espaceclient&state=0&redirect_uri=https%3A%2F%2Fmonespace.grdf.fr%2F_codexch&nonce={2}&by_pass_okta=1&capp=meg"}}""" + + +Logger = logging.getLogger(__name__) + +MeterReading = Dict[str, Any] + +MeterReadings = List[MeterReading] + +MeterReadingsByFrequency = Dict[str, MeterReadings] + + +# ------------------------------------------------------------------------------------------------------------ +class IDataSource(ABC): + + @abstractmethod + def load(self, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + pass + + +# ------------------------------------------------------------------------------------------------------------ +class WebDataSource(IDataSource): + + # ------------------------------------------------------ + def __init__(self, username: str, password: str): + + self.__username = username + self.__password = password + + # ------------------------------------------------------ + def load(self, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + + session = Session() + + session.headers.update(LOGIN_HEADER) + + self._login(session, self.__username, self.__password) + + res = self._loadFromSession(session, pceIdentifier, startDate, endDate, frequencies) + + Logger.debug("The data update terminates normally") + + return res + + # ------------------------------------------------------ + def _login(self, session: Session, username: str, password: str): + + # Get auth_nonce token. + session.get(AUTH_NONCE_URL) + if "auth_nonce" not in session.cookies: + raise Exception("Login error: Cannot get auth_nonce token") + auth_nonce = session.cookies.get("auth_nonce") + + # Build the login payload as a json string. + payload = LOGIN_PAYLOAD.format(username, password, auth_nonce) + + # Build the login payload as a python object. + data = json.loads(payload) + + # Send the login command. + response = session.post(LOGIN_URL, data=data) + + # Check login result. + loginData = response.json() + + response.raise_for_status() + + if "status" in loginData and "error" in loginData and loginData["status"] >= 400: + raise Exception(f"{loginData['error']} ({loginData['status']})") + + if "state" in loginData and loginData["state"] != "SUCCESS": + raise Exception(loginData["error"]) + + @abstractmethod + def _loadFromSession(self, session: Session, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + pass + + +# ------------------------------------------------------------------------------------------------------------ +class ExcelWebDataSource(WebDataSource): + + DATA_URL = "https://monespace.grdf.fr/api/e-conso/pce/consommation/informatives/telecharger?dateDebut={0}&dateFin={1}&frequence={3}&pceList%5B%5D={2}" + + DATE_FORMAT = "%Y-%m-%d" + + FREQUENCY_VALUES = { + Frequency.HOURLY: "Horaire", + Frequency.DAILY: "Journalier", + Frequency.WEEKLY: "Hebdomadaire", + Frequency.MONTHLY: "Mensuel", + Frequency.YEARLY: "Journalier" + } + + DATA_FILENAME = 'Donnees_informatives_*.xlsx' + + # ------------------------------------------------------ + def __init__(self, username: str, password: str, tmpDirectory: str): + + super().__init__(username, password) + + self.__tmpDirectory = tmpDirectory + + # ------------------------------------------------------ + def _loadFromSession(self, session: Session, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + + res = {} + + # XLSX is in the TMP directory + data_file_path_pattern = self.__tmpDirectory + '/' + ExcelWebDataSource.DATA_FILENAME + + # We remove an eventual existing data file (from a previous run that has not deleted it). + file_list = glob.glob(data_file_path_pattern) + for filename in file_list: + if os.path.isfile(filename): + os.remove(filename) + + if frequencies is None: + # Transform Enum in List. + frequencyList = [frequency for frequency in Frequency] + else: + # Get unique values. + frequencyList = set(frequencies) + + for frequency in frequencyList: + # Inject parameters. + downloadUrl = ExcelWebDataSource.DATA_URL.format(startDate.strftime(ExcelWebDataSource.DATE_FORMAT), endDate.strftime(ExcelWebDataSource.DATE_FORMAT), pceIdentifier, ExcelWebDataSource.FREQUENCY_VALUES[frequency]) + + session.get(downloadUrl) # First request does not return anything : strange... + + Logger.debug(f"Loading data of frequency {ExcelWebDataSource.FREQUENCY_VALUES[frequency]} from {startDate.strftime(ExcelWebDataSource.DATE_FORMAT)} to {endDate.strftime(ExcelWebDataSource.DATE_FORMAT)}") + + self.__downloadFile(session, downloadUrl, self.__tmpDirectory) + + # Load the XLSX file into the data structure + file_list = glob.glob(data_file_path_pattern) + + if len(file_list) == 0: + Logger.warning(f"Not any data file has been found in '{self.__tmpDirectory}' directory") + + for filename in file_list: + res[frequency.value] = ExcelParser.parse(filename, frequency if frequency != Frequency.YEARLY else Frequency.DAILY) + os.remove(filename) + + # We compute yearly from daily data. + if frequency == Frequency.YEARLY: + res[frequency.value] = FrequencyConverter.computeYearly(res[frequency.value]) + + return res + + # ------------------------------------------------------ + def __downloadFile(self, session: Session, url: str, path: str): + + response = session.get(url) + + response.raise_for_status() + + filename = response.headers["Content-Disposition"].split("filename=")[1] + + open(f"{path}/{filename}", "wb").write(response.content) + + +# ------------------------------------------------------------------------------------------------------------ +class ExcelFileDataSource(IDataSource): + + def __init__(self, excelFile: str): + + self.__excelFile = excelFile + + def load(self, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + + res = {} + + if frequencies is None: + # Transform Enum in List. + frequencyList = [frequency for frequency in Frequency] + else: + # Get unique values. + frequencyList = set(frequencies) + + for frequency in frequencyList: + if frequency != Frequency.YEARLY: + res[frequency.value] = ExcelParser.parse(self.__excelFile, frequency) + else: + daily = ExcelParser.parse(self.__excelFile, Frequency.DAILY) + res[frequency.value] = FrequencyConverter.computeYearly(daily) + + return res + + +# ------------------------------------------------------------------------------------------------------------ +class JsonWebDataSource(WebDataSource): + + DATA_URL = "https://monespace.grdf.fr/api/e-conso/pce/consommation/informatives?dateDebut={0}&dateFin={1}&pceList%5B%5D={2}" + + TEMPERATURES_URL = "https://monespace.grdf.fr/api/e-conso/pce/{0}/meteo?dateFinPeriode={1}&nbJours={2}" + + INPUT_DATE_FORMAT = "%Y-%m-%d" + + OUTPUT_DATE_FORMAT = "%d/%m/%Y" + + def __init__(self, username: str, password: str): + + super().__init__(username, password) + + def _loadFromSession(self, session: Session, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + + res = {} + + computeByFrequency = { + Frequency.HOURLY: FrequencyConverter.computeHourly, + Frequency.DAILY: FrequencyConverter.computeDaily, + Frequency.WEEKLY: FrequencyConverter.computeWeekly, + Frequency.MONTHLY: FrequencyConverter.computeMonthly, + Frequency.YEARLY: FrequencyConverter.computeYearly + } + + # Data URL: Inject parameters. + downloadUrl = JsonWebDataSource.DATA_URL.format(startDate.strftime(JsonWebDataSource.INPUT_DATE_FORMAT), endDate.strftime(JsonWebDataSource.INPUT_DATE_FORMAT), pceIdentifier) + + # First request never returns data. + session.get(downloadUrl) + + # Get consumption data. + data = session.get(downloadUrl).text + + # Temperatures URL: Inject parameters. + endDate = date.today() - timedelta(days=1) if endDate >= date.today() else endDate + days = min((endDate - startDate).days, 730) + temperaturesUrl = JsonWebDataSource.TEMPERATURES_URL.format(pceIdentifier, endDate.strftime(JsonWebDataSource.INPUT_DATE_FORMAT), days) + + # Get weather data. + temperatures = session.get(temperaturesUrl).text + + # Transform all the data into the target structure. + daily = JsonParser.parse(data, temperatures, pceIdentifier) + + if frequencies is None: + # Transform Enum in List. + frequencyList = [frequency for frequency in Frequency] + else: + # Get unique values. + frequencyList = set(frequencies) + + for frequency in frequencyList: + res[frequency.value] = computeByFrequency[frequency](daily) + + return res + + +# ------------------------------------------------------------------------------------------------------------ +class JsonFileDataSource(IDataSource): + + def __init__(self, consumptionJsonFile: str, temperatureJsonFile): + + self.__consumptionJsonFile = consumptionJsonFile + self.__temperatureJsonFile = temperatureJsonFile + + def load(self, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + + res = {} + + with open(self.__consumptionJsonFile) as consumptionJsonFile: + with open(self.__temperatureJsonFile) as temperatureJsonFile: + daily = JsonParser.parse(consumptionJsonFile.read(), temperatureJsonFile.read(), pceIdentifier) + + computeByFrequency = { + Frequency.HOURLY: FrequencyConverter.computeHourly, + Frequency.DAILY: FrequencyConverter.computeDaily, + Frequency.WEEKLY: FrequencyConverter.computeWeekly, + Frequency.MONTHLY: FrequencyConverter.computeMonthly, + Frequency.YEARLY: FrequencyConverter.computeYearly + } + + if frequencies is None: + # Transform Enum in List. + frequencyList = [frequency for frequency in Frequency] + else: + # Get unique values. + frequencyList = set(frequencies) + + for frequency in frequencyList: + res[frequency.value] = computeByFrequency[frequency](daily) + + return res + + +# ------------------------------------------------------------------------------------------------------------ +class TestDataSource(IDataSource): + + def __init__(self): + + pass + + def load(self, pceIdentifier: str, startDate: date, endDate: date, frequencies: Optional[List[Frequency]] = None) -> MeterReadingsByFrequency: + + res = {} + + dataSampleFilenameByFrequency = { + Frequency.HOURLY: "hourly_data_sample.json", + Frequency.DAILY: "daily_data_sample.json", + Frequency.WEEKLY: "weekly_data_sample.json", + Frequency.MONTHLY: "monthly_data_sample.json", + Frequency.YEARLY: "yearly_data_sample.json" + } + + if frequencies is None: + # Transform Enum in List. + frequencyList = [frequency for frequency in Frequency] + else: + # Get unique values. + frequencyList = set(frequencies) + + for frequency in frequencyList: + dataSampleFilename = f"{os.path.dirname(os.path.abspath(__file__))}/resources/{dataSampleFilenameByFrequency[frequency]}" + + with open(dataSampleFilename) as jsonFile: + res[frequency.value] = cast(List[Dict[PropertyName, Any]], json.load(jsonFile)) + + return res + + +# ------------------------------------------------------------------------------------------------------------ +class FrequencyConverter: + + MONTHS = [ + "Janvier", + "Février", + "Mars", + "Avril", + "Mai", + "Juin", + "Juillet", + "Août", + "Septembre", + "Octobre", + "Novembre", + "Décembre" + ] + + # ------------------------------------------------------ + @staticmethod + def computeHourly(daily: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + + return [] + + # ------------------------------------------------------ + @staticmethod + def computeDaily(daily: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + + return daily + + # ------------------------------------------------------ + @staticmethod + def computeWeekly(daily: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + + df = pd.DataFrame(daily) + + # Trimming head and trailing spaces and convert to datetime. + df["date_time"] = pd.to_datetime(df["time_period"].str.strip(), format=JsonWebDataSource.OUTPUT_DATE_FORMAT) + + # Get the first day of week. + df["first_day_of_week"] = pd.to_datetime(df["date_time"].dt.strftime("%W %Y 1"), format="%W %Y %w") + + # Get the last day of week. + df["last_day_of_week"] = pd.to_datetime(df["date_time"].dt.strftime("%W %Y 0"), format="%W %Y %w") + + # Reformat the time period. + df["time_period"] = "Du " + df["first_day_of_week"].dt.strftime(JsonWebDataSource.OUTPUT_DATE_FORMAT).astype(str) + " au " + df["last_day_of_week"].dt.strftime(JsonWebDataSource.OUTPUT_DATE_FORMAT).astype(str) + + # Aggregate rows by month_year. + df = df[["first_day_of_week", "time_period", "start_index_m3", "end_index_m3", "volume_m3", "energy_kwh", "timestamp"]].groupby("time_period").agg(first_day_of_week=('first_day_of_week', 'min'), start_index_m3=('start_index_m3', 'min'), end_index_m3=('end_index_m3', 'max'), volume_m3=('volume_m3', 'sum'), energy_kwh=('energy_kwh', 'sum'), timestamp=('timestamp', 'min'), count=('energy_kwh', 'count')).reset_index() + + # Sort rows by month ascending. + df = df.sort_values(by=['first_day_of_week']) + + # Select rows where we have a full week (7 days) except for the current week. + df = pd.concat([df[(df["count"] == 7)], df.tail(1)]) + + # Select target columns. + df = df[["time_period", "start_index_m3", "end_index_m3", "volume_m3", "energy_kwh", "timestamp"]] + + res = cast(List[Dict[str, Any]], df.to_dict('records')) + + return res + + # ------------------------------------------------------ + @staticmethod + def computeMonthly(daily: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + + df = pd.DataFrame(daily) + + # Trimming head and trailing spaces and convert to datetime. + df["date_time"] = pd.to_datetime(df["time_period"].str.strip(), format=JsonWebDataSource.OUTPUT_DATE_FORMAT) + + # Get the corresponding month-year. + df["month_year"] = df["date_time"].apply(lambda x: FrequencyConverter.MONTHS[x.month - 1]).astype(str) + " " + df["date_time"].dt.strftime("%Y").astype(str) + + # Aggregate rows by month_year. + df = df[["date_time", "month_year", "start_index_m3", "end_index_m3", "volume_m3", "energy_kwh", "timestamp"]].groupby("month_year").agg(first_day_of_month=('date_time', 'min'), start_index_m3=('start_index_m3', 'min'), end_index_m3=('end_index_m3', 'max'), volume_m3=('volume_m3', 'sum'), energy_kwh=('energy_kwh', 'sum'), timestamp=('timestamp', 'min'), count=('energy_kwh', 'count')).reset_index() + + # Sort rows by month ascending. + df = df.sort_values(by=['first_day_of_month']) + + # Select rows where we have a full month (more than 27 days) except for the current month. + df = pd.concat([df[(df["count"] >= 28)], df.tail(1)]) + + # Rename columns for their target names. + df = df.rename(columns={"month_year": "time_period"}) + + # Select target columns. + df = df[["time_period", "start_index_m3", "end_index_m3", "volume_m3", "energy_kwh", "timestamp"]] + + res = cast(List[Dict[str, Any]], df.to_dict('records')) + + return res + + # ------------------------------------------------------ + @staticmethod + def computeYearly(daily: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + + df = pd.DataFrame(daily) + + # Trimming head and trailing spaces and convert to datetime. + df["date_time"] = pd.to_datetime(df["time_period"].str.strip(), format=JsonWebDataSource.OUTPUT_DATE_FORMAT) + + # Get the corresponding year. + df["year"] = df["date_time"].dt.strftime("%Y") + + # Aggregate rows by month_year. + df = df[["year", "start_index_m3", "end_index_m3", "volume_m3", "energy_kwh", "timestamp"]].groupby("year").agg(start_index_m3=('start_index_m3', 'min'), end_index_m3=('end_index_m3', 'max'), volume_m3=('volume_m3', 'sum'), energy_kwh=('energy_kwh', 'sum'), timestamp=('timestamp', 'min'), count=('energy_kwh', 'count')).reset_index() + + # Sort rows by month ascending. + df = df.sort_values(by=['year']) + + # Select rows where we have almost a full year (more than 360) except for the current month. + df = pd.concat([df[(df["count"] >= 360)], df.tail(1)]) + + # Rename columns for their target names. + df = df.rename(columns={"year": "time_period"}) + + # Select target columns. + df = df[["time_period", "start_index_m3", "end_index_m3", "volume_m3", "energy_kwh", "timestamp"]] + + res = cast(List[Dict[str, Any]], df.to_dict('records')) + + return res diff --git a/pygazpar/enum.py b/pygazpar/enum.py index c31580a..16d4ccb 100644 --- a/pygazpar/enum.py +++ b/pygazpar/enum.py @@ -13,13 +13,23 @@ class PropertyName(Enum): TYPE = "type" TIMESTAMP = "timestamp" + def __str__(self): + return self.value + + def __repr__(self): + return self.__str__() + # ------------------------------------------------------------------------------------------------------------ class Frequency(Enum): - HOURLY = 0 - DAILY = 1 - WEEKLY = 2 - MONTHLY = 3 + HOURLY = "hourly" + DAILY = "daily" + WEEKLY = "weekly" + MONTHLY = "monthly" + YEARLY = "yearly" def __str__(self): - return self.name + return self.value + + def __repr__(self): + return self.__str__() diff --git a/pygazpar/datafileparser.py b/pygazpar/excelparser.py similarity index 56% rename from pygazpar/datafileparser.py rename to pygazpar/excelparser.py index d2f5892..b0b2507 100644 --- a/pygazpar/datafileparser.py +++ b/pygazpar/excelparser.py @@ -10,24 +10,24 @@ FIRST_DATA_LINE_NUMBER = 10 +Logger = logging.getLogger(__name__) -# ------------------------------------------------------------------------------------------------------------ -class DataFileParser: - logger = logging.getLogger(__name__) +# ------------------------------------------------------------------------------------------------------------ +class ExcelParser: # ------------------------------------------------------ @staticmethod def parse(dataFilename: str, dataReadingFrequency: Frequency) -> List[Dict[str, Any]]: parseByFrequency = { - Frequency.HOURLY: DataFileParser.__parseHourly, - Frequency.DAILY: DataFileParser.__parseDaily, - Frequency.WEEKLY: DataFileParser.__parseWeekly, - Frequency.MONTHLY: DataFileParser.__parseMonthly + Frequency.HOURLY: ExcelParser.__parseHourly, + Frequency.DAILY: ExcelParser.__parseDaily, + Frequency.WEEKLY: ExcelParser.__parseWeekly, + Frequency.MONTHLY: ExcelParser.__parseMonthly } - DataFileParser.logger.debug(f"Loading Excel data file '{dataFilename}'...") + Logger.debug(f"Loading Excel data file '{dataFilename}'...") workbook = load_workbook(filename=dataFilename) @@ -72,18 +72,18 @@ def __parseDaily(worksheet: Worksheet) -> List[Dict[str, Any]]: for rownum in range(minRowNum, maxRowNum + 1): row = {} if worksheet.cell(column=2, row=rownum).value is not None: - DataFileParser.__fillRow(row, PropertyName.TIME_PERIOD.value, worksheet.cell(column=2, row=rownum), False) # type: ignore - DataFileParser.__fillRow(row, PropertyName.START_INDEX.value, worksheet.cell(column=3, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.END_INDEX.value, worksheet.cell(column=4, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.VOLUME.value, worksheet.cell(column=5, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.ENERGY.value, worksheet.cell(column=6, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.CONVERTER_FACTOR.value, worksheet.cell(column=7, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.TEMPERATURE.value, worksheet.cell(column=8, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.TYPE.value, worksheet.cell(column=9, row=rownum), False) # type: ignore + ExcelParser.__fillRow(row, PropertyName.TIME_PERIOD.value, worksheet.cell(column=2, row=rownum), False) # type: ignore + ExcelParser.__fillRow(row, PropertyName.START_INDEX.value, worksheet.cell(column=3, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.END_INDEX.value, worksheet.cell(column=4, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.VOLUME.value, worksheet.cell(column=5, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.ENERGY.value, worksheet.cell(column=6, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.CONVERTER_FACTOR.value, worksheet.cell(column=7, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.TEMPERATURE.value, worksheet.cell(column=8, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.TYPE.value, worksheet.cell(column=9, row=rownum), False) # type: ignore row[PropertyName.TIMESTAMP.value] = data_timestamp res.append(row) - DataFileParser.logger.debug(f"Daily data read successfully between row #{minRowNum} and row #{maxRowNum}") + Logger.debug(f"Daily data read successfully between row #{minRowNum} and row #{maxRowNum}") return res @@ -101,13 +101,13 @@ def __parseWeekly(worksheet: Worksheet) -> List[Dict[str, Any]]: for rownum in range(minRowNum, maxRowNum + 1): row = {} if worksheet.cell(column=2, row=rownum).value is not None: - DataFileParser.__fillRow(row, PropertyName.TIME_PERIOD.value, worksheet.cell(column=2, row=rownum), False) # type: ignore - DataFileParser.__fillRow(row, PropertyName.VOLUME.value, worksheet.cell(column=3, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.ENERGY.value, worksheet.cell(column=4, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.TIME_PERIOD.value, worksheet.cell(column=2, row=rownum), False) # type: ignore + ExcelParser.__fillRow(row, PropertyName.VOLUME.value, worksheet.cell(column=3, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.ENERGY.value, worksheet.cell(column=4, row=rownum), True) # type: ignore row[PropertyName.TIMESTAMP.value] = data_timestamp res.append(row) - DataFileParser.logger.debug(f"Weekly data read successfully between row #{minRowNum} and row #{maxRowNum}") + Logger.debug(f"Weekly data read successfully between row #{minRowNum} and row #{maxRowNum}") return res @@ -125,12 +125,12 @@ def __parseMonthly(worksheet: Worksheet) -> List[Dict[str, Any]]: for rownum in range(minRowNum, maxRowNum + 1): row = {} if worksheet.cell(column=2, row=rownum).value is not None: - DataFileParser.__fillRow(row, PropertyName.TIME_PERIOD.value, worksheet.cell(column=2, row=rownum), False) # type: ignore - DataFileParser.__fillRow(row, PropertyName.VOLUME.value, worksheet.cell(column=3, row=rownum), True) # type: ignore - DataFileParser.__fillRow(row, PropertyName.ENERGY.value, worksheet.cell(column=4, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.TIME_PERIOD.value, worksheet.cell(column=2, row=rownum), False) # type: ignore + ExcelParser.__fillRow(row, PropertyName.VOLUME.value, worksheet.cell(column=3, row=rownum), True) # type: ignore + ExcelParser.__fillRow(row, PropertyName.ENERGY.value, worksheet.cell(column=4, row=rownum), True) # type: ignore row[PropertyName.TIMESTAMP.value] = data_timestamp res.append(row) - DataFileParser.logger.debug(f"Monthly data read successfully between row #{minRowNum} and row #{maxRowNum}") + Logger.debug(f"Monthly data read successfully between row #{minRowNum} and row #{maxRowNum}") return res diff --git a/pygazpar/jsonparser.py b/pygazpar/jsonparser.py new file mode 100644 index 0000000..54fdc50 --- /dev/null +++ b/pygazpar/jsonparser.py @@ -0,0 +1,50 @@ +import json +import logging +from datetime import datetime +from pygazpar.enum import PropertyName +from typing import Any, List, Dict + +INPUT_DATE_FORMAT = "%Y-%m-%d" + +OUTPUT_DATE_FORMAT = "%d/%m/%Y" + +Logger = logging.getLogger(__name__) + + +# ------------------------------------------------------------------------------------------------------------ +class JsonParser: + + # ------------------------------------------------------ + @staticmethod + def parse(jsonStr: str, temperaturesStr: str, pceIdentifier: str) -> List[Dict[str, Any]]: + + res = [] + + data = json.loads(jsonStr) + + temperatures = json.loads(temperaturesStr) + + # Timestamp of the data. + data_timestamp = datetime.now().isoformat() + + for releve in data[pceIdentifier]['releves']: + temperature = releve['temperature'] + if temperature is None: + temperature = temperatures.get(releve['journeeGaziere']) + + item = {} + item[PropertyName.TIME_PERIOD.value] = datetime.strftime(datetime.strptime(releve['journeeGaziere'], INPUT_DATE_FORMAT), OUTPUT_DATE_FORMAT) + item[PropertyName.START_INDEX.value] = releve['indexDebut'] + item[PropertyName.END_INDEX.value] = releve['indexFin'] + item[PropertyName.VOLUME.value] = releve['volumeBrutConsomme'] + item[PropertyName.ENERGY.value] = releve['energieConsomme'] + item[PropertyName.CONVERTER_FACTOR.value] = releve['coeffConversion'] + item[PropertyName.TEMPERATURE.value] = temperature + item[PropertyName.TYPE.value] = releve['qualificationReleve'] + item[PropertyName.TIMESTAMP.value] = data_timestamp + + res.append(item) + + Logger.debug("Daily data read successfully from Json") + + return res diff --git a/pygazpar/resources/yearly_data_sample.json b/pygazpar/resources/yearly_data_sample.json new file mode 100644 index 0000000..ec12034 --- /dev/null +++ b/pygazpar/resources/yearly_data_sample.json @@ -0,0 +1,18 @@ +[ + { + "time_period": "2021", + "start_index_m3": 12582.0, + "end_index_m3": 14661.0, + "volume_m3": 2099.0, + "energy_kwh": 23148.0, + "timestamp": "2022-12-10T12:05:11.466539" + }, + { + "time_period": "2022", + "start_index_m3": 14661.0, + "end_index_m3": 15988.0, + "volume_m3": 1344.0, + "energy_kwh": 14887.0, + "timestamp": "2022-12-10T12:05:11.466539" + } +] \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 6e7e85d..d69eeef 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,3 +2,5 @@ flake8 pytest openpyxl requests +python-dotenv +pandas diff --git a/samples/__init__.py b/samples/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/samples/excelSample.py b/samples/excelSample.py new file mode 100644 index 0000000..ca89cf7 --- /dev/null +++ b/samples/excelSample.py @@ -0,0 +1,31 @@ +import sys +import os +import dotenv +import json +import pygazpar + + +def main(): + + # Load environment variables GRDF_USERNAME, GRDF_PASSWORD, PCE_IDENTIFIER from .env file. + dotenv.load_dotenv() + + username = os.environ["GRDF_USERNAME"] + password = os.environ["GRDF_PASSWORD"] + pceIdentifier = os.environ["PCE_IDENTIFIER"] + + client = pygazpar.Client(pygazpar.ExcelWebDataSource( + username=username, + password=password, + tmpDirectory="tmp") + ) + + data = client.loadSince(pceIdentifier=pceIdentifier, + lastNDays=60, + frequencies=[pygazpar.Frequency.DAILY, pygazpar.Frequency.MONTHLY]) + + print(json.dumps(data, indent=2)) + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/samples/jsonSample.py b/samples/jsonSample.py new file mode 100644 index 0000000..ca690a9 --- /dev/null +++ b/samples/jsonSample.py @@ -0,0 +1,30 @@ +import sys +import os +import dotenv +import json +import pygazpar + + +def main(): + + # Load environment variables GRDF_USERNAME, GRDF_PASSWORD, PCE_IDENTIFIER from .env file. + dotenv.load_dotenv() + + username = os.environ["GRDF_USERNAME"] + password = os.environ["GRDF_PASSWORD"] + pceIdentifier = os.environ["PCE_IDENTIFIER"] + + client = pygazpar.Client(pygazpar.JsonWebDataSource( + username=username, + password=password) + ) + + data = client.loadSince(pceIdentifier=pceIdentifier, + lastNDays=60, + frequencies=[pygazpar.Frequency.DAILY, pygazpar.Frequency.MONTHLY]) + + print(json.dumps(data, indent=2)) + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/samples/testSample.py b/samples/testSample.py new file mode 100644 index 0000000..0f14309 --- /dev/null +++ b/samples/testSample.py @@ -0,0 +1,18 @@ +import sys +import json +import pygazpar + + +def main(): + + client = pygazpar.Client(pygazpar.TestDataSource()) + + data = client.loadSince(pceIdentifier="xxx", + lastNDays=60, + frequencies=[pygazpar.Frequency.DAILY, pygazpar.Frequency.MONTHLY]) + + print(json.dumps(data, indent=2)) + + +if __name__ == '__main__': + sys.exit(main()) diff --git a/setup.cfg b/setup.cfg index 96f567a..c1b981c 100644 --- a/setup.cfg +++ b/setup.cfg @@ -25,17 +25,21 @@ classifiers = Development Status :: 5 - Production/Stable Topic :: Software Development :: Libraries Operating System :: OS Independent + Programming Language :: Python :: 3.7 + Programming Language :: Python :: 3.8 Programming Language :: Python :: 3.9 - Programming Language :: Python :: 3.10 + Programming Language :: Python :: 3.10 + Programming Language :: Python :: 3.11 [options] zip_safe = False include_package_data = True packages = find: -python_requires = >=3.9 +python_requires = >=3.7 install_requires = openpyxl >= 2.6.3 requests >= 2.26.0 + pandas [options.entry_points] console_scripts = @@ -44,4 +48,4 @@ console_scripts = [bdist_wheel] universal = False plat-name = any -python-tag = py38 +python-tag = py37 diff --git a/tests/resources/donnees_informatives.json b/tests/resources/donnees_informatives.json new file mode 100644 index 0000000..75ccd5c --- /dev/null +++ b/tests/resources/donnees_informatives.json @@ -0,0 +1,19736 @@ +{ + "22423299474865": { + "frequence": null, + "idPce": "22423299474865", + "releves": [ + { + "coeffConversion": 11.12, + "dateDebutReleve": "2019-11-30T06:00:00+00:00", + "dateFinReleve": "2019-12-01T06:00:00+00:00", + "energieConsomme": 75, + "frequenceReleve": null, + "indexDebut": 10373, + "indexFin": 10380, + "journeeGaziere": "2019-11-30", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 7, + "volumeConverti": null + }, + { + "coeffConversion": 11.12, + "dateDebutReleve": "2019-12-01T06:00:00+00:00", + "dateFinReleve": "2019-12-02T06:00:00+00:00", + "energieConsomme": 146, + "frequenceReleve": null, + "indexDebut": 10380, + "indexFin": 10393, + "journeeGaziere": "2019-12-01", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 13, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-02T06:00:00+00:00", + "dateFinReleve": "2019-12-03T06:00:00+00:00", + "energieConsomme": 174, + "frequenceReleve": null, + "indexDebut": 10393, + "indexFin": 10409, + "journeeGaziere": "2019-12-02", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 16, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-03T06:00:00+00:00", + "dateFinReleve": "2019-12-04T06:00:00+00:00", + "energieConsomme": 151, + "frequenceReleve": null, + "indexDebut": 10409, + "indexFin": 10422, + "journeeGaziere": "2019-12-03", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 14, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-04T06:00:00+00:00", + "dateFinReleve": "2019-12-05T06:00:00+00:00", + "energieConsomme": 139, + "frequenceReleve": null, + "indexDebut": 10422, + "indexFin": 10434, + "journeeGaziere": "2019-12-04", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 12, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-05T06:00:00+00:00", + "dateFinReleve": "2019-12-06T06:00:00+00:00", + "energieConsomme": 134, + "frequenceReleve": null, + "indexDebut": 10434, + "indexFin": 10446, + "journeeGaziere": "2019-12-05", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 12, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-06T06:00:00+00:00", + "dateFinReleve": "2019-12-07T06:00:00+00:00", + "energieConsomme": 175, + "frequenceReleve": null, + "indexDebut": 10446, + "indexFin": 10462, + "journeeGaziere": "2019-12-06", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 16, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-07T06:00:00+00:00", + "dateFinReleve": "2019-12-08T06:00:00+00:00", + "energieConsomme": 79, + "frequenceReleve": null, + "indexDebut": 10462, + "indexFin": 10469, + "journeeGaziere": "2019-12-07", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 7, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-08T06:00:00+00:00", + "dateFinReleve": "2019-12-09T06:00:00+00:00", + "energieConsomme": 140, + "frequenceReleve": null, + "indexDebut": 10469, + "indexFin": 10482, + "journeeGaziere": "2019-12-08", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 13, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-09T06:00:00+00:00", + "dateFinReleve": "2019-12-10T06:00:00+00:00", + "energieConsomme": 108, + "frequenceReleve": null, + "indexDebut": 10482, + "indexFin": 10491, + "journeeGaziere": "2019-12-09", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 10, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-10T06:00:00+00:00", + "dateFinReleve": "2019-12-11T06:00:00+00:00", + "energieConsomme": 135, + "frequenceReleve": null, + "indexDebut": 10491, + "indexFin": 10504, + "journeeGaziere": "2019-12-10", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 12, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-11T06:00:00+00:00", + "dateFinReleve": "2019-12-12T06:00:00+00:00", + "energieConsomme": 133, + "frequenceReleve": null, + "indexDebut": 10504, + "indexFin": 10515, + "journeeGaziere": "2019-12-11", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 12, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-12T06:00:00+00:00", + "dateFinReleve": "2019-12-13T06:00:00+00:00", + "energieConsomme": 127, + "frequenceReleve": null, + "indexDebut": 10515, + "indexFin": 10527, + "journeeGaziere": "2019-12-12", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 11, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-13T06:00:00+00:00", + "dateFinReleve": "2019-12-14T06:00:00+00:00", + "energieConsomme": 114, + "frequenceReleve": null, + "indexDebut": 10527, + "indexFin": 10537, + "journeeGaziere": "2019-12-13", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 10, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-14T06:00:00+00:00", + "dateFinReleve": "2019-12-15T06:00:00+00:00", + "energieConsomme": 124, + "frequenceReleve": null, + "indexDebut": 10537, + "indexFin": 10548, + "journeeGaziere": "2019-12-14", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 11, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-15T06:00:00+00:00", + "dateFinReleve": "2019-12-16T06:00:00+00:00", + "energieConsomme": 98, + "frequenceReleve": null, + "indexDebut": 10548, + "indexFin": 10557, + "journeeGaziere": "2019-12-15", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 9, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-16T06:00:00+00:00", + "dateFinReleve": "2019-12-17T06:00:00+00:00", + "energieConsomme": 99, + "frequenceReleve": null, + "indexDebut": 10557, + "indexFin": 10566, + "journeeGaziere": "2019-12-16", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 9, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-17T06:00:00+00:00", + "dateFinReleve": "2019-12-18T06:00:00+00:00", + "energieConsomme": 112, + "frequenceReleve": null, + "indexDebut": 10566, + "indexFin": 10576, + "journeeGaziere": "2019-12-17", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 10, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-18T06:00:00+00:00", + "dateFinReleve": "2019-12-19T06:00:00+00:00", + "energieConsomme": 87, + "frequenceReleve": null, + "indexDebut": 10576, + "indexFin": 10584, + "journeeGaziere": "2019-12-18", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 8, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-19T06:00:00+00:00", + "dateFinReleve": "2019-12-20T06:00:00+00:00", + "energieConsomme": 122, + "frequenceReleve": null, + "indexDebut": 10584, + "indexFin": 10595, + "journeeGaziere": "2019-12-19", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 11, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-20T06:00:00+00:00", + "dateFinReleve": "2019-12-21T06:00:00+00:00", + "energieConsomme": 75, + "frequenceReleve": null, + "indexDebut": 10595, + "indexFin": 10601, + "journeeGaziere": "2019-12-20", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 7, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-21T06:00:00+00:00", + "dateFinReleve": "2019-12-22T06:00:00+00:00", + "energieConsomme": 120, + "frequenceReleve": null, + "indexDebut": 10601, + "indexFin": 10612, + "journeeGaziere": "2019-12-21", + "natureReleve": "Informative Journalier", + "pcs": null, + "pta": null, + "qualificationReleve": "Mesur\u00e9", + "status": null, + "temperature": null, + "volumeBrutConsomme": 11, + "volumeConverti": null + }, + { + "coeffConversion": 11.17, + "dateDebutReleve": "2019-12-22T06:00:00+00:00", + "dateFinReleve": "2019-12-23T06:00:00+00:00", + "energieConsomme": 17, + "frequenceReleve": null, + "indexDebut": 10612, + 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"2022-09-27": 14.76, + "2022-09-28": 12.25, + "2022-09-29": 10.93, + "2022-09-30": 13.66, + "2022-10-01": 17.109999999999999, + "2022-10-02": 14.98, + "2022-10-03": 11.35, + "2022-10-04": 11.35, + "2022-10-05": 16.239999999999998, + "2022-10-06": 13.42, + "2022-10-07": 14, + "2022-10-08": 13.19, + "2022-10-09": 13.06, + "2022-10-10": 14.890000000000001, + "2022-10-11": 12.94, + "2022-10-12": 14.210000000000001, + "2022-10-13": 14.49, + "2022-10-14": 15.460000000000001, + "2022-10-15": 16.18, + "2022-10-16": 17.469999999999999, + "2022-10-17": 17.300000000000001, + "2022-10-18": 16.579999999999998, + "2022-10-19": 17.699999999999999, + "2022-10-20": 17.219999999999999, + "2022-10-21": 16.379999999999999, + "2022-10-22": 16.829999999999998, + "2022-10-23": 18.25, + "2022-10-24": 15.699999999999999, + "2022-10-25": 16.059999999999999, + "2022-10-26": 16.77, + "2022-10-27": 18.02, + "2022-10-28": 18.359999999999999, + "2022-10-29": 18.140000000000001, + "2022-10-30": 15.289999999999999, + "2022-10-31": 16.300000000000001, + "2022-11-01": 13.81, + "2022-11-02": 12.41, + "2022-11-03": 11.43, + "2022-11-04": 9.8499999999999996, + "2022-11-05": 9.75, + "2022-11-06": 10.49, + "2022-11-07": 12.93, + "2022-11-08": 13.83, + "2022-11-09": 11.289999999999999, + "2022-11-10": 9.5600000000000005, + "2022-11-11": 9.8800000000000008, + "2022-11-12": 10.970000000000001, + "2022-11-13": 9.3499999999999996, + "2022-11-14": 9.8399999999999999, + "2022-11-15": 10.66, + "2022-11-16": 11.76, + "2022-11-17": 11.25, + "2022-11-18": 9.0600000000000005, + "2022-11-19": 8.4900000000000002, + "2022-11-20": 7.7800000000000002, + "2022-11-21": 6.6200000000000001, + "2022-11-22": 8.3499999999999996, + "2022-11-23": 8.9399999999999995, + "2022-11-24": 10.16, + "2022-11-25": 8.8200000000000003, + "2022-11-26": 6.79, + "2022-11-27": 8.2400000000000002, + "2022-11-28": 9.0399999999999991, + "2022-11-29": 7.6900000000000004, + "2022-11-30": 6.5099999999999998 +} diff --git a/tests/test_client.py b/tests/test_client.py index 28d71d6..02f7563 100644 --- a/tests/test_client.py +++ b/tests/test_client.py @@ -1,6 +1,6 @@ from pygazpar.enum import Frequency from pygazpar.client import Client -from pygazpar.clientV2 import ClientV2 +from pygazpar.datasource import JsonWebDataSource, TestDataSource, ExcelWebDataSource import os import pytest @@ -40,66 +40,106 @@ def teardown_method(self): """ def test_login_error(self): - client = Client("WrongUserName", "WrongPassword", "WrongPCENumber", Frequency.DAILY, tmpDirectory=self.__tmp_directory, lastNDays=365, testMode=False) + client = Client(JsonWebDataSource("WrongUsername", "WrongPassword")) with pytest.raises(Exception): - client.update() + client.loadSince(self.__pceIdentifier, 365, [Frequency.DAILY]) - @pytest.mark.skip(reason="Hourly data is not yet implemented") def test_hourly_live(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.HOURLY, tmpDirectory=self.__tmp_directory, lastNDays=30) - client.update() + client = Client(JsonWebDataSource(self.__username, self.__password)) - assert (len(client.data()) > 0) + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.HOURLY]) + + assert (len(data[Frequency.HOURLY.value]) == 0) # @pytest.mark.skip(reason="Requires live data") - def test_daily_live(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.DAILY, tmpDirectory=self.__tmp_directory, lastNDays=720) - client.update() + def test_daily_jsonweb(self): + client = Client(JsonWebDataSource(self.__username, self.__password)) - assert (len(client.data()) > 0) + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.DAILY]) - # @pytest.mark.skip(reason="Requires live data") - def test_weekly_live(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.WEEKLY, tmpDirectory=self.__tmp_directory, lastNDays=30) - client.update() + assert (len(data[Frequency.DAILY.value]) > 0) - assert (len(client.data()) > 0) + def test_weekly_jsonweb(self): + client = Client(JsonWebDataSource(self.__username, self.__password)) - # @pytest.mark.skip(reason="Requires live data") - def test_monthly_live(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.MONTHLY, tmpDirectory=self.__tmp_directory, lastNDays=1095) - client.update() + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.WEEKLY]) + + assert (len(data[Frequency.WEEKLY.value]) >= 51 and len(data[Frequency.WEEKLY.value]) <= 54) + + def test_monthly_jsonweb(self): + client = Client(JsonWebDataSource(self.__username, self.__password)) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.MONTHLY]) + + assert (len(data[Frequency.MONTHLY.value]) >= 12 and len(data[Frequency.MONTHLY.value]) <= 13) + + def test_yearly_jsonweb(self): + client = Client(ExcelWebDataSource(self.__username, self.__password, self.__tmp_directory)) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.YEARLY]) + + assert (len(data[Frequency.YEARLY.value]) == 1) + + def test_daily_excelweb(self): + client = Client(ExcelWebDataSource(self.__username, self.__password, self.__tmp_directory)) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.DAILY]) + + assert (len(data[Frequency.DAILY.value]) > 0) + + def test_weekly_excelweb(self): + client = Client(ExcelWebDataSource(self.__username, self.__password, self.__tmp_directory)) - assert (len(client.data()) > 0) + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.WEEKLY]) + + assert (len(data[Frequency.WEEKLY.value]) >= 51 and len(data[Frequency.WEEKLY.value]) <= 54) + + def test_monthly_excelweb(self): + client = Client(ExcelWebDataSource(self.__username, self.__password, self.__tmp_directory)) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.MONTHLY]) + + assert (len(data[Frequency.MONTHLY.value]) >= 12 and len(data[Frequency.MONTHLY.value]) <= 13) + + def test_yearly_excelweb(self): + client = Client(ExcelWebDataSource(self.__username, self.__password, self.__tmp_directory)) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.YEARLY]) + + assert (len(data[Frequency.YEARLY.value]) == 1) def test_hourly_sample(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.HOURLY, tmpDirectory=self.__tmp_directory, lastNDays=365, testMode=True) - client.update() + client = Client(TestDataSource()) - assert (len(client.data()) == 0) + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.HOURLY]) + + assert (len(data[Frequency.HOURLY.value]) == 0) def test_daily_sample(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.DAILY, tmpDirectory=self.__tmp_directory, lastNDays=365, testMode=True) - client.update() + client = Client(TestDataSource()) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.DAILY]) - assert (len(client.data()) > 0) + assert (len(data[Frequency.DAILY.value]) == 711) def test_weekly_sample(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.WEEKLY, tmpDirectory=self.__tmp_directory, lastNDays=365, testMode=True) - client.update() + client = Client(TestDataSource()) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.WEEKLY]) - assert (len(client.data()) > 0) + assert (len(data[Frequency.WEEKLY.value]) > 0) def test_monthly_sample(self): - client = Client(self.__username, self.__password, self.__pceIdentifier, Frequency.MONTHLY, tmpDirectory=self.__tmp_directory, lastNDays=30, testMode=True) - client.update() + client = Client(TestDataSource()) - assert (len(client.data()) > 0) + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.MONTHLY]) - # @pytest.mark.skip(reason="Requires live data") - def test_clientV2(self): - client = ClientV2(self.__username, self.__password, self.__pceIdentifier, lastNDays=360, testMode=False) - client.update() + assert (len(data[Frequency.MONTHLY.value]) > 0) + + def test_yearly_sample(self): + client = Client(TestDataSource()) + + data = client.loadSince(self.__pceIdentifier, 365, [Frequency.YEARLY]) - assert (len(client.data()) == 360) + assert (len(data[Frequency.YEARLY.value]) == 2) diff --git a/tests/test_datafileparser.py b/tests/test_datafileparser.py index ae1d5fd..819a96b 100644 --- a/tests/test_datafileparser.py +++ b/tests/test_datafileparser.py @@ -1,17 +1,20 @@ -from pygazpar.datafileparser import DataFileParser +from pygazpar.excelparser import ExcelParser from pygazpar.enum import Frequency class TestDataFileParser: + # ------------------------------------------------------ def test_daily_sample(self): - data = DataFileParser.parse("tests/resources/Donnees_informatives_PCE_DAILY.xlsx", Frequency.DAILY) + data = ExcelParser.parse("tests/resources/Donnees_informatives_PCE_DAILY.xlsx", Frequency.DAILY) assert (len(data) == 363) + # ------------------------------------------------------ def test_weekly_sample(self): - data = DataFileParser.parse("tests/resources/Donnees_informatives_PCE_WEEKLY.xlsx", Frequency.WEEKLY) + data = ExcelParser.parse("tests/resources/Donnees_informatives_PCE_WEEKLY.xlsx", Frequency.WEEKLY) assert (len(data) == 53) + # ------------------------------------------------------ def test_monthly_sample(self): - data = DataFileParser.parse("tests/resources/Donnees_informatives_PCE_MONTHLY.xlsx", Frequency.MONTHLY) + data = ExcelParser.parse("tests/resources/Donnees_informatives_PCE_MONTHLY.xlsx", Frequency.MONTHLY) assert (len(data) == 13) diff --git a/tests/test_datasource.py b/tests/test_datasource.py new file mode 100644 index 0000000..2750c0e --- /dev/null +++ b/tests/test_datasource.py @@ -0,0 +1,166 @@ +import os +from pygazpar.datasource import TestDataSource, JsonFileDataSource, ExcelFileDataSource, JsonWebDataSource, ExcelWebDataSource +from pygazpar.enum import Frequency +from datetime import date, timedelta +from dotenv import load_dotenv + + +class TestAllDataSource: + + # ------------------------------------------------------ + @classmethod + def setup_class(cls): + """ setup any state specific to the execution of the given class (which + usually contains tests). + """ + + # ------------------------------------------------------ + @classmethod + def teardown_class(cls): + """ teardown any state that was previously setup with a call to + setup_class. + """ + + # ------------------------------------------------------ + def setup_method(self): + """ setup any state tied to the execution of the given method in a + class. setup_method is invoked for every test method of a class. + """ + tmpdir = os.path.normpath(f"{os.getcwd()}/tmp") + + # We create the tmp directory if not already exists. + if not os.path.exists(tmpdir): + os.mkdir(tmpdir) + + load_dotenv() + + self.__username = os.environ["GRDF_USERNAME"] + self.__password = os.environ["GRDF_PASSWORD"] + self.__pceIdentifier = os.environ["PCE_IDENTIFIER"] + self.__tmp_directory = tmpdir + + # ------------------------------------------------------ + def teardown_method(self): + """ teardown any state that was previously setup with a setup_method + call. + """ + + # ------------------------------------------------------ + def test_sample(self): + + dataSource = TestDataSource() + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate) + + assert (len(data[Frequency.DAILY.value]) == 711) + + assert (len(data[Frequency.WEEKLY.value]) == 102) + + assert (len(data[Frequency.MONTHLY.value]) == 24) + + assert (len(data[Frequency.YEARLY.value]) == 2) + + # ------------------------------------------------------ + def test_jsonfile_sample(self): + + dataSource = JsonFileDataSource("tests/resources/donnees_informatives.json", "tests/resources/temperatures.json") + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate, [Frequency.DAILY, Frequency.WEEKLY, Frequency.MONTHLY, Frequency.YEARLY]) + + assert (len(data[Frequency.DAILY.value]) == 1096) + + assert (len(data[Frequency.WEEKLY.value]) == 155) + + assert (len(data[Frequency.MONTHLY.value]) == 37) + + assert (len(data[Frequency.YEARLY.value]) == 3) + + # ------------------------------------------------------ + def test_daily_excelfile_sample(self): + + dataSource = ExcelFileDataSource("tests/resources/Donnees_informatives_PCE_DAILY.xlsx") + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate, [Frequency.DAILY]) + + assert (len(data[Frequency.DAILY.value]) == 363) + + # ------------------------------------------------------ + def test_weekly_excelfile_sample(self): + + dataSource = ExcelFileDataSource("tests/resources/Donnees_informatives_PCE_WEEKLY.xlsx") + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate, [Frequency.WEEKLY]) + + assert (len(data[Frequency.WEEKLY.value]) == 53) + + # ------------------------------------------------------ + def test_monthly_excelfile_sample(self): + + dataSource = ExcelFileDataSource("tests/resources/Donnees_informatives_PCE_MONTHLY.xlsx") + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate, [Frequency.MONTHLY]) + + assert (len(data[Frequency.MONTHLY.value]) == 13) + + # ------------------------------------------------------ + def test_yearly_excelfile_sample(self): + + dataSource = ExcelFileDataSource("tests/resources/Donnees_informatives_PCE_DAILY.xlsx") + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate, [Frequency.YEARLY]) + + assert (len(data[Frequency.YEARLY.value]) == 1) + + # ------------------------------------------------------ + def test_jsonweb(self): + + dataSource = JsonWebDataSource(self.__username, self.__password) + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate, [Frequency.DAILY, Frequency.WEEKLY, Frequency.MONTHLY, Frequency.YEARLY]) + + assert (len(data[Frequency.DAILY.value]) > 0) + + assert (len(data[Frequency.WEEKLY.value]) >= 51 and len(data[Frequency.WEEKLY.value]) <= 54) + + assert (len(data[Frequency.MONTHLY.value]) >= 12 and len(data[Frequency.MONTHLY.value]) <= 13) + + assert (len(data[Frequency.YEARLY.value]) == 1) + + # ------------------------------------------------------ + def test_excelweb(self): + + dataSource = ExcelWebDataSource(self.__username, self.__password, self.__tmp_directory) + + endDate = date.today() + startDate = endDate + timedelta(days=-365) + + data = dataSource.load(self.__pceIdentifier, startDate, endDate, [Frequency.DAILY, Frequency.WEEKLY, Frequency.MONTHLY, Frequency.YEARLY]) + + assert (len(data[Frequency.DAILY.value]) > 0) + + assert (len(data[Frequency.WEEKLY.value]) >= 51 and len(data[Frequency.WEEKLY.value]) <= 54) + + assert (len(data[Frequency.MONTHLY.value]) >= 12 and len(data[Frequency.MONTHLY.value]) <= 13) + + assert (len(data[Frequency.YEARLY.value]) == 1)